galaxy.schema package

class galaxy.schema.BootstrapAdminUser(*, id: int = 0, email: str | None = None, username: str | None = None, preferences: Dict[str, str] = {}, bootstrap_admin_user: bool = True)

Bases: BaseModel

id: int

email: str | None

username: str | None

preferences: Dict[str, str]

bootstrap_admin_user: bool

all_roles() → list

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'bootstrap_admin_user': FieldInfo(annotation=bool, required=False, default=True), 'email': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'id': FieldInfo(annotation=int, required=False, default=0), 'preferences': FieldInfo(annotation=Dict[str, str], required=False, default={}), 'username': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.ValueFilterQueryParams(*, q: List[str] | str | None = None, qv: List[str] | str | None = None)

Bases: BaseModel

Allows filtering/querying elements by value like q=<property>-<operator>&qv=<value>

Multiple q/qv queries can be concatenated.

q: List[str] | str | None

qv: List[str] | str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'q': FieldInfo(annotation=Union[List[str], str, NoneType], required=False, default=None, title='Filter Query', description='Generally a property name to filter by followed by an (often optional) hyphen and operator string.', examples=['create_time-gt']), 'qv': FieldInfo(annotation=Union[List[str], str, NoneType], required=False, default=None, title='Filter Value', description='The value to filter by.', examples=['2015-01-29'])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.PaginationQueryParams(*, offset: int | None[int | None] = 0, limit: int | None[int | None] = None)

Bases: BaseModel

Used to paginate a the request results by limiting and offsetting.

offset: int | None

limit: int | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'limit': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Limit', description='The maximum number of items to return.', metadata=[Ge(ge=1)]), 'offset': FieldInfo(annotation=Union[int, NoneType], required=False, default=0, title='Offset', description='Starts at the beginning skip the first ( offset - 1 ) items and begin returning at the Nth item', metadata=[Ge(ge=0)])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.FilterQueryParams(*, offset: int | None[int | None] = 0, limit: int | None[int | None] = None, q: List[str] | str | None = None, qv: List[str] | str | None = None, order: str | None = None)

Bases: ValueFilterQueryParams, PaginationQueryParams

Contains full filtering options to query elements, paginate and order them.

order: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'limit': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Limit', description='The maximum number of items to return.', metadata=[Ge(ge=1)]), 'offset': FieldInfo(annotation=Union[int, NoneType], required=False, default=0, title='Offset', description='Starts at the beginning skip the first ( offset - 1 ) items and begin returning at the Nth item', metadata=[Ge(ge=0)]), 'order': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Order', description="String containing one of the valid ordering attributes followed (optionally) by '-asc' or '-dsc' for ascending and descending order respectively. Orders can be stacked as a comma-separated list of values.", examples=['name-dsc,create_time']), 'q': FieldInfo(annotation=Union[List[str], str, NoneType], required=False, default=None, title='Filter Query', description='Generally a property name to filter by followed by an (often optional) hyphen and operator string.', examples=['create_time-gt']), 'qv': FieldInfo(annotation=Union[List[str], str, NoneType], required=False, default=None, title='Filter Value', description='The value to filter by.', examples=['2015-01-29'])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.SerializationParams(*, view: str | None = None, keys: List[str] | None = None, default_view: str | None = None)

Bases: BaseModel

Contains common parameters for customizing model serialization.

view: str | None

keys: List[str] | None

default_view: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'default_view': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Default View', description='The item view that will be used in case none was specified.'), 'keys': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None, title='Keys', description='List of keys (name of the attributes) that will be returned in addition to the ones included in the `view`.'), 'view': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='View', description='The name of the view used to serialize this item. This will return a predefined set of attributes of the item.', examples=['summary'])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.PdfDocumentType(value)

Bases: str, Enum

An enumeration.

invocation_report = 'invocation_report'

page = 'page'

class galaxy.schema.APIKeyModel(*, key: str, create_time: datetime)

Bases: BaseModel

key: str

create_time: datetime

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this API key was created.'), 'key': FieldInfo(annotation=str, required=True, title='Key', description='API key to interact with the Galaxy API')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

galaxy.schema.partial_model(include: List[str] | None = None, exclude: List[str] | None = None) → Callable[[Type[T]], Type[T]]

Decorator to make all model fields optional

Submodules

galaxy.schema.fetch_data module

class galaxy.schema.fetch_data.FetchBaseModel

Bases: Model

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.ElementsFromType(value)

Bases: str, Enum

An enumeration.

archive = 'archive'

bagit = 'bagit'

bagit_archive = 'bagit_archive'

directory = 'directory'

class galaxy.schema.fetch_data.BaseFetchDataTarget(*, auto_decompress: bool = False)

Bases: FetchBaseModel

auto_decompress: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.ItemsFromSrc(value)

Bases: str, Enum

An enumeration.

url = 'url'

files = 'files'

path = 'path'

ftp_import = 'ftp_import'

server_dir = 'server_dir'

class galaxy.schema.fetch_data.Src(value)

Bases: str, Enum

An enumeration.

url = 'url'

pasted = 'pasted'

files = 'files'

path = 'path'

composite = 'composite'

ftp_import = 'ftp_import'

server_dir = 'server_dir'

class galaxy.schema.fetch_data.DestinationType(value)

Bases: str, Enum

An enumeration.

library = 'library'

library_folder = 'library_folder'

hdcas = 'hdcas'

hdas = 'hdas'

class galaxy.schema.fetch_data.HdaDestination(*, type: typing_extensions.Literal[hdas])

Bases: FetchBaseModel

type: typing_extensions.Literal[hdas]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['hdas'], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.HdcaDestination(*, type: typing_extensions.Literal[hdca])

Bases: FetchBaseModel

type: typing_extensions.Literal[hdca]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=Literal['hdca'], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.LibraryFolderDestination(*, type: typing_extensions.Literal[library_folder], library_folder_id: int[int])

Bases: FetchBaseModel

type: typing_extensions.Literal[library_folder]

library_folder_id: int[int]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'library_folder_id': FieldInfo(annotation=int, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'type': FieldInfo(annotation=Literal['library_folder'], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.BaseCollectionTarget(*, auto_decompress: bool = False, destination: HdcaDestination, collection_type: str | None = None, tags: List[str] | None = None, name: str | None = None)

Bases: BaseFetchDataTarget

destination: HdcaDestination

collection_type: str | None

tags: List[str] | None

name: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'destination': FieldInfo(annotation=HdcaDestination, required=True), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.LibraryDestination(*, type: typing_extensions.Literal[library], name: str, description: str | None = None, synopsis: str | None = None)

Bases: FetchBaseModel

type: typing_extensions.Literal[library]

name: str

description: str | None

synopsis: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Description for library to create'), 'name': FieldInfo(annotation=str, required=True, description='Must specify a library name'), 'synopsis': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, description='Description for library to create'), 'type': FieldInfo(annotation=Literal['library'], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.ExtraFiles(*, items_from: str | None = None, src: Src, fuzzy_root: bool | None = True)

Bases: FetchBaseModel

items_from: str | None

src: Src

fuzzy_root: bool | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'fuzzy_root': FieldInfo(annotation=Union[bool, NoneType], required=False, default=True, description='Prevent Galaxy from checking for a single file in a directory and re-interpreting the archive'), 'items_from': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'src': FieldInfo(annotation=Src, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.FetchDatasetHash(*, hash_function: typing_extensions.Literal[MD5, SHA - 1, SHA - 256, SHA - 512], hash_value: str)

Bases: Model

hash_function: typing_extensions.Literal[MD5, SHA-1, SHA-256, SHA-512]

hash_value: str

model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'hash_function': FieldInfo(annotation=Literal['MD5', 'SHA-1', 'SHA-256', 'SHA-512'], required=True), 'hash_value': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.BaseDataElement(*, name: str | int | float | bool[str | int | float | bool] | None = None, dbkey: str = '?', info: str | None = None, ext: str = 'auto', space_to_tab: bool = False, to_posix_lines: bool = False, deferred: bool = False, tags: List[str] | None = None, created_from_basename: str | None = None, extra_files: ExtraFiles | None = None, auto_decompress: bool = False, elements_from: ElementsFromType | None = None, collection_type: str | None = None, MD5: str | None = None, SHA1: str | None = None, SHA256: str | None = None, SHA512: str | None = None, hashes: List[FetchDatasetHash] | None = None, description: str | None = None)

Bases: FetchBaseModel

name: str | int | float | bool[str | int | float | bool] | None

dbkey: str

info: str | None

ext: str

space_to_tab: bool

to_posix_lines: bool

deferred: bool

tags: List[str] | None

created_from_basename: str | None

extra_files: ExtraFiles | None

auto_decompress: bool

items_from: ElementsFromType | None

collection_type: str | None

MD5: str | None

SHA1: str | None

SHA256: str | None

SHA512: str | None

hashes: List[FetchDatasetHash] | None

description: str | None

model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'MD5': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'SHA1': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-1', alias_priority=2), 'SHA256': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-256', alias_priority=2), 'SHA512': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-512', alias_priority=2), 'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'dbkey': FieldInfo(annotation=str, required=False, default='?'), 'deferred': FieldInfo(annotation=bool, required=False, default=False), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'ext': FieldInfo(annotation=str, required=False, default='auto'), 'extra_files': FieldInfo(annotation=Union[ExtraFiles, NoneType], required=False, default=None), 'hashes': FieldInfo(annotation=Union[List[galaxy.schema.fetch_data.FetchDatasetHash], NoneType], required=False, default=None), 'info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'items_from': FieldInfo(annotation=Union[ElementsFromType, NoneType], required=False, default=None, alias='elements_from', alias_priority=2), 'name': FieldInfo(annotation=Union[Annotated[Union[str, int, float, bool], AfterValidator(func=<function <lambda>>)], NoneType], required=False, default=None), 'space_to_tab': FieldInfo(annotation=bool, required=False, default=False), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'to_posix_lines': FieldInfo(annotation=bool, required=False, default=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.FileDataElement(*, name: str | int | float | bool[str | int | float | bool] | None = None, dbkey: str = '?', info: str | None = None, ext: str = 'auto', space_to_tab: bool = False, to_posix_lines: bool = False, deferred: bool = False, tags: List[str] | None = None, created_from_basename: str | None = None, extra_files: ExtraFiles | None = None, auto_decompress: bool = False, elements_from: ElementsFromType | None = None, collection_type: str | None = None, MD5: str | None = None, SHA1: str | None = None, SHA256: str | None = None, SHA512: str | None = None, hashes: List[FetchDatasetHash] | None = None, description: str | None = None, src: typing_extensions.Literal[files])

Bases: BaseDataElement

src: typing_extensions.Literal[files]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'MD5': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'SHA1': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-1', alias_priority=2), 'SHA256': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-256', alias_priority=2), 'SHA512': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-512', alias_priority=2), 'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'dbkey': FieldInfo(annotation=str, required=False, default='?'), 'deferred': FieldInfo(annotation=bool, required=False, default=False), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'ext': FieldInfo(annotation=str, required=False, default='auto'), 'extra_files': FieldInfo(annotation=Union[ExtraFiles, NoneType], required=False, default=None), 'hashes': FieldInfo(annotation=Union[List[galaxy.schema.fetch_data.FetchDatasetHash], NoneType], required=False, default=None), 'info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'items_from': FieldInfo(annotation=Union[ElementsFromType, NoneType], required=False, default=None, alias='elements_from', alias_priority=2), 'name': FieldInfo(annotation=Union[Annotated[Union[str, int, float, bool], AfterValidator(func=<function <lambda>>)], NoneType], required=False, default=None), 'space_to_tab': FieldInfo(annotation=bool, required=False, default=False), 'src': FieldInfo(annotation=Literal['files'], required=True), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'to_posix_lines': FieldInfo(annotation=bool, required=False, default=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.PastedDataElement(*, name: str | int | float | bool[str | int | float | bool] | None = None, dbkey: str = '?', info: str | None = None, ext: str = 'auto', space_to_tab: bool = False, to_posix_lines: bool = False, deferred: bool = False, tags: List[str] | None = None, created_from_basename: str | None = None, extra_files: ExtraFiles | None = None, auto_decompress: bool = False, elements_from: ElementsFromType | None = None, collection_type: str | None = None, MD5: str | None = None, SHA1: str | None = None, SHA256: str | None = None, SHA512: str | None = None, hashes: List[FetchDatasetHash] | None = None, description: str | None = None, src: typing_extensions.Literal[pasted], paste_content: str | int | float | bool[str | int | float | bool])

Bases: BaseDataElement

src: typing_extensions.Literal[pasted]

paste_content: str | int | float | bool[str | int | float | bool]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'MD5': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'SHA1': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-1', alias_priority=2), 'SHA256': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-256', alias_priority=2), 'SHA512': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-512', alias_priority=2), 'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'dbkey': FieldInfo(annotation=str, required=False, default='?'), 'deferred': FieldInfo(annotation=bool, required=False, default=False), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'ext': FieldInfo(annotation=str, required=False, default='auto'), 'extra_files': FieldInfo(annotation=Union[ExtraFiles, NoneType], required=False, default=None), 'hashes': FieldInfo(annotation=Union[List[galaxy.schema.fetch_data.FetchDatasetHash], NoneType], required=False, default=None), 'info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'items_from': FieldInfo(annotation=Union[ElementsFromType, NoneType], required=False, default=None, alias='elements_from', alias_priority=2), 'name': FieldInfo(annotation=Union[Annotated[Union[str, int, float, bool], AfterValidator(func=<function <lambda>>)], NoneType], required=False, default=None), 'paste_content': FieldInfo(annotation=Union[str, int, float, bool], required=True, description='Content to upload', metadata=[AfterValidator(func=<function <lambda>>)]), 'space_to_tab': FieldInfo(annotation=bool, required=False, default=False), 'src': FieldInfo(annotation=Literal['pasted'], required=True), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'to_posix_lines': FieldInfo(annotation=bool, required=False, default=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.UrlDataElement(*, name: str | int | float | bool[str | int | float | bool] | None = None, dbkey: str = '?', info: str | None = None, ext: str = 'auto', space_to_tab: bool = False, to_posix_lines: bool = False, deferred: bool = False, tags: List[str] | None = None, created_from_basename: str | None = None, extra_files: ExtraFiles | None = None, auto_decompress: bool = False, elements_from: ElementsFromType | None = None, collection_type: str | None = None, MD5: str | None = None, SHA1: str | None = None, SHA256: str | None = None, SHA512: str | None = None, hashes: List[FetchDatasetHash] | None = None, description: str | None = None, src: typing_extensions.Literal[url], url: str)

Bases: BaseDataElement

src: typing_extensions.Literal[url]

url: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'MD5': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'SHA1': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-1', alias_priority=2), 'SHA256': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-256', alias_priority=2), 'SHA512': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-512', alias_priority=2), 'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'dbkey': FieldInfo(annotation=str, required=False, default='?'), 'deferred': FieldInfo(annotation=bool, required=False, default=False), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'ext': FieldInfo(annotation=str, required=False, default='auto'), 'extra_files': FieldInfo(annotation=Union[ExtraFiles, NoneType], required=False, default=None), 'hashes': FieldInfo(annotation=Union[List[galaxy.schema.fetch_data.FetchDatasetHash], NoneType], required=False, default=None), 'info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'items_from': FieldInfo(annotation=Union[ElementsFromType, NoneType], required=False, default=None, alias='elements_from', alias_priority=2), 'name': FieldInfo(annotation=Union[Annotated[Union[str, int, float, bool], AfterValidator(func=<function <lambda>>)], NoneType], required=False, default=None), 'space_to_tab': FieldInfo(annotation=bool, required=False, default=False), 'src': FieldInfo(annotation=Literal['url'], required=True), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'to_posix_lines': FieldInfo(annotation=bool, required=False, default=False), 'url': FieldInfo(annotation=str, required=True, description='URL to upload')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.ServerDirElement(*, name: str | int | float | bool[str | int | float | bool] | None = None, dbkey: str = '?', info: str | None = None, ext: str = 'auto', space_to_tab: bool = False, to_posix_lines: bool = False, deferred: bool = False, tags: List[str] | None = None, created_from_basename: str | None = None, extra_files: ExtraFiles | None = None, auto_decompress: bool = False, elements_from: ElementsFromType | None = None, collection_type: str | None = None, MD5: str | None = None, SHA1: str | None = None, SHA256: str | None = None, SHA512: str | None = None, hashes: List[FetchDatasetHash] | None = None, description: str | None = None, src: typing_extensions.Literal[server_dir], server_dir: str, link_data_only: bool | None = None)

Bases: BaseDataElement

src: typing_extensions.Literal[server_dir]

server_dir: str

link_data_only: bool | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'MD5': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'SHA1': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-1', alias_priority=2), 'SHA256': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-256', alias_priority=2), 'SHA512': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-512', alias_priority=2), 'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'dbkey': FieldInfo(annotation=str, required=False, default='?'), 'deferred': FieldInfo(annotation=bool, required=False, default=False), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'ext': FieldInfo(annotation=str, required=False, default='auto'), 'extra_files': FieldInfo(annotation=Union[ExtraFiles, NoneType], required=False, default=None), 'hashes': FieldInfo(annotation=Union[List[galaxy.schema.fetch_data.FetchDatasetHash], NoneType], required=False, default=None), 'info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'items_from': FieldInfo(annotation=Union[ElementsFromType, NoneType], required=False, default=None, alias='elements_from', alias_priority=2), 'link_data_only': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'name': FieldInfo(annotation=Union[Annotated[Union[str, int, float, bool], AfterValidator(func=<function <lambda>>)], NoneType], required=False, default=None), 'server_dir': FieldInfo(annotation=str, required=True), 'space_to_tab': FieldInfo(annotation=bool, required=False, default=False), 'src': FieldInfo(annotation=Literal['server_dir'], required=True), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'to_posix_lines': FieldInfo(annotation=bool, required=False, default=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.FtpImportElement(*, name: str | int | float | bool[str | int | float | bool] | None = None, dbkey: str = '?', info: str | None = None, ext: str = 'auto', space_to_tab: bool = False, to_posix_lines: bool = False, deferred: bool = False, tags: List[str] | None = None, created_from_basename: str | None = None, extra_files: ExtraFiles | None = None, auto_decompress: bool = False, elements_from: ElementsFromType | None = None, collection_type: str | None = None, MD5: str | None = None, SHA1: str | None = None, SHA256: str | None = None, SHA512: str | None = None, hashes: List[FetchDatasetHash] | None = None, description: str | None = None, src: typing_extensions.Literal[ftp_import], ftp_path: str)

Bases: BaseDataElement

src: typing_extensions.Literal[ftp_import]

ftp_path: str

collection_type: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'MD5': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'SHA1': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-1', alias_priority=2), 'SHA256': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-256', alias_priority=2), 'SHA512': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-512', alias_priority=2), 'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'dbkey': FieldInfo(annotation=str, required=False, default='?'), 'deferred': FieldInfo(annotation=bool, required=False, default=False), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'ext': FieldInfo(annotation=str, required=False, default='auto'), 'extra_files': FieldInfo(annotation=Union[ExtraFiles, NoneType], required=False, default=None), 'ftp_path': FieldInfo(annotation=str, required=True), 'hashes': FieldInfo(annotation=Union[List[galaxy.schema.fetch_data.FetchDatasetHash], NoneType], required=False, default=None), 'info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'items_from': FieldInfo(annotation=Union[ElementsFromType, NoneType], required=False, default=None, alias='elements_from', alias_priority=2), 'name': FieldInfo(annotation=Union[Annotated[Union[str, int, float, bool], AfterValidator(func=<function <lambda>>)], NoneType], required=False, default=None), 'space_to_tab': FieldInfo(annotation=bool, required=False, default=False), 'src': FieldInfo(annotation=Literal['ftp_import'], required=True), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'to_posix_lines': FieldInfo(annotation=bool, required=False, default=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.ItemsFromModel(*, src: ItemsFromSrc, path: str | None = None, ftp_path: str | None = None, server_dir: str | None = None, url: str | None = None)

Bases: Model

src: ItemsFromSrc

path: str | None

ftp_path: str | None

server_dir: str | None

url: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'ftp_path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'server_dir': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'src': FieldInfo(annotation=ItemsFromSrc, required=True), 'url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.FtpImportTarget(*, auto_decompress: bool = False, destination: HdcaDestination, collection_type: str | None = None, tags: List[str] | None = None, name: str | None = None, src: typing_extensions.Literal[ftp_import], ftp_path: str, elements_from: ElementsFromType | None = None)

Bases: BaseCollectionTarget

src: typing_extensions.Literal[ftp_import]

ftp_path: str

items_from: ElementsFromType | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'destination': FieldInfo(annotation=HdcaDestination, required=True), 'ftp_path': FieldInfo(annotation=str, required=True), 'items_from': FieldInfo(annotation=Union[ElementsFromType, NoneType], required=False, default=None, alias='elements_from', alias_priority=2), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'src': FieldInfo(annotation=Literal['ftp_import'], required=True), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.PathDataElement(*, name: str | int | float | bool[str | int | float | bool] | None = None, dbkey: str = '?', info: str | None = None, ext: str = 'auto', space_to_tab: bool = False, to_posix_lines: bool = False, deferred: bool = False, tags: List[str] | None = None, created_from_basename: str | None = None, extra_files: ExtraFiles | None = None, auto_decompress: bool = False, elements_from: ElementsFromType | None = None, collection_type: str | None = None, MD5: str | None = None, SHA1: str | None = None, SHA256: str | None = None, SHA512: str | None = None, hashes: List[FetchDatasetHash] | None = None, description: str | None = None, src: typing_extensions.Literal[path], path: str, link_data_only: bool | None = None)

Bases: BaseDataElement

src: typing_extensions.Literal[path]

path: str

items_from: ElementsFromType | None

link_data_only: bool | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'MD5': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'SHA1': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-1', alias_priority=2), 'SHA256': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-256', alias_priority=2), 'SHA512': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-512', alias_priority=2), 'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'dbkey': FieldInfo(annotation=str, required=False, default='?'), 'deferred': FieldInfo(annotation=bool, required=False, default=False), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'ext': FieldInfo(annotation=str, required=False, default='auto'), 'extra_files': FieldInfo(annotation=Union[ExtraFiles, NoneType], required=False, default=None), 'hashes': FieldInfo(annotation=Union[List[galaxy.schema.fetch_data.FetchDatasetHash], NoneType], required=False, default=None), 'info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'items_from': FieldInfo(annotation=Union[ElementsFromType, NoneType], required=False, default=None, alias='elements_from', alias_priority=2), 'link_data_only': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'name': FieldInfo(annotation=Union[Annotated[Union[str, int, float, bool], AfterValidator(func=<function <lambda>>)], NoneType], required=False, default=None), 'path': FieldInfo(annotation=str, required=True), 'space_to_tab': FieldInfo(annotation=bool, required=False, default=False), 'src': FieldInfo(annotation=Literal['path'], required=True), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'to_posix_lines': FieldInfo(annotation=bool, required=False, default=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.CompositeDataElement(*, name: str | int | float | bool[str | int | float | bool] | None = None, dbkey: str = '?', info: str | None = None, ext: str = 'auto', space_to_tab: bool = False, to_posix_lines: bool = False, deferred: bool = False, tags: List[str] | None = None, created_from_basename: str | None = None, extra_files: ExtraFiles | None = None, auto_decompress: bool = False, elements_from: ElementsFromType | None = None, collection_type: str | None = None, MD5: str | None = None, SHA1: str | None = None, SHA256: str | None = None, SHA512: str | None = None, hashes: List[FetchDatasetHash] | None = None, description: str | None = None, src: typing_extensions.Literal[composite], composite: CompositeItems, metadata: Dict[str, Any] | None = None)

Bases: BaseDataElement

src: typing_extensions.Literal[composite]

composite: CompositeItems

metadata: Dict[str, Any] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'MD5': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'SHA1': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-1', alias_priority=2), 'SHA256': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-256', alias_priority=2), 'SHA512': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-512', alias_priority=2), 'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'composite': FieldInfo(annotation=CompositeItems, required=True), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'dbkey': FieldInfo(annotation=str, required=False, default='?'), 'deferred': FieldInfo(annotation=bool, required=False, default=False), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'ext': FieldInfo(annotation=str, required=False, default='auto'), 'extra_files': FieldInfo(annotation=Union[ExtraFiles, NoneType], required=False, default=None), 'hashes': FieldInfo(annotation=Union[List[galaxy.schema.fetch_data.FetchDatasetHash], NoneType], required=False, default=None), 'info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'items_from': FieldInfo(annotation=Union[ElementsFromType, NoneType], required=False, default=None, alias='elements_from', alias_priority=2), 'metadata': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'name': FieldInfo(annotation=Union[Annotated[Union[str, int, float, bool], AfterValidator(func=<function <lambda>>)], NoneType], required=False, default=None), 'space_to_tab': FieldInfo(annotation=bool, required=False, default=False), 'src': FieldInfo(annotation=Literal['composite'], required=True), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'to_posix_lines': FieldInfo(annotation=bool, required=False, default=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.CompositeItems(*, elements: List[FileDataElement | PastedDataElement | UrlDataElement | PathDataElement | ServerDirElement | FtpImportElement])

Bases: FetchBaseModel

items: List[FileDataElement | PastedDataElement | UrlDataElement | PathDataElement | ServerDirElement | FtpImportElement]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'items': FieldInfo(annotation=List[Union[galaxy.schema.fetch_data.FileDataElement, galaxy.schema.fetch_data.PastedDataElement, galaxy.schema.fetch_data.UrlDataElement, galaxy.schema.fetch_data.PathDataElement, galaxy.schema.fetch_data.ServerDirElement, galaxy.schema.fetch_data.FtpImportElement]], required=True, alias='elements', alias_priority=2)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.NestedElement(*, name: str | int | float | bool[str | int | float | bool] | None = None, dbkey: str = '?', info: str | None = None, ext: str = 'auto', space_to_tab: bool = False, to_posix_lines: bool = False, deferred: bool = False, tags: List[str] | None = None, created_from_basename: str | None = None, extra_files: ExtraFiles | None = None, auto_decompress: bool = False, elements_from: ElementsFromType | None = None, collection_type: str | None = None, MD5: str | None = None, SHA1: str | None = None, SHA256: str | None = None, SHA512: str | None = None, hashes: List[FetchDatasetHash] | None = None, description: str | None = None, elements: List[FileDataElement | galaxy.schema.fetch_data.PastedDataElement | galaxy.schema.fetch_data.UrlDataElement | galaxy.schema.fetch_data.PathDataElement | galaxy.schema.fetch_data.ServerDirElement | galaxy.schema.fetch_data.FtpImportElement | galaxy.schema.fetch_data.CompositeDataElement[FileDataElement | PastedDataElement | UrlDataElement | PathDataElement | ServerDirElement | FtpImportElement | CompositeDataElement] | NestedElement])

Bases: BaseDataElement

items: List[AnyElement | NestedElement]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'forbid', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'MD5': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'SHA1': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-1', alias_priority=2), 'SHA256': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-256', alias_priority=2), 'SHA512': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='SHA-512', alias_priority=2), 'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'dbkey': FieldInfo(annotation=str, required=False, default='?'), 'deferred': FieldInfo(annotation=bool, required=False, default=False), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'ext': FieldInfo(annotation=str, required=False, default='auto'), 'extra_files': FieldInfo(annotation=Union[ExtraFiles, NoneType], required=False, default=None), 'hashes': FieldInfo(annotation=Union[List[galaxy.schema.fetch_data.FetchDatasetHash], NoneType], required=False, default=None), 'info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'items': FieldInfo(annotation=List[Union[Annotated[Union[galaxy.schema.fetch_data.FileDataElement, galaxy.schema.fetch_data.PastedDataElement, galaxy.schema.fetch_data.UrlDataElement, galaxy.schema.fetch_data.PathDataElement, galaxy.schema.fetch_data.ServerDirElement, galaxy.schema.fetch_data.FtpImportElement, galaxy.schema.fetch_data.CompositeDataElement], FieldInfo(annotation=NoneType, required=True, discriminator='src')], galaxy.schema.fetch_data.NestedElement]], required=True, alias='elements', alias_priority=2), 'items_from': FieldInfo(annotation=Union[ElementsFromType, NoneType], required=False, default=None, alias='elements_from', alias_priority=2), 'name': FieldInfo(annotation=Union[Annotated[Union[str, int, float, bool], AfterValidator(func=<function <lambda>>)], NoneType], required=False, default=None), 'space_to_tab': FieldInfo(annotation=bool, required=False, default=False), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'to_posix_lines': FieldInfo(annotation=bool, required=False, default=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.BaseDataTarget(*, auto_decompress: bool = False, destination: HdaDestination | LibraryFolderDestination | LibraryDestination)

Bases: BaseFetchDataTarget

destination: HdaDestination | LibraryFolderDestination | LibraryDestination

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'destination': FieldInfo(annotation=Union[HdaDestination, LibraryFolderDestination, LibraryDestination], required=True, discriminator='type')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.DataElementsTarget(*, auto_decompress: bool = False, destination: HdaDestination | LibraryFolderDestination | LibraryDestination, elements: List[FileDataElement | galaxy.schema.fetch_data.PastedDataElement | galaxy.schema.fetch_data.UrlDataElement | galaxy.schema.fetch_data.PathDataElement | galaxy.schema.fetch_data.ServerDirElement | galaxy.schema.fetch_data.FtpImportElement | galaxy.schema.fetch_data.CompositeDataElement[FileDataElement | PastedDataElement | UrlDataElement | PathDataElement | ServerDirElement | FtpImportElement | CompositeDataElement] | NestedElement])

Bases: BaseDataTarget

items: List[FileDataElement | galaxy.schema.fetch_data.PastedDataElement | galaxy.schema.fetch_data.UrlDataElement | galaxy.schema.fetch_data.PathDataElement | galaxy.schema.fetch_data.ServerDirElement | galaxy.schema.fetch_data.FtpImportElement | galaxy.schema.fetch_data.CompositeDataElement[FileDataElement | PastedDataElement | UrlDataElement | PathDataElement | ServerDirElement | FtpImportElement | CompositeDataElement] | NestedElement]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'destination': FieldInfo(annotation=Union[HdaDestination, LibraryFolderDestination, LibraryDestination], required=True, discriminator='type'), 'items': FieldInfo(annotation=List[Union[Annotated[Union[galaxy.schema.fetch_data.FileDataElement, galaxy.schema.fetch_data.PastedDataElement, galaxy.schema.fetch_data.UrlDataElement, galaxy.schema.fetch_data.PathDataElement, galaxy.schema.fetch_data.ServerDirElement, galaxy.schema.fetch_data.FtpImportElement, galaxy.schema.fetch_data.CompositeDataElement], FieldInfo(annotation=NoneType, required=True, discriminator='src')], galaxy.schema.fetch_data.NestedElement]], required=True, alias='elements', alias_priority=2)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.DataElementsFromTarget(*, src: ItemsFromSrc, path: str | None = None, ftp_path: str | None = None, server_dir: str | None = None, url: str | None = None, auto_decompress: bool = False, destination: HdaDestination | LibraryFolderDestination | LibraryDestination, elements_from: ElementsFromType)

Bases: BaseDataTarget, ItemsFromModel

items_from: ElementsFromType

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'destination': FieldInfo(annotation=Union[HdaDestination, LibraryFolderDestination, LibraryDestination], required=True, discriminator='type'), 'ftp_path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'items_from': FieldInfo(annotation=ElementsFromType, required=True, alias='elements_from', alias_priority=2), 'path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'server_dir': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'src': FieldInfo(annotation=ItemsFromSrc, required=True), 'url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.HdcaDataItemsTarget(*, auto_decompress: bool = False, destination: HdcaDestination, collection_type: str | None = None, tags: List[str] | None = None, name: str | None = None, elements: List[FileDataElement | galaxy.schema.fetch_data.PastedDataElement | galaxy.schema.fetch_data.UrlDataElement | galaxy.schema.fetch_data.PathDataElement | galaxy.schema.fetch_data.ServerDirElement | galaxy.schema.fetch_data.FtpImportElement | galaxy.schema.fetch_data.CompositeDataElement[FileDataElement | PastedDataElement | UrlDataElement | PathDataElement | ServerDirElement | FtpImportElement | CompositeDataElement] | NestedElement])

Bases: BaseCollectionTarget

items: List[FileDataElement | galaxy.schema.fetch_data.PastedDataElement | galaxy.schema.fetch_data.UrlDataElement | galaxy.schema.fetch_data.PathDataElement | galaxy.schema.fetch_data.ServerDirElement | galaxy.schema.fetch_data.FtpImportElement | galaxy.schema.fetch_data.CompositeDataElement[FileDataElement | PastedDataElement | UrlDataElement | PathDataElement | ServerDirElement | FtpImportElement | CompositeDataElement] | NestedElement]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'destination': FieldInfo(annotation=HdcaDestination, required=True), 'items': FieldInfo(annotation=List[Union[Annotated[Union[galaxy.schema.fetch_data.FileDataElement, galaxy.schema.fetch_data.PastedDataElement, galaxy.schema.fetch_data.UrlDataElement, galaxy.schema.fetch_data.PathDataElement, galaxy.schema.fetch_data.ServerDirElement, galaxy.schema.fetch_data.FtpImportElement, galaxy.schema.fetch_data.CompositeDataElement], FieldInfo(annotation=NoneType, required=True, discriminator='src')], galaxy.schema.fetch_data.NestedElement]], required=True, alias='elements', alias_priority=2), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.HdcaDataItemsFromTarget(*, src: ItemsFromSrc, path: str | None = None, ftp_path: str | None = None, server_dir: str | None = None, url: str | None = None, auto_decompress: bool = False, destination: HdcaDestination, collection_type: str | None = None, tags: List[str] | None = None, name: str | None = None, elements_from: ElementsFromType)

Bases: BaseCollectionTarget, ItemsFromModel

items_from: ElementsFromType

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'auto_decompress': FieldInfo(annotation=bool, required=False, default=False, description='Decompress compressed data before sniffing?'), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'destination': FieldInfo(annotation=HdcaDestination, required=True), 'ftp_path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'items_from': FieldInfo(annotation=ElementsFromType, required=True, alias='elements_from', alias_priority=2), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'server_dir': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'src': FieldInfo(annotation=ItemsFromSrc, required=True), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.FilesPayload(*, filename: str, local_filename: str)

Bases: Model

filename: str

local_filename: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'filename': FieldInfo(annotation=str, required=True), 'local_filename': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.BaseDataPayload(*, history_id: int[int], **extra_data: Any)

Bases: FetchBaseModel

history_id: int[int]

model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

classmethod targets_string_to_json(v)

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'history_id': FieldInfo(annotation=int, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.FetchDataPayload(*, history_id: int[int], targets: List[DataElementsTarget | HdcaDataItemsTarget | DataElementsFromTarget | HdcaDataItemsFromTarget | FtpImportTarget], **extra_data: Any)

Bases: BaseDataPayload

targets: List[DataElementsTarget | HdcaDataItemsTarget | DataElementsFromTarget | HdcaDataItemsFromTarget | FtpImportTarget]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'history_id': FieldInfo(annotation=int, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'targets': FieldInfo(annotation=List[Union[galaxy.schema.fetch_data.DataElementsTarget, galaxy.schema.fetch_data.HdcaDataItemsTarget, galaxy.schema.fetch_data.DataElementsFromTarget, galaxy.schema.fetch_data.HdcaDataItemsFromTarget, galaxy.schema.fetch_data.FtpImportTarget]], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.fetch_data.FetchDataFormPayload(*, history_id: int[int], targets: List[galaxy.schema.fetch_data.DataElementsTarget | galaxy.schema.fetch_data.HdcaDataItemsTarget | galaxy.schema.fetch_data.DataElementsFromTarget | galaxy.schema.fetch_data.HdcaDataItemsFromTarget | galaxy.schema.fetch_data.FtpImportTarget][List[DataElementsTarget | HdcaDataItemsTarget | DataElementsFromTarget | HdcaDataItemsFromTarget | FtpImportTarget]] | List[DataElementsTarget | HdcaDataItemsTarget | DataElementsFromTarget | HdcaDataItemsFromTarget | FtpImportTarget], **extra_data: Any)

Bases: BaseDataPayload

targets: List[galaxy.schema.fetch_data.DataElementsTarget | galaxy.schema.fetch_data.HdcaDataItemsTarget | galaxy.schema.fetch_data.DataElementsFromTarget | galaxy.schema.fetch_data.HdcaDataItemsFromTarget | galaxy.schema.fetch_data.FtpImportTarget][List[DataElementsTarget | HdcaDataItemsTarget | DataElementsFromTarget | HdcaDataItemsFromTarget | FtpImportTarget]] | List[DataElementsTarget | HdcaDataItemsTarget | DataElementsFromTarget | HdcaDataItemsFromTarget | FtpImportTarget]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'history_id': FieldInfo(annotation=int, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'targets': FieldInfo(annotation=Union[Annotated[List[Union[galaxy.schema.fetch_data.DataElementsTarget, galaxy.schema.fetch_data.HdcaDataItemsTarget, galaxy.schema.fetch_data.DataElementsFromTarget, galaxy.schema.fetch_data.HdcaDataItemsFromTarget, galaxy.schema.fetch_data.FtpImportTarget]], Json], List[Union[galaxy.schema.fetch_data.DataElementsTarget, galaxy.schema.fetch_data.HdcaDataItemsTarget, galaxy.schema.fetch_data.DataElementsFromTarget, galaxy.schema.fetch_data.HdcaDataItemsFromTarget, galaxy.schema.fetch_data.FtpImportTarget]]], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

galaxy.schema.fields module

class galaxy.schema.fields.Security

Bases: object

security: IdEncodingHelper

galaxy.schema.fields.ensure_valid_id(v: str) → str

galaxy.schema.fields.ensure_valid_folder_id(v)

galaxy.schema.fields.literal_to_value(arg)

galaxy.schema.fields.is_optional(field)

galaxy.schema.fields.ModelClassField(default_value)

Represents a database model class name annotated as a constant pydantic Field. :param class_name: The name of the database class. :return: A constant pydantic Field with default annotations for model classes.

galaxy.schema.fields.accept_wildcard_defaults_to_json(v)

galaxy.schema.remote_files module

class galaxy.schema.remote_files.RemoteFilesTarget(value)

Bases: str, Enum

An enumeration.

ftpdir = 'ftpdir'

userdir = 'userdir'

importdir = 'importdir'

class galaxy.schema.remote_files.RemoteFilesFormat(value)

Bases: str, Enum

An enumeration.

flat = 'flat'

jstree = 'jstree'

uri = 'uri'

class galaxy.schema.remote_files.RemoteFilesDisableMode(value)

Bases: str, Enum

An enumeration.

folders = 'folders'

files = 'files'

class galaxy.schema.remote_files.FilesSourceSupports(*, pagination: bool = False, search: bool = False, sorting: bool = False)

Bases: Model

pagination: bool[bool]

search: bool[bool]

sorting: bool[bool]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'pagination': FieldInfo(annotation=bool, required=False, default=False, description='Whether this file source supports server-side pagination.'), 'search': FieldInfo(annotation=bool, required=False, default=False, description='Whether this file source supports server-side search.'), 'sorting': FieldInfo(annotation=bool, required=False, default=False, description='Whether this file source supports server-side sorting.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.remote_files.FilesSourcePlugin(*, id: str, type: str, label: str, doc: str | None = None, browsable: bool, writable: bool, requires_roles: str | None = None, requires_groups: str | None = None, url: str | None = None, supports: FilesSourceSupports = FilesSourceSupports(pagination=False, search=False, sorting=False))

Bases: Model

id: str

type: str

label: str

doc: str | None

browsable: bool

writable: bool

requires_roles: str | None

requires_groups: str | None

url: str | None

supports: FilesSourceSupports[FilesSourceSupports]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'browsable': FieldInfo(annotation=bool, required=True, title='Browsable', description='Whether this file source plugin can list items.'), 'doc': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Documentation', description='Documentation or extended description for this plugin.', examples=["Galaxy's library import directory"]), 'id': FieldInfo(annotation=str, required=True, title='ID', description='The `FilesSource` plugin identifier', examples=['_import']), 'label': FieldInfo(annotation=str, required=True, title='Label', description='The display label for this plugin.', examples=['Library Import Directory']), 'requires_groups': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Requires groups', description='Only users belonging to the groups specified here can access this files source.'), 'requires_roles': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Requires roles', description='Only users with the roles specified here can access this files source.'), 'supports': FieldInfo(annotation=FilesSourceSupports, required=False, default=FilesSourceSupports(pagination=False, search=False, sorting=False), description='Features supported by this file source.'), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The type of the plugin.', examples=['gximport']), 'url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='URL', description='Optional URL that might be provided by some plugins to link to the remote source.'), 'writable': FieldInfo(annotation=bool, required=True, title='Writeable', description='Whether this files source plugin allows write access.', examples=[False])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.remote_files.BrowsableFilesSourcePlugin(*, id: str, type: str, label: str, doc: str | None = None, browsable: typing_extensions.Literal[True], writable: bool, requires_roles: str | None = None, requires_groups: str | None = None, url: str | None = None, supports: FilesSourceSupports = FilesSourceSupports(pagination=False, search=False, sorting=False), uri_root: str)

Bases: FilesSourcePlugin

browsable: typing_extensions.Literal[True]

uri_root: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'browsable': FieldInfo(annotation=Literal[True], required=True), 'doc': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Documentation', description='Documentation or extended description for this plugin.', examples=["Galaxy's library import directory"]), 'id': FieldInfo(annotation=str, required=True, title='ID', description='The `FilesSource` plugin identifier', examples=['_import']), 'label': FieldInfo(annotation=str, required=True, title='Label', description='The display label for this plugin.', examples=['Library Import Directory']), 'requires_groups': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Requires groups', description='Only users belonging to the groups specified here can access this files source.'), 'requires_roles': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Requires roles', description='Only users with the roles specified here can access this files source.'), 'supports': FieldInfo(annotation=FilesSourceSupports, required=False, default=FilesSourceSupports(pagination=False, search=False, sorting=False), description='Features supported by this file source.'), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The type of the plugin.', examples=['gximport']), 'uri_root': FieldInfo(annotation=str, required=True, title='URI root', description='The URI root used by this type of plugin.', examples=['gximport://']), 'url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='URL', description='Optional URL that might be provided by some plugins to link to the remote source.'), 'writable': FieldInfo(annotation=bool, required=True, title='Writeable', description='Whether this files source plugin allows write access.', examples=[False])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.remote_files.FilesSourcePluginList(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[BrowsableFilesSourcePlugin | FilesSourcePlugin]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[Union[galaxy.schema.remote_files.BrowsableFilesSourcePlugin, galaxy.schema.remote_files.FilesSourcePlugin]], required=False, default=[], title='List of files source plugins', examples=[{'id': '_import', 'type': 'gximport', 'uri_root': 'gximport://', 'label': 'Library Import Directory', 'doc': "Galaxy's library import directory", 'writable': False, 'browsable': True}])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.remote_files.RemoteEntry(*, name: str, uri: str, path: str)

Bases: Model

name: str

uri: str

path: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the entry.'), 'path': FieldInfo(annotation=str, required=True, title='Path', description='The path of the entry.'), 'uri': FieldInfo(annotation=str, required=True, title='URI', description='The URI of the entry.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.remote_files.RemoteDirectory(*, name: str, uri: str, path: str, class_: typing_extensions.Literal[Directory])

Bases: RemoteEntry

class_: typing_extensions.Literal[Directory]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'class_': FieldInfo(annotation=Literal['Directory'], required=True, alias='class', alias_priority=2), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the entry.'), 'path': FieldInfo(annotation=str, required=True, title='Path', description='The path of the entry.'), 'uri': FieldInfo(annotation=str, required=True, title='URI', description='The URI of the entry.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.remote_files.RemoteFile(*, name: str, uri: str, path: str, class_: typing_extensions.Literal[File], size: int, ctime: str)

Bases: RemoteEntry

class_: typing_extensions.Literal[File]

size: int

ctime: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'class_': FieldInfo(annotation=Literal['File'], required=True, alias='class', alias_priority=2), 'ctime': FieldInfo(annotation=str, required=True, title='Creation time', description='The creation time of the file.'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the entry.'), 'path': FieldInfo(annotation=str, required=True, title='Path', description='The path of the entry.'), 'size': FieldInfo(annotation=int, required=True, title='Size', description='The size of the file in bytes.'), 'uri': FieldInfo(annotation=str, required=True, title='URI', description='The URI of the entry.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.remote_files.ListJstreeResponse(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[Any]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[Any], required=False, default=[], title='List of files', description='List of files in Jstree format.', json_schema_extra={'deprecated': True})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.remote_files.ListUriResponse(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[RemoteFile | galaxy.schema.remote_files.RemoteDirectory[RemoteFile | RemoteDirectory]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[Annotated[Union[galaxy.schema.remote_files.RemoteFile, galaxy.schema.remote_files.RemoteDirectory], FieldInfo(annotation=NoneType, required=True, discriminator='class_')]], required=False, default=[], title='List of remote entries', description='List of directories and files.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.remote_files.CreateEntryPayload(*, target: str, name: str)

Bases: Model

target: str

name: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the entry to create.', examples=['my_new_entry']), 'target': FieldInfo(annotation=str, required=True, title='Target', description='The target file source to create the entry in.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.remote_files.CreatedEntryResponse(*, name: str, uri: str, external_link: str | None = None)

Bases: Model

name: str

uri: str

external_link: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'external_link': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='External link', description='An optional external link to the created entry if available.'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the created entry.', examples=['my_new_entry']), 'uri': FieldInfo(annotation=str, required=True, title='URI', description='The URI of the created entry.', examples=['gxfiles://my_new_entry'])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

galaxy.schema.schema module

This module contains general pydantic models and common schema field annotations for them.

class galaxy.schema.schema.DatasetState(value)

Bases: str, Enum

An enumeration.

NEW = 'new'

UPLOAD = 'upload'

QUEUED = 'queued'

RUNNING = 'running'

OK = 'ok'

EMPTY = 'empty'

ERROR = 'error'

PAUSED = 'paused'

SETTING_METADATA = 'setting_metadata'

FAILED_METADATA = 'failed_metadata'

DEFERRED = 'deferred'

DISCARDED = 'discarded'

classmethod values()

class galaxy.schema.schema.JobState(value)

Bases: str, Enum

An enumeration.

NEW = 'new'

RESUBMITTED = 'resubmitted'

UPLOAD = 'upload'

WAITING = 'waiting'

QUEUED = 'queued'

RUNNING = 'running'

OK = 'ok'

ERROR = 'error'

FAILED = 'failed'

PAUSED = 'paused'

DELETING = 'deleting'

DELETED = 'deleted'

STOPPING = 'stop'

STOPPED = 'stopped'

SKIPPED = 'skipped'

class galaxy.schema.schema.DatasetCollectionPopulatedState(value)

Bases: str, Enum

An enumeration.

NEW = 'new'

OK = 'ok'

FAILED = 'failed'

class galaxy.schema.schema.HashFunctionNames(value)

Bases: str, Enum

Hash function names that can be used to generate checksums for datasets.

md5 = 'MD5'

sha1 = 'SHA-1'

sha256 = 'SHA-256'

sha512 = 'SHA-512'

class galaxy.schema.schema.Model

Bases: BaseModel

Base model definition with common configuration used by all derived models.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.RequireOneSetOption

Bases: Model

check_some_ids_passed()

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.BaseUserModel(*, id: str[str], username: str, email: str, deleted: bool)

Bases: Model

id: str[str]

username: str

email: str

deleted: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description=' User is deleted'), 'email': FieldInfo(annotation=str, required=True, title='Email', description='Email of the user'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the user', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'username': FieldInfo(annotation=str, required=True, title='user_name', description='The name of the user.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WithModelClass

Bases: object

model_class: str

classmethod set_default(data)

class galaxy.schema.schema.UserModel(*, model_class: typing_extensions.Literal[User], id: str[str], username: str, email: str, deleted: bool, active: bool, last_password_change: datetime | None)

Bases: BaseUserModel, WithModelClass

User in a transaction context.

active: bool

model_class: typing_extensions.Literal[User]

last_password_change: datetime | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'active': FieldInfo(annotation=bool, required=True, title='Active', description='User is active'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description=' User is deleted'), 'email': FieldInfo(annotation=str, required=True, title='Email', description='Email of the user'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the user', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'last_password_change': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Last password change', description=''), 'model_class': FieldInfo(annotation=Literal['User'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'User', 'type': 'string'}), 'username': FieldInfo(annotation=str, required=True, title='user_name', description='The name of the user.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LimitedUserModel(*, id: str[str], username: str | None = None, email: str | None = None)

Bases: Model

This is used when config options (expose_user_name and expose_user_email) are in place.

id: str[str]

username: str | None

email: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'email': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the user', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'username': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DiskUsageUserModel(*, total_disk_usage: float, nice_total_disk_usage: str)

Bases: Model

total_disk_usage: float

nice_total_disk_usage: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'nice_total_disk_usage': FieldInfo(annotation=str, required=True, title='Nice total disc usage', description='Size of all non-purged, unique datasets of the user in a nice format.'), 'total_disk_usage': FieldInfo(annotation=float, required=True, title='Total disk usage', description='Size of all non-purged, unique datasets of the user in bytes.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CreatedUserModel(*, model_class: typing_extensions.Literal[User], total_disk_usage: float, nice_total_disk_usage: str, id: str[str], username: str, email: str, deleted: bool, active: bool, last_password_change: datetime | None, preferred_object_store_id: str | None = None)

Bases: UserModel, DiskUsageUserModel

preferred_object_store_id: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'active': FieldInfo(annotation=bool, required=True, title='Active', description='User is active'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description=' User is deleted'), 'email': FieldInfo(annotation=str, required=True, title='Email', description='Email of the user'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the user', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'last_password_change': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Last password change', description=''), 'model_class': FieldInfo(annotation=Literal['User'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'User', 'type': 'string'}), 'nice_total_disk_usage': FieldInfo(annotation=str, required=True, title='Nice total disc usage', description='Size of all non-purged, unique datasets of the user in a nice format.'), 'preferred_object_store_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Preferred Object Store ID', description='The ID of the object store that should be used to store new datasets in this history.'), 'total_disk_usage': FieldInfo(annotation=float, required=True, title='Total disk usage', description='Size of all non-purged, unique datasets of the user in bytes.'), 'username': FieldInfo(annotation=str, required=True, title='user_name', description='The name of the user.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.AnonUserModel(*, total_disk_usage: float, nice_total_disk_usage: str, quota_percent: float | None = None)

Bases: DiskUsageUserModel

quota_percent: float | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'nice_total_disk_usage': FieldInfo(annotation=str, required=True, title='Nice total disc usage', description='Size of all non-purged, unique datasets of the user in a nice format.'), 'quota_percent': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, title='Quota percent', description='Percentage of the storage quota applicable to the user.'), 'total_disk_usage': FieldInfo(annotation=float, required=True, title='Total disk usage', description='Size of all non-purged, unique datasets of the user in bytes.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DetailedUserModel(*, total_disk_usage: float, nice_total_disk_usage: str, quota_percent: float | None = None, id: str[str], username: str, email: str, deleted: bool, is_admin: bool, purged: bool, preferences: Dict[Any, Any], preferred_object_store_id: str | None = None, quota: str, quota_bytes: int | None = None, tags_used: List[str])

Bases: BaseUserModel, AnonUserModel

is_admin: bool

purged: bool

preferences: Dict[Any, Any]

preferred_object_store_id: str | None

quota: str

quota_bytes: int | None

tags_used: List[str]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description=' User is deleted'), 'email': FieldInfo(annotation=str, required=True, title='Email', description='Email of the user'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the user', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'is_admin': FieldInfo(annotation=bool, required=True, title='Is admin', description='User is admin'), 'nice_total_disk_usage': FieldInfo(annotation=str, required=True, title='Nice total disc usage', description='Size of all non-purged, unique datasets of the user in a nice format.'), 'preferences': FieldInfo(annotation=Dict[Any, Any], required=True, title='Preferences', description='Preferences of the user'), 'preferred_object_store_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Preferred Object Store ID', description='The ID of the object store that should be used to store new datasets in this history.'), 'purged': FieldInfo(annotation=bool, required=True, title='Purged', description='User is purged'), 'quota': FieldInfo(annotation=str, required=True, title='Quota', description='Quota applicable to the user'), 'quota_bytes': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Quota in bytes', description='Quota applicable to the user in bytes.'), 'quota_percent': FieldInfo(annotation=Union[float, NoneType], required=False, default=None, title='Quota percent', description='Percentage of the storage quota applicable to the user.'), 'tags_used': FieldInfo(annotation=List[str], required=True, title='Tags used', description='Tags used by the user'), 'total_disk_usage': FieldInfo(annotation=float, required=True, title='Total disk usage', description='Size of all non-purged, unique datasets of the user in bytes.'), 'username': FieldInfo(annotation=str, required=True, title='user_name', description='The name of the user.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UserUpdatePayload(*, active: bool | None = None, username: str | None = None, preferred_object_store_id: str | None = None)

Bases: Model

active: bool | None[bool | None]

username: str | None[str | None]

preferred_object_store_id: str | None[str | None]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'active': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Active', description='User is active'), 'preferred_object_store_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Preferred Object Store ID', description='The ID of the object store that should be used to store new datasets in this history.'), 'username': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username', description='The name of the user.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UserCreationPayload(*, password: str, email: str, username: str)

Bases: Model

password: str

email: str

username: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'email': FieldInfo(annotation=str, required=True, title='Email', description='Email of the user'), 'password': FieldInfo(annotation=str, required=True, title='user_password', description='The password of the user.'), 'username': FieldInfo(annotation=str, required=True, title='user_name', description='The name of the user.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.RemoteUserCreationPayload(*, remote_user_email: str)

Bases: Model

remote_user_email: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'remote_user_email': FieldInfo(annotation=str, required=True, title='Email', description='Email of the user')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UserDeletionPayload(*, purge: bool = False)

Bases: Model

purge: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'purge': FieldInfo(annotation=bool, required=False, default=False, title='Purge user', description='Purge the user. Deprecated, please use the `purge` query parameter instead.', json_schema_extra={'deprecated': True})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.FavoriteObject(*, object_id: str)

Bases: Model

object_id: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'object_id': FieldInfo(annotation=str, required=True, title='Object ID', description='The id of an object the user wants to favorite.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.FavoriteObjectsSummary(*, tools: List[str])

Bases: Model

tools: List[str]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'tools': FieldInfo(annotation=List[str], required=True, title='Favorite tools', description='The name of the tools the user favored.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.FavoriteObjectType(value)

Bases: str, Enum

An enumeration.

tools = 'tools'

class galaxy.schema.schema.DeletedCustomBuild(*, message: str)

Bases: Model

message: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'message': FieldInfo(annotation=str, required=True, title='Deletion message', description='Confirmation of the custom build deletion.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CustomBuildBaseModel(*, name: str)

Bases: Model

name: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the custom build.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CustomBuildLenType(value)

Bases: str, Enum

An enumeration.

file = 'file'

fasta = 'fasta'

text = 'text'

class galaxy.schema.schema.CustomBuildCreationPayload(*, name: str, len_type: CustomBuildLenType, len_value: str)

Bases: CustomBuildBaseModel

len_type: CustomBuildLenType

len_value: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'len_type': FieldInfo(annotation=CustomBuildLenType, required=True, alias='len|type', alias_priority=2, title='Length type', description='The type of the len file.'), 'len_value': FieldInfo(annotation=str, required=True, alias='len|value', alias_priority=2, title='Length value', description='The content of the length file.'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the custom build.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CreatedCustomBuild(*, name: str, len: str[str], count: str | None = None, fasta: str[str] | None = None, linecount: str[str] | None = None)

Bases: CustomBuildBaseModel

len: str[str]

count: str | None

fasta: str[str] | None

linecount: str[str] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'count': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Count', description='The number of chromosomes/contigs.'), 'fasta': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Fasta', description='The primary id of the fasta file from a history.'), 'len': FieldInfo(annotation=str, required=True, title='Length', description='The primary id of the len file.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'linecount': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Line count', description='The primary id of a linecount dataset.'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the custom build.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CustomBuildModel(*, name: str, len: str[str], count: str | None = None, fasta: str[str] | None = None, linecount: str[str] | None = None, id: str)

Bases: CreatedCustomBuild

id: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'count': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Count', description='The number of chromosomes/contigs.'), 'fasta': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Fasta', description='The primary id of the fasta file from a history.'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='The ID of the custom build.'), 'len': FieldInfo(annotation=str, required=True, title='Length', description='The primary id of the len file.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'linecount': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Line count', description='The primary id of a linecount dataset.'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the custom build.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CustomBuildsCollection(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[CustomBuildModel]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[galaxy.schema.schema.CustomBuildModel], required=True, title='Custom builds collection', description='The custom builds associated with the user.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.GroupModel(*, model_class: typing_extensions.Literal[Group], id: int[int], name: str)

Bases: Model, WithModelClass

User group model

model_class: typing_extensions.Literal[Group]

id: int[int]

name: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=int, required=True, title='ID', description='Encoded group ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['Group'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Group', 'type': 'string'}), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the group.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobSourceType(value)

Bases: str, Enum

Available types of job sources (model classes) that produce dataset collections.

Job = 'Job'

ImplicitCollectionJobs = 'ImplicitCollectionJobs'

WorkflowInvocation = 'WorkflowInvocation'

class galaxy.schema.schema.HistoryContentType(value)

Bases: str, Enum

Available types of History contents.

dataset = 'dataset'

dataset_collection = 'dataset_collection'

class galaxy.schema.schema.HistoryImportArchiveSourceType(value)

Bases: str, Enum

Available types of History archive sources.

url = 'url'

file = 'file'

class galaxy.schema.schema.DCEType(value)

Bases: str, Enum

Available types of dataset collection elements.

hda = 'hda'

dataset_collection = 'dataset_collection'

class galaxy.schema.schema.DatasetSourceType(value)

Bases: str, Enum

An enumeration.

hda = 'hda'

ldda = 'ldda'

class galaxy.schema.schema.DataItemSourceType(value)

Bases: str, Enum

An enumeration.

hda = 'hda'

ldda = 'ldda'

hdca = 'hdca'

dce = 'dce'

dc = 'dc'

class galaxy.schema.schema.ColletionSourceType(value)

Bases: str, Enum

An enumeration.

hda = 'hda'

ldda = 'ldda'

hdca = 'hdca'

new_collection = 'new_collection'

class galaxy.schema.schema.HistoryContentSource(value)

Bases: str, Enum

An enumeration.

hda = 'hda'

hdca = 'hdca'

library = 'library'

library_folder = 'library_folder'

new_collection = 'new_collection'

class galaxy.schema.schema.TagCollection(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

Represents the collection of tags associated with an item.

root: List[str[str]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[Annotated[str, FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(pattern='^([^\\s.:])+(\\.[^\\s.:]+)*(:\\S+)?$')])]], required=True, title='Tags', description='The collection of tags associated with an item.', examples=['COVID-19', '#myFancyTag', 'covid19.galaxyproject.org'])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.MetadataFile(*, file_type: str, download_url: str)

Bases: Model

Metadata file associated with a dataset.

file_type: str

download_url: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'download_url': FieldInfo(annotation=str, required=True, title='Download URL', description='The URL to download this item from the server.'), 'file_type': FieldInfo(annotation=str, required=True, title='File Type', description='TODO')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DatasetPermissions(*, manage: List[int[int]] = [], access: List[int[int]] = [])

Bases: Model

Role-based permissions for accessing and managing a dataset.

manage: List[int[int]]

access: List[int[int]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'access': FieldInfo(annotation=List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], required=False, default=[], title='Access', description='The set of roles (encoded IDs) that can access this dataset.'), 'manage': FieldInfo(annotation=List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], required=False, default=[], title='Management', description='The set of roles (encoded IDs) that can manage this dataset.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.Hyperlink(*, target: str, href: str, text: str)

Bases: Model

Represents some text with an Hyperlink.

target: str

href: str[str]

text: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'href': FieldInfo(annotation=str, required=True, title='Href', description='The URL of the linked document.'), 'target': FieldInfo(annotation=str, required=True, title='Target', description='Specifies where to open the linked document.', examples=['_blank']), 'text': FieldInfo(annotation=str, required=True, title='Text', description='The text placeholder for the link.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DisplayApp(*, label: str, links: List[Hyperlink])

Bases: Model

Basic linked information about an application that can display certain datatypes.

label: str

links: List[Hyperlink]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'label': FieldInfo(annotation=str, required=True, title='Label', description='The label or title of the Display Application.'), 'links': FieldInfo(annotation=List[galaxy.schema.schema.Hyperlink], required=True, title='Links', description='The collection of link details for this Display Application.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.Visualization

Bases: Model

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryItemBase(*, id: str[str], name: str | None, history_id: str[str], hid: int, deleted: bool, visible: bool)

Bases: Model

Basic information provided by items contained in a History.

id: str[str]

name: str | None

history_id: str[str]

hid: int

deleted: bool

visible: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'hid': FieldInfo(annotation=int, required=True, title='HID', description='The index position of this item in the History.'), 'history_id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'name': FieldInfo(annotation=Union[str, NoneType], required=True, title='Name', description='The name of the item.'), 'visible': FieldInfo(annotation=bool, required=True, title='Visible', description='Whether this item is visible or hidden to the user by default.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryItemCommon(*, id: str[str], name: str | None, history_id: str[str], hid: int, deleted: bool, visible: bool, type_id: str | None = None, type: str, create_time: datetime | None, update_time: datetime | None, url: str, tags: TagCollection)

Bases: HistoryItemBase

Common information provided by items contained in a History.

type_id: str | None

type: str

create_time: datetime | None

update_time: datetime | None

url: str[str]

tags: TagCollection

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'hid': FieldInfo(annotation=int, required=True, title='HID', description='The index position of this item in the History.'), 'history_id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'name': FieldInfo(annotation=Union[str, NoneType], required=True, title='Name', description='The name of the item.'), 'tags': FieldInfo(annotation=TagCollection, required=True), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The type of this item.'), 'type_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Type - ID', description='The type and the encoded ID of this item. Used for caching.', examples=['dataset-616e371b2cc6c62e']), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'visible': FieldInfo(annotation=bool, required=True, title='Visible', description='Whether this item is visible or hidden to the user by default.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDACommon(*, id: str[str], name: str | None, history_id: str[str], hid: int, deleted: bool, visible: bool, type_id: str | None = None, type: str, create_time: datetime | None, update_time: datetime | None, url: str, tags: TagCollection, history_content_type: typing_extensions.Literal[dataset], copied_from_ldda_id: str[str] | None = None)

Bases: HistoryItemCommon

history_content_type: typing_extensions.Literal[dataset][typing_extensions.Literal[dataset]]

copied_from_ldda_id: str[str] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'copied_from_ldda_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None), 'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'hid': FieldInfo(annotation=int, required=True, title='HID', description='The index position of this item in the History.'), 'history_content_type': FieldInfo(annotation=Literal['dataset'], required=True, title='History Content Type', description='This is always `dataset` for datasets.'), 'history_id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'name': FieldInfo(annotation=Union[str, NoneType], required=True, title='Name', description='The name of the item.'), 'tags': FieldInfo(annotation=TagCollection, required=True), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The type of this item.'), 'type_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Type - ID', description='The type and the encoded ID of this item. Used for caching.', examples=['dataset-616e371b2cc6c62e']), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'visible': FieldInfo(annotation=bool, required=True, title='Visible', description='Whether this item is visible or hidden to the user by default.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDASummary(*, id: str[str], name: str | None, history_id: str[str], hid: int, deleted: bool, visible: bool, type_id: str | None = None, type: str, create_time: datetime | None, update_time: datetime | None, url: str, tags: TagCollection, history_content_type: typing_extensions.Literal[dataset], copied_from_ldda_id: str[str] | None = None, dataset_id: str[str], state: DatasetState[DatasetState], extension: str | None, purged: bool, genome_build: str | None = '?')

Bases: HDACommon

History Dataset Association summary information.

dataset_id: str[str]

state: DatasetState[DatasetState]

extension: str | None

purged: bool

genome_build: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'copied_from_ldda_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None), 'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Create Time', description='The time and date this item was created.'), 'dataset_id': FieldInfo(annotation=str, required=True, title='Dataset ID', description='The encoded ID of the dataset associated with this item.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'extension': FieldInfo(annotation=Union[str, NoneType], required=True, title='Extension', description='The extension of the dataset.', examples=['txt']), 'genome_build': FieldInfo(annotation=Union[str, NoneType], required=False, default='?', title='Genome Build', description='TODO'), 'hid': FieldInfo(annotation=int, required=True, title='HID', description='The index position of this item in the History.'), 'history_content_type': FieldInfo(annotation=Literal['dataset'], required=True, title='History Content Type', description='This is always `dataset` for datasets.'), 'history_id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'name': FieldInfo(annotation=Union[str, NoneType], required=True, title='Name', description='The name of the item.'), 'purged': FieldInfo(annotation=bool, required=True, title='Purged', description='Whether this dataset has been removed from disk.'), 'state': FieldInfo(annotation=DatasetState, required=True, title='State', description='The current state of this dataset.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined)]), 'tags': FieldInfo(annotation=TagCollection, required=True), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The type of this item.'), 'type_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Type - ID', description='The type and the encoded ID of this item. Used for caching.', examples=['dataset-616e371b2cc6c62e']), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'visible': FieldInfo(annotation=bool, required=True, title='Visible', description='Whether this item is visible or hidden to the user by default.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDAInaccessible(*, id: str[str], name: str | None, history_id: str[str], hid: int, deleted: bool, visible: bool, type_id: str | None = None, type: str, create_time: datetime | None, update_time: datetime | None, url: str, tags: TagCollection, history_content_type: typing_extensions.Literal[dataset], copied_from_ldda_id: str[str] | None = None, accessible: typing_extensions.Literal[False], state: DatasetState[DatasetState])

Bases: HDACommon

History Dataset Association information when the user can not access it.

accessible: typing_extensions.Literal[False]

state: DatasetState[DatasetState]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'accessible': FieldInfo(annotation=Literal[False], required=True), 'copied_from_ldda_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None), 'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'hid': FieldInfo(annotation=int, required=True, title='HID', description='The index position of this item in the History.'), 'history_content_type': FieldInfo(annotation=Literal['dataset'], required=True, title='History Content Type', description='This is always `dataset` for datasets.'), 'history_id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'name': FieldInfo(annotation=Union[str, NoneType], required=True, title='Name', description='The name of the item.'), 'state': FieldInfo(annotation=DatasetState, required=True, title='State', description='The current state of this dataset.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined)]), 'tags': FieldInfo(annotation=TagCollection, required=True), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The type of this item.'), 'type_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Type - ID', description='The type and the encoded ID of this item. Used for caching.', examples=['dataset-616e371b2cc6c62e']), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'visible': FieldInfo(annotation=bool, required=True, title='Visible', description='Whether this item is visible or hidden to the user by default.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DatasetValidatedState(value)

Bases: str, Enum

An enumeration.

UNKNOWN = 'unknown'

INVALID = 'invalid'

OK = 'ok'

class galaxy.schema.schema.DatasetHash(*, model_class: typing_extensions.Literal[DatasetHash], id: str[str], hash_function: HashFunctionNames, hash_value: str, extra_files_path: str | None = None)

Bases: Model

model_class: typing_extensions.Literal[DatasetHash]

id: str[str]

hash_function: HashFunctionNames

hash_value: str

extra_files_path: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'extra_files_path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Extra Files Path', description='The path to the extra files used to generate the hash.'), 'hash_function': FieldInfo(annotation=HashFunctionNames, required=True, title='Hash Function', description='The hash function used to generate the hash.'), 'hash_value': FieldInfo(annotation=str, required=True, title='Hash Value', description='The hash value.'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the dataset hash.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['DatasetHash'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'DatasetHash', 'type': 'string'})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DatasetSource(*, id: str[str], source_uri: str, extra_files_path: str | None = None, transform: List[Any] | None = None)

Bases: Model

id: str[str]

source_uri: str[str]

extra_files_path: str | None[str | None]

transform: List[Any] | None[List[Any] | None]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'extra_files_path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Extra Files Path', description='The path to the extra files.'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the dataset source.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'source_uri': FieldInfo(annotation=str, required=True, title='Source URI', description='The URI of the dataset source.'), 'transform': FieldInfo(annotation=Union[List[Any], NoneType], required=False, default=None, title='Transform', description='The transformations applied to the dataset source.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDADetailed(*, model_class: typing_extensions.Literal[HistoryDatasetAssociation], id: str[str], name: str | None, history_id: str[str], hid: int, deleted: bool, visible: bool, type_id: str | None = None, type: typing_extensions.Literal[file] = 'file', create_time: datetime | None, update_time: datetime | None, url: str, tags: TagCollection, history_content_type: typing_extensions.Literal[dataset], copied_from_ldda_id: str[str] | None = None, dataset_id: str[str], state: DatasetState[DatasetState], extension: str | None, purged: bool, genome_build: str | None = '?', hda_ldda: DatasetSourceType = DatasetSourceType.hda, accessible: bool, misc_info: str | None = None, misc_blurb: str | None = None, file_ext: str, file_size: int, resubmitted: bool, metadata: Any | None = None, meta_files: List[MetadataFile], data_type: str, peek: str | None = None, creating_job: str, rerunnable: bool, uuid: UUID[UUID], permissions: DatasetPermissions, file_name: str | None = None, display_apps: List[DisplayApp], display_types: List[DisplayApp], validated_state: DatasetValidatedState, validated_state_message: str | None = None, annotation: str | None, download_url: str, api_type: typing_extensions.Literal[file] = 'file', created_from_basename: str | None = None, hashes: List[DatasetHash], drs_id: str, sources: List[DatasetSource], copied_from_history_dataset_association_id: str[str] | None = None)

Bases: HDASummary, WithModelClass

History Dataset Association detailed information.

model_class: typing_extensions.Literal[HistoryDatasetAssociation][typing_extensions.Literal[HistoryDatasetAssociation]]

hda_ldda: DatasetSourceType

accessible: bool

misc_info: str | None

misc_blurb: str | None

file_ext: str

file_size: int

resubmitted: bool

metadata: Any | None

meta_files: List[MetadataFile]

data_type: str

peek: str | None

creating_job: str

rerunnable: bool

uuid: UUID[UUID]

permissions: DatasetPermissions

file_name: str | None

display_apps: List[DisplayApp]

display_types: List[DisplayApp]

validated_state: DatasetValidatedState

validated_state_message: str | None

annotation: str | None

download_url: str

type: typing_extensions.Literal[file][typing_extensions.Literal[file]]

api_type: typing_extensions.Literal[file][typing_extensions.Literal[file]]

created_from_basename: str | None

hashes: List[galaxy.schema.schema.DatasetHash][List[DatasetHash]]

drs_id: str[str]

sources: List[galaxy.schema.schema.DatasetSource][List[DatasetSource]]

copied_from_history_dataset_association_id: str[str] | None[str[str] | None]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'accessible': FieldInfo(annotation=bool, required=True, title='Accessible', description='Whether this item is accessible to the current user due to permissions.'), 'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'api_type': FieldInfo(annotation=Literal['file'], required=False, default='file', title='API Type', description='TODO', json_schema_extra={'deprecated': True}), 'copied_from_history_dataset_association_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, description='ID of HDA this HDA was copied from.'), 'copied_from_ldda_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None), 'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Create Time', description='The time and date this item was created.'), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Created from basename', description='The basename of the output that produced this dataset.'), 'creating_job': FieldInfo(annotation=str, required=True, title='Creating Job ID', description='The encoded ID of the job that created this dataset.'), 'data_type': FieldInfo(annotation=str, required=True, title='Data Type', description='The fully qualified name of the class implementing the data type of this dataset.', examples=['galaxy.datatypes.data.Text']), 'dataset_id': FieldInfo(annotation=str, required=True, title='Dataset ID', description='The encoded ID of the dataset associated with this item.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'display_apps': FieldInfo(annotation=List[galaxy.schema.schema.DisplayApp], required=True, title='Display Applications', description='Contains new-style display app urls.'), 'display_types': FieldInfo(annotation=List[galaxy.schema.schema.DisplayApp], required=True, title='Legacy Display Applications', description='Contains old-style display app urls.'), 'download_url': FieldInfo(annotation=str, required=True, title='Download URL', description='The URL to download this item from the server.'), 'drs_id': FieldInfo(annotation=str, required=True, title='DRS ID', description='The DRS ID of the dataset.'), 'extension': FieldInfo(annotation=Union[str, NoneType], required=True, title='Extension', description='The extension of the dataset.', examples=['txt']), 'file_ext': FieldInfo(annotation=str, required=True, title='File extension', description='The extension of the file.'), 'file_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='File Name', description='The full path to the dataset file.'), 'file_size': FieldInfo(annotation=int, required=True, title='File Size', description='The file size in bytes.'), 'genome_build': FieldInfo(annotation=Union[str, NoneType], required=False, default='?', title='Genome Build', description='TODO'), 'hashes': FieldInfo(annotation=List[galaxy.schema.schema.DatasetHash], required=True, title='Hashes', description='The list of hashes associated with this dataset.'), 'hda_ldda': FieldInfo(annotation=DatasetSourceType, required=False, default=<DatasetSourceType.hda: 'hda'>, title='HDA or LDDA', description='Whether this dataset belongs to a history (HDA) or a library (LDDA).'), 'hid': FieldInfo(annotation=int, required=True, title='HID', description='The index position of this item in the History.'), 'history_content_type': FieldInfo(annotation=Literal['dataset'], required=True, title='History Content Type', description='This is always `dataset` for datasets.'), 'history_id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'meta_files': FieldInfo(annotation=List[galaxy.schema.schema.MetadataFile], required=True, title='Metadata Files', description='Collection of metadata files associated with this dataset.'), 'metadata': FieldInfo(annotation=Union[Any, NoneType], required=False, default=None, title='Metadata', description='The metadata associated with this dataset.'), 'misc_blurb': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Miscellaneous Blurb', description='TODO'), 'misc_info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Miscellaneous Information', description='TODO'), 'model_class': FieldInfo(annotation=Literal['HistoryDatasetAssociation'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'HistoryDatasetAssociation', 'type': 'string'}), 'name': FieldInfo(annotation=Union[str, NoneType], required=True, title='Name', description='The name of the item.'), 'peek': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Peek', description='A few lines of contents from the start of the file.'), 'permissions': FieldInfo(annotation=DatasetPermissions, required=True, title='Permissions', description='Role-based access and manage control permissions for the dataset.'), 'purged': FieldInfo(annotation=bool, required=True, title='Purged', description='Whether this dataset has been removed from disk.'), 'rerunnable': FieldInfo(annotation=bool, required=True, title='Rerunnable', description='Whether the job creating this dataset can be run again.'), 'resubmitted': FieldInfo(annotation=bool, required=True, title='Resubmitted', description='Whether the job creating this dataset has been resubmitted.'), 'sources': FieldInfo(annotation=List[galaxy.schema.schema.DatasetSource], required=True, title='Sources', description='The list of sources associated with this dataset.'), 'state': FieldInfo(annotation=DatasetState, required=True, title='State', description='The current state of this dataset.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined)]), 'tags': FieldInfo(annotation=TagCollection, required=True), 'type': FieldInfo(annotation=Literal['file'], required=False, default='file', title='Type', description='This is always `file` for datasets.'), 'type_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Type - ID', description='The type and the encoded ID of this item. Used for caching.', examples=['dataset-616e371b2cc6c62e']), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'uuid': FieldInfo(annotation=UUID, required=True, title='UUID', description='Universal unique identifier for this dataset.', metadata=[UuidVersion(uuid_version=4)]), 'validated_state': FieldInfo(annotation=DatasetValidatedState, required=True, title='Validated State', description='The state of the datatype validation for this dataset.'), 'validated_state_message': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Validated State Message', description='The message with details about the datatype validation result for this dataset.'), 'visible': FieldInfo(annotation=bool, required=True, title='Visible', description='Whether this item is visible or hidden to the user by default.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDAExtended(*, model_class: typing_extensions.Literal[HistoryDatasetAssociation], id: str[str], name: str | None, history_id: str[str], hid: int, deleted: bool, visible: bool, type_id: str | None = None, type: typing_extensions.Literal[file] = 'file', create_time: datetime | None, update_time: datetime | None, url: str, tags: TagCollection, history_content_type: typing_extensions.Literal[dataset], copied_from_ldda_id: str[str] | None = None, dataset_id: str[str], state: DatasetState[DatasetState], extension: str | None, purged: bool, genome_build: str | None = '?', hda_ldda: DatasetSourceType = DatasetSourceType.hda, accessible: bool, misc_info: str | None = None, misc_blurb: str | None = None, file_ext: str, file_size: int, resubmitted: bool, metadata: Any | None = None, meta_files: List[MetadataFile], data_type: str, peek: str | None = None, creating_job: str, rerunnable: bool, uuid: UUID[UUID], permissions: DatasetPermissions, file_name: str | None = None, display_apps: List[DisplayApp], display_types: List[DisplayApp], validated_state: DatasetValidatedState, validated_state_message: str | None = None, annotation: str | None, download_url: str, api_type: typing_extensions.Literal[file] = 'file', created_from_basename: str | None = None, hashes: List[DatasetHash], drs_id: str, sources: List[DatasetSource], copied_from_history_dataset_association_id: str[str] | None = None, tool_version: str, parent_id: int[int] | None = None, designation: str | None = None)

Bases: HDADetailed

History Dataset Association extended information.

tool_version: str

parent_id: int[int] | None

designation: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'accessible': FieldInfo(annotation=bool, required=True, title='Accessible', description='Whether this item is accessible to the current user due to permissions.'), 'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'api_type': FieldInfo(annotation=Literal['file'], required=False, default='file', title='API Type', description='TODO', json_schema_extra={'deprecated': True}), 'copied_from_history_dataset_association_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, description='ID of HDA this HDA was copied from.'), 'copied_from_ldda_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None), 'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Create Time', description='The time and date this item was created.'), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Created from basename', description='The basename of the output that produced this dataset.'), 'creating_job': FieldInfo(annotation=str, required=True, title='Creating Job ID', description='The encoded ID of the job that created this dataset.'), 'data_type': FieldInfo(annotation=str, required=True, title='Data Type', description='The fully qualified name of the class implementing the data type of this dataset.', examples=['galaxy.datatypes.data.Text']), 'dataset_id': FieldInfo(annotation=str, required=True, title='Dataset ID', description='The encoded ID of the dataset associated with this item.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'designation': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Designation', description='TODO'), 'display_apps': FieldInfo(annotation=List[galaxy.schema.schema.DisplayApp], required=True, title='Display Applications', description='Contains new-style display app urls.'), 'display_types': FieldInfo(annotation=List[galaxy.schema.schema.DisplayApp], required=True, title='Legacy Display Applications', description='Contains old-style display app urls.'), 'download_url': FieldInfo(annotation=str, required=True, title='Download URL', description='The URL to download this item from the server.'), 'drs_id': FieldInfo(annotation=str, required=True, title='DRS ID', description='The DRS ID of the dataset.'), 'extension': FieldInfo(annotation=Union[str, NoneType], required=True, title='Extension', description='The extension of the dataset.', examples=['txt']), 'file_ext': FieldInfo(annotation=str, required=True, title='File extension', description='The extension of the file.'), 'file_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='File Name', description='The full path to the dataset file.'), 'file_size': FieldInfo(annotation=int, required=True, title='File Size', description='The file size in bytes.'), 'genome_build': FieldInfo(annotation=Union[str, NoneType], required=False, default='?', title='Genome Build', description='TODO'), 'hashes': FieldInfo(annotation=List[galaxy.schema.schema.DatasetHash], required=True, title='Hashes', description='The list of hashes associated with this dataset.'), 'hda_ldda': FieldInfo(annotation=DatasetSourceType, required=False, default=<DatasetSourceType.hda: 'hda'>, title='HDA or LDDA', description='Whether this dataset belongs to a history (HDA) or a library (LDDA).'), 'hid': FieldInfo(annotation=int, required=True, title='HID', description='The index position of this item in the History.'), 'history_content_type': FieldInfo(annotation=Literal['dataset'], required=True, title='History Content Type', description='This is always `dataset` for datasets.'), 'history_id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'meta_files': FieldInfo(annotation=List[galaxy.schema.schema.MetadataFile], required=True, title='Metadata Files', description='Collection of metadata files associated with this dataset.'), 'metadata': FieldInfo(annotation=Union[Any, NoneType], required=False, default=None, title='Metadata', description='The metadata associated with this dataset.'), 'misc_blurb': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Miscellaneous Blurb', description='TODO'), 'misc_info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Miscellaneous Information', description='TODO'), 'model_class': FieldInfo(annotation=Literal['HistoryDatasetAssociation'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'HistoryDatasetAssociation', 'type': 'string'}), 'name': FieldInfo(annotation=Union[str, NoneType], required=True, title='Name', description='The name of the item.'), 'parent_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Parent ID', description='TODO'), 'peek': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Peek', description='A few lines of contents from the start of the file.'), 'permissions': FieldInfo(annotation=DatasetPermissions, required=True, title='Permissions', description='Role-based access and manage control permissions for the dataset.'), 'purged': FieldInfo(annotation=bool, required=True, title='Purged', description='Whether this dataset has been removed from disk.'), 'rerunnable': FieldInfo(annotation=bool, required=True, title='Rerunnable', description='Whether the job creating this dataset can be run again.'), 'resubmitted': FieldInfo(annotation=bool, required=True, title='Resubmitted', description='Whether the job creating this dataset has been resubmitted.'), 'sources': FieldInfo(annotation=List[galaxy.schema.schema.DatasetSource], required=True, title='Sources', description='The list of sources associated with this dataset.'), 'state': FieldInfo(annotation=DatasetState, required=True, title='State', description='The current state of this dataset.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined)]), 'tags': FieldInfo(annotation=TagCollection, required=True), 'tool_version': FieldInfo(annotation=str, required=True, title='Tool Version', description='The version of the tool that produced this dataset.'), 'type': FieldInfo(annotation=Literal['file'], required=False, default='file', title='Type', description='This is always `file` for datasets.'), 'type_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Type - ID', description='The type and the encoded ID of this item. Used for caching.', examples=['dataset-616e371b2cc6c62e']), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'uuid': FieldInfo(annotation=UUID, required=True, title='UUID', description='Universal unique identifier for this dataset.', metadata=[UuidVersion(uuid_version=4)]), 'validated_state': FieldInfo(annotation=DatasetValidatedState, required=True, title='Validated State', description='The state of the datatype validation for this dataset.'), 'validated_state_message': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Validated State Message', description='The message with details about the datatype validation result for this dataset.'), 'visible': FieldInfo(annotation=bool, required=True, title='Visible', description='Whether this item is visible or hidden to the user by default.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DCSummary(*, model_class: typing_extensions.Literal[DatasetCollection], id: str[str], create_time: datetime, update_time: datetime, collection_type: str, populated_state: DatasetCollectionPopulatedState, populated_state_message: str | None = None, element_count: int | None = None)

Bases: Model, WithModelClass

Dataset Collection summary information.

model_class: typing_extensions.Literal[DatasetCollection]

id: str[str]

create_time: datetime

update_time: datetime

collection_type: str

populated_state: DatasetCollectionPopulatedState

populated_state_message: str | None

element_count: int | None[int | None]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'collection_type': FieldInfo(annotation=str, required=True, title='Collection Type', description='The type of the collection, can be `list`, `paired`, or define subcollections using `:` as separator like `list:paired` or `list:list`.'), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'element_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Element Count', description='The number of elements contained in the dataset collection. It may be None or undefined if the collection could not be populated.'), 'id': FieldInfo(annotation=str, required=True, title='Dataset Collection ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['DatasetCollection'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'DatasetCollection', 'type': 'string'}), 'populated_state': FieldInfo(annotation=DatasetCollectionPopulatedState, required=True, title='Populated State', description="Indicates the general state of the elements in the dataset collection:- 'new': new dataset collection, unpopulated elements.- 'ok': collection elements populated (HDAs may or may not have errors).- 'failed': some problem populating, won't be populated."), 'populated_state_message': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Populated State Message', description='Optional message with further information in case the population of the dataset collection failed.'), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDAObject(*, model_class: typing_extensions.Literal[HistoryDatasetAssociation], id: str[str], state: DatasetState[DatasetState], hda_ldda: DatasetSourceType = DatasetSourceType.hda, history_id: str[str], tags: List[str], copied_from_ldda_id: str[str] | None = None, accessible: bool | None = None, purged: bool, **extra_data: Any)

Bases: Model, WithModelClass

History Dataset Association Object

id: str[str]

model_class: typing_extensions.Literal[HistoryDatasetAssociation]

state: DatasetState[DatasetState]

hda_ldda: DatasetSourceType

history_id: str[str]

tags: List[str]

copied_from_ldda_id: str[str] | None

accessible: bool | None

purged: bool

model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'accessible': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'copied_from_ldda_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None), 'hda_ldda': FieldInfo(annotation=DatasetSourceType, required=False, default=<DatasetSourceType.hda: 'hda'>, title='HDA or LDDA', description='Whether this dataset belongs to a history (HDA) or a library (LDDA).'), 'history_id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=str, required=True, title='History Dataset Association ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['HistoryDatasetAssociation'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'HistoryDatasetAssociation', 'type': 'string'}), 'purged': FieldInfo(annotation=bool, required=True), 'state': FieldInfo(annotation=DatasetState, required=True, title='State', description='The current state of this dataset.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined)]), 'tags': FieldInfo(annotation=List[str], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DCObject(*, model_class: typing_extensions.Literal[DatasetCollection], id: str[str], collection_type: str, populated: bool = None, element_count: int | None = None, contents_url: str[str] | None = None, elements: List[DCESummary] = [])

Bases: Model, WithModelClass

Dataset Collection Object

id: str[str]

model_class: typing_extensions.Literal[DatasetCollection]

collection_type: str

populated: bool[bool]

element_count: int | None[int | None]

contents_url: str[str] | None

elements: List[DCESummary]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'collection_type': FieldInfo(annotation=str, required=True, title='Collection Type', description='The type of the collection, can be `list`, `paired`, or define subcollections using `:` as separator like `list:paired` or `list:list`.'), 'contents_url': FieldInfo(annotation=Union[Annotated[str, FieldInfo(annotation=NoneType, required=True, title='Contents URL', description='The relative URL to access the contents of this History.')], NoneType], required=False, default=None), 'element_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Element Count', description='The number of elements contained in the dataset collection. It may be None or undefined if the collection could not be populated.'), 'elements': FieldInfo(annotation=List[galaxy.schema.schema.DCESummary], required=False, default=[], title='Elements', description='The summary information of each of the elements inside the dataset collection.'), 'id': FieldInfo(annotation=str, required=True, title='Dataset Collection ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['DatasetCollection'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'DatasetCollection', 'type': 'string'}), 'populated': FieldInfo(annotation=bool, required=False, default=None, title='Populated', description='Whether the dataset collection elements (and any subcollections elements) were successfully populated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DCESummary(*, model_class: typing_extensions.Literal[DatasetCollectionElement], id: str[str], element_index: int, element_identifier: str, element_type: DCEType | None = None, object: HDAObject | HDADetailed | DCObject | None = None)

Bases: Model, WithModelClass

Dataset Collection Element summary information.

id: str[str]

model_class: typing_extensions.Literal[DatasetCollectionElement]

element_index: int

element_identifier: str

element_type: DCEType | None

object: HDAObject | HDADetailed | DCObject | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'element_identifier': FieldInfo(annotation=str, required=True, title='Element Identifier', description='The actual name of this element.'), 'element_index': FieldInfo(annotation=int, required=True, title='Element Index', description='The position index of this element inside the collection.'), 'element_type': FieldInfo(annotation=Union[DCEType, NoneType], required=False, default=None, title='Element Type', description='The type of the element. Used to interpret the `object` field.'), 'id': FieldInfo(annotation=str, required=True, title='Dataset Collection Element ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['DatasetCollectionElement'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'DatasetCollectionElement', 'type': 'string'}), 'object': FieldInfo(annotation=Union[HDAObject, HDADetailed, DCObject, NoneType], required=False, default=None, title='Object', description="The element's specific data depending on the value of `element_type`.")}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DCDetailed(*, model_class: typing_extensions.Literal[DatasetCollection], id: str[str], create_time: datetime, update_time: datetime, collection_type: str, populated_state: DatasetCollectionPopulatedState, populated_state_message: str | None = None, element_count: int | None = None, populated: bool = None, elements: List[DCESummary] = [])

Bases: DCSummary

Dataset Collection detailed information.

populated: bool[bool]

elements: List[DCESummary]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'collection_type': FieldInfo(annotation=str, required=True, title='Collection Type', description='The type of the collection, can be `list`, `paired`, or define subcollections using `:` as separator like `list:paired` or `list:list`.'), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'element_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Element Count', description='The number of elements contained in the dataset collection. It may be None or undefined if the collection could not be populated.'), 'elements': FieldInfo(annotation=List[galaxy.schema.schema.DCESummary], required=False, default=[], title='Elements', description='The summary information of each of the elements inside the dataset collection.'), 'id': FieldInfo(annotation=str, required=True, title='Dataset Collection ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['DatasetCollection'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'DatasetCollection', 'type': 'string'}), 'populated': FieldInfo(annotation=bool, required=False, default=None, title='Populated', description='Whether the dataset collection elements (and any subcollections elements) were successfully populated.'), 'populated_state': FieldInfo(annotation=DatasetCollectionPopulatedState, required=True, title='Populated State', description="Indicates the general state of the elements in the dataset collection:- 'new': new dataset collection, unpopulated elements.- 'ok': collection elements populated (HDAs may or may not have errors).- 'failed': some problem populating, won't be populated."), 'populated_state_message': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Populated State Message', description='Optional message with further information in case the population of the dataset collection failed.'), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDCJobStateSummary(*, all_jobs: int = 0, new: int = 0, waiting: int = 0, running: int = 0, error: int = 0, paused: int = 0, skipped: int = 0, deleted_new: int = 0, resubmitted: int = 0, queued: int = 0, ok: int = 0, failed: int = 0, deleted: int = 0, upload: int = 0)

Bases: Model

Overview of the job states working inside a dataset collection.

all_jobs: int

new: int

waiting: int

running: int

error: int

paused: int

skipped: int

deleted_new: int

resubmitted: int

queued: int

ok: int

failed: int

deleted: int

upload: int

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'all_jobs': FieldInfo(annotation=int, required=False, default=0, title='All jobs', description='Total number of jobs associated with a dataset collection.'), 'deleted': FieldInfo(annotation=int, required=False, default=0, title='Deleted jobs', description='Number of jobs in the `deleted` state.'), 'deleted_new': FieldInfo(annotation=int, required=False, default=0, title='Deleted new jobs', description='Number of jobs in the `deleted_new` state.'), 'error': FieldInfo(annotation=int, required=False, default=0, title='Jobs with errors', description='Number of jobs in the `error` state.'), 'failed': FieldInfo(annotation=int, required=False, default=0, title='Failed jobs', description='Number of jobs in the `failed` state.'), 'new': FieldInfo(annotation=int, required=False, default=0, title='New jobs', description='Number of jobs in the `new` state.'), 'ok': FieldInfo(annotation=int, required=False, default=0, title='OK jobs', description='Number of jobs in the `ok` state.'), 'paused': FieldInfo(annotation=int, required=False, default=0, title='Paused jobs', description='Number of jobs in the `paused` state.'), 'queued': FieldInfo(annotation=int, required=False, default=0, title='Queued jobs', description='Number of jobs in the `queued` state.'), 'resubmitted': FieldInfo(annotation=int, required=False, default=0, title='Resubmitted jobs', description='Number of jobs in the `resubmitted` state.'), 'running': FieldInfo(annotation=int, required=False, default=0, title='Running jobs', description='Number of jobs in the `running` state.'), 'skipped': FieldInfo(annotation=int, required=False, default=0, title='Skipped jobs', description='Number of jobs that were skipped due to conditional workflow step execution.'), 'upload': FieldInfo(annotation=int, required=False, default=0, title='Upload jobs', description='Number of jobs in the `upload` state.'), 'waiting': FieldInfo(annotation=int, required=False, default=0, title='Waiting jobs', description='Number of jobs in the `waiting` state.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDCACommon(*, id: str[str], name: str | None, history_id: str[str], hid: int, deleted: bool, visible: bool, type_id: str | None = None, type: str, create_time: datetime | None, update_time: datetime | None, url: str, tags: TagCollection, history_content_type: typing_extensions.Literal[dataset_collection])

Bases: HistoryItemCommon

history_content_type: typing_extensions.Literal[dataset_collection][typing_extensions.Literal[dataset_collection]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'hid': FieldInfo(annotation=int, required=True, title='HID', description='The index position of this item in the History.'), 'history_content_type': FieldInfo(annotation=Literal['dataset_collection'], required=True, title='History Content Type', description='This is always `dataset_collection` for dataset collections.'), 'history_id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'name': FieldInfo(annotation=Union[str, NoneType], required=True, title='Name', description='The name of the item.'), 'tags': FieldInfo(annotation=TagCollection, required=True), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The type of this item.'), 'type_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Type - ID', description='The type and the encoded ID of this item. Used for caching.', examples=['dataset-616e371b2cc6c62e']), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'visible': FieldInfo(annotation=bool, required=True, title='Visible', description='Whether this item is visible or hidden to the user by default.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDCASummary(*, model_class: typing_extensions.Literal[HistoryDatasetCollectionAssociation], id: str[str], name: str | None, history_id: str[str], hid: int, deleted: bool, visible: bool, type_id: str | None = None, type: typing_extensions.Literal[collection] = 'collection', create_time: datetime | None, update_time: datetime | None, url: str, tags: TagCollection, history_content_type: typing_extensions.Literal[dataset_collection], collection_type: str, populated_state: DatasetCollectionPopulatedState, populated_state_message: str | None = None, element_count: int | None = None, elements_datatypes: Set[str], job_source_id: str[str] | None = None, job_source_type: JobSourceType | None = None, job_state_summary: HDCJobStateSummary | None = None, contents_url: str, collection_id: str[str])

Bases: HDCACommon, WithModelClass

History Dataset Collection Association summary information.

model_class: typing_extensions.Literal[HistoryDatasetCollectionAssociation]

type: typing_extensions.Literal[collection][typing_extensions.Literal[collection]]

collection_type: str

populated_state: DatasetCollectionPopulatedState

populated_state_message: str | None

element_count: int | None[int | None]

elements_datatypes: Set[str]

job_source_id: str[str] | None

job_source_type: JobSourceType | None

job_state_summary: HDCJobStateSummary | None

contents_url: str[str]

collection_id: str[str]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'collection_id': FieldInfo(annotation=str, required=True, title='Dataset Collection ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'collection_type': FieldInfo(annotation=str, required=True, title='Collection Type', description='The type of the collection, can be `list`, `paired`, or define subcollections using `:` as separator like `list:paired` or `list:list`.'), 'contents_url': FieldInfo(annotation=str, required=True, title='Contents URL', description='The relative URL to access the contents of this History.'), 'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'element_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Element Count', description='The number of elements contained in the dataset collection. It may be None or undefined if the collection could not be populated.'), 'elements_datatypes': FieldInfo(annotation=Set[str], required=True, description='A set containing all the different element datatypes in the collection.'), 'hid': FieldInfo(annotation=int, required=True, title='HID', description='The index position of this item in the History.'), 'history_content_type': FieldInfo(annotation=Literal['dataset_collection'], required=True, title='History Content Type', description='This is always `dataset_collection` for dataset collections.'), 'history_id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'job_source_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Job Source ID', description='The encoded ID of the Job that produced this dataset collection. Used to track the state of the job.'), 'job_source_type': FieldInfo(annotation=Union[JobSourceType, NoneType], required=False, default=None, title='Job Source Type', description='The type of job (model class) that produced this dataset collection. Used to track the state of the job.'), 'job_state_summary': FieldInfo(annotation=Union[HDCJobStateSummary, NoneType], required=False, default=None, title='Job State Summary', description='Overview of the job states working inside the dataset collection.'), 'model_class': FieldInfo(annotation=Literal['HistoryDatasetCollectionAssociation'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'HistoryDatasetCollectionAssociation', 'type': 'string'}), 'name': FieldInfo(annotation=Union[str, NoneType], required=True, title='Name', description='The name of the item.'), 'populated_state': FieldInfo(annotation=DatasetCollectionPopulatedState, required=True, title='Populated State', description="Indicates the general state of the elements in the dataset collection:- 'new': new dataset collection, unpopulated elements.- 'ok': collection elements populated (HDAs may or may not have errors).- 'failed': some problem populating, won't be populated."), 'populated_state_message': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Populated State Message', description='Optional message with further information in case the population of the dataset collection failed.'), 'tags': FieldInfo(annotation=TagCollection, required=True), 'type': FieldInfo(annotation=Literal['collection'], required=False, default='collection', title='Type', description='This is always `collection` for dataset collections.'), 'type_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Type - ID', description='The type and the encoded ID of this item. Used for caching.', examples=['dataset-616e371b2cc6c62e']), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'visible': FieldInfo(annotation=bool, required=True, title='Visible', description='Whether this item is visible or hidden to the user by default.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDCADetailed(*, model_class: typing_extensions.Literal[HistoryDatasetCollectionAssociation], id: str[str], name: str | None, history_id: str[str], hid: int, deleted: bool, visible: bool, type_id: str | None = None, type: typing_extensions.Literal[collection] = 'collection', create_time: datetime | None, update_time: datetime | None, url: str, tags: TagCollection, history_content_type: typing_extensions.Literal[dataset_collection], collection_type: str, populated_state: DatasetCollectionPopulatedState, populated_state_message: str | None = None, element_count: int | None = None, elements_datatypes: Set[str], job_source_id: str[str] | None = None, job_source_type: JobSourceType | None = None, job_state_summary: HDCJobStateSummary | None = None, contents_url: str, collection_id: str[str], populated: bool = None, elements: List[DCESummary] = [], implicit_collection_jobs_id: str[str] | None = None)

Bases: HDCASummary

History Dataset Collection Association detailed information.

populated: bool[bool]

elements: List[DCESummary]

implicit_collection_jobs_id: str[str] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'collection_id': FieldInfo(annotation=str, required=True, title='Dataset Collection ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'collection_type': FieldInfo(annotation=str, required=True, title='Collection Type', description='The type of the collection, can be `list`, `paired`, or define subcollections using `:` as separator like `list:paired` or `list:list`.'), 'contents_url': FieldInfo(annotation=str, required=True, title='Contents URL', description='The relative URL to access the contents of this History.'), 'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'element_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Element Count', description='The number of elements contained in the dataset collection. It may be None or undefined if the collection could not be populated.'), 'elements': FieldInfo(annotation=List[galaxy.schema.schema.DCESummary], required=False, default=[], title='Elements', description='The summary information of each of the elements inside the dataset collection.'), 'elements_datatypes': FieldInfo(annotation=Set[str], required=True, description='A set containing all the different element datatypes in the collection.'), 'hid': FieldInfo(annotation=int, required=True, title='HID', description='The index position of this item in the History.'), 'history_content_type': FieldInfo(annotation=Literal['dataset_collection'], required=True, title='History Content Type', description='This is always `dataset_collection` for dataset collections.'), 'history_id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'implicit_collection_jobs_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, description='Encoded ID for the ICJ object describing the collection of jobs corresponding to this collection'), 'job_source_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Job Source ID', description='The encoded ID of the Job that produced this dataset collection. Used to track the state of the job.'), 'job_source_type': FieldInfo(annotation=Union[JobSourceType, NoneType], required=False, default=None, title='Job Source Type', description='The type of job (model class) that produced this dataset collection. Used to track the state of the job.'), 'job_state_summary': FieldInfo(annotation=Union[HDCJobStateSummary, NoneType], required=False, default=None, title='Job State Summary', description='Overview of the job states working inside the dataset collection.'), 'model_class': FieldInfo(annotation=Literal['HistoryDatasetCollectionAssociation'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'HistoryDatasetCollectionAssociation', 'type': 'string'}), 'name': FieldInfo(annotation=Union[str, NoneType], required=True, title='Name', description='The name of the item.'), 'populated': FieldInfo(annotation=bool, required=False, default=None, title='Populated', description='Whether the dataset collection elements (and any subcollections elements) were successfully populated.'), 'populated_state': FieldInfo(annotation=DatasetCollectionPopulatedState, required=True, title='Populated State', description="Indicates the general state of the elements in the dataset collection:- 'new': new dataset collection, unpopulated elements.- 'ok': collection elements populated (HDAs may or may not have errors).- 'failed': some problem populating, won't be populated."), 'populated_state_message': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Populated State Message', description='Optional message with further information in case the population of the dataset collection failed.'), 'tags': FieldInfo(annotation=TagCollection, required=True), 'type': FieldInfo(annotation=Literal['collection'], required=False, default='collection', title='Type', description='This is always `collection` for dataset collections.'), 'type_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Type - ID', description='The type and the encoded ID of this item. Used for caching.', examples=['dataset-616e371b2cc6c62e']), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'visible': FieldInfo(annotation=bool, required=True, title='Visible', description='Whether this item is visible or hidden to the user by default.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryContentItemBase(*, history_content_type: HistoryContentType)

Bases: Model

Identifies a dataset or collection contained in a History.

history_content_type: HistoryContentType

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'history_content_type': FieldInfo(annotation=HistoryContentType, required=True, title='Content Type', description='The type of this item.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryContentItem(*, history_content_type: HistoryContentType, id: int[int])

Bases: HistoryContentItemBase

id: int[int]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'history_content_type': FieldInfo(annotation=HistoryContentType, required=True, title='Content Type', description='The type of this item.'), 'id': FieldInfo(annotation=int, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.EncodedHistoryContentItem(*, history_content_type: HistoryContentType, id: str[str])

Bases: HistoryContentItemBase

id: str[str]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'history_content_type': FieldInfo(annotation=HistoryContentType, required=True, title='Content Type', description='The type of this item.'), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UpdateContentItem(*, history_content_type: HistoryContentType, id: int[int], **extra_data: Any)

Bases: HistoryContentItem

Used for updating a particular history item. All fields are optional.

model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'history_content_type': FieldInfo(annotation=HistoryContentType, required=True, title='Content Type', description='The type of this item.'), 'id': FieldInfo(annotation=int, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

id: int[int]

history_content_type: HistoryContentType

class galaxy.schema.schema.UpdateHistoryContentsBatchPayload(*, items: List[UpdateContentItem], **extra_data: Any)

Bases: Model

Contains property values that will be updated for all the history items provided.

items: List[UpdateContentItem]

model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'json_schema_extra': {'example': {'items': [{'history_content_type': 'dataset', 'id': 'string'}], 'visible': False}}, 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'items': FieldInfo(annotation=List[galaxy.schema.schema.UpdateContentItem], required=True, title='Items', description='A list of content items to update with the changes.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryContentItemOperation(value)

Bases: str, Enum

An enumeration.

hide = 'hide'

unhide = 'unhide'

delete = 'delete'

undelete = 'undelete'

purge = 'purge'

change_datatype = 'change_datatype'

change_dbkey = 'change_dbkey'

add_tags = 'add_tags'

remove_tags = 'remove_tags'

class galaxy.schema.schema.BulkOperationParams(*, type: str)

Bases: Model

type: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'type': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ChangeDatatypeOperationParams(*, type: typing_extensions.Literal[change_datatype], datatype: str)

Bases: BulkOperationParams

type: typing_extensions.Literal[change_datatype]

datatype: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'datatype': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['change_datatype'], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ChangeDbkeyOperationParams(*, type: typing_extensions.Literal[change_dbkey], dbkey: str)

Bases: BulkOperationParams

type: typing_extensions.Literal[change_dbkey]

dbkey: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'dbkey': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['change_dbkey'], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.TagOperationParams(*, type: typing_extensions.Literal[add_tags] | typing_extensions.Literal[remove_tags], tags: List[str])

Bases: BulkOperationParams

type: typing_extensions.Literal[add_tags] | typing_extensions.Literal[remove_tags]

tags: List[str]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'tags': FieldInfo(annotation=List[str], required=True), 'type': FieldInfo(annotation=Union[Literal['add_tags'], Literal['remove_tags']], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryContentBulkOperationPayload(*, operation: HistoryContentItemOperation, items: List[HistoryContentItem] | None = None, params: ChangeDatatypeOperationParams | ChangeDbkeyOperationParams | TagOperationParams | None = None)

Bases: Model

operation: HistoryContentItemOperation

items: List[HistoryContentItem] | None

params: ChangeDatatypeOperationParams | ChangeDbkeyOperationParams | TagOperationParams | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'items': FieldInfo(annotation=Union[List[galaxy.schema.schema.HistoryContentItem], NoneType], required=False, default=None), 'operation': FieldInfo(annotation=HistoryContentItemOperation, required=True), 'params': FieldInfo(annotation=Union[ChangeDatatypeOperationParams, ChangeDbkeyOperationParams, TagOperationParams, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.BulkOperationItemError(*, item: EncodedHistoryContentItem, error: str)

Bases: Model

item: EncodedHistoryContentItem

error: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'error': FieldInfo(annotation=str, required=True), 'item': FieldInfo(annotation=EncodedHistoryContentItem, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryContentBulkOperationResult(*, success_count: int, errors: List[BulkOperationItemError])

Bases: Model

success_count: int

errors: List[BulkOperationItemError]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'errors': FieldInfo(annotation=List[galaxy.schema.schema.BulkOperationItemError], required=True), 'success_count': FieldInfo(annotation=int, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UpdateHistoryContentsPayload(*, name: str | None = None, deleted: bool | None = None, visible: bool | None = None, annotation: str | None = None, tags: TagCollection | None = None, **extra_data: Any)

Bases: Model

Can contain arbitrary/dynamic fields that will be updated for a particular history item.

name: str | None

deleted: bool | None

visible: bool | None

annotation: str | None

tags: TagCollection | None

model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'json_schema_extra': {'example': {'annotation': 'Test', 'visible': False}}, 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Annotation', description='A user-defined annotation for this item.'), 'deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Deleted', description='Whether this item is marked as deleted.'), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The new name of the item.'), 'tags': FieldInfo(annotation=Union[TagCollection, NoneType], required=False, default=None, title='Tags', description='A list of tags to add to this item.'), 'visible': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Visible', description='Whether this item is visible in the history.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistorySummary(*, model_class: typing_extensions.Literal[History], id: str[str], name: str, deleted: bool, purged: bool, archived: bool, url: str, published: bool, count: int, annotation: str | None, tags: TagCollection, update_time: datetime, preferred_object_store_id: str | None = None)

Bases: Model, WithModelClass

History summary information.

model_class: typing_extensions.Literal[History]

id: str[str]

name: str

deleted: bool

purged: bool

archived: bool

url: str[str]

published: bool

count: int

annotation: str | None

tags: TagCollection

update_time: datetime

preferred_object_store_id: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'archived': FieldInfo(annotation=bool, required=True, title='Archived', description='Whether this item has been archived and is no longer active.'), 'count': FieldInfo(annotation=int, required=True, title='Count', description='The number of items in the history.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['History'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'History', 'type': 'string'}), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the history.'), 'preferred_object_store_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Preferred Object Store ID', description='The ID of the object store that should be used to store new datasets in this history.'), 'published': FieldInfo(annotation=bool, required=True, title='Published', description='Whether this resource is currently publicly available to all users.'), 'purged': FieldInfo(annotation=bool, required=True, title='Purged', description='Whether this item has been permanently removed.'), 'tags': FieldInfo(annotation=TagCollection, required=True), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryActiveContentCounts(*, active: int, hidden: int, deleted: int)

Bases: Model

Contains the number of active, deleted or hidden items in a History.

active: int

hidden: int

deleted: int

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'active': FieldInfo(annotation=int, required=True, title='Active', description='Number of active datasets.'), 'deleted': FieldInfo(annotation=int, required=True, title='Deleted', description='Number of deleted datasets.'), 'hidden': FieldInfo(annotation=int, required=True, title='Hidden', description='Number of hidden datasets.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryDetailed(*, model_class: typing_extensions.Literal[History], id: str[str], name: str, deleted: bool, purged: bool, archived: bool, url: str, published: bool, count: int, annotation: str | None, tags: TagCollection, update_time: datetime, preferred_object_store_id: str | None = None, contents_url: str, size: int, user_id: str[str] | None = None, create_time: datetime, importable: bool, slug: str | None = None, username: str | None = None, username_and_slug: str | None = None, genome_build: str | None = '?', state: DatasetState, state_ids: Dict[DatasetState, List[int[int]]], state_details: Dict[DatasetState, int])

Bases: HistorySummary

History detailed information.

contents_url: str[str]

size: int

user_id: str[str] | None

create_time: datetime

importable: bool

slug: str | None

username: str | None

username_and_slug: str | None

genome_build: str | None

state: DatasetState

state_ids: Dict[DatasetState, List[int[int]]]

state_details: Dict[DatasetState, int]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'archived': FieldInfo(annotation=bool, required=True, title='Archived', description='Whether this item has been archived and is no longer active.'), 'contents_url': FieldInfo(annotation=str, required=True, title='Contents URL', description='The relative URL to access the contents of this History.'), 'count': FieldInfo(annotation=int, required=True, title='Count', description='The number of items in the history.'), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'genome_build': FieldInfo(annotation=Union[str, NoneType], required=False, default='?', title='Genome Build', description='TODO'), 'id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'importable': FieldInfo(annotation=bool, required=True, title='Importable', description='Whether this History can be imported by other users with a shared link.'), 'model_class': FieldInfo(annotation=Literal['History'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'History', 'type': 'string'}), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the history.'), 'preferred_object_store_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Preferred Object Store ID', description='The ID of the object store that should be used to store new datasets in this history.'), 'published': FieldInfo(annotation=bool, required=True, title='Published', description='Whether this resource is currently publicly available to all users.'), 'purged': FieldInfo(annotation=bool, required=True, title='Purged', description='Whether this item has been permanently removed.'), 'size': FieldInfo(annotation=int, required=True, title='Size', description='The total size of the contents of this history in bytes.'), 'slug': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Slug', description='Part of the URL to uniquely identify this History by link in a readable way.'), 'state': FieldInfo(annotation=DatasetState, required=True, title='State', description='The current state of the History based on the states of the datasets it contains.'), 'state_details': FieldInfo(annotation=Dict[galaxy.schema.schema.DatasetState, int], required=True, title='State Counts', description='A dictionary keyed to possible dataset states and valued with the number of datasets in this history that have those states.'), 'state_ids': FieldInfo(annotation=Dict[galaxy.schema.schema.DatasetState, List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]]], required=True, title='State IDs', description='A dictionary keyed to possible dataset states and valued with lists containing the ids of each HDA in that state.'), 'tags': FieldInfo(annotation=TagCollection, required=True), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'user_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='User ID', description='The encoded ID of the user that owns this History.'), 'username': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username', description='Owner of the history'), 'username_and_slug': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username and slug', description='The relative URL in the form of /u/{username}/h/{slug}')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CustomHistoryView(*, model_class: typing_extensions.Literal[History] | None = None, id: str | None[str | None] = None, name: str | None = None, deleted: bool | None = None, purged: bool | None = None, archived: bool | None = None, url: str | None = None, published: bool | None = None, count: int | None = None, annotation: str | None = None, tags: TagCollection | None = None, update_time: datetime | None = None, preferred_object_store_id: str | None = None, contents_url: str | None = None, size: int | None = None, user_id: str[str] | None = None, create_time: datetime | None = None, importable: bool | None = None, slug: str | None = None, username: str | None = None, username_and_slug: str | None = None, genome_build: str | None = None, state: DatasetState | None = None, state_ids: Dict[DatasetState, List[int[int]]] | None = None, state_details: Dict[DatasetState, int] | None = None, contents_active: HistoryActiveContentCounts | None = None, contents_states: Dict[DatasetState | DatasetCollectionPopulatedState, int] | None = None, nice_size: str | None = None)

Bases: CustomHistoryView

contents_active: HistoryActiveContentCounts | None

contents_states: Dict[DatasetState | DatasetCollectionPopulatedState, int] | None

nice_size: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'archived': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Archived', description='Whether this item has been archived and is no longer active.'), 'contents_active': FieldInfo(annotation=Union[HistoryActiveContentCounts, NoneType], required=False, default=None, title='Contents Active', description='Contains the number of active, deleted or hidden items in a History.'), 'contents_states': FieldInfo(annotation=Union[Dict[Union[galaxy.schema.schema.DatasetState, galaxy.schema.schema.DatasetCollectionPopulatedState], int], NoneType], required=False, default=None, title='Contents States', description='A dictionary keyed to possible dataset states and valued with the number of datasets in this history that have those states.'), 'contents_url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Contents URL', description='The relative URL to access the contents of this History.'), 'count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Count', description='The number of items in the history.'), 'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Deleted', description='Whether this item is marked as deleted.'), 'genome_build': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Genome Build', description='TODO'), 'id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'importable': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Importable', description='Whether this History can be imported by other users with a shared link.'), 'model_class': FieldInfo(annotation=Union[Literal['History'], NoneType], required=False, default=None, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'History', 'type': 'string'}), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The name of the history.'), 'nice_size': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Nice Size', description='The total size of the contents of this history in a human-readable format.'), 'preferred_object_store_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Preferred Object Store ID', description='The ID of the object store that should be used to store new datasets in this history.'), 'published': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Published', description='Whether this resource is currently publicly available to all users.'), 'purged': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Purged', description='Whether this item has been permanently removed.'), 'size': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Size', description='The total size of the contents of this history in bytes.'), 'slug': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Slug', description='Part of the URL to uniquely identify this History by link in a readable way.'), 'state': FieldInfo(annotation=Union[DatasetState, NoneType], required=False, default=None, title='State', description='The current state of the History based on the states of the datasets it contains.'), 'state_details': FieldInfo(annotation=Union[Dict[galaxy.schema.schema.DatasetState, int], NoneType], required=False, default=None, title='State Counts', description='A dictionary keyed to possible dataset states and valued with the number of datasets in this history that have those states.'), 'state_ids': FieldInfo(annotation=Union[Dict[galaxy.schema.schema.DatasetState, List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]]], NoneType], required=False, default=None, title='State IDs', description='A dictionary keyed to possible dataset states and valued with lists containing the ids of each HDA in that state.'), 'tags': FieldInfo(annotation=Union[TagCollection, NoneType], required=False, default=None), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'user_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='User ID', description='The encoded ID of the user that owns this History.'), 'username': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username', description='Owner of the history'), 'username_and_slug': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username and slug', description='The relative URL in the form of /u/{username}/h/{slug}')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

model_class: typing_extensions.Literal[History] | None

id: str | None

name: str | None

deleted: bool | None

purged: bool | None

archived: bool | None

url: str | None

published: bool | None

count: int | None

annotation: str | None

tags: TagCollection | None

update_time: datetime | None

preferred_object_store_id: str | None

contents_url: str | None

size: int | None

user_id: str[str] | None

create_time: datetime | None

importable: bool | None

slug: str | None

username: str | None

username_and_slug: str | None

genome_build: str | None

state: DatasetState | None

state_ids: Dict[DatasetState, List[int[int]]] | None

state_details: Dict[DatasetState, int] | None

class galaxy.schema.schema.UpdateHistoryPayload(*, name: str | None = None, annotation: str | None = None, tags: TagCollection | None = None, published: bool | None = None, importable: bool | None = None, deleted: bool | None = None, purged: bool | None = None, genome_build: str | None = None, preferred_object_store_id: str | None = None)

Bases: Model

name: str | None

annotation: str | None

tags: TagCollection | None

published: bool | None

importable: bool | None

deleted: bool | None

purged: bool | None

genome_build: str | None

preferred_object_store_id: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'genome_build': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'importable': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'preferred_object_store_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'published': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'purged': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'tags': FieldInfo(annotation=Union[TagCollection, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ExportHistoryArchivePayload(*, gzip: bool | None = True, include_hidden: bool | None = False, include_deleted: bool | None = False, file_name: str | None = None, directory_uri: str | None = None, force: bool | None = None)

Bases: Model

gzip: bool | None

include_hidden: bool | None

include_deleted: bool | None

file_name: str | None

directory_uri: str | None

force: bool | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'directory_uri': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Directory URI', description='A writable directory destination where the history will be exported using the `galaxy.files` URI infrastructure.'), 'file_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='File Name', description='The name of the file containing the exported history.'), 'force': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Force Rebuild', description='Whether to force a rebuild of the history archive.'), 'gzip': FieldInfo(annotation=Union[bool, NoneType], required=False, default=True, title='GZip', description='Whether to export as gzip archive.'), 'include_deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False, title='Include Deleted', description='Whether to include deleted datasets in the exported archive.'), 'include_hidden': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False, title='Include Hidden', description='Whether to include hidden datasets in the exported archive.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowIndexQueryPayload(*, show_deleted: bool = False, show_hidden: bool = False, show_published: bool | None = None, show_shared: bool | None = None, sort_by: typing_extensions.Literal[create_time, update_time, name] | None = None, sort_desc: bool | None = None, limit: int | None[int | None] = None, offset: int | None = 0, search: str | None = None, skip_step_counts: bool = False)

Bases: Model

show_deleted: bool

show_hidden: bool

show_published: bool | None

show_shared: bool | None

sort_by: typing_extensions.Literal[create_time, update_time, name] | None

sort_desc: bool | None

limit: int | None

offset: int | None

search: str | None

skip_step_counts: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'limit': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, metadata=[Lt(lt=1000)]), 'offset': FieldInfo(annotation=Union[int, NoneType], required=False, default=0, description='Number of workflows to skip'), 'search': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Filter text', description='Freetext to search.'), 'show_deleted': FieldInfo(annotation=bool, required=False, default=False), 'show_hidden': FieldInfo(annotation=bool, required=False, default=False), 'show_published': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'show_shared': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'skip_step_counts': FieldInfo(annotation=bool, required=False, default=False), 'sort_by': FieldInfo(annotation=Union[Literal['create_time', 'update_time', 'name'], NoneType], required=False, default=None, title='Sort By', description='Sort workflows by this attribute'), 'sort_desc': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Sort descending', description='Explicitly sort by descending if sort_by is specified.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobIndexSortByEnum(value)

Bases: str, Enum

An enumeration.

create_time = 'create_time'

update_time = 'update_time'

class galaxy.schema.schema.JobIndexQueryPayload(*, states: List[str] | None = None, user_details: bool = False, user_id: int[int] | None = None, tool_ids: List[str] | None = None, tool_ids_like: List[str] | None = None, date_range_min: datetime[datetime] | date | None = None, date_range_max: datetime[datetime] | date | None = None, history_id: int[int] | None = None, workflow_id: int[int] | None = None, invocation_id: int[int] | None = None, implicit_collection_jobs_id: int[int] | None = None, order_by: JobIndexSortByEnum = JobIndexSortByEnum.update_time, search: str | None = None, limit: int = 500, offset: int = 0)

Bases: Model

states: List[str] | None

user_details: bool

user_id: int[int] | None

tool_ids: List[str] | None

tool_ids_like: List[str] | None

date_range_min: datetime[datetime] | date | None

date_range_max: datetime[datetime] | date | None

history_id: int[int] | None

workflow_id: int[int] | None

invocation_id: int[int] | None

implicit_collection_jobs_id: int[int] | None

order_by: JobIndexSortByEnum

search: str | None

limit: int

offset: int

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'date_range_max': FieldInfo(annotation=Union[Annotated[datetime.datetime, AfterValidator(func=<function strip_tzinfo>)], date, NoneType], required=False, default=None), 'date_range_min': FieldInfo(annotation=Union[Annotated[datetime.datetime, AfterValidator(func=<function strip_tzinfo>)], date, NoneType], required=False, default=None), 'history_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None), 'implicit_collection_jobs_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None), 'invocation_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None), 'limit': FieldInfo(annotation=int, required=False, default=500), 'offset': FieldInfo(annotation=int, required=False, default=0), 'order_by': FieldInfo(annotation=JobIndexSortByEnum, required=False, default=<JobIndexSortByEnum.update_time: 'update_time'>), 'search': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'states': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'tool_ids': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'tool_ids_like': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None), 'user_details': FieldInfo(annotation=bool, required=False, default=False), 'user_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None), 'workflow_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.InvocationSortByEnum(value)

Bases: str, Enum

An enumeration.

create_time = 'create_time'

update_time = 'update_time'

none = 'None'

class galaxy.schema.schema.InvocationIndexQueryPayload(*, workflow_id: int | None = None, history_id: int | None = None, job_id: int | None = None, user_id: int | None = None, sort_by: InvocationSortByEnum | None = None, sort_desc: bool = False, include_terminal: bool = True, limit: int | None[int | None] = 100, offset: int | None = 0, include_nested_invocations: bool = True)

Bases: Model

workflow_id: int | None

history_id: int | None

job_id: int | None

user_id: int | None

sort_by: InvocationSortByEnum | None

sort_desc: bool

include_terminal: bool

limit: int | None

offset: int | None

include_nested_invocations: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'history_id': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='History ID', description='Return only invocations for this History ID'), 'include_nested_invocations': FieldInfo(annotation=bool, required=False, default=True), 'include_terminal': FieldInfo(annotation=bool, required=False, default=True, description='Set to false to only include terminal Invocations.'), 'job_id': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Job ID', description='Return only invocations for this Job ID'), 'limit': FieldInfo(annotation=Union[int, NoneType], required=False, default=100, metadata=[Lt(lt=1000)]), 'offset': FieldInfo(annotation=Union[int, NoneType], required=False, default=0, description='Number of invocations to skip'), 'sort_by': FieldInfo(annotation=Union[InvocationSortByEnum, NoneType], required=False, default=None, title='Sort By', description='Sort Workflow Invocations by this attribute'), 'sort_desc': FieldInfo(annotation=bool, required=False, default=False, description='Sort in descending order?'), 'user_id': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='User ID', description='Return invocations for this User ID'), 'workflow_id': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Workflow ID', description='Return only invocations for this Workflow ID')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.PageIndexQueryPayload(*, deleted: bool = False, limit: int | None[int | None] = 100, offset: int | None = 0, show_own: bool | None = None, show_published: bool | None = None, show_shared: bool | None = None, search: str | None = None, sort_by: typing_extensions.Literal[create_time, title, update_time, username] = 'update_time', sort_desc: bool | None = False, user_id: int[int] | None = None)

Bases: Model

deleted: bool

limit: int | None

offset: int | None

show_own: bool | None

show_published: bool | None

show_shared: bool | None

search: str | None

sort_by: typing_extensions.Literal[create_time, title, update_time, username]

sort_desc: bool | None

user_id: int[int] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'deleted': FieldInfo(annotation=bool, required=False, default=False), 'limit': FieldInfo(annotation=Union[int, NoneType], required=False, default=100, title='Limit', description='Maximum number of pages to return.', metadata=[Lt(lt=1000)]), 'offset': FieldInfo(annotation=Union[int, NoneType], required=False, default=0, title='Offset', description='Number of pages to skip.'), 'search': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Filter text', description='Freetext to search.'), 'show_own': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'show_published': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'show_shared': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'sort_by': FieldInfo(annotation=Literal['create_time', 'title', 'update_time', 'username'], required=False, default='update_time', title='Sort By', description='Sort pages by this attribute.'), 'sort_desc': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False, title='Sort descending', description='Sort in descending order.'), 'user_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CreateHistoryPayload(*, name: str | None = None, history_id: int[int] | None = None, all_datasets: bool | None = True, archive_source: str | None = None, archive_type: HistoryImportArchiveSourceType | None = HistoryImportArchiveSourceType.url, archive_file: Any | None = None)

Bases: Model

name: str | None

history_id: int[int] | None

all_datasets: bool | None

archive_source: str | None

archive_type: HistoryImportArchiveSourceType | None

archive_file: Any | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'all_datasets': FieldInfo(annotation=Union[bool, NoneType], required=False, default=True, title='All Datasets', description='Whether to copy also deleted HDAs/HDCAs. Only applies when providing a `history_id` to copy from.'), 'archive_file': FieldInfo(annotation=Union[Any, NoneType], required=False, default=None, title='Archive File', description='Uploaded file information when importing the history from a file.'), 'archive_source': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Archive Source', description="The URL that will generate the archive to import when `archive_type='url'`. "), 'archive_type': FieldInfo(annotation=Union[HistoryImportArchiveSourceType, NoneType], required=False, default=<HistoryImportArchiveSourceType.url: 'url'>, title='Archive Type', description='The type of source from where the new history will be imported.'), 'history_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='History ID', description='The encoded ID of the history to copy. Provide this value only if you want to copy an existing history.'), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The new history name.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CollectionElementIdentifier(*, name: str | None = None, src: ColletionSourceType, id: int[int] | None = None, collection_type: str | None = None, element_identifiers: List[CollectionElementIdentifier] | None = None, tags: List[str] | None = None)

Bases: Model

name: str | None

src: ColletionSourceType

id: int[int] | None

collection_type: str | None

element_identifiers: List[CollectionElementIdentifier] | None

tags: List[str] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Collection Type', description='The type of the collection, can be `list`, `paired`, or define subcollections using `:` as separator like `list:paired` or `list:list`.'), 'element_identifiers': FieldInfo(annotation=Union[List[galaxy.schema.schema.CollectionElementIdentifier], NoneType], required=False, default=None, title='Element Identifiers', description='List of elements that should be in the new sub-collection.'), 'id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='ID', description='The encoded ID of the element.'), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The name of the element.'), 'src': FieldInfo(annotation=ColletionSourceType, required=True, title='Source', description='The source of the element.'), 'tags': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None, title='Tags', description='The list of tags associated with the element.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CreateNewCollectionPayload(*, collection_type: str | None = None, element_identifiers: List[CollectionElementIdentifier] | None = None, name: str | None = None, hide_source_items: bool | None = False, copy_elements: bool | None = True, instance_type: typing_extensions.Literal[history, library] | None = 'history', history_id: int[int] | None = None, folder_id: int[int] | None = None)

Bases: Model

collection_type: str | None

element_identifiers: List[CollectionElementIdentifier] | None

name: str | None

hide_source_items: bool | None

copy_elements: bool | None

instance_type: typing_extensions.Literal[history, library] | None

history_id: int[int] | None

folder_id: int[int] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Collection Type', description='The type of the collection, can be `list`, `paired`, or define subcollections using `:` as separator like `list:paired` or `list:list`.'), 'copy_elements': FieldInfo(annotation=Union[bool, NoneType], required=False, default=True, title='Copy Elements', description='Whether to create a copy of the source HDAs for the new collection.'), 'element_identifiers': FieldInfo(annotation=Union[List[galaxy.schema.schema.CollectionElementIdentifier], NoneType], required=False, default=None, title='Element Identifiers', description='List of elements that should be in the new collection.'), 'folder_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_folder_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, description='The ID of the library folder that will contain the collection. Required if `instance_type=library`.'), 'hide_source_items': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False, title='Hide Source Items', description='Whether to mark the original HDAs as hidden.'), 'history_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, description='The ID of the history that will contain the collection. Required if `instance_type=history`.'), 'instance_type': FieldInfo(annotation=Union[Literal['history', 'library'], NoneType], required=False, default='history', title='Instance Type', description='The type of the instance, either `history` (default) or `library`.'), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The name of the new collection.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ModelStoreFormat(value)

Bases: str, Enum

Available types of model stores for export.

TGZ = 'tgz'

TAR = 'tar'

TAR_DOT_GZ = 'tar.gz'

BAG_DOT_ZIP = 'bag.zip'

BAG_DOT_TAR = 'bag.tar'

BAG_DOT_TGZ = 'bag.tgz'

ROCRATE_ZIP = 'rocrate.zip'

BCO_JSON = 'bco.json'

classmethod is_compressed(value: ModelStoreFormat)

classmethod is_bag(value: ModelStoreFormat)

class galaxy.schema.schema.StoreContentSource(*, store_content_uri: str | None = None, store_dict: Dict[str, Any] | None = None, model_store_format: ModelStoreFormat | None = None)

Bases: Model

store_content_uri: str | None

store_dict: Dict[str, Any] | None

model_store_format: ModelStoreFormat | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'model_store_format': FieldInfo(annotation=Union[ModelStoreFormat, NoneType], required=False, default=None), 'store_content_uri': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'store_dict': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CreateHistoryFromStore(*, store_content_uri: str | None = None, store_dict: Dict[str, Any] | None = None, model_store_format: ModelStoreFormat | None = None)

Bases: StoreContentSource

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'model_store_format': FieldInfo(annotation=Union[ModelStoreFormat, NoneType], required=False, default=None), 'store_content_uri': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'store_dict': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

store_content_uri: str | None

store_dict: Dict[str, Any] | None

model_store_format: ModelStoreFormat | None

class galaxy.schema.schema.StoreExportPayload(*, model_store_format: ModelStoreFormat = ModelStoreFormat.TAR_DOT_GZ, include_files: bool = True, include_deleted: bool = False, include_hidden: bool = False)

Bases: Model

model_store_format: ModelStoreFormat

include_files: bool

include_deleted: bool

include_hidden: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'include_deleted': FieldInfo(annotation=bool, required=False, default=False, title='Include deleted', description='Include file contents for deleted datasets (if include_files is True).'), 'include_files': FieldInfo(annotation=bool, required=False, default=True, description='include materialized files in export when available'), 'include_hidden': FieldInfo(annotation=bool, required=False, default=False, title='Include hidden', description='Include file contents for hidden datasets (if include_files is True).'), 'model_store_format': FieldInfo(annotation=ModelStoreFormat, required=False, default=<ModelStoreFormat.TAR_DOT_GZ: 'tar.gz'>, description='format of model store to export')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ShortTermStoreExportPayload(*, model_store_format: ModelStoreFormat = ModelStoreFormat.TAR_DOT_GZ, include_files: bool = True, include_deleted: bool = False, include_hidden: bool = False, short_term_storage_request_id: UUID, duration: int | float | None = None)

Bases: StoreExportPayload

short_term_storage_request_id: UUID

duration: int | float | None[int | float | None]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'duration': FieldInfo(annotation=Union[int, float, NoneType], required=False, default=None), 'include_deleted': FieldInfo(annotation=bool, required=False, default=False, title='Include deleted', description='Include file contents for deleted datasets (if include_files is True).'), 'include_files': FieldInfo(annotation=bool, required=False, default=True, description='include materialized files in export when available'), 'include_hidden': FieldInfo(annotation=bool, required=False, default=False, title='Include hidden', description='Include file contents for hidden datasets (if include_files is True).'), 'model_store_format': FieldInfo(annotation=ModelStoreFormat, required=False, default=<ModelStoreFormat.TAR_DOT_GZ: 'tar.gz'>, description='format of model store to export'), 'short_term_storage_request_id': FieldInfo(annotation=UUID, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.BcoGenerationParametersMixin(*, bco_merge_history_metadata: bool = False, bco_override_environment_variables: Dict[str, str] | None = None, bco_override_empirical_error: Dict[str, str] | None = None, bco_override_algorithmic_error: Dict[str, str] | None = None, bco_override_xref: List[XrefItem] | None = None)

Bases: BaseModel

bco_merge_history_metadata: bool

bco_override_environment_variables: Dict[str, str] | None

bco_override_empirical_error: Dict[str, str] | None

bco_override_algorithmic_error: Dict[str, str] | None

bco_override_xref: List[XrefItem] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'bco_merge_history_metadata': FieldInfo(annotation=bool, required=False, default=False, description='When reading tags/annotations to generate BCO object include history metadata.'), 'bco_override_algorithmic_error': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override algorithmic error for 'error domain' when generating BioCompute object."), 'bco_override_empirical_error': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override empirical error for 'error domain' when generating BioCompute object."), 'bco_override_environment_variables': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override environment variables for 'execution_domain' when generating BioCompute object."), 'bco_override_xref': FieldInfo(annotation=Union[List[galaxy.schema.bco.description_domain.XrefItem], NoneType], required=False, default=None, description="Override xref for 'description domain' when generating BioCompute object.")}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WriteStoreToPayload(*, model_store_format: ModelStoreFormat = ModelStoreFormat.TAR_DOT_GZ, include_files: bool = True, include_deleted: bool = False, include_hidden: bool = False, target_uri: str)

Bases: StoreExportPayload

target_uri: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'include_deleted': FieldInfo(annotation=bool, required=False, default=False, title='Include deleted', description='Include file contents for deleted datasets (if include_files is True).'), 'include_files': FieldInfo(annotation=bool, required=False, default=True, description='include materialized files in export when available'), 'include_hidden': FieldInfo(annotation=bool, required=False, default=False, title='Include hidden', description='Include file contents for hidden datasets (if include_files is True).'), 'model_store_format': FieldInfo(annotation=ModelStoreFormat, required=False, default=<ModelStoreFormat.TAR_DOT_GZ: 'tar.gz'>, description='format of model store to export'), 'target_uri': FieldInfo(annotation=str, required=True, title='Target URI', description='Galaxy Files URI to write mode store content to.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ObjectExportResponseBase(*, id: str[str], ready: bool, preparing: bool, up_to_date: bool)

Bases: Model

id: str[str]

ready: bool

preparing: bool

up_to_date: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, title='ID', description='The encoded database ID of the export request.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'preparing': FieldInfo(annotation=bool, required=True, title='Preparing', description='Whether the archive is currently being built or in preparation.'), 'ready': FieldInfo(annotation=bool, required=True, title='Ready', description='Whether the export has completed successfully and the archive is ready'), 'up_to_date': FieldInfo(annotation=bool, required=True, title='Up to Date', description='False, if a new export archive should be generated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobExportHistoryArchiveModel(*, id: str[str], ready: bool, preparing: bool, up_to_date: bool, job_id: str[str], download_url: str, external_download_latest_url: Url, external_download_permanent_url: Url)

Bases: ObjectExportResponseBase

job_id: str[str]

download_url: str

external_download_latest_url: Url

external_download_permanent_url: Url

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'download_url': FieldInfo(annotation=str, required=True, title='Download URL', description='Relative API URL to download the exported history archive.'), 'external_download_latest_url': FieldInfo(annotation=Url, required=True, title='External Download Latest URL', description='Fully qualified URL to download the latests version of the exported history archive.'), 'external_download_permanent_url': FieldInfo(annotation=Url, required=True, title='External Download Permanent URL', description='Fully qualified URL to download this particular version of the exported history archive.'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='The encoded database ID of the export request.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'job_id': FieldInfo(annotation=str, required=True, title='Job ID', description='The encoded database ID of the job that generated this history export archive.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'preparing': FieldInfo(annotation=bool, required=True, title='Preparing', description='Whether the archive is currently being built or in preparation.'), 'ready': FieldInfo(annotation=bool, required=True, title='Ready', description='Whether the export has completed successfully and the archive is ready'), 'up_to_date': FieldInfo(annotation=bool, required=True, title='Up to Date', description='False, if a new export archive should be generated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ExportObjectType(value)

Bases: str, Enum

Types of objects that can be exported.

HISTORY = 'history'

INVOCATION = 'invocation'

class galaxy.schema.schema.ExportObjectRequestMetadata(*, object_id: str[str], object_type: ExportObjectType, user_id: str[str] | None = None, payload: WriteStoreToPayload | ShortTermStoreExportPayload)

Bases: Model

object_id: str[str]

object_type: ExportObjectType

user_id: str[str] | None

payload: WriteStoreToPayload | ShortTermStoreExportPayload

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'object_id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'object_type': FieldInfo(annotation=ExportObjectType, required=True), 'payload': FieldInfo(annotation=Union[WriteStoreToPayload, ShortTermStoreExportPayload], required=True), 'user_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ExportObjectResultMetadata(*, success: bool, error: str | None = None)

Bases: Model

success: bool

error: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'error': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'success': FieldInfo(annotation=bool, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ExportObjectMetadata(*, request_data: ExportObjectRequestMetadata, result_data: ExportObjectResultMetadata | None = None)

Bases: Model

request_data: ExportObjectRequestMetadata

result_data: ExportObjectResultMetadata | None

is_short_term()

Whether the export is a short term export.

is_ready()

Whether the export has finished and it’s ready to be used.

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'request_data': FieldInfo(annotation=ExportObjectRequestMetadata, required=True), 'result_data': FieldInfo(annotation=Union[ExportObjectResultMetadata, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ObjectExportTaskResponse(*, id: str[str], ready: bool, preparing: bool, up_to_date: bool, task_uuid: UUID[UUID], create_time: datetime, export_metadata: ExportObjectMetadata | None = None)

Bases: ObjectExportResponseBase

task_uuid: UUID[UUID]

create_time: datetime

export_metadata: ExportObjectMetadata | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'export_metadata': FieldInfo(annotation=Union[ExportObjectMetadata, NoneType], required=False, default=None), 'id': FieldInfo(annotation=str, required=True, title='ID', description='The encoded database ID of the export request.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'preparing': FieldInfo(annotation=bool, required=True, title='Preparing', description='Whether the archive is currently being built or in preparation.'), 'ready': FieldInfo(annotation=bool, required=True, title='Ready', description='Whether the export has completed successfully and the archive is ready'), 'task_uuid': FieldInfo(annotation=UUID, required=True, title='Task ID', description='The identifier of the task processing the export.', metadata=[UuidVersion(uuid_version=4)]), 'up_to_date': FieldInfo(annotation=bool, required=True, title='Up to Date', description='False, if a new export archive should be generated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobExportHistoryArchiveListResponse(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[JobExportHistoryArchiveModel]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[galaxy.schema.schema.JobExportHistoryArchiveModel], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ExportTaskListResponse(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[ObjectExportTaskResponse]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[galaxy.schema.schema.ObjectExportTaskResponse], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ArchiveHistoryRequestPayload(*, archive_export_id: int[int] | None = None, purge_history: bool = False)

Bases: Model

archive_export_id: int[int] | None

purge_history: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'archive_export_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Export Record ID', description='The encoded ID of the export record to associate with this history archival.This is used to be able to recover the history from the export record.'), 'purge_history': FieldInfo(annotation=bool, required=False, default=False, title='Purge History', description='Whether to purge the history after archiving it. It requires an `archive_export_id` to be set.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ExportRecordData(*, model_store_format: ModelStoreFormat = ModelStoreFormat.TAR_DOT_GZ, include_files: bool = True, include_deleted: bool = False, include_hidden: bool = False, target_uri: str)

Bases: WriteStoreToPayload

Data of an export record associated with a history that was archived.

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'include_deleted': FieldInfo(annotation=bool, required=False, default=False, title='Include deleted', description='Include file contents for deleted datasets (if include_files is True).'), 'include_files': FieldInfo(annotation=bool, required=False, default=True, description='include materialized files in export when available'), 'include_hidden': FieldInfo(annotation=bool, required=False, default=False, title='Include hidden', description='Include file contents for hidden datasets (if include_files is True).'), 'model_store_format': FieldInfo(annotation=ModelStoreFormat, required=False, default=<ModelStoreFormat.TAR_DOT_GZ: 'tar.gz'>, description='format of model store to export'), 'target_uri': FieldInfo(annotation=str, required=True, title='Target URI', description='Galaxy Files URI to write mode store content to.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

target_uri: str

model_store_format: ModelStoreFormat

include_files: bool

include_deleted: bool

include_hidden: bool

class galaxy.schema.schema.ExportAssociationData(*, export_record_data: ExportRecordData | None = None)

Bases: Model

export_record_data: ExportRecordData | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'export_record_data': FieldInfo(annotation=Union[ExportRecordData, NoneType], required=False, default=None, title='Export Record Data', description='The export record data associated with this archived history. Used to recover the history.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ArchivedHistorySummary(*, model_class: typing_extensions.Literal[History], export_record_data: ExportRecordData | None = None, id: str[str], name: str, deleted: bool, purged: bool, archived: bool, url: str, published: bool, count: int, annotation: str | None, tags: TagCollection, update_time: datetime, preferred_object_store_id: str | None = None)

Bases: HistorySummary, ExportAssociationData

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'archived': FieldInfo(annotation=bool, required=True, title='Archived', description='Whether this item has been archived and is no longer active.'), 'count': FieldInfo(annotation=int, required=True, title='Count', description='The number of items in the history.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'export_record_data': FieldInfo(annotation=Union[ExportRecordData, NoneType], required=False, default=None, title='Export Record Data', description='The export record data associated with this archived history. Used to recover the history.'), 'id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['History'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'History', 'type': 'string'}), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the history.'), 'preferred_object_store_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Preferred Object Store ID', description='The ID of the object store that should be used to store new datasets in this history.'), 'published': FieldInfo(annotation=bool, required=True, title='Published', description='Whether this resource is currently publicly available to all users.'), 'purged': FieldInfo(annotation=bool, required=True, title='Purged', description='Whether this item has been permanently removed.'), 'tags': FieldInfo(annotation=TagCollection, required=True), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

model_class: typing_extensions.Literal[History]

id: str[str]

name: str

deleted: bool

purged: bool

archived: bool

url: str[str]

published: bool

count: int

annotation: str | None

tags: TagCollection

update_time: datetime

preferred_object_store_id: str | None

class galaxy.schema.schema.ArchivedHistoryDetailed(*, model_class: typing_extensions.Literal[History], export_record_data: ExportRecordData | None = None, id: str[str], name: str, deleted: bool, purged: bool, archived: bool, url: str, published: bool, count: int, annotation: str | None, tags: TagCollection, update_time: datetime, preferred_object_store_id: str | None = None, contents_url: str, size: int, user_id: str[str] | None = None, create_time: datetime, importable: bool, slug: str | None = None, username: str | None = None, username_and_slug: str | None = None, genome_build: str | None = '?', state: DatasetState, state_ids: Dict[DatasetState, List[int[int]]], state_details: Dict[DatasetState, int])

Bases: HistoryDetailed, ExportAssociationData

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'archived': FieldInfo(annotation=bool, required=True, title='Archived', description='Whether this item has been archived and is no longer active.'), 'contents_url': FieldInfo(annotation=str, required=True, title='Contents URL', description='The relative URL to access the contents of this History.'), 'count': FieldInfo(annotation=int, required=True, title='Count', description='The number of items in the history.'), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'export_record_data': FieldInfo(annotation=Union[ExportRecordData, NoneType], required=False, default=None, title='Export Record Data', description='The export record data associated with this archived history. Used to recover the history.'), 'genome_build': FieldInfo(annotation=Union[str, NoneType], required=False, default='?', title='Genome Build', description='TODO'), 'id': FieldInfo(annotation=str, required=True, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'importable': FieldInfo(annotation=bool, required=True, title='Importable', description='Whether this History can be imported by other users with a shared link.'), 'model_class': FieldInfo(annotation=Literal['History'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'History', 'type': 'string'}), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the history.'), 'preferred_object_store_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Preferred Object Store ID', description='The ID of the object store that should be used to store new datasets in this history.'), 'published': FieldInfo(annotation=bool, required=True, title='Published', description='Whether this resource is currently publicly available to all users.'), 'purged': FieldInfo(annotation=bool, required=True, title='Purged', description='Whether this item has been permanently removed.'), 'size': FieldInfo(annotation=int, required=True, title='Size', description='The total size of the contents of this history in bytes.'), 'slug': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Slug', description='Part of the URL to uniquely identify this History by link in a readable way.'), 'state': FieldInfo(annotation=DatasetState, required=True, title='State', description='The current state of the History based on the states of the datasets it contains.'), 'state_details': FieldInfo(annotation=Dict[galaxy.schema.schema.DatasetState, int], required=True, title='State Counts', description='A dictionary keyed to possible dataset states and valued with the number of datasets in this history that have those states.'), 'state_ids': FieldInfo(annotation=Dict[galaxy.schema.schema.DatasetState, List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]]], required=True, title='State IDs', description='A dictionary keyed to possible dataset states and valued with lists containing the ids of each HDA in that state.'), 'tags': FieldInfo(annotation=TagCollection, required=True), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'user_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='User ID', description='The encoded ID of the user that owns this History.'), 'username': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username', description='Owner of the history'), 'username_and_slug': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username and slug', description='The relative URL in the form of /u/{username}/h/{slug}')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

contents_url: str[str]

size: int

user_id: str[str] | None

create_time: datetime

importable: bool

slug: str | None

username: str | None

username_and_slug: str | None

genome_build: str | None

state: DatasetState

state_ids: Dict[DatasetState, List[int[int]]]

state_details: Dict[DatasetState, int]

model_class: HISTORY_MODEL_CLASS

id: HistoryID

name: str

deleted: bool

purged: bool

archived: bool

url: RelativeUrlField

published: bool

count: int

annotation: str | None

tags: TagCollection

update_time: datetime

preferred_object_store_id: str | None

class galaxy.schema.schema.CustomArchivedHistoryView(*, model_class: typing_extensions.Literal[History] | None = None, export_record_data: ExportRecordData | None = None, id: str | None[str | None] = None, name: str | None = None, deleted: bool | None = None, purged: bool | None = None, archived: bool | None = None, url: str | None = None, published: bool | None = None, count: int | None = None, annotation: str | None = None, tags: TagCollection | None = None, update_time: datetime | None = None, preferred_object_store_id: str | None = None, contents_url: str | None = None, size: int | None = None, user_id: str[str] | None = None, create_time: datetime | None = None, importable: bool | None = None, slug: str | None = None, username: str | None = None, username_and_slug: str | None = None, genome_build: str | None = None, state: DatasetState | None = None, state_ids: Dict[DatasetState, List[int[int]]] | None = None, state_details: Dict[DatasetState, int] | None = None, contents_active: HistoryActiveContentCounts | None = None, contents_states: Dict[DatasetState | DatasetCollectionPopulatedState, int] | None = None, nice_size: str | None = None)

Bases: CustomArchivedHistoryView

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'archived': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Archived', description='Whether this item has been archived and is no longer active.'), 'contents_active': FieldInfo(annotation=Union[HistoryActiveContentCounts, NoneType], required=False, default=None, title='Contents Active', description='Contains the number of active, deleted or hidden items in a History.'), 'contents_states': FieldInfo(annotation=Union[Dict[Union[galaxy.schema.schema.DatasetState, galaxy.schema.schema.DatasetCollectionPopulatedState], int], NoneType], required=False, default=None, title='Contents States', description='A dictionary keyed to possible dataset states and valued with the number of datasets in this history that have those states.'), 'contents_url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Contents URL', description='The relative URL to access the contents of this History.'), 'count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Count', description='The number of items in the history.'), 'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Deleted', description='Whether this item is marked as deleted.'), 'export_record_data': FieldInfo(annotation=Union[ExportRecordData, NoneType], required=False, default=None, title='Export Record Data', description='The export record data associated with this archived history. Used to recover the history.'), 'genome_build': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Genome Build', description='TODO'), 'id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'importable': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Importable', description='Whether this History can be imported by other users with a shared link.'), 'model_class': FieldInfo(annotation=Union[Literal['History'], NoneType], required=False, default=None, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'History', 'type': 'string'}), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The name of the history.'), 'nice_size': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Nice Size', description='The total size of the contents of this history in a human-readable format.'), 'preferred_object_store_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Preferred Object Store ID', description='The ID of the object store that should be used to store new datasets in this history.'), 'published': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Published', description='Whether this resource is currently publicly available to all users.'), 'purged': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Purged', description='Whether this item has been permanently removed.'), 'size': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Size', description='The total size of the contents of this history in bytes.'), 'slug': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Slug', description='Part of the URL to uniquely identify this History by link in a readable way.'), 'state': FieldInfo(annotation=Union[DatasetState, NoneType], required=False, default=None, title='State', description='The current state of the History based on the states of the datasets it contains.'), 'state_details': FieldInfo(annotation=Union[Dict[galaxy.schema.schema.DatasetState, int], NoneType], required=False, default=None, title='State Counts', description='A dictionary keyed to possible dataset states and valued with the number of datasets in this history that have those states.'), 'state_ids': FieldInfo(annotation=Union[Dict[galaxy.schema.schema.DatasetState, List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]]], NoneType], required=False, default=None, title='State IDs', description='A dictionary keyed to possible dataset states and valued with lists containing the ids of each HDA in that state.'), 'tags': FieldInfo(annotation=Union[TagCollection, NoneType], required=False, default=None), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'user_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='User ID', description='The encoded ID of the user that owns this History.'), 'username': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username', description='Owner of the history'), 'username_and_slug': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username and slug', description='The relative URL in the form of /u/{username}/h/{slug}')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

model_class: typing_extensions.Literal[History] | None

export_record_data: ExportRecordData | None

id: str | None

name: str | None

deleted: bool | None

purged: bool | None

archived: bool | None

url: str | None

published: bool | None

count: int | None

annotation: str | None

tags: TagCollection | None

update_time: datetime | None

preferred_object_store_id: str | None

contents_url: str | None

size: int | None

user_id: str[str] | None

create_time: datetime | None

importable: bool | None

slug: str | None

username: str | None

username_and_slug: str | None

genome_build: str | None

state: DatasetState | None

state_ids: Dict[DatasetState, List[int[int]]] | None

state_details: Dict[DatasetState, int] | None

contents_active: HistoryActiveContentCounts | None

contents_states: Dict[DatasetState | DatasetCollectionPopulatedState, int] | None

nice_size: str | None

class galaxy.schema.schema.LabelValuePair(*, label: str, value: str)

Bases: Model

Generic Label/Value pair model.

label: str

value: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'label': FieldInfo(annotation=str, required=True, title='Label', description='The label of the item.'), 'value': FieldInfo(annotation=str, required=True, title='Value', description='The value of the item.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CustomBuildsMetadataResponse(*, installed_builds: List[LabelValuePair], fasta_hdas: List[LabelValuePair])

Bases: Model

installed_builds: List[LabelValuePair]

fasta_hdas: List[LabelValuePair]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'fasta_hdas': FieldInfo(annotation=List[galaxy.schema.schema.LabelValuePair], required=True, title='Fasta HDAs', description='A list of label/value pairs with all the datasets of type `FASTA` contained in the History.\n - `label` is item position followed by the name of the dataset.\n - `value` is the encoded database ID of the dataset.\n'), 'installed_builds': FieldInfo(annotation=List[galaxy.schema.schema.LabelValuePair], required=True, title='Installed Builds', description='TODO')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobIdResponse(*, job_id: str[str])

Bases: Model

Contains the ID of the job associated with a particular request.

job_id: str[str]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'job_id': FieldInfo(annotation=str, required=True, title='Job ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobBaseModel(*, model_class: typing_extensions.Literal[Job], id: str[str], history_id: str[str] | None = None, tool_id: str, state: JobState, exit_code: int | None = None, create_time: datetime, update_time: datetime, galaxy_version: str | None = None)

Bases: Model, WithModelClass

id: str[str]

history_id: str[str] | None

model_class: typing_extensions.Literal[Job]

tool_id: str

state: JobState

exit_code: int | None

create_time: datetime

update_time: datetime

galaxy_version: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'exit_code': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Exit Code', description='The exit code returned by the tool. Can be unset if the job is not completed yet.'), 'galaxy_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Galaxy Version', description='The (major) version of Galaxy used to create this job.', examples=['21.05']), 'history_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='History ID', description='The encoded ID of the history associated with this item.'), 'id': FieldInfo(annotation=str, required=True, title='Job ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['Job'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Job', 'type': 'string'}), 'state': FieldInfo(annotation=JobState, required=True, title='State', description='Current state of the job.'), 'tool_id': FieldInfo(annotation=str, required=True, title='Tool ID', description='Identifier of the tool that generated this job.'), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobImportHistoryResponse(*, model_class: typing_extensions.Literal[Job], id: str[str], history_id: str[str] | None = None, tool_id: str, state: JobState, exit_code: int | None = None, create_time: datetime, update_time: datetime, galaxy_version: str | None = None, message: str)

Bases: JobBaseModel

message: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'exit_code': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Exit Code', description='The exit code returned by the tool. Can be unset if the job is not completed yet.'), 'galaxy_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Galaxy Version', description='The (major) version of Galaxy used to create this job.', examples=['21.05']), 'history_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='History ID', description='The encoded ID of the history associated with this item.'), 'id': FieldInfo(annotation=str, required=True, title='Job ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'message': FieldInfo(annotation=str, required=True, title='Message', description='Text message containing information about the history import.'), 'model_class': FieldInfo(annotation=Literal['Job'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Job', 'type': 'string'}), 'state': FieldInfo(annotation=JobState, required=True, title='State', description='Current state of the job.'), 'tool_id': FieldInfo(annotation=str, required=True, title='Tool ID', description='Identifier of the tool that generated this job.'), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ItemStateSummary(*, id: str[str], populated_state: DatasetCollectionPopulatedState, states: Dict[JobState, int] = {})

Bases: Model

id: str[str]

populated_state: DatasetCollectionPopulatedState

states: Dict[JobState, int]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'populated_state': FieldInfo(annotation=DatasetCollectionPopulatedState, required=True, title='Populated State', description="Indicates the general state of the elements in the dataset collection:- 'new': new dataset collection, unpopulated elements.- 'ok': collection elements populated (HDAs may or may not have errors).- 'failed': some problem populating, won't be populated."), 'states': FieldInfo(annotation=Dict[galaxy.schema.schema.JobState, int], required=False, default={}, title='States', description='A dictionary of job states and the number of jobs in that state.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobStateSummary(*, id: str[str], populated_state: DatasetCollectionPopulatedState, states: Dict[JobState, int] = {}, model: typing_extensions.Literal[Job])

Bases: ItemStateSummary

model: typing_extensions.Literal[Job]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model': FieldInfo(annotation=Literal['Job'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Job', 'type': 'string'}), 'populated_state': FieldInfo(annotation=DatasetCollectionPopulatedState, required=True, title='Populated State', description="Indicates the general state of the elements in the dataset collection:- 'new': new dataset collection, unpopulated elements.- 'ok': collection elements populated (HDAs may or may not have errors).- 'failed': some problem populating, won't be populated."), 'states': FieldInfo(annotation=Dict[galaxy.schema.schema.JobState, int], required=False, default={}, title='States', description='A dictionary of job states and the number of jobs in that state.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ImplicitCollectionJobsStateSummary(*, id: str[str], populated_state: DatasetCollectionPopulatedState, states: Dict[JobState, int] = {}, model: typing_extensions.Literal[ImplicitCollectionJobs])

Bases: ItemStateSummary

model: typing_extensions.Literal[ImplicitCollectionJobs]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model': FieldInfo(annotation=Literal['ImplicitCollectionJobs'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'ImplicitCollectionJobs', 'type': 'string'}), 'populated_state': FieldInfo(annotation=DatasetCollectionPopulatedState, required=True, title='Populated State', description="Indicates the general state of the elements in the dataset collection:- 'new': new dataset collection, unpopulated elements.- 'ok': collection elements populated (HDAs may or may not have errors).- 'failed': some problem populating, won't be populated."), 'states': FieldInfo(annotation=Dict[galaxy.schema.schema.JobState, int], required=False, default={}, title='States', description='A dictionary of job states and the number of jobs in that state.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowInvocationStateSummary(*, id: str[str], populated_state: DatasetCollectionPopulatedState, states: Dict[JobState, int] = {}, model: typing_extensions.Literal[WorkflowInvocation])

Bases: ItemStateSummary

model: typing_extensions.Literal[WorkflowInvocation]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model': FieldInfo(annotation=Literal['WorkflowInvocation'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'WorkflowInvocation', 'type': 'string'}), 'populated_state': FieldInfo(annotation=DatasetCollectionPopulatedState, required=True, title='Populated State', description="Indicates the general state of the elements in the dataset collection:- 'new': new dataset collection, unpopulated elements.- 'ok': collection elements populated (HDAs may or may not have errors).- 'failed': some problem populating, won't be populated."), 'states': FieldInfo(annotation=Dict[galaxy.schema.schema.JobState, int], required=False, default={}, title='States', description='A dictionary of job states and the number of jobs in that state.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobSummary(*, model_class: typing_extensions.Literal[Job], id: str[str], history_id: str[str] | None = None, tool_id: str, state: JobState, exit_code: int | None = None, create_time: datetime, update_time: datetime, galaxy_version: str | None = None, external_id: str | None = None, handler: str | None = None, job_runner_name: str | None = None, command_line: str | None = None, user_email: str | None = None)

Bases: JobBaseModel

Basic information about a job.

external_id: str | None

handler: str | None

job_runner_name: str | None

command_line: str | None

user_email: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'command_line': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Command Line', description='The command line produced by the job. Users can see this value if allowed in the configuration, administrator can always see this value.'), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'exit_code': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Exit Code', description='The exit code returned by the tool. Can be unset if the job is not completed yet.'), 'external_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='External ID', description='The job id used by the external job runner (Condor, Pulsar, etc.). Only administrator can see this value.'), 'galaxy_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Galaxy Version', description='The (major) version of Galaxy used to create this job.', examples=['21.05']), 'handler': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Job Handler', description='The job handler process assigned to handle this job. Only administrator can see this value.'), 'history_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='History ID', description='The encoded ID of the history associated with this item.'), 'id': FieldInfo(annotation=str, required=True, title='Job ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'job_runner_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Job Runner Name', description='Name of the job runner plugin that handles this job. Only administrator can see this value.'), 'model_class': FieldInfo(annotation=Literal['Job'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Job', 'type': 'string'}), 'state': FieldInfo(annotation=JobState, required=True, title='State', description='Current state of the job.'), 'tool_id': FieldInfo(annotation=str, required=True, title='Tool ID', description='Identifier of the tool that generated this job.'), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.'), 'user_email': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='User Email', description='The email of the user that owns this job. Only the owner of the job and administrators can see this value.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DatasetSourceIdBase(*, src: DatasetSourceType)

Bases: Model

src: DatasetSourceType

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'src': FieldInfo(annotation=DatasetSourceType, required=True, title='Source', description='The source of this dataset, either `hda` or `ldda` depending of its origin.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DatasetSourceId(*, src: DatasetSourceType, id: int[int])

Bases: DatasetSourceIdBase

id: int[int]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=int, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'src': FieldInfo(annotation=DatasetSourceType, required=True, title='Source', description='The source of this dataset, either `hda` or `ldda` depending of its origin.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.EncodedDatasetSourceId(*, src: DatasetSourceType, id: str[str])

Bases: DatasetSourceIdBase

id: str[str]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'src': FieldInfo(annotation=DatasetSourceType, required=True, title='Source', description='The source of this dataset, either `hda` or `ldda` depending of its origin.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.EncodedDataItemSourceId(*, id: str[str], src: DataItemSourceType)

Bases: Model

id: str[str]

src: DataItemSourceType

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'src': FieldInfo(annotation=DataItemSourceType, required=True, title='Source', description='The source of this dataset, either `hda`, `ldda`, `hdca`, `dce` or `dc` depending of its origin.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.EncodedJobParameterHistoryItem(*, id: str[str], src: DataItemSourceType, hid: int | None = None, name: str)

Bases: EncodedDataItemSourceId

hid: int | None

name: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'hid': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'name': FieldInfo(annotation=str, required=True), 'src': FieldInfo(annotation=DataItemSourceType, required=True, title='Source', description='The source of this dataset, either `hda`, `ldda`, `hdca`, `dce` or `dc` depending of its origin.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DatasetJobInfo(*, src: DatasetSourceType, id: int[int], uuid: UUID[UUID])

Bases: DatasetSourceId

uuid: UUID[UUID]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=int, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'src': FieldInfo(annotation=DatasetSourceType, required=True, title='Source', description='The source of this dataset, either `hda` or `ldda` depending of its origin.'), 'uuid': FieldInfo(annotation=UUID, required=True, title='UUID', description='Universal unique identifier for this dataset.', metadata=[UuidVersion(uuid_version=4)])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobDetails(*, model_class: typing_extensions.Literal[Job], id: str[str], history_id: str[str] | None = None, tool_id: str, state: JobState, exit_code: int | None = None, create_time: datetime, update_time: datetime, galaxy_version: str | None = None, external_id: str | None = None, handler: str | None = None, job_runner_name: str | None = None, command_line: str | None = None, user_email: str | None = None, command_version: str, params: Any = None, inputs: Dict[str, DatasetJobInfo] = {}, outputs: Dict[str, DatasetJobInfo] = {})

Bases: JobSummary

command_version: str

params: Any

inputs: Dict[str, DatasetJobInfo]

outputs: Dict[str, DatasetJobInfo]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'command_line': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Command Line', description='The command line produced by the job. Users can see this value if allowed in the configuration, administrator can always see this value.'), 'command_version': FieldInfo(annotation=str, required=True, title='Command Version', description='Tool version indicated during job execution.'), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'exit_code': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Exit Code', description='The exit code returned by the tool. Can be unset if the job is not completed yet.'), 'external_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='External ID', description='The job id used by the external job runner (Condor, Pulsar, etc.). Only administrator can see this value.'), 'galaxy_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Galaxy Version', description='The (major) version of Galaxy used to create this job.', examples=['21.05']), 'handler': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Job Handler', description='The job handler process assigned to handle this job. Only administrator can see this value.'), 'history_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='History ID', description='The encoded ID of the history associated with this item.'), 'id': FieldInfo(annotation=str, required=True, title='Job ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'inputs': FieldInfo(annotation=Dict[str, galaxy.schema.schema.DatasetJobInfo], required=False, default={}, title='Inputs', description='Dictionary mapping all the tool inputs (by name) with the corresponding dataset information.'), 'job_runner_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Job Runner Name', description='Name of the job runner plugin that handles this job. Only administrator can see this value.'), 'model_class': FieldInfo(annotation=Literal['Job'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Job', 'type': 'string'}), 'outputs': FieldInfo(annotation=Dict[str, galaxy.schema.schema.DatasetJobInfo], required=False, default={}, title='Outputs', description='Dictionary mapping all the tool outputs (by name) with the corresponding dataset information.'), 'params': FieldInfo(annotation=Any, required=False, default=None, title='Parameters', description='Object containing all the parameters of the tool associated with this job. The specific parameters depend on the tool itself.'), 'state': FieldInfo(annotation=JobState, required=True, title='State', description='Current state of the job.'), 'tool_id': FieldInfo(annotation=str, required=True, title='Tool ID', description='Identifier of the tool that generated this job.'), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.'), 'user_email': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='User Email', description='The email of the user that owns this job. Only the owner of the job and administrators can see this value.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobMetric(*, title: str, value: str, plugin: str, name: str, raw_value: str)

Bases: Model

title: str

value: str

plugin: str

name: str

raw_value: str

model_config: ClassVar[ConfigDict] = {'json_schema_extra': {'example': {'name': 'start_epoch', 'plugin': 'core', 'raw_value': '1614261340.0000000', 'title': 'Job Start Time', 'value': '2021-02-25 14:55:40'}}, 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the metric variable.'), 'plugin': FieldInfo(annotation=str, required=True, title='Plugin', description='The instrumenter plugin that generated this metric.'), 'raw_value': FieldInfo(annotation=str, required=True, title='Raw Value', description='The raw value of the metric as a string.'), 'title': FieldInfo(annotation=str, required=True, title='Title', description='A descriptive title for this metric.'), 'value': FieldInfo(annotation=str, required=True, title='Value', description='The textual representation of the metric value.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowJobMetric(*, title: str, value: str, plugin: str, name: str, raw_value: str, tool_id: str, job_id: str, step_index: int, step_label: str | None)

Bases: JobMetric

tool_id: str

job_id: str

step_index: int

step_label: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'json_schema_extra': {'example': {'name': 'start_epoch', 'plugin': 'core', 'raw_value': '1614261340.0000000', 'title': 'Job Start Time', 'value': '2021-02-25 14:55:40'}}, 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'job_id': FieldInfo(annotation=str, required=True), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the metric variable.'), 'plugin': FieldInfo(annotation=str, required=True, title='Plugin', description='The instrumenter plugin that generated this metric.'), 'raw_value': FieldInfo(annotation=str, required=True, title='Raw Value', description='The raw value of the metric as a string.'), 'step_index': FieldInfo(annotation=int, required=True), 'step_label': FieldInfo(annotation=Union[str, NoneType], required=True), 'title': FieldInfo(annotation=str, required=True, title='Title', description='A descriptive title for this metric.'), 'tool_id': FieldInfo(annotation=str, required=True), 'value': FieldInfo(annotation=str, required=True, title='Value', description='The textual representation of the metric value.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobMetricCollection(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

Represents a collection of metrics associated with a Job.

root: List[JobMetric]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[galaxy.schema.schema.JobMetric], required=False, default=[], title='Job Metrics', description='Collections of metrics provided by `JobInstrumenter` plugins on a particular job.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.JobFullDetails(*, model_class: typing_extensions.Literal[Job], id: str[str], history_id: str[str] | None = None, tool_id: str, state: JobState, exit_code: int | None = None, create_time: datetime, update_time: datetime, galaxy_version: str | None = None, external_id: str | None = None, handler: str | None = None, job_runner_name: str | None = None, command_line: str | None = None, user_email: str | None = None, command_version: str, params: Any = None, inputs: Dict[str, DatasetJobInfo] = {}, outputs: Dict[str, DatasetJobInfo] = {}, tool_stdout: str, tool_stderr: str, job_stdout: str, job_stderr: str, stdout: str, stderr: str, job_messages: List[str], job_metrics: JobMetricCollection | None = None)

Bases: JobDetails

tool_stdout: str

tool_stderr: str

job_stdout: str

job_stderr: str

stdout: str

stderr: str

job_messages: List[str]

job_metrics: JobMetricCollection | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'command_line': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Command Line', description='The command line produced by the job. Users can see this value if allowed in the configuration, administrator can always see this value.'), 'command_version': FieldInfo(annotation=str, required=True, title='Command Version', description='Tool version indicated during job execution.'), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'exit_code': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Exit Code', description='The exit code returned by the tool. Can be unset if the job is not completed yet.'), 'external_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='External ID', description='The job id used by the external job runner (Condor, Pulsar, etc.). Only administrator can see this value.'), 'galaxy_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Galaxy Version', description='The (major) version of Galaxy used to create this job.', examples=['21.05']), 'handler': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Job Handler', description='The job handler process assigned to handle this job. Only administrator can see this value.'), 'history_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='History ID', description='The encoded ID of the history associated with this item.'), 'id': FieldInfo(annotation=str, required=True, title='Job ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'inputs': FieldInfo(annotation=Dict[str, galaxy.schema.schema.DatasetJobInfo], required=False, default={}, title='Inputs', description='Dictionary mapping all the tool inputs (by name) with the corresponding dataset information.'), 'job_messages': FieldInfo(annotation=List[str], required=True, title='Job Messages', description='List with additional information and possible reasons for a failed job.'), 'job_metrics': FieldInfo(annotation=Union[JobMetricCollection, NoneType], required=False, default=None, title='Job Metrics', description='Collections of metrics provided by `JobInstrumenter` plugins on a particular job. Only administrators can see these metrics.'), 'job_runner_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Job Runner Name', description='Name of the job runner plugin that handles this job. Only administrator can see this value.'), 'job_stderr': FieldInfo(annotation=str, required=True, title='Job Standard Error', description='The captured standard error of the job execution.'), 'job_stdout': FieldInfo(annotation=str, required=True, title='Job Standard Output', description='The captured standard output of the job execution.'), 'model_class': FieldInfo(annotation=Literal['Job'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Job', 'type': 'string'}), 'outputs': FieldInfo(annotation=Dict[str, galaxy.schema.schema.DatasetJobInfo], required=False, default={}, title='Outputs', description='Dictionary mapping all the tool outputs (by name) with the corresponding dataset information.'), 'params': FieldInfo(annotation=Any, required=False, default=None, title='Parameters', description='Object containing all the parameters of the tool associated with this job. The specific parameters depend on the tool itself.'), 'state': FieldInfo(annotation=JobState, required=True, title='State', description='Current state of the job.'), 'stderr': FieldInfo(annotation=str, required=True, title='Standard Error', description='Combined tool and job standard error streams.'), 'stdout': FieldInfo(annotation=str, required=True, title='Standard Output', description='Combined tool and job standard output streams.'), 'tool_id': FieldInfo(annotation=str, required=True, title='Tool ID', description='Identifier of the tool that generated this job.'), 'tool_stderr': FieldInfo(annotation=str, required=True, title='Tool Standard Error', description='The captured standard error of the tool executed by the job.'), 'tool_stdout': FieldInfo(annotation=str, required=True, title='Tool Standard Output', description='The captured standard output of the tool executed by the job.'), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.'), 'user_email': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='User Email', description='The email of the user that owns this job. Only the owner of the job and administrators can see this value.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.StoredWorkflowSummary(*, model_class: typing_extensions.Literal[StoredWorkflow], id: str[str], create_time: datetime, update_time: datetime, name: str, url: str, published: bool, annotations: List[str] | None = None, tags: TagCollection, deleted: bool, hidden: bool, owner: str, latest_workflow_uuid: UUID[UUID] | None = None, number_of_steps: int | None = None, show_in_tool_panel: bool | None = None)

Bases: Model, WithModelClass

id: str[str]

model_class: typing_extensions.Literal[StoredWorkflow]

create_time: datetime

update_time: datetime

name: str

url: str[str]

published: bool

annotations: List[str] | None

tags: TagCollection

deleted: bool

hidden: bool

owner: str

latest_workflow_uuid: UUID[UUID] | None

number_of_steps: int | None

show_in_tool_panel: bool | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotations': FieldInfo(annotation=Union[List[str], NoneType], required=False, default=None, title='Annotations', description='An list of annotations to provide details or to help understand the purpose and usage of this workflow.'), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this item is marked as deleted.'), 'hidden': FieldInfo(annotation=bool, required=True, title='Hidden', description='TODO'), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'latest_workflow_uuid': FieldInfo(annotation=Union[Annotated[uuid.UUID, UuidVersion(uuid_version=4)], NoneType], required=False, default=None, title='Latest workflow UUID', description='TODO'), 'model_class': FieldInfo(annotation=Literal['StoredWorkflow'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'StoredWorkflow', 'type': 'string'}), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the history.'), 'number_of_steps': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Number of Steps', description='The number of steps that make up this workflow.'), 'owner': FieldInfo(annotation=str, required=True, title='Owner', description='The name of the user who owns this workflow.'), 'published': FieldInfo(annotation=bool, required=True, title='Published', description='Whether this workflow is currently publicly available to all users.'), 'show_in_tool_panel': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Show in Tool Panel', description='Whether to display this workflow in the Tools Panel.'), 'tags': FieldInfo(annotation=TagCollection, required=True), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowInput(*, label: str | None, value: Any | None, uuid: UUID[UUID] | None)

Bases: Model

label: str | None

value: Any | None

uuid: UUID[UUID] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'label': FieldInfo(annotation=Union[str, NoneType], required=True, title='Label', description='Label of the input.'), 'uuid': FieldInfo(annotation=Union[Annotated[uuid.UUID, UuidVersion(uuid_version=4)], NoneType], required=True, title='UUID', description='Universal unique identifier of the input.'), 'value': FieldInfo(annotation=Union[Any, NoneType], required=True, title='Value', description='TODO')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowOutput(*, label: str | None = None, output_name: str, uuid: UUID[UUID] | None = None)

Bases: Model

label: str | None

output_name: str

uuid: UUID[UUID] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'label': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Label', description='Label of the output.'), 'output_name': FieldInfo(annotation=str, required=True, title='Output Name', description='The name assigned to the output.'), 'uuid': FieldInfo(annotation=Union[Annotated[uuid.UUID, UuidVersion(uuid_version=4)], NoneType], required=False, default=None, title='UUID', description='Universal unique identifier of the output.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.InputStep(*, source_step: int, step_output: str)

Bases: Model

source_step: int

step_output: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'source_step': FieldInfo(annotation=int, required=True, title='Source Step', description='The identifier of the workflow step connected to this particular input.'), 'step_output': FieldInfo(annotation=str, required=True, title='Step Output', description='The name of the output generated by the source step.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowStepBase(*, id: int, annotation: str | None, input_steps: Dict[str, InputStep], when: str | None, tool_id: str | None = None, tool_version: str | None = None, tool_inputs: Any = None)

Bases: Model

id: int

annotation: str | None

input_steps: Dict[str, InputStep]

when: str | None

tool_id: str | None

tool_version: str | None

tool_inputs: Any

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the step. It matches the index order of the step inside the workflow.'), 'input_steps': FieldInfo(annotation=Dict[str, galaxy.schema.schema.InputStep], required=True, title='Input Steps', description='A dictionary containing information about the inputs connected to this workflow step.'), 'tool_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool ID', description='The unique name of the tool associated with this step.'), 'tool_inputs': FieldInfo(annotation=Any, required=False, default=None, title='Tool Inputs', description='TODO'), 'tool_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool Version', description='The version of the tool associated with this step.'), 'when': FieldInfo(annotation=Union[str, NoneType], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.InputDataStep(*, id: int, annotation: str | None, input_steps: Dict[str, InputStep], when: str | None, tool_id: str | None = None, tool_version: str | None = None, tool_inputs: Any = None, type: typing_extensions.Literal[data_input])

Bases: WorkflowStepBase

type: typing_extensions.Literal[data_input]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the step. It matches the index order of the step inside the workflow.'), 'input_steps': FieldInfo(annotation=Dict[str, galaxy.schema.schema.InputStep], required=True, title='Input Steps', description='A dictionary containing information about the inputs connected to this workflow step.'), 'tool_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool ID', description='The unique name of the tool associated with this step.'), 'tool_inputs': FieldInfo(annotation=Any, required=False, default=None, title='Tool Inputs', description='TODO'), 'tool_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool Version', description='The version of the tool associated with this step.'), 'type': FieldInfo(annotation=Literal['data_input'], required=True), 'when': FieldInfo(annotation=Union[str, NoneType], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.InputDataCollectionStep(*, id: int, annotation: str | None, input_steps: Dict[str, InputStep], when: str | None, tool_id: str | None = None, tool_version: str | None = None, tool_inputs: Any = None, type: typing_extensions.Literal[data_collection_input])

Bases: WorkflowStepBase

type: typing_extensions.Literal[data_collection_input]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the step. It matches the index order of the step inside the workflow.'), 'input_steps': FieldInfo(annotation=Dict[str, galaxy.schema.schema.InputStep], required=True, title='Input Steps', description='A dictionary containing information about the inputs connected to this workflow step.'), 'tool_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool ID', description='The unique name of the tool associated with this step.'), 'tool_inputs': FieldInfo(annotation=Any, required=False, default=None, title='Tool Inputs', description='TODO'), 'tool_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool Version', description='The version of the tool associated with this step.'), 'type': FieldInfo(annotation=Literal['data_collection_input'], required=True), 'when': FieldInfo(annotation=Union[str, NoneType], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.InputParameterStep(*, id: int, annotation: str | None, input_steps: Dict[str, InputStep], when: str | None, tool_id: str | None = None, tool_version: str | None = None, tool_inputs: Any = None, type: typing_extensions.Literal[parameter_input])

Bases: WorkflowStepBase

type: typing_extensions.Literal[parameter_input]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the step. It matches the index order of the step inside the workflow.'), 'input_steps': FieldInfo(annotation=Dict[str, galaxy.schema.schema.InputStep], required=True, title='Input Steps', description='A dictionary containing information about the inputs connected to this workflow step.'), 'tool_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool ID', description='The unique name of the tool associated with this step.'), 'tool_inputs': FieldInfo(annotation=Any, required=False, default=None, title='Tool Inputs', description='TODO'), 'tool_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool Version', description='The version of the tool associated with this step.'), 'type': FieldInfo(annotation=Literal['parameter_input'], required=True), 'when': FieldInfo(annotation=Union[str, NoneType], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.PauseStep(*, id: int, annotation: str | None, input_steps: Dict[str, InputStep], when: str | None, tool_id: str | None = None, tool_version: str | None = None, tool_inputs: Any = None, type: typing_extensions.Literal[pause])

Bases: WorkflowStepBase

type: typing_extensions.Literal[pause]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the step. It matches the index order of the step inside the workflow.'), 'input_steps': FieldInfo(annotation=Dict[str, galaxy.schema.schema.InputStep], required=True, title='Input Steps', description='A dictionary containing information about the inputs connected to this workflow step.'), 'tool_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool ID', description='The unique name of the tool associated with this step.'), 'tool_inputs': FieldInfo(annotation=Any, required=False, default=None, title='Tool Inputs', description='TODO'), 'tool_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool Version', description='The version of the tool associated with this step.'), 'type': FieldInfo(annotation=Literal['pause'], required=True), 'when': FieldInfo(annotation=Union[str, NoneType], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ToolStep(*, id: int, annotation: str | None, input_steps: Dict[str, InputStep], when: str | None, tool_id: str | None = None, tool_version: str | None = None, tool_inputs: Any = None, type: typing_extensions.Literal[tool])

Bases: WorkflowStepBase

type: typing_extensions.Literal[tool]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the step. It matches the index order of the step inside the workflow.'), 'input_steps': FieldInfo(annotation=Dict[str, galaxy.schema.schema.InputStep], required=True, title='Input Steps', description='A dictionary containing information about the inputs connected to this workflow step.'), 'tool_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool ID', description='The unique name of the tool associated with this step.'), 'tool_inputs': FieldInfo(annotation=Any, required=False, default=None, title='Tool Inputs', description='TODO'), 'tool_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool Version', description='The version of the tool associated with this step.'), 'type': FieldInfo(annotation=Literal['tool'], required=True), 'when': FieldInfo(annotation=Union[str, NoneType], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.SubworkflowStep(*, id: int, annotation: str | None, input_steps: Dict[str, InputStep], when: str | None, tool_id: str | None = None, tool_version: str | None = None, tool_inputs: Any = None, type: typing_extensions.Literal[subworkflow], workflow_id: str[str])

Bases: WorkflowStepBase

type: typing_extensions.Literal[subworkflow]

workflow_id: str[str]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the step. It matches the index order of the step inside the workflow.'), 'input_steps': FieldInfo(annotation=Dict[str, galaxy.schema.schema.InputStep], required=True, title='Input Steps', description='A dictionary containing information about the inputs connected to this workflow step.'), 'tool_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool ID', description='The unique name of the tool associated with this step.'), 'tool_inputs': FieldInfo(annotation=Any, required=False, default=None, title='Tool Inputs', description='TODO'), 'tool_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool Version', description='The version of the tool associated with this step.'), 'type': FieldInfo(annotation=Literal['subworkflow'], required=True), 'when': FieldInfo(annotation=Union[str, NoneType], required=True), 'workflow_id': FieldInfo(annotation=str, required=True, title='Workflow ID', description='The encoded ID of the workflow that will be run on this step.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.Creator(*, class_: str, name: str | None = None, address: str | None = None, alternateName: str | None = None, email: str | None = None, faxNumber: str | None = None, identifier: str | None = None, image: Url[Url] | None = None, telephone: str | None = None, url: Url[Url] | None = None)

Bases: Model

class_: str

name: str | None

address: str | None

alternate_name: str | None

email: str | None

fax_number: str | None

identifier: str | None

image: Url[Url] | None

telephone: str | None

url: Url[Url] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'address': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Address'), 'alternate_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='alternateName', alias_priority=2, title='Alternate Name'), 'class_': FieldInfo(annotation=str, required=True, alias='class', alias_priority=2, title='Class', description='The class representing this creator.'), 'email': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Email'), 'fax_number': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='faxNumber', alias_priority=2, title='Fax Number'), 'identifier': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Identifier', description='Identifier (typically an orcid.org ID)'), 'image': FieldInfo(annotation=Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=None, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False, default=None, title='Image URL'), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The name of the creator.'), 'telephone': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Telephone'), 'url': FieldInfo(annotation=Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=None, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False, default=None, title='URL')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.Organization(*, class_: str = 'Organization', name: str | None = None, address: str | None = None, alternateName: str | None = None, email: str | None = None, faxNumber: str | None = None, identifier: str | None = None, image: Url[Url] | None = None, telephone: str | None = None, url: Url[Url] | None = None)

Bases: Creator

class_: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'address': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Address'), 'alternate_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='alternateName', alias_priority=2, title='Alternate Name'), 'class_': FieldInfo(annotation=str, required=False, default='Organization', alias='class', alias_priority=2), 'email': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Email'), 'fax_number': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='faxNumber', alias_priority=2, title='Fax Number'), 'identifier': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Identifier', description='Identifier (typically an orcid.org ID)'), 'image': FieldInfo(annotation=Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=None, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False, default=None, title='Image URL'), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The name of the creator.'), 'telephone': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Telephone'), 'url': FieldInfo(annotation=Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=None, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False, default=None, title='URL')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.Person(*, class_: str = 'Person', name: str | None = None, address: str | None = None, alternateName: str | None = None, email: str | None = None, faxNumber: str | None = None, identifier: str | None = None, image: Url[Url] | None = None, telephone: str | None = None, url: Url[Url] | None = None, familyName: str | None = None, givenName: str | None = None, honorificPrefix: str | None = None, honorificSuffix: str | None = None, jobTitle: str | None = None)

Bases: Creator

class_: str

family_name: str | None

givenName: str | None

honorific_prefix: str | None

honorific_suffix: str | None

job_title: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'address': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Address'), 'alternate_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='alternateName', alias_priority=2, title='Alternate Name'), 'class_': FieldInfo(annotation=str, required=False, default='Person', alias='class', alias_priority=2), 'email': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Email'), 'family_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='familyName', alias_priority=2, title='Family Name'), 'fax_number': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='faxNumber', alias_priority=2, title='Fax Number'), 'givenName': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='givenName', alias_priority=2, title='Given Name'), 'honorific_prefix': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='honorificPrefix', alias_priority=2, title='Honorific Prefix', description='Honorific Prefix (e.g. Dr/Mrs/Mr)'), 'honorific_suffix': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='honorificSuffix', alias_priority=2, title='Honorific Suffix', description='Honorific Suffix (e.g. M.D.)'), 'identifier': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Identifier', description='Identifier (typically an orcid.org ID)'), 'image': FieldInfo(annotation=Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=None, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False, default=None, title='Image URL'), 'job_title': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, alias='jobTitle', alias_priority=2, title='Job Title'), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The name of the creator.'), 'telephone': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Telephone'), 'url': FieldInfo(annotation=Union[Annotated[pydantic_core._pydantic_core.Url, UrlConstraints(max_length=None, allowed_schemes=['http', 'https'], host_required=None, default_host=None, default_port=None, default_path=None)], NoneType], required=False, default=None, title='URL')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.Input(*, name: str, description: str)

Bases: Model

name: str

description: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'description': FieldInfo(annotation=str, required=True, title='Description', description='The annotation or description of the input.'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the input.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.Output(*, name: str, type: str)

Bases: Model

name: str

type: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the output.'), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The extension or type of output.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.InputConnection(*, id: int, output_name: str, input_subworkflow_step_id: int | None = None)

Bases: Model

id: int

output_name: str

input_subworkflow_step_id: int | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the input.'), 'input_subworkflow_step_id': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Input Subworkflow Step ID', description='TODO'), 'output_name': FieldInfo(annotation=str, required=True, title='Output Name', description='The name assigned to the output.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowStepLayoutPosition(*, bottom: int, top: int, left: int, right: int, x: int, y: int, height: int, width: int)

Bases: Model

Position and dimensions of the workflow step represented by a box on the graph.

bottom: int

top: int

left: int

right: int

x: int

y: int

height: int

width: int

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'bottom': FieldInfo(annotation=int, required=True, title='Bottom', description='Position in pixels of the bottom of the box.'), 'height': FieldInfo(annotation=int, required=True, title='Height', description='Height of the box in pixels.'), 'left': FieldInfo(annotation=int, required=True, title='Left', description='Left margin or left-most position of the box.'), 'right': FieldInfo(annotation=int, required=True, title='Right', description='Right margin or right-most position of the box.'), 'top': FieldInfo(annotation=int, required=True, title='Top', description='Position in pixels of the top of the box.'), 'width': FieldInfo(annotation=int, required=True, title='Width', description='Width of the box in pixels.'), 'x': FieldInfo(annotation=int, required=True, title='X', description='Horizontal pixel coordinate of the top right corner of the box.'), 'y': FieldInfo(annotation=int, required=True, title='Y', description='Vertical pixel coordinate of the top right corner of the box.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowStepToExportBase(*, id: int, type: str, name: str, annotation: str | None, tool_id: str | None = None, uuid: UUID[UUID], label: str | None = None, inputs: List[Input], outputs: List[Output], input_connections: Dict[str, InputConnection] = {}, position: WorkflowStepLayoutPosition, workflow_outputs: List[WorkflowOutput] = [])

Bases: Model

id: int

type: str

name: str

annotation: str | None

tool_id: str | None

uuid: UUID[UUID]

label: str | None

inputs: List[Input]

outputs: List[Output]

input_connections: Dict[str, InputConnection]

position: WorkflowStepLayoutPosition

workflow_outputs: List[WorkflowOutput]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the step. It matches the index order of the step inside the workflow.'), 'input_connections': FieldInfo(annotation=Dict[str, galaxy.schema.schema.InputConnection], required=False, default={}, title='Input Connections', description='TODO'), 'inputs': FieldInfo(annotation=List[galaxy.schema.schema.Input], required=True, title='Inputs', description='TODO'), 'label': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Label'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The descriptive name of the module or step.'), 'outputs': FieldInfo(annotation=List[galaxy.schema.schema.Output], required=True, title='Outputs', description='TODO'), 'position': FieldInfo(annotation=WorkflowStepLayoutPosition, required=True, title='Position', description='Layout position of this step in the graph'), 'tool_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool ID', description='The unique name of the tool associated with this step.'), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The type of workflow module.'), 'uuid': FieldInfo(annotation=UUID, required=True, title='UUID', description='Universal unique identifier of the workflow.', metadata=[UuidVersion(uuid_version=4)]), 'workflow_outputs': FieldInfo(annotation=List[galaxy.schema.schema.WorkflowOutput], required=False, default=[], title='Workflow Outputs', description='Workflow outputs associated with this step.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowStepToExport(*, id: int, type: str, name: str, annotation: str | None, tool_id: str | None = None, uuid: UUID[UUID], label: str | None = None, inputs: List[Input], outputs: List[Output], input_connections: Dict[str, InputConnection] = {}, position: WorkflowStepLayoutPosition, workflow_outputs: List[WorkflowOutput] = [], content_id: str | None = None, tool_version: str | None = None, tool_state: Json, errors: str | None = None)

Bases: WorkflowStepToExportBase

content_id: str | None

tool_version: str | None

tool_state: Json

errors: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'content_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Content ID', description='TODO'), 'errors': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Errors', description='An message indicating possible errors in the step.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the step. It matches the index order of the step inside the workflow.'), 'input_connections': FieldInfo(annotation=Dict[str, galaxy.schema.schema.InputConnection], required=False, default={}, title='Input Connections', description='TODO'), 'inputs': FieldInfo(annotation=List[galaxy.schema.schema.Input], required=True, title='Inputs', description='TODO'), 'label': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Label'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The descriptive name of the module or step.'), 'outputs': FieldInfo(annotation=List[galaxy.schema.schema.Output], required=True, title='Outputs', description='TODO'), 'position': FieldInfo(annotation=WorkflowStepLayoutPosition, required=True, title='Position', description='Layout position of this step in the graph'), 'tool_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool ID', description='The unique name of the tool associated with this step.'), 'tool_state': FieldInfo(annotation=Json, required=True, title='Tool State', description='JSON string containing the serialized representation of the persistable state of the step.'), 'tool_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool Version', description='The version of the tool associated with this step.'), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The type of workflow module.'), 'uuid': FieldInfo(annotation=UUID, required=True, title='UUID', description='Universal unique identifier of the workflow.', metadata=[UuidVersion(uuid_version=4)]), 'workflow_outputs': FieldInfo(annotation=List[galaxy.schema.schema.WorkflowOutput], required=False, default=[], title='Workflow Outputs', description='Workflow outputs associated with this step.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ToolShedRepositorySummary(*, name: str, owner: str, changeset_revision: str, tool_shed: str)

Bases: Model

name: str

owner: str

changeset_revision: str

tool_shed: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'changeset_revision': FieldInfo(annotation=str, required=True, title='Changeset Revision', description='TODO'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the repository.'), 'owner': FieldInfo(annotation=str, required=True, title='Owner', description='The owner of the repository.'), 'tool_shed': FieldInfo(annotation=str, required=True, title='Tool Shed', description='The Tool Shed base URL.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.PostJobAction(*, action_type: str, output_name: str, action_arguments: Dict[str, Any])

Bases: Model

action_type: str

output_name: str

action_arguments: Dict[str, Any]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'action_arguments': FieldInfo(annotation=Dict[str, Any], required=True, title='Action Arguments', description='Any additional arguments needed by the action.'), 'action_type': FieldInfo(annotation=str, required=True, title='Action Type', description='The type of action to run.'), 'output_name': FieldInfo(annotation=str, required=True, title='Output Name', description='The name of the output that will be affected by the action.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowToolStepToExport(*, id: int, type: str, name: str, annotation: str | None, tool_id: str | None = None, uuid: UUID[UUID], label: str | None = None, inputs: List[Input], outputs: List[Output], input_connections: Dict[str, InputConnection] = {}, position: WorkflowStepLayoutPosition, workflow_outputs: List[WorkflowOutput] = [], tool_shed_repository: ToolShedRepositorySummary, post_job_actions: Dict[str, PostJobAction])

Bases: WorkflowStepToExportBase

tool_shed_repository: ToolShedRepositorySummary

post_job_actions: Dict[str, PostJobAction]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the step. It matches the index order of the step inside the workflow.'), 'input_connections': FieldInfo(annotation=Dict[str, galaxy.schema.schema.InputConnection], required=False, default={}, title='Input Connections', description='TODO'), 'inputs': FieldInfo(annotation=List[galaxy.schema.schema.Input], required=True, title='Inputs', description='TODO'), 'label': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Label'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The descriptive name of the module or step.'), 'outputs': FieldInfo(annotation=List[galaxy.schema.schema.Output], required=True, title='Outputs', description='TODO'), 'position': FieldInfo(annotation=WorkflowStepLayoutPosition, required=True, title='Position', description='Layout position of this step in the graph'), 'post_job_actions': FieldInfo(annotation=Dict[str, galaxy.schema.schema.PostJobAction], required=True, title='Post-job Actions', description='Set of actions that will be run when the job finish.'), 'tool_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool ID', description='The unique name of the tool associated with this step.'), 'tool_shed_repository': FieldInfo(annotation=ToolShedRepositorySummary, required=True, title='Tool Shed Repository', description='Information about the origin repository of this tool.'), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The type of workflow module.'), 'uuid': FieldInfo(annotation=UUID, required=True, title='UUID', description='Universal unique identifier of the workflow.', metadata=[UuidVersion(uuid_version=4)]), 'workflow_outputs': FieldInfo(annotation=List[galaxy.schema.schema.WorkflowOutput], required=False, default=[], title='Workflow Outputs', description='Workflow outputs associated with this step.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.SubworkflowStepToExport(*, id: int, type: str, name: str, annotation: str | None, tool_id: str | None = None, uuid: UUID[UUID], label: str | None = None, inputs: List[Input], outputs: List[Output], input_connections: Dict[str, InputConnection] = {}, position: WorkflowStepLayoutPosition, workflow_outputs: List[WorkflowOutput] = [])

Bases: WorkflowStepToExportBase

subworkflow: WorkflowToExport

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The identifier of the step. It matches the index order of the step inside the workflow.'), 'input_connections': FieldInfo(annotation=Dict[str, galaxy.schema.schema.InputConnection], required=False, default={}, title='Input Connections', description='TODO'), 'inputs': FieldInfo(annotation=List[galaxy.schema.schema.Input], required=True, title='Inputs', description='TODO'), 'label': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Label'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The descriptive name of the module or step.'), 'outputs': FieldInfo(annotation=List[galaxy.schema.schema.Output], required=True, title='Outputs', description='TODO'), 'position': FieldInfo(annotation=WorkflowStepLayoutPosition, required=True, title='Position', description='Layout position of this step in the graph'), 'subworkflow': FieldInfo(annotation=WorkflowToExport, required=True, title='Subworkflow', description='Full information about the subworkflow associated with this step.'), 'tool_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Tool ID', description='The unique name of the tool associated with this step.'), 'type': FieldInfo(annotation=str, required=True, title='Type', description='The type of workflow module.'), 'uuid': FieldInfo(annotation=UUID, required=True, title='UUID', description='Universal unique identifier of the workflow.', metadata=[UuidVersion(uuid_version=4)]), 'workflow_outputs': FieldInfo(annotation=List[galaxy.schema.schema.WorkflowOutput], required=False, default=[], title='Workflow Outputs', description='Workflow outputs associated with this step.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowToExport(*, a_galaxy_workflow: str = 'true', format_version: str = '0.1', name: str, annotation: str | None, tags: TagCollection, uuid: UUID[UUID] | None = None, creator: List[Person | Organization] | None = None, license: str | None = None, version: int, steps: Dict[int, SubworkflowStepToExport | WorkflowToolStepToExport | WorkflowStepToExport] = {})

Bases: Model

a_galaxy_workflow: str

format_version: str

name: str

annotation: str | None

tags: TagCollection

uuid: UUID[UUID] | None

creator: List[Person | Organization] | None

license: str | None

version: int

steps: Dict[int, SubworkflowStepToExport | WorkflowToolStepToExport | WorkflowStepToExport]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'a_galaxy_workflow': FieldInfo(annotation=str, required=False, default='true', title='Galaxy Workflow', description='Whether this workflow is a Galaxy Workflow.'), 'annotation': FieldInfo(annotation=Union[str, NoneType], required=True, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'creator': FieldInfo(annotation=Union[List[Union[galaxy.schema.schema.Person, galaxy.schema.schema.Organization]], NoneType], required=False, default=None, title='Creator', description='Additional information about the creator (or multiple creators) of this workflow.'), 'format_version': FieldInfo(annotation=str, required=False, default='0.1', alias='format-version', alias_priority=2, title='Galaxy Workflow', description='Whether this workflow is a Galaxy Workflow.'), 'license': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='License', description='SPDX Identifier of the license associated with this workflow.'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the workflow.'), 'steps': FieldInfo(annotation=Dict[int, Union[galaxy.schema.schema.SubworkflowStepToExport, galaxy.schema.schema.WorkflowToolStepToExport, galaxy.schema.schema.WorkflowStepToExport]], required=False, default={}, title='Steps', description='A dictionary with information about all the steps of the workflow.'), 'tags': FieldInfo(annotation=TagCollection, required=True), 'uuid': FieldInfo(annotation=Union[Annotated[uuid.UUID, UuidVersion(uuid_version=4)], NoneType], required=False, default=None, title='UUID', description='Universal unique identifier of the workflow.'), 'version': FieldInfo(annotation=int, required=True, title='Version', description='The version of the workflow represented by an incremental number.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.BasicRoleModel(*, id: str[str], name: str, type: str)

Bases: Model

id: str[str]

name: str[str]

type: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the role', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'name': FieldInfo(annotation=str, required=True, title='Name', description='Name of the role'), 'type': FieldInfo(annotation=str, required=True, title='Type', description='Type or category of the role')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.RoleModelResponse(*, model_class: typing_extensions.Literal[Role], id: str[str], name: str, type: str, description: str[str] | None, url: str)

Bases: BasicRoleModel, WithModelClass

description: str[str] | None

url: str[str]

model_class: typing_extensions.Literal[Role]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'description': FieldInfo(annotation=Union[Annotated[str, FieldInfo(annotation=NoneType, required=True, title='Description', description='Description of the role')], NoneType], required=True), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the role', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['Role'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Role', 'type': 'string'}), 'name': FieldInfo(annotation=str, required=True, title='Name', description='Name of the role'), 'type': FieldInfo(annotation=str, required=True, title='Type', description='Type or category of the role'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.RoleDefinitionModel(*, name: str, description: str, user_ids: List[int[int]] | None = [], group_ids: List[int[int]] | None = [])

Bases: Model

name: str[str]

description: str[str]

user_ids: List[int[int]] | None

group_ids: List[int[int]] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'description': FieldInfo(annotation=str, required=True, title='Description', description='Description of the role'), 'group_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], NoneType], required=False, default=[], title='Group IDs'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='Name of the role'), 'user_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], NoneType], required=False, default=[], title='User IDs')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.RoleListResponse(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[RoleModelResponse]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[galaxy.schema.schema.RoleModelResponse], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.GroupRoleResponse(*, id: str[str], name: str, url: str)

Bases: Model

id: str[str]

name: str[str]

url: str[str]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the role', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'name': FieldInfo(annotation=str, required=True, title='Name', description='Name of the role'), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.GroupRoleListResponse(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[GroupRoleResponse]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[galaxy.schema.schema.GroupRoleResponse], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.GroupUserResponse(*, id: str[str], email: str, url: str)

Bases: Model

id: str[str]

email: str

url: str[str]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'email': FieldInfo(annotation=str, required=True, title='Email', description='Email of the user'), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'url': FieldInfo(annotation=str, required=True, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True})}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.GroupUserListResponse(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[GroupUserResponse]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[galaxy.schema.schema.GroupUserResponse], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ImportToolDataBundleUriSource(*, src: typing_extensions.Literal[uri], uri: str)

Bases: Model

src: typing_extensions.Literal[uri]

uri: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'src': FieldInfo(annotation=Literal['uri'], required=True, title='src', description='Indicates that the tool data should be resolved by a URI.'), 'uri': FieldInfo(annotation=str, required=True, title='uri', description='URI to fetch tool data bundle from (file:// URIs are fine because this is an admin-only operation)')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ImportToolDataBundleDatasetSource(*, src: typing_extensions.Literal[hda, ldda], id: int[int])

Bases: Model

src: typing_extensions.Literal[hda, ldda]

id: int[int]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=int, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'src': FieldInfo(annotation=Literal['hda', 'ldda'], required=True, title='src', description='Indicates that the tool data should be resolved from a dataset.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ToolShedRepository(*, tool_shed_url: str = 'https://toolshed.g2.bx.psu.edu/', name: str, owner: str)

Bases: Model

tool_shed_url: str

name: str

owner: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'name': FieldInfo(annotation=str, required=True, title='Name', description='Name of repository'), 'owner': FieldInfo(annotation=str, required=True, title='Owner', description='Owner of repository'), 'tool_shed_url': FieldInfo(annotation=str, required=False, default='https://toolshed.g2.bx.psu.edu/', title='Tool Shed URL', description='Tool Shed target')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ToolShedRepositoryChangeset(*, tool_shed_url: str = 'https://toolshed.g2.bx.psu.edu/', name: str, owner: str, changeset_revision: str)

Bases: ToolShedRepository

changeset_revision: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'changeset_revision': FieldInfo(annotation=str, required=True), 'name': FieldInfo(annotation=str, required=True, title='Name', description='Name of repository'), 'owner': FieldInfo(annotation=str, required=True, title='Owner', description='Owner of repository'), 'tool_shed_url': FieldInfo(annotation=str, required=False, default='https://toolshed.g2.bx.psu.edu/', title='Tool Shed URL', description='Tool Shed target')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.InstalledRepositoryToolShedStatus(*, latest_installable_revision: str | None, revision_update: str, revision_upgrade: str | None = None, repository_deprecated: str | None)

Bases: Model

latest_installable_revision: str | None

revision_update: str

revision_upgrade: str | None

repository_deprecated: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'latest_installable_revision': FieldInfo(annotation=Union[str, NoneType], required=True, title='Latest installed revision', description='Most recent version available on the tool shed'), 'repository_deprecated': FieldInfo(annotation=Union[str, NoneType], required=True, title='Repository deprecated', description='Repository has been depreciated on the tool shed'), 'revision_update': FieldInfo(annotation=str, required=True), 'revision_upgrade': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.InstalledToolShedRepository(*, model_class: typing_extensions.Literal[ToolShedRepository], id: str[str], status: str, name: str, owner: str, deleted: bool, ctx_rev: str | None, error_message: str = 'Installation error message, the empty string means no error was recorded', installed_changeset_revision: str, tool_shed: str, dist_to_shed: bool, uninstalled: bool, changeset_revision: str, tool_shed_status: InstalledRepositoryToolShedStatus | None)

Bases: Model, WithModelClass

model_class: typing_extensions.Literal[ToolShedRepository]

id: str[str]

status: str

name: str

owner: str

deleted: bool

ctx_rev: str | None

error_message: str

installed_changeset_revision: str

tool_shed: str

dist_to_shed: bool

uninstalled: bool

changeset_revision: str

tool_shed_status: InstalledRepositoryToolShedStatus | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'changeset_revision': FieldInfo(annotation=str, required=True, title='Changeset revision', description='Changeset revision of the repository - a mercurial commit hash'), 'ctx_rev': FieldInfo(annotation=Union[str, NoneType], required=True, title='Changeset revision number', description='The linearized 0-based index of the changeset on the tool shed (0, 1, 2,...)'), 'deleted': FieldInfo(annotation=bool, required=True), 'dist_to_shed': FieldInfo(annotation=bool, required=True), 'error_message': FieldInfo(annotation=str, required=False, default='Installation error message, the empty string means no error was recorded'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the install tool shed repository.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'installed_changeset_revision': FieldInfo(annotation=str, required=True, title='Installed changeset revision', description='Initially installed changeset revision. Used to construct path to repository within Galaxies filesystem. Does not change if a repository is updated.'), 'model_class': FieldInfo(annotation=Literal['ToolShedRepository'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'ToolShedRepository', 'type': 'string'}), 'name': FieldInfo(annotation=str, required=True, title='Name', description='Name of repository'), 'owner': FieldInfo(annotation=str, required=True, title='Owner', description='Owner of repository'), 'status': FieldInfo(annotation=str, required=True), 'tool_shed': FieldInfo(annotation=str, required=True, title='Tool shed', description='Hostname of the tool shed this was installed from'), 'tool_shed_status': FieldInfo(annotation=Union[InstalledRepositoryToolShedStatus, NoneType], required=True, title='Latest updated status from the tool shed'), 'uninstalled': FieldInfo(annotation=bool, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.InstalledToolShedRepositories(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[InstalledToolShedRepository]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[galaxy.schema.schema.InstalledToolShedRepository], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CheckForUpdatesResponse(*, status: typing_extensions.Literal[ok, error], message: str)

Bases: Model

status: typing_extensions.Literal[ok, error]

message: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'message': FieldInfo(annotation=str, required=True, title='Message', description='Unstructured description of tool shed updates discovered or failure'), 'status': FieldInfo(annotation=Literal['ok', 'error'], required=True, title='Status', description="'ok' or 'error'")}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryPermissionScope(value)

Bases: str, Enum

An enumeration.

current = 'current'

available = 'available'

class galaxy.schema.schema.LibraryLegacySummary(*, model_class: typing_extensions.Literal[Library], id: str[str], name: str, description: str | None = '', synopsis: str | None = None, root_folder_id: str[str], create_time: datetime, deleted: bool)

Bases: Model, WithModelClass

model_class: typing_extensions.Literal[Library]

id: str[str]

name: str

description: str | None

synopsis: str | None

root_folder_id: str[str]

create_time: datetime

deleted: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this Library has been deleted.'), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default='', title='Description', description='A detailed description of the Library.'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the Library.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['Library'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Library', 'type': 'string'}), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the Library.'), 'root_folder_id': FieldInfo(annotation=str, required=True, title='Root Folder ID', description="Encoded ID of the Library's base folder.", metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'synopsis': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Description', description='A short text describing the contents of the Library.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibrarySummary(*, model_class: typing_extensions.Literal[Library], id: str[str], name: str, description: str | None = '', synopsis: str | None = None, root_folder_id: str[str], create_time: datetime, deleted: bool, create_time_pretty: str, public: bool, can_user_add: bool, can_user_modify: bool, can_user_manage: bool)

Bases: LibraryLegacySummary

create_time_pretty: str

public: bool

can_user_add: bool

can_user_modify: bool

can_user_manage: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'can_user_add': FieldInfo(annotation=bool, required=True, title='Can User Add', description='Whether the current user can add contents to this Library.'), 'can_user_manage': FieldInfo(annotation=bool, required=True, title='Can User Manage', description='Whether the current user can manage the Library and its contents.'), 'can_user_modify': FieldInfo(annotation=bool, required=True, title='Can User Modify', description='Whether the current user can modify this Library.'), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'create_time_pretty': FieldInfo(annotation=str, required=True, title='Create Time Pretty', description='Nice time representation of the creation date.', examples=['2 months ago']), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this Library has been deleted.'), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default='', title='Description', description='A detailed description of the Library.'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the Library.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['Library'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Library', 'type': 'string'}), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the Library.'), 'public': FieldInfo(annotation=bool, required=True, title='Public', description='Whether this Library has been deleted.'), 'root_folder_id': FieldInfo(annotation=str, required=True, title='Root Folder ID', description="Encoded ID of the Library's base folder.", metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'synopsis': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Description', description='A short text describing the contents of the Library.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibrarySummaryList(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[LibrarySummary]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[galaxy.schema.schema.LibrarySummary], required=False, default=[], title='List with summary information of Libraries.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CreateLibraryPayload(*, name: str, description: str | None = '', synopsis: str | None = '')

Bases: Model

name: str

description: str | None

synopsis: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'description': FieldInfo(annotation=Union[str, NoneType], required=False, default='', title='Description', description='A detailed description of the Library.'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the Library.'), 'synopsis': FieldInfo(annotation=Union[str, NoneType], required=False, default='', title='Synopsis', description='A short text describing the contents of the Library.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CreateLibrariesFromStore(*, store_content_uri: str | None = None, store_dict: Dict[str, Any] | None = None, model_store_format: ModelStoreFormat | None = None)

Bases: StoreContentSource

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'model_store_format': FieldInfo(annotation=Union[ModelStoreFormat, NoneType], required=False, default=None), 'store_content_uri': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'store_dict': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

store_content_uri: str | None

store_dict: Dict[str, Any] | None

model_store_format: ModelStoreFormat | None

class galaxy.schema.schema.UpdateLibraryPayload(*, name: str | None = None, description: str | None = None, synopsis: str | None = None)

Bases: Model

name: str | None

description: str | None

synopsis: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Description', description='A detailed description of the Library. Leave unset to keep the existing.'), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The new name of the Library. Leave unset to keep the existing.'), 'synopsis': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Synopsis', description='A short text describing the contents of the Library. Leave unset to keep the existing.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DeleteLibraryPayload(*, undelete: bool)

Bases: Model

undelete: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'undelete': FieldInfo(annotation=bool, required=True, title='Undelete', description='Whether to restore this previously deleted library.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryCurrentPermissions(*, access_library_role_list: List[List[str]], modify_library_role_list: List[List[str]], manage_library_role_list: List[List[str]], add_library_item_role_list: List[List[str]])

Bases: Model

access_library_role_list: List[List[str]]

modify_library_role_list: List[List[str]]

manage_library_role_list: List[List[str]]

add_library_item_role_list: List[List[str]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'access_library_role_list': FieldInfo(annotation=List[List[str]], required=True, title='Access Role List', description='A list containing pairs of role names and corresponding encoded IDs which have access to the Library.'), 'add_library_item_role_list': FieldInfo(annotation=List[List[str]], required=True, title='Add Role List', description='A list containing pairs of role names and corresponding encoded IDs which can add items to the Library.'), 'manage_library_role_list': FieldInfo(annotation=List[List[str]], required=True, title='Manage Role List', description='A list containing pairs of role names and corresponding encoded IDs which can manage the Library.'), 'modify_library_role_list': FieldInfo(annotation=List[List[str]], required=True, title='Modify Role List', description='A list containing pairs of role names and corresponding encoded IDs which can modify the Library.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LegacyLibraryPermissionsPayload(*, LIBRARY_ACCESS_in: List[int[int]] | int[int] | None = [], LIBRARY_MODIFY_in: List[int[int]] | int[int] | None = [], LIBRARY_ADD_in: List[int[int]] | int[int] | None = [], LIBRARY_MANAGE_in: List[int[int]] | int[int] | None = [])

Bases: RequireOneSetOption

LIBRARY_ACCESS_in: List[int[int]] | int[int] | None

LIBRARY_MODIFY_in: List[int[int]] | int[int] | None

LIBRARY_ADD_in: List[int[int]] | int[int] | None

LIBRARY_MANAGE_in: List[int[int]] | int[int] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'LIBRARY_ACCESS_in': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], title='Access IDs', description='A list of role encoded IDs defining roles that should have access permission on the library.'), 'LIBRARY_ADD_in': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], title='Manage IDs', description='A list of role encoded IDs defining roles that should have manage permission on the library.'), 'LIBRARY_MANAGE_in': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], title='Modify IDs', description='A list of role encoded IDs defining roles that should have modify permission on the library.'), 'LIBRARY_MODIFY_in': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], title='Add IDs', description='A list of role encoded IDs defining roles that should be able to add items to the library.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryPermissionAction(value)

Bases: str, Enum

An enumeration.

set_permissions = 'set_permissions'

remove_restrictions = 'remove_restrictions'

class galaxy.schema.schema.DatasetPermissionAction(value)

Bases: str, Enum

An enumeration.

set_permissions = 'set_permissions'

make_private = 'make_private'

remove_restrictions = 'remove_restrictions'

class galaxy.schema.schema.LibraryPermissionsPayloadBase(*, add_ids: List[int[int]] | int[int] | None = [], manage_ids: List[int[int]] | int[int] | None = [], modify_ids: List[int[int]] | int[int] | None = [])

Bases: RequireOneSetOption

add_ids: List[int[int]] | int[int] | None

manage_ids: List[int[int]] | int[int] | None

modify_ids: List[int[int]] | int[int] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'add_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], alias='add_ids[]', alias_priority=2, title='Add IDs', description='A list of role encoded IDs defining roles that should be able to add items to the library.'), 'manage_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], alias='manage_ids[]', alias_priority=2, title='Manage IDs', description='A list of role encoded IDs defining roles that should have manage permission on the library.'), 'modify_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], alias='modify_ids[]', alias_priority=2, title='Modify IDs', description='A list of role encoded IDs defining roles that should have modify permission on the library.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryPermissionsPayload(*, add_ids: List[int[int]] | int[int] | None = [], manage_ids: List[int[int]] | int[int] | None = [], modify_ids: List[int[int]] | int[int] | None = [], action: LibraryPermissionAction | None = None, access_ids: List[int[int]] | int[int] | None = [])

Bases: LibraryPermissionsPayloadBase

action: LibraryPermissionAction | None

access_ids: List[int[int]] | int[int] | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'access_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], alias='access_ids[]', alias_priority=2, title='Access IDs', description='A list of role encoded IDs defining roles that should have access permission on the library.'), 'action': FieldInfo(annotation=Union[LibraryPermissionAction, NoneType], required=False, default=None, title='Action', description='Indicates what action should be performed on the Library.'), 'add_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], alias='add_ids[]', alias_priority=2, title='Add IDs', description='A list of role encoded IDs defining roles that should be able to add items to the library.'), 'manage_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], alias='manage_ids[]', alias_priority=2, title='Manage IDs', description='A list of role encoded IDs defining roles that should have manage permission on the library.'), 'modify_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], alias='modify_ids[]', alias_priority=2, title='Modify IDs', description='A list of role encoded IDs defining roles that should have modify permission on the library.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryFolderPermissionAction(value)

Bases: str, Enum

An enumeration.

set_permissions = 'set_permissions'

class galaxy.schema.schema.LibraryFolderPermissionsPayload(*, add_ids: List[int[int]] | int[int] | None = [], manage_ids: List[int[int]] | int[int] | None = [], modify_ids: List[int[int]] | int[int] | None = [], action: LibraryFolderPermissionAction | None = None)

Bases: LibraryPermissionsPayloadBase

action: LibraryFolderPermissionAction | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'action': FieldInfo(annotation=Union[LibraryFolderPermissionAction, NoneType], required=False, default=None, title='Action', description='Indicates what action should be performed on the library folder.'), 'add_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], alias='add_ids[]', alias_priority=2, title='Add IDs', description='A list of role encoded IDs defining roles that should be able to add items to the library.'), 'manage_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], alias='manage_ids[]', alias_priority=2, title='Manage IDs', description='A list of role encoded IDs defining roles that should have manage permission on the library.'), 'modify_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=[], alias='modify_ids[]', alias_priority=2, title='Modify IDs', description='A list of role encoded IDs defining roles that should have modify permission on the library.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryFolderDetails(*, model_class: typing_extensions.Literal[LibraryFolder], id: str[str], name: str, description: str | None = '', item_count: int, parent_library_id: str[str], parent_id: str[str] | None = None, genome_build: str | None = '?', update_time: datetime, deleted: bool, library_path: List[str] = [])

Bases: Model, WithModelClass

model_class: typing_extensions.Literal[LibraryFolder]

id: str[str]

name: str

description: str | None

item_count: int

parent_library_id: str[str]

parent_id: str[str] | None

genome_build: str | None

update_time: datetime

deleted: bool

library_path: List[str]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this folder is marked as deleted.'), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default='', title='Description', description='A detailed description of the library folder.'), 'genome_build': FieldInfo(annotation=Union[str, NoneType], required=False, default='?', title='Genome Build', description='TODO'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the library folder.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'item_count': FieldInfo(annotation=int, required=True, title='Item Count', description='A detailed description of the library folder.'), 'library_path': FieldInfo(annotation=List[str], required=False, default=[], title='Path', description='The list of folder names composing the path to this folder.'), 'model_class': FieldInfo(annotation=Literal['LibraryFolder'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'LibraryFolder', 'type': 'string'}), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the library folder.'), 'parent_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Parent Folder ID', description="Encoded ID of the parent folder. Empty if it's the root folder."), 'parent_library_id': FieldInfo(annotation=str, required=True, title='Parent Library ID', description='Encoded ID of the Library this folder belongs to.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CreateLibraryFolderPayload(*, name: str, description: str | None = '')

Bases: Model

name: str

description: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'description': FieldInfo(annotation=Union[str, NoneType], required=False, default='', title='Description', description='A detailed description of the library folder.'), 'name': FieldInfo(annotation=str, required=True, title='Name', description='The name of the library folder.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UpdateLibraryFolderPayload(*, name: str | None = None, description: str | None = None)

Bases: Model

name: str | None

description: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'description': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Description', description='The new description of the library folder.'), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The new name of the library folder.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryAvailablePermissions(*, roles: List[BasicRoleModel], page: int, page_limit: int, total: int)

Bases: Model

roles: List[BasicRoleModel]

page: int

page_limit: int

total: int

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'page': FieldInfo(annotation=int, required=True, title='Page', description='Current page.'), 'page_limit': FieldInfo(annotation=int, required=True, title='Page Limit', description='Maximum number of items per page.'), 'roles': FieldInfo(annotation=List[galaxy.schema.schema.BasicRoleModel], required=True, title='Roles', description='A list containing available roles that can be assigned to a particular permission.'), 'total': FieldInfo(annotation=int, required=True, title='Total', description='Total number of items')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryFolderCurrentPermissions(*, modify_folder_role_list: List[List[str]], manage_folder_role_list: List[List[str]], add_library_item_role_list: List[List[str]])

Bases: Model

modify_folder_role_list: List[List[str]]

manage_folder_role_list: List[List[str]]

add_library_item_role_list: List[List[str]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'add_library_item_role_list': FieldInfo(annotation=List[List[str]], required=True, title='Add Role List', description='A list containing pairs of role names and corresponding encoded IDs which can add items to the Library folder.'), 'manage_folder_role_list': FieldInfo(annotation=List[List[str]], required=True, title='Manage Role List', description='A list containing pairs of role names and corresponding encoded IDs which can manage the Library folder.'), 'modify_folder_role_list': FieldInfo(annotation=List[List[str]], required=True, title='Modify Role List', description='A list containing pairs of role names and corresponding encoded IDs which can modify the Library folder.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryFolderContentsIndexQueryPayload(*, limit: int = 10, offset: int = 0, search_text: str | None = None, include_deleted: bool | None = None, order_by: typing_extensions.Literal[name, description, type, size, update_time] = 'name', sort_desc: bool | None = False)

Bases: Model

limit: int

offset: int

search_text: str | None

include_deleted: bool | None

order_by: typing_extensions.Literal[name, description, type, size, update_time]

sort_desc: bool | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'include_deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None), 'limit': FieldInfo(annotation=int, required=False, default=10), 'offset': FieldInfo(annotation=int, required=False, default=0), 'order_by': FieldInfo(annotation=Literal['name', 'description', 'type', 'size', 'update_time'], required=False, default='name'), 'search_text': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'sort_desc': FieldInfo(annotation=Union[bool, NoneType], required=False, default=False)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryFolderItemBase(*, name: str, type: str, create_time: datetime, update_time: datetime, can_manage: bool, deleted: bool)

Bases: Model

name: str

type: str

create_time: datetime

update_time: datetime

can_manage: bool

deleted: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'can_manage': FieldInfo(annotation=bool, required=True), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True), 'name': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=str, required=True), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.FolderLibraryFolderItem(*, name: str, type: typing_extensions.Literal[folder], create_time: datetime, update_time: datetime, can_manage: bool, deleted: bool, id: str[str], can_modify: bool, description: str | None = '')

Bases: LibraryFolderItemBase

id: str[str]

type: typing_extensions.Literal[folder]

can_modify: bool

description: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'can_manage': FieldInfo(annotation=bool, required=True), 'can_modify': FieldInfo(annotation=bool, required=True), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True), 'description': FieldInfo(annotation=Union[str, NoneType], required=False, default='', title='Description', description='A detailed description of the library folder.'), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'name': FieldInfo(annotation=str, required=True), 'type': FieldInfo(annotation=Literal['folder'], required=True), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.FileLibraryFolderItem(*, name: str, type: typing_extensions.Literal[file], create_time: datetime, update_time: datetime, can_manage: bool, deleted: bool, id: str[str], file_ext: str, date_uploaded: datetime, is_unrestricted: bool, is_private: bool, state: DatasetState[DatasetState], file_size: str, raw_size: int, ldda_id: str[str], tags: TagCollection, message: str | None = None)

Bases: LibraryFolderItemBase

id: str[str]

type: typing_extensions.Literal[file]

file_ext: str

date_uploaded: datetime

is_unrestricted: bool

is_private: bool

state: DatasetState[DatasetState]

file_size: str

raw_size: int

ldda_id: str[str]

tags: TagCollection

message: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'can_manage': FieldInfo(annotation=bool, required=True), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'date_uploaded': FieldInfo(annotation=datetime, required=True), 'deleted': FieldInfo(annotation=bool, required=True), 'file_ext': FieldInfo(annotation=str, required=True), 'file_size': FieldInfo(annotation=str, required=True), 'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'is_private': FieldInfo(annotation=bool, required=True), 'is_unrestricted': FieldInfo(annotation=bool, required=True), 'ldda_id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'message': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'name': FieldInfo(annotation=str, required=True), 'raw_size': FieldInfo(annotation=int, required=True), 'state': FieldInfo(annotation=DatasetState, required=True, title='State', description='The current state of this dataset.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined)]), 'tags': FieldInfo(annotation=TagCollection, required=True), 'type': FieldInfo(annotation=Literal['file'], required=True), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryFolderMetadata(*, parent_library_id: str[str], folder_name: str, folder_description: str, total_rows: int, can_modify_folder: bool, can_add_library_item: bool, full_path: List[Tuple[str[str], str]])

Bases: Model

parent_library_id: str[str]

folder_name: str

folder_description: str

total_rows: int

can_modify_folder: bool

can_add_library_item: bool

full_path: List[Tuple[str[str], str]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'can_add_library_item': FieldInfo(annotation=bool, required=True), 'can_modify_folder': FieldInfo(annotation=bool, required=True), 'folder_description': FieldInfo(annotation=str, required=True), 'folder_name': FieldInfo(annotation=str, required=True), 'full_path': FieldInfo(annotation=List[Tuple[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], str]], required=True), 'parent_library_id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'total_rows': FieldInfo(annotation=int, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LibraryFolderContentsIndexResult(*, metadata: LibraryFolderMetadata, folder_contents: List[FileLibraryFolderItem | galaxy.schema.schema.FolderLibraryFolderItem[FileLibraryFolderItem | FolderLibraryFolderItem]])

Bases: Model

metadata: LibraryFolderMetadata

folder_contents: List[FileLibraryFolderItem | galaxy.schema.schema.FolderLibraryFolderItem[FileLibraryFolderItem | FolderLibraryFolderItem]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'folder_contents': FieldInfo(annotation=List[Annotated[Union[galaxy.schema.schema.FileLibraryFolderItem, galaxy.schema.schema.FolderLibraryFolderItem], FieldInfo(annotation=NoneType, required=True, discriminator='type')]], required=True), 'metadata': FieldInfo(annotation=LibraryFolderMetadata, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CreateLibraryFilePayload(*, from_hda_id: int[int] | None = None, from_hdca_id: int[int] | None = None, ldda_message: str | None = '')

Bases: Model

from_hda_id: int[int] | None

from_hdca_id: int[int] | None

ldda_message: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'from_hda_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='From HDA ID', description='The ID of an accessible HDA to copy into the library.'), 'from_hdca_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='From HDCA ID', description='The ID of an accessible HDCA to copy into the library. Nested collections are not allowed, you must flatten the collection first.'), 'ldda_message': FieldInfo(annotation=Union[str, NoneType], required=False, default='', title='LDDA Message', description='The new message attribute of the LDDA created.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DatasetAssociationRoles(*, access_dataset_roles: List[List[str]] = [], manage_dataset_roles: List[List[str]] = [], modify_item_roles: List[List[str]] = [])

Bases: Model

access_dataset_roles: List[List[str]]

manage_dataset_roles: List[List[str]]

modify_item_roles: List[List[str]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'access_dataset_roles': FieldInfo(annotation=List[List[str]], required=False, default=[], title='Access Roles', description='A list of roles that can access the dataset. The user has to **have all these roles** in order to access this dataset. Users without access permission **cannot** have other permissions on this dataset. If there are no access roles set on the dataset it is considered **unrestricted**.'), 'manage_dataset_roles': FieldInfo(annotation=List[List[str]], required=False, default=[], title='Manage Roles', description='A list of roles that can manage permissions on the dataset. Users with **any** of these roles can manage permissions of this dataset. If you remove yourself you will lose the ability to manage this dataset unless you are an admin.'), 'modify_item_roles': FieldInfo(annotation=List[List[str]], required=False, default=[], title='Modify Roles', description='A list of roles that can modify the library item. This is a library related permission. User with **any** of these roles can modify name, metadata, and other information about this library item.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UpdateDatasetPermissionsPayloadBase(*, action: DatasetPermissionAction | None = DatasetPermissionAction.set_permissions)

Bases: Model

action: DatasetPermissionAction | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'action': FieldInfo(annotation=Union[DatasetPermissionAction, NoneType], required=False, default=<DatasetPermissionAction.set_permissions: 'set_permissions'>, title='Action', description='Indicates what action should be performed on the dataset.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UpdateDatasetPermissionsPayload(*, action: DatasetPermissionAction | None = DatasetPermissionAction.set_permissions, access_ids: List[int[int]] | int[int] | None = None, manage_ids: List[int[int]] | int[int] | None = None, modify_ids: List[int[int]] | int[int] | None = None)

Bases: UpdateDatasetPermissionsPayloadBase

access_ids: List[int[int]] | int[int] | None[List[int[int]] | int[int] | None]

manage_ids: List[int[int]] | int[int] | None[List[int[int]] | int[int] | None]

modify_ids: List[int[int]] | int[int] | None[List[int[int]] | int[int] | None]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'access_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, alias='access_ids[]', alias_priority=2), 'action': FieldInfo(annotation=Union[DatasetPermissionAction, NoneType], required=False, default=<DatasetPermissionAction.set_permissions: 'set_permissions'>, title='Action', description='Indicates what action should be performed on the dataset.'), 'manage_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, alias='manage_ids[]', alias_priority=2), 'modify_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, alias='modify_ids[]', alias_priority=2)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UpdateDatasetPermissionsPayloadAliasB(*, action: DatasetPermissionAction | None = DatasetPermissionAction.set_permissions, access: List[int[int]] | int[int] | None = None, manage: List[int[int]] | int[int] | None = None, modify: List[int[int]] | int[int] | None = None)

Bases: UpdateDatasetPermissionsPayloadBase

access: List[int[int]] | int[int] | None[List[int[int]] | int[int] | None]

manage: List[int[int]] | int[int] | None[List[int[int]] | int[int] | None]

modify: List[int[int]] | int[int] | None[List[int[int]] | int[int] | None]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'access': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Access IDs', description='A list of role encoded IDs defining roles that should have access permission on the dataset.'), 'action': FieldInfo(annotation=Union[DatasetPermissionAction, NoneType], required=False, default=<DatasetPermissionAction.set_permissions: 'set_permissions'>, title='Action', description='Indicates what action should be performed on the dataset.'), 'manage': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Manage IDs', description='A list of role encoded IDs defining roles that should have manage permission on the dataset.'), 'modify': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Modify IDs', description='A list of role encoded IDs defining roles that should have modify permission on the dataset.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UpdateDatasetPermissionsPayloadAliasC(*, action: DatasetPermissionAction | None = DatasetPermissionAction.set_permissions, access_ids: List[int[int]] | int[int] | None = None, manage_ids: List[int[int]] | int[int] | None = None, modify_ids: List[int[int]] | int[int] | None = None)

Bases: UpdateDatasetPermissionsPayloadBase

access_ids: List[int[int]] | int[int] | None[List[int[int]] | int[int] | None]

manage_ids: List[int[int]] | int[int] | None[List[int[int]] | int[int] | None]

modify_ids: List[int[int]] | int[int] | None[List[int[int]] | int[int] | None]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'access_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Access IDs', description='A list of role encoded IDs defining roles that should have access permission on the dataset.'), 'action': FieldInfo(annotation=Union[DatasetPermissionAction, NoneType], required=False, default=<DatasetPermissionAction.set_permissions: 'set_permissions'>, title='Action', description='Indicates what action should be performed on the dataset.'), 'manage_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Manage IDs', description='A list of role encoded IDs defining roles that should have manage permission on the dataset.'), 'modify_ids': FieldInfo(annotation=Union[List[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Modify IDs', description='A list of role encoded IDs defining roles that should have modify permission on the dataset.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDACustom(*, model_class: typing_extensions.Literal[HistoryDatasetAssociation] | None = None, id: str | None[str | None] = None, name: str | None = None, history_id: str | None[str | None] = None, hid: int | None = None, deleted: bool | None = None, visible: bool | None = None, type_id: str | None = None, type: typing_extensions.Literal[file] | None = None, create_time: datetime | None = None, update_time: datetime | None = None, url: str | None = None, tags: TagCollection | None = None, history_content_type: typing_extensions.Literal[dataset] | None = None, copied_from_ldda_id: str[str] | None = None, dataset_id: str | None[str | None] = None, state: DatasetState | None[DatasetState | None] = None, extension: str | None = None, purged: bool | None = None, genome_build: str | None = None, hda_ldda: DatasetSourceType | None = None, accessible: bool | None = None, misc_info: str | None = None, misc_blurb: str | None = None, file_ext: str | None = None, file_size: int | None = None, resubmitted: bool | None = None, metadata: Any | None = None, meta_files: List[MetadataFile] | None = None, data_type: str | None = None, peek: str | None = None, creating_job: str | None = None, rerunnable: bool | None = None, uuid: UUID[UUID] | None = None, permissions: DatasetPermissions | None = None, file_name: str | None = None, display_apps: List[DisplayApp] | None = None, display_types: List[DisplayApp] | None = None, validated_state: DatasetValidatedState | None = None, validated_state_message: str | None = None, annotation: str | None = None, download_url: str | None = None, api_type: typing_extensions.Literal[file] | None = None, created_from_basename: str | None = None, hashes: List[DatasetHash] | None = None, drs_id: str | None = None, sources: List[DatasetSource] | None = None, copied_from_history_dataset_association_id: str[str] | None = None, visualizations: List[Visualization] | None = None, **extra_data: Any)

Bases: HDACustom

uuid: UUID[UUID] | None

visualizations: List[Visualization] | None

model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'accessible': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Accessible', description='Whether this item is accessible to the current user due to permissions.'), 'annotation': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Annotation', description='An annotation to provide details or to help understand the purpose and usage of this item.'), 'api_type': FieldInfo(annotation=Union[Literal['file'], NoneType], required=False, default=None, title='API Type', description='TODO', json_schema_extra={'deprecated': True}), 'copied_from_history_dataset_association_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, description='ID of HDA this HDA was copied from.'), 'copied_from_ldda_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None), 'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None, title='Create Time', description='The time and date this item was created.'), 'created_from_basename': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Created from basename', description='The basename of the output that produced this dataset.'), 'creating_job': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Creating Job ID', description='The encoded ID of the job that created this dataset.'), 'data_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Data Type', description='The fully qualified name of the class implementing the data type of this dataset.', examples=['galaxy.datatypes.data.Text']), 'dataset_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Dataset ID', description='The encoded ID of the dataset associated with this item.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Deleted', description='Whether this item is marked as deleted.'), 'display_apps': FieldInfo(annotation=Union[List[galaxy.schema.schema.DisplayApp], NoneType], required=False, default=None, title='Display Applications', description='Contains new-style display app urls.'), 'display_types': FieldInfo(annotation=Union[List[galaxy.schema.schema.DisplayApp], NoneType], required=False, default=None, title='Legacy Display Applications', description='Contains old-style display app urls.'), 'download_url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Download URL', description='The URL to download this item from the server.'), 'drs_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='DRS ID', description='The DRS ID of the dataset.'), 'extension': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Extension', description='The extension of the dataset.', examples=['txt']), 'file_ext': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='File extension', description='The extension of the file.'), 'file_name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='File Name', description='The full path to the dataset file.'), 'file_size': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='File Size', description='The file size in bytes.'), 'genome_build': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Genome Build', description='TODO'), 'hashes': FieldInfo(annotation=Union[List[galaxy.schema.schema.DatasetHash], NoneType], required=False, default=None, title='Hashes', description='The list of hashes associated with this dataset.'), 'hda_ldda': FieldInfo(annotation=Union[DatasetSourceType, NoneType], required=False, default=None, title='HDA or LDDA', description='Whether this dataset belongs to a history (HDA) or a library (LDDA).'), 'hid': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='HID', description='The index position of this item in the History.'), 'history_content_type': FieldInfo(annotation=Union[Literal['dataset'], NoneType], required=False, default=None, title='History Content Type', description='This is always `dataset` for datasets.'), 'history_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'meta_files': FieldInfo(annotation=Union[List[galaxy.schema.schema.MetadataFile], NoneType], required=False, default=None, title='Metadata Files', description='Collection of metadata files associated with this dataset.'), 'metadata': FieldInfo(annotation=Union[Any, NoneType], required=False, default=None, title='Metadata', description='The metadata associated with this dataset.'), 'misc_blurb': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Miscellaneous Blurb', description='TODO'), 'misc_info': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Miscellaneous Information', description='TODO'), 'model_class': FieldInfo(annotation=Union[Literal['HistoryDatasetAssociation'], NoneType], required=False, default=None, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'HistoryDatasetAssociation', 'type': 'string'}), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The name of the item.'), 'peek': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Peek', description='A few lines of contents from the start of the file.'), 'permissions': FieldInfo(annotation=Union[DatasetPermissions, NoneType], required=False, default=None, title='Permissions', description='Role-based access and manage control permissions for the dataset.'), 'purged': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Purged', description='Whether this dataset has been removed from disk.'), 'rerunnable': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Rerunnable', description='Whether the job creating this dataset can be run again.'), 'resubmitted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Resubmitted', description='Whether the job creating this dataset has been resubmitted.'), 'sources': FieldInfo(annotation=Union[List[galaxy.schema.schema.DatasetSource], NoneType], required=False, default=None, title='Sources', description='The list of sources associated with this dataset.'), 'state': FieldInfo(annotation=Union[DatasetState, NoneType], required=False, default=None, title='State', description='The current state of this dataset.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined)]), 'tags': FieldInfo(annotation=Union[TagCollection, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Union[Literal['file'], NoneType], required=False, default=None, title='Type', description='This is always `file` for datasets.'), 'type_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Type - ID', description='The type and the encoded ID of this item. Used for caching.', examples=['dataset-616e371b2cc6c62e']), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'uuid': FieldInfo(annotation=Union[Annotated[uuid.UUID, UuidVersion(uuid_version=4)], NoneType], required=False, default=None), 'validated_state': FieldInfo(annotation=Union[DatasetValidatedState, NoneType], required=False, default=None, title='Validated State', description='The state of the datatype validation for this dataset.'), 'validated_state_message': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Validated State Message', description='The message with details about the datatype validation result for this dataset.'), 'visible': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Visible', description='Whether this item is visible or hidden to the user by default.'), 'visualizations': FieldInfo(annotation=Union[List[galaxy.schema.schema.Visualization], NoneType], required=False, default=None, title='Visualizations', description='The collection of visualizations that can be applied to this dataset.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

model_class: typing_extensions.Literal[HistoryDatasetAssociation] | None

id: str | None

name: str | None

history_id: str | None

hid: int | None

deleted: bool | None

visible: bool | None

type_id: str | None

type: typing_extensions.Literal[file] | None

create_time: datetime | None

update_time: datetime | None

url: str | None

tags: TagCollection | None

history_content_type: typing_extensions.Literal[dataset] | None

copied_from_ldda_id: str[str] | None

dataset_id: str | None

state: DatasetState | None

extension: str | None

purged: bool | None

genome_build: str | None

hda_ldda: DatasetSourceType | None

accessible: bool | None

misc_info: str | None

misc_blurb: str | None

file_ext: str | None

file_size: int | None

resubmitted: bool | None

metadata: Any | None

meta_files: List[MetadataFile] | None

data_type: str | None

peek: str | None

creating_job: str | None

rerunnable: bool | None

permissions: DatasetPermissions | None

file_name: str | None

display_apps: List[DisplayApp] | None

display_types: List[DisplayApp] | None

validated_state: DatasetValidatedState | None

validated_state_message: str | None

annotation: str | None

download_url: str | None

api_type: typing_extensions.Literal[file] | None

created_from_basename: str | None

hashes: List[DatasetHash] | None

drs_id: str | None

sources: List[DatasetSource] | None

copied_from_history_dataset_association_id: str[str] | None

class galaxy.schema.schema.HDCACustom(*, model_class: typing_extensions.Literal[HistoryDatasetCollectionAssociation] | None = None, id: str | None[str | None] = None, name: str | None = None, history_id: str | None[str | None] = None, hid: int | None = None, deleted: bool | None = None, visible: bool | None = None, type_id: str | None = None, type: typing_extensions.Literal[collection] | None = None, create_time: datetime | None = None, update_time: datetime | None = None, url: str | None = None, tags: TagCollection | None = None, history_content_type: typing_extensions.Literal[dataset_collection] | None = None, collection_type: str | None = None, populated_state: DatasetCollectionPopulatedState | None = None, populated_state_message: str | None = None, element_count: int | None = None, elements_datatypes: Set[str] | None = None, job_source_id: str[str] | None = None, job_source_type: JobSourceType | None = None, job_state_summary: HDCJobStateSummary | None = None, contents_url: str | None = None, collection_id: str | None[str | None] = None, populated: bool | None = None, elements: List[DCESummary] | None = None, implicit_collection_jobs_id: str[str] | None = None)

Bases: HDCACustom

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'collection_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Dataset Collection ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'collection_type': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Collection Type', description='The type of the collection, can be `list`, `paired`, or define subcollections using `:` as separator like `list:paired` or `list:list`.'), 'contents_url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Contents URL', description='The relative URL to access the contents of this History.'), 'create_time': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Deleted', description='Whether this item is marked as deleted.'), 'element_count': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='Element Count', description='The number of elements contained in the dataset collection. It may be None or undefined if the collection could not be populated.'), 'elements': FieldInfo(annotation=Union[List[galaxy.schema.schema.DCESummary], NoneType], required=False, default=None, title='Elements', description='The summary information of each of the elements inside the dataset collection.'), 'elements_datatypes': FieldInfo(annotation=Union[Set[str], NoneType], required=False, default=None, description='A set containing all the different element datatypes in the collection.'), 'hid': FieldInfo(annotation=Union[int, NoneType], required=False, default=None, title='HID', description='The index position of this item in the History.'), 'history_content_type': FieldInfo(annotation=Union[Literal['dataset_collection'], NoneType], required=False, default=None, title='History Content Type', description='This is always `dataset_collection` for dataset collections.'), 'history_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='History ID', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'implicit_collection_jobs_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, description='Encoded ID for the ICJ object describing the collection of jobs corresponding to this collection'), 'job_source_id': FieldInfo(annotation=Union[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Job Source ID', description='The encoded ID of the Job that produced this dataset collection. Used to track the state of the job.'), 'job_source_type': FieldInfo(annotation=Union[JobSourceType, NoneType], required=False, default=None, title='Job Source Type', description='The type of job (model class) that produced this dataset collection. Used to track the state of the job.'), 'job_state_summary': FieldInfo(annotation=Union[HDCJobStateSummary, NoneType], required=False, default=None, title='Job State Summary', description='Overview of the job states working inside the dataset collection.'), 'model_class': FieldInfo(annotation=Union[Literal['HistoryDatasetCollectionAssociation'], NoneType], required=False, default=None, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'HistoryDatasetCollectionAssociation', 'type': 'string'}), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name', description='The name of the item.'), 'populated': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Populated', description='Whether the dataset collection elements (and any subcollections elements) were successfully populated.'), 'populated_state': FieldInfo(annotation=Union[DatasetCollectionPopulatedState, NoneType], required=False, default=None, title='Populated State', description="Indicates the general state of the elements in the dataset collection:- 'new': new dataset collection, unpopulated elements.- 'ok': collection elements populated (HDAs may or may not have errors).- 'failed': some problem populating, won't be populated."), 'populated_state_message': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Populated State Message', description='Optional message with further information in case the population of the dataset collection failed.'), 'tags': FieldInfo(annotation=Union[TagCollection, NoneType], required=False, default=None), 'type': FieldInfo(annotation=Union[Literal['collection'], NoneType], required=False, default=None, title='Type', description='This is always `collection` for dataset collections.'), 'type_id': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Type - ID', description='The type and the encoded ID of this item. Used for caching.', examples=['dataset-616e371b2cc6c62e']), 'update_time': FieldInfo(annotation=Union[datetime, NoneType], required=False, default=None, title='Update Time', description='The last time and date this item was updated.'), 'url': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='URL', description='The relative URL to access this item.', json_schema_extra={'deprecated': True}), 'visible': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Visible', description='Whether this item is visible or hidden to the user by default.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

model_class: typing_extensions.Literal[HistoryDatasetCollectionAssociation] | None

id: str | None

name: str | None

history_id: str | None

hid: int | None

deleted: bool | None

visible: bool | None

type_id: str | None

type: typing_extensions.Literal[collection] | None

create_time: datetime | None

update_time: datetime | None

url: str | None

tags: TagCollection | None

history_content_type: typing_extensions.Literal[dataset_collection] | None

collection_type: str | None

populated_state: DatasetCollectionPopulatedState | None

populated_state_message: str | None

element_count: int | None

elements_datatypes: Set[str] | None

job_source_id: str[str] | None

job_source_type: JobSourceType | None

job_state_summary: HDCJobStateSummary | None

contents_url: str | None

collection_id: str | None

populated: bool | None

elements: List[DCESummary] | None

implicit_collection_jobs_id: str[str] | None

class galaxy.schema.schema.DeleteHistoryContentPayload(*, purge: bool = False, recursive: bool = False, stop_job: bool = False)

Bases: Model

purge: bool

recursive: bool

stop_job: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'purge': FieldInfo(annotation=bool, required=False, default=False, title='Purge', description='Whether to remove the dataset from storage. Datasets will only be removed from storage once all HDAs or LDDAs that refer to this datasets are deleted.'), 'recursive': FieldInfo(annotation=bool, required=False, default=False, title='Recursive', description='When deleting a dataset collection, whether to also delete containing datasets.'), 'stop_job': FieldInfo(annotation=bool, required=False, default=False, title='Stop Job', description="Whether to stop the creating job if all the job's outputs are deleted.")}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.DeleteHistoryContentResult(*, id: int[int], deleted: bool, purged: bool | None = None)

Bases: Model

Contains minimum information about the deletion state of a history item.

Can also contain any other properties of the item.

id: int[int]

deleted: bool

purged: bool | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='True if the item was successfully deleted.'), 'id': FieldInfo(annotation=int, required=True, title='ID', description='The encoded ID of the history item.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'purged': FieldInfo(annotation=Union[bool, NoneType], required=False, default=None, title='Purged', description='True if the item was successfully removed from disk.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryContentsArchiveDryRunResult(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

Contains a collection of filepath/filename entries that represent the contents that would have been included in the archive. This is returned when the dry_run flag is active when creating an archive with the contents of the history.

This is used for debugging purposes.

root: List[Tuple[str, str]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[Tuple[str, str]], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryContentStats(*, total_matches: int)

Bases: Model

total_matches: int

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'total_matches': FieldInfo(annotation=int, required=True, title='Total Matches', description='The total number of items that match the search query without any pagination')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryContentsResult(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

List of history content items. Can contain different views and kinds of items.

root: List[HDACustom | galaxy.schema.schema.HDADetailed | galaxy.schema.schema.HDASummary | galaxy.schema.schema.HDAInaccessible | galaxy.schema.schema.HDCACustom | galaxy.schema.schema.HDCADetailed | galaxy.schema.schema.HDCASummary[HDACustom | HDADetailed | HDASummary | HDAInaccessible | HDCACustom | HDCADetailed | HDCASummary]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[Annotated[Union[galaxy.schema.schema.HDACustom, galaxy.schema.schema.HDADetailed, galaxy.schema.schema.HDASummary, galaxy.schema.schema.HDAInaccessible, galaxy.schema.schema.HDCACustom, galaxy.schema.schema.HDCADetailed, galaxy.schema.schema.HDCASummary], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])]], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HistoryContentsWithStatsResult(*, stats: HistoryContentStats, contents: List[HDACustom | galaxy.schema.schema.HDADetailed | galaxy.schema.schema.HDASummary | galaxy.schema.schema.HDAInaccessible | galaxy.schema.schema.HDCACustom | galaxy.schema.schema.HDCADetailed | galaxy.schema.schema.HDCASummary[HDACustom | HDADetailed | HDASummary | HDAInaccessible | HDCACustom | HDCADetailed | HDCASummary]])

Bases: Model

Includes stats with items counting

stats: HistoryContentStats

contents: List[HDACustom | galaxy.schema.schema.HDADetailed | galaxy.schema.schema.HDASummary | galaxy.schema.schema.HDAInaccessible | galaxy.schema.schema.HDCACustom | galaxy.schema.schema.HDCADetailed | galaxy.schema.schema.HDCASummary[HDACustom | HDADetailed | HDASummary | HDAInaccessible | HDCACustom | HDCADetailed | HDCASummary]]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'contents': FieldInfo(annotation=List[Annotated[Union[galaxy.schema.schema.HDACustom, galaxy.schema.schema.HDADetailed, galaxy.schema.schema.HDASummary, galaxy.schema.schema.HDAInaccessible, galaxy.schema.schema.HDCACustom, galaxy.schema.schema.HDCADetailed, galaxy.schema.schema.HDCASummary], FieldInfo(annotation=NoneType, required=True, metadata=[_PydanticGeneralMetadata(union_mode='left_to_right')])]], required=True, title='Contents', description='The items matching the search query. Only the items fitting in the current page limit will be returned.'), 'stats': FieldInfo(annotation=HistoryContentStats, required=True, title='Stats', description='Contains counting stats for the query.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.SharingOptions(value)

Bases: str, Enum

Options for sharing resources that may have restricted access to all or part of their contents.

make_public = 'make_public'

make_accessible_to_shared = 'make_accessible_to_shared'

no_changes = 'no_changes'

class galaxy.schema.schema.ShareWithExtra(*, can_share: bool = False)

Bases: Model

can_share: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'can_share': FieldInfo(annotation=bool, required=False, default=False, title='Can Share', description='Indicates whether the resource can be directly shared or requires further actions.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ShareWithPayload(*, user_ids: List[int[int] | str], share_option: SharingOptions | None = None)

Bases: Model

user_ids: List[int[int] | str]

share_option: SharingOptions | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'share_option': FieldInfo(annotation=Union[SharingOptions, NoneType], required=False, default=None, title='Share Option', description="User choice for sharing resources which its contents may be restricted:\n - None: The user did not choose anything yet or no option is needed.\n - make_public: The contents of the resource will be made publicly accessible.\n - make_accessible_to_shared: This will automatically create a new `sharing role` allowing protected contents to be accessed only by the desired users.\n - no_changes: This won't change the current permissions for the contents. The user which this resource will be shared may not be able to access all its contents.\n"), 'user_ids': FieldInfo(annotation=List[Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], str]], required=True, title='User Identifiers', description='A collection of encoded IDs (or email addresses) of users that this resource will be shared with.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.SetSlugPayload(*, new_slug: str)

Bases: Model

new_slug: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'new_slug': FieldInfo(annotation=str, required=True, title='New Slug', description='The slug that will be used to access this shared item.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UserEmail(*, id: str[str], email: str)

Bases: Model

id: str[str]

email: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'email': FieldInfo(annotation=str, required=True, title='Email', description='The email of the user.'), 'id': FieldInfo(annotation=str, required=True, title='User ID', description='The encoded ID of the user.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.UserBeaconSetting(*, enabled: bool)

Bases: Model

enabled: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'enabled': FieldInfo(annotation=bool, required=True, title='Enabled', description='True if beacon sharing is enabled')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.SharingStatus(*, id: str[str], title: str, importable: bool, published: bool, users_shared_with: List[UserEmail] = [], email_hash: str | None = None, username: str | None = None, username_and_slug: str | None = None)

Bases: Model

id: str[str]

title: str

importable: bool

published: bool

users_shared_with: List[UserEmail]

email_hash: str | None

username: str | None

username_and_slug: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'email_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Encoded Email', description='Encoded owner email.'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='The encoded ID of the resource to be shared.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'importable': FieldInfo(annotation=bool, required=True, title='Importable', description='Whether this resource can be published using a link.'), 'published': FieldInfo(annotation=bool, required=True, title='Published', description='Whether this resource is currently published.'), 'title': FieldInfo(annotation=str, required=True, title='Title', description='The title or name of the resource.'), 'username': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username', description="The owner's username."), 'username_and_slug': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username and slug', description='The relative URL in the form of /u/{username}/{resource_single_char}/{slug}'), 'users_shared_with': FieldInfo(annotation=List[galaxy.schema.schema.UserEmail], required=False, default=[], title='Users shared with', description='The list of encoded ids for users the resource has been shared.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.HDABasicInfo(*, id: str[str], name: str)

Bases: Model

id: str[str]

name: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'name': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ShareHistoryExtra(*, can_share: bool = False, can_change: List[HDABasicInfo] = [], cannot_change: List[HDABasicInfo] = [], accessible_count: int = 0)

Bases: ShareWithExtra

can_change: List[HDABasicInfo]

cannot_change: List[HDABasicInfo]

accessible_count: int

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'accessible_count': FieldInfo(annotation=int, required=False, default=0, title='Accessible Count', description='The number of datasets in the history that are public or accessible by all the target users.'), 'can_change': FieldInfo(annotation=List[galaxy.schema.schema.HDABasicInfo], required=False, default=[], title='Can Change', description='A collection of datasets that are not accessible by one or more of the target users and that can be made accessible for others by the user sharing the history.'), 'can_share': FieldInfo(annotation=bool, required=False, default=False, title='Can Share', description='Indicates whether the resource can be directly shared or requires further actions.'), 'cannot_change': FieldInfo(annotation=List[galaxy.schema.schema.HDABasicInfo], required=False, default=[], title='Cannot Change', description='A collection of datasets that are not accessible by one or more of the target users and that cannot be made accessible for others by the user sharing the history.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ShareWithStatus(*, id: str[str], title: str, importable: bool, published: bool, users_shared_with: List[UserEmail] = [], email_hash: str | None = None, username: str | None = None, username_and_slug: str | None = None, errors: List[str] = [], extra: ShareWithExtra | None = None)

Bases: SharingStatus

errors: List[str]

extra: ShareWithExtra | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'email_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Encoded Email', description='Encoded owner email.'), 'errors': FieldInfo(annotation=List[str], required=False, default=[], title='Errors', description='Collection of messages indicating that the resource was not shared with some (or all users) due to an error.'), 'extra': FieldInfo(annotation=Union[ShareWithExtra, NoneType], required=False, default=None, title='Extra', description='Optional extra information about this shareable resource that may be of interest. The contents of this field depend on the particular resource.'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='The encoded ID of the resource to be shared.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'importable': FieldInfo(annotation=bool, required=True, title='Importable', description='Whether this resource can be published using a link.'), 'published': FieldInfo(annotation=bool, required=True, title='Published', description='Whether this resource is currently published.'), 'title': FieldInfo(annotation=str, required=True, title='Title', description='The title or name of the resource.'), 'username': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username', description="The owner's username."), 'username_and_slug': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username and slug', description='The relative URL in the form of /u/{username}/{resource_single_char}/{slug}'), 'users_shared_with': FieldInfo(annotation=List[galaxy.schema.schema.UserEmail], required=False, default=[], title='Users shared with', description='The list of encoded ids for users the resource has been shared.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ShareHistoryWithStatus(*, id: str[str], title: str, importable: bool, published: bool, users_shared_with: List[UserEmail] = [], email_hash: str | None = None, username: str | None = None, username_and_slug: str | None = None, errors: List[str] = [], extra: ShareHistoryExtra)

Bases: ShareWithStatus

extra: ShareHistoryExtra

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'email_hash': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Encoded Email', description='Encoded owner email.'), 'errors': FieldInfo(annotation=List[str], required=False, default=[], title='Errors', description='Collection of messages indicating that the resource was not shared with some (or all users) due to an error.'), 'extra': FieldInfo(annotation=ShareHistoryExtra, required=True, title='Extra', description='Optional extra information about this shareable resource that may be of interest. The contents of this field depend on the particular resource.'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='The encoded ID of the resource to be shared.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'importable': FieldInfo(annotation=bool, required=True, title='Importable', description='Whether this resource can be published using a link.'), 'published': FieldInfo(annotation=bool, required=True, title='Published', description='Whether this resource is currently published.'), 'title': FieldInfo(annotation=str, required=True, title='Title', description='The title or name of the resource.'), 'username': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username', description="The owner's username."), 'username_and_slug': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Username and slug', description='The relative URL in the form of /u/{username}/{resource_single_char}/{slug}'), 'users_shared_with': FieldInfo(annotation=List[galaxy.schema.schema.UserEmail], required=False, default=[], title='Users shared with', description='The list of encoded ids for users the resource has been shared.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.PageContentFormat(value)

Bases: str, Enum

An enumeration.

markdown = 'markdown'

html = 'html'

class galaxy.schema.schema.PageSummaryBase(*, title: str, slug: str[str])

Bases: Model

title: str

slug: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'slug': FieldInfo(annotation=str, required=True, title='Identifier', description='The title slug for the page URL, must be unique.', metadata=[_PydanticGeneralMetadata(pattern='^[^/:?#]+$')]), 'title': FieldInfo(annotation=str, required=True, title='Title', description='The name of the page.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.MaterializeDatasetInstanceAPIRequest(*, source: DatasetSourceType, content: int[int])

Bases: Model

source: DatasetSourceType

content: int[int]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'content': FieldInfo(annotation=int, required=True, title='Content', description='Depending on the `source` it can be:\n- The encoded id of the source library dataset\n- The encoded id of the HDA\n', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'source': FieldInfo(annotation=DatasetSourceType, required=True, title='Source', description='The source of the content. Can be other history element to be copied or library elements.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.MaterializeDatasetInstanceRequest(*, source: DatasetSourceType, content: int[int], history_id: int[int])

Bases: MaterializeDatasetInstanceAPIRequest

history_id: int[int]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'content': FieldInfo(annotation=int, required=True, title='Content', description='Depending on the `source` it can be:\n- The encoded id of the source library dataset\n- The encoded id of the HDA\n', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'history_id': FieldInfo(annotation=int, required=True, metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'source': FieldInfo(annotation=DatasetSourceType, required=True, title='Source', description='The source of the content. Can be other history element to be copied or library elements.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ChatPayload(*, query: str, context: str | None = '')

Bases: Model

query: str

context: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'context': FieldInfo(annotation=Union[str, NoneType], required=False, default='', title='Context', description='The context for the chatbot.'), 'query': FieldInfo(annotation=str, required=True, title='Query', description='The query to be sent to the chatbot.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ChatResponse(*, response: str, error_code: int | None, error_message: str | None)

Bases: BaseModel

response: str

error_code: int | None

error_message: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'error_code': FieldInfo(annotation=Union[int, NoneType], required=True, title='Error Code', description='The error code, if any, for the chat query.'), 'error_message': FieldInfo(annotation=Union[str, NoneType], required=True, title='Error Message', description='The error message, if any, for the chat query.'), 'response': FieldInfo(annotation=str, required=True, title='Response', description='The response to the chat query.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CreatePagePayload(*, title: str, slug: str[str], content_format: PageContentFormat = PageContentFormat.html, content: str | None = '', annotation: str | None = None, invocation_id: int[int] | None = None, **extra_data: Any)

Bases: PageSummaryBase

content_format: PageContentFormat

content: str | None

annotation: str | None

invocation_id: int[int] | None

model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'annotation': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Annotation', description='Annotation that will be attached to the page.'), 'content': FieldInfo(annotation=Union[str, NoneType], required=False, default='', title='Content', description='Raw text contents of the last page revision (type dependent on content_format).'), 'content_format': FieldInfo(annotation=PageContentFormat, required=False, default=<PageContentFormat.html: 'html'>, title='Content format', description='Either `markdown` or `html`.'), 'invocation_id': FieldInfo(annotation=Union[Annotated[int, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), BeforeValidator(func=<function ensure_valid_id>, json_schema_input_type=PydanticUndefined), PlainSerializer(func=<function <lambda>>, return_type=<class 'str'>, when_used='json'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')], NoneType], required=False, default=None, title='Workflow invocation ID', description='Encoded ID used by workflow generated reports.'), 'slug': FieldInfo(annotation=str, required=True, title='Identifier', description='The title slug for the page URL, must be unique.', metadata=[_PydanticGeneralMetadata(pattern='^[^/:?#]+$')]), 'title': FieldInfo(annotation=str, required=True, title='Title', description='The name of the page.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.AsyncTaskResultSummary(*, id: str, ignored: bool, name: str | None = None, queue: str | None = None)

Bases: Model

id: str

ignored: bool

name: str | None

queue: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, title='ID', description='Celery AsyncResult ID for this task'), 'ignored': FieldInfo(annotation=bool, required=True, title='Ignored', description='Indicated whether the Celery AsyncResult will be available for retrieval'), 'name': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Name of task being done derived from Celery AsyncResult'), 'queue': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Queue of task being done derived from Celery AsyncResult')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ToolRequestState(value)

Bases: str, Enum

An enumeration.

NEW = 'new'

SUBMITTED = 'submitted'

FAILED = 'failed'

class galaxy.schema.schema.ToolRequestModel(*, id: str[str], request: Dict[str, Any], state: ToolRequestState, state_message: str | None)

Bases: Model

id: str[str]

request: Dict[str, Any]

state: ToolRequestState

state_message: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the role', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'request': FieldInfo(annotation=Dict[str, Any], required=True), 'state': FieldInfo(annotation=ToolRequestState, required=True), 'state_message': FieldInfo(annotation=Union[str, NoneType], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.AsyncFile(*, storage_request_id: UUID, task: AsyncTaskResultSummary)

Bases: Model

storage_request_id: UUID

task: AsyncTaskResultSummary

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'storage_request_id': FieldInfo(annotation=UUID, required=True), 'task': FieldInfo(annotation=AsyncTaskResultSummary, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.PageSummary(*, model_class: typing_extensions.Literal[Page], title: str, slug: str[str], id: str[str], username: str, email_hash: str, published: bool, importable: bool, deleted: bool, latest_revision_id: str[str], revision_ids: List[str[str]], create_time: datetime, update_time: datetime, tags: TagCollection)

Bases: PageSummaryBase, WithModelClass

id: str[str]

model_class: typing_extensions.Literal[Page]

username: str

email_hash: str

published: bool

importable: bool

deleted: bool

latest_revision_id: str[str]

revision_ids: List[str[str]]

create_time: datetime

update_time: datetime

tags: TagCollection

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this Page has been deleted.'), 'email_hash': FieldInfo(annotation=str, required=True, title='Encoded email', description='The encoded email of the user.'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the Page.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'importable': FieldInfo(annotation=bool, required=True, title='Importable', description='Whether this Page can be imported.'), 'latest_revision_id': FieldInfo(annotation=str, required=True, title='Latest revision ID', description='The encoded ID of the last revision of this Page.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['Page'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Page', 'type': 'string'}), 'published': FieldInfo(annotation=bool, required=True, title='Published', description='Whether this Page has been published.'), 'revision_ids': FieldInfo(annotation=List[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], required=True, title='List of revisions', description='The history with the encoded ID of each revision of the Page.'), 'slug': FieldInfo(annotation=str, required=True, title='Identifier', description='The title slug for the page URL, must be unique.', metadata=[_PydanticGeneralMetadata(pattern='^[^/:?#]+$')]), 'tags': FieldInfo(annotation=TagCollection, required=True), 'title': FieldInfo(annotation=str, required=True, title='Title', description='The name of the page.'), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.'), 'username': FieldInfo(annotation=str, required=True, title='Username', description='The name of the user owning this Page.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.OAuth2State(*, route: str, nonce: str)

Bases: BaseModel

route: str

nonce: str

encode() → str

static decode(base64_param: str) → OAuth2State

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'nonce': FieldInfo(annotation=str, required=True), 'route': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.PageDetails(*, model_class: typing_extensions.Literal[Page], title: str, slug: str[str], id: str[str], username: str, email_hash: str, published: bool, importable: bool, deleted: bool, latest_revision_id: str[str], revision_ids: List[str[str]], create_time: datetime, update_time: datetime, tags: TagCollection, content_format: PageContentFormat = PageContentFormat.html, content: str | None = '', generate_version: str | None = None, generate_time: str | None = None, **extra_data: Any)

Bases: PageSummary

content_format: PageContentFormat

content: str | None

generate_version: str | None

generate_time: str | None

model_config: ClassVar[ConfigDict] = {'extra': 'allow', 'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_fields: ClassVar[Dict[str, FieldInfo]] = {'content': FieldInfo(annotation=Union[str, NoneType], required=False, default='', title='Content', description='Raw text contents of the last page revision (type dependent on content_format).'), 'content_format': FieldInfo(annotation=PageContentFormat, required=False, default=<PageContentFormat.html: 'html'>, title='Content format', description='Either `markdown` or `html`.'), 'create_time': FieldInfo(annotation=datetime, required=True, title='Create Time', description='The time and date this item was created.'), 'deleted': FieldInfo(annotation=bool, required=True, title='Deleted', description='Whether this Page has been deleted.'), 'email_hash': FieldInfo(annotation=str, required=True, title='Encoded email', description='The encoded email of the user.'), 'generate_time': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Galaxy Version', description='The version of Galaxy this object was generated with.'), 'generate_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None, title='Galaxy Version', description='The version of Galaxy this object was generated with.'), 'id': FieldInfo(annotation=str, required=True, title='ID', description='Encoded ID of the Page.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'importable': FieldInfo(annotation=bool, required=True, title='Importable', description='Whether this Page can be imported.'), 'latest_revision_id': FieldInfo(annotation=str, required=True, title='Latest revision ID', description='The encoded ID of the last revision of this Page.', metadata=[BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]), 'model_class': FieldInfo(annotation=Literal['Page'], required=True, title='Model class', description='The name of the database model class.', json_schema_extra={'const': 'Page', 'type': 'string'}), 'published': FieldInfo(annotation=bool, required=True, title='Published', description='Whether this Page has been published.'), 'revision_ids': FieldInfo(annotation=List[Annotated[str, BeforeValidator(func=<function <lambda>>, json_schema_input_type=PydanticUndefined), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='serialization'), WithJsonSchema(json_schema={'type': 'string', 'example': '0123456789ABCDEF', 'pattern': '[0-9a-fA-F]+', 'minLength': 16}, mode='validation')]], required=True, title='List of revisions', description='The history with the encoded ID of each revision of the Page.'), 'slug': FieldInfo(annotation=str, required=True, title='Identifier', description='The title slug for the page URL, must be unique.', metadata=[_PydanticGeneralMetadata(pattern='^[^/:?#]+$')]), 'tags': FieldInfo(annotation=TagCollection, required=True), 'title': FieldInfo(annotation=str, required=True, title='Title', description='The name of the page.'), 'update_time': FieldInfo(annotation=datetime, required=True, title='Update Time', description='The last time and date this item was updated.'), 'username': FieldInfo(annotation=str, required=True, title='Username', description='The name of the user owning this Page.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.PageSummaryList(root: RootModelRootType = PydanticUndefined)

Bases: RootModel

root: List[PageSummary]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'root': FieldInfo(annotation=List[galaxy.schema.schema.PageSummary], required=False, default=[], title='List with summary information of Pages.')}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.LandingRequestState(value)

Bases: str, Enum

An enumeration.

UNCLAIMED = 'unclaimed'

CLAIMED = 'claimed'

class galaxy.schema.schema.CreateToolLandingRequestPayload(*, tool_id: str, tool_version: str | None = None, request_state: Dict[str, Any] | None = None, client_secret: str | None = None, public: bool = False)

Bases: Model

tool_id: str

tool_version: str | None

request_state: Dict[str, Any] | None

client_secret: str | None

public: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'client_secret': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'public': FieldInfo(annotation=bool, required=False, default=False), 'request_state': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'tool_id': FieldInfo(annotation=str, required=True), 'tool_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.CreateWorkflowLandingRequestPayload(*, workflow_id: str, workflow_target_type: typing_extensions.Literal[stored_workflow, workflow, trs_url], request_state: Dict[str, Any] | None = None, client_secret: str | None = None, public: bool = False)

Bases: Model

workflow_id: str

workflow_target_type: typing_extensions.Literal[stored_workflow, workflow, trs_url]

request_state: Dict[str, Any] | None

client_secret: str | None

public: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'client_secret': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'public': FieldInfo(annotation=bool, required=False, default=False, description='If workflow landing request is public anyone with the uuid can use the landing request. If not public the request must be claimed before use and additional verification might occur.'), 'request_state': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'workflow_id': FieldInfo(annotation=str, required=True), 'workflow_target_type': FieldInfo(annotation=Literal['stored_workflow', 'workflow', 'trs_url'], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ClaimLandingPayload(*, client_secret: str | None = None)

Bases: Model

client_secret: str | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'client_secret': FieldInfo(annotation=Union[str, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.ToolLandingRequest(*, uuid: UUID[UUID], tool_id: str, tool_version: str | None = None, request_state: Dict[str, Any] | None = None, state: LandingRequestState)

Bases: Model

uuid: UUID[UUID]

tool_id: str

tool_version: str | None

request_state: Dict[str, Any] | None

state: LandingRequestState

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'request_state': FieldInfo(annotation=Union[Dict[str, Any], NoneType], required=False, default=None), 'state': FieldInfo(annotation=LandingRequestState, required=True), 'tool_id': FieldInfo(annotation=str, required=True), 'tool_version': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'uuid': FieldInfo(annotation=UUID, required=True, title='UUID', description='Universal unique identifier for this dataset.', metadata=[UuidVersion(uuid_version=4)])}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.WorkflowLandingRequest(*, uuid: UUID[UUID], workflow_id: str, workflow_target_type: typing_extensions.Literal[stored_workflow, workflow, trs_url], request_state: Dict[str, Any], state: LandingRequestState)

Bases: Model

uuid: UUID[UUID]

workflow_id: str

workflow_target_type: typing_extensions.Literal[stored_workflow, workflow, trs_url]

request_state: Dict[str, Any]

state: LandingRequestState

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'request_state': FieldInfo(annotation=Dict[str, Any], required=True), 'state': FieldInfo(annotation=LandingRequestState, required=True), 'uuid': FieldInfo(annotation=UUID, required=True, title='UUID', description='Universal unique identifier for this dataset.', metadata=[UuidVersion(uuid_version=4)]), 'workflow_id': FieldInfo(annotation=str, required=True), 'workflow_target_type': FieldInfo(annotation=Literal['stored_workflow', 'workflow', 'trs_url'], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.MessageExceptionModel(*, err_msg: str, err_code: int)

Bases: BaseModel

err_msg: str

err_code: int

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'err_code': FieldInfo(annotation=int, required=True), 'err_msg': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.schema.SanitizedString

Bases: str

classmethod validate(value)

galaxy.schema.tasks module

class galaxy.schema.tasks.SetupHistoryExportJob(*, history_id: int, job_id: int, store_directory: str, include_files: bool, include_hidden: bool, include_deleted: bool)

Bases: Model

history_id: int

job_id: int

store_directory: str

include_files: bool

include_hidden: bool

include_deleted: bool

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'history_id': FieldInfo(annotation=int, required=True), 'include_deleted': FieldInfo(annotation=bool, required=True), 'include_files': FieldInfo(annotation=bool, required=True), 'include_hidden': FieldInfo(annotation=bool, required=True), 'job_id': FieldInfo(annotation=int, required=True), 'store_directory': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.PrepareDatasetCollectionDownload(*, short_term_storage_request_id: UUID, history_dataset_collection_association_id: int)

Bases: Model

short_term_storage_request_id: UUID

history_dataset_collection_association_id: int

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'history_dataset_collection_association_id': FieldInfo(annotation=int, required=True), 'short_term_storage_request_id': FieldInfo(annotation=UUID, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.GeneratePdfDownload(*, short_term_storage_request_id: UUID, basic_markdown: str, document_type: PdfDocumentType)

Bases: Model

short_term_storage_request_id: UUID

basic_markdown: str

document_type: PdfDocumentType

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'basic_markdown': FieldInfo(annotation=str, required=True), 'document_type': FieldInfo(annotation=PdfDocumentType, required=True), 'short_term_storage_request_id': FieldInfo(annotation=UUID, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.RequestUser(*, user_id: int)

Bases: Model

user_id: int

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'user_id': FieldInfo(annotation=int, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.GenerateHistoryDownload(*, model_store_format: ModelStoreFormat = ModelStoreFormat.TAR_DOT_GZ, include_files: bool = True, include_deleted: bool = False, include_hidden: bool = False, short_term_storage_request_id: UUID, duration: int | float | None = None, history_id: int, user: RequestUser, export_association_id: int | None = None)

Bases: ShortTermStoreExportPayload

history_id: int

user: RequestUser

export_association_id: int | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'duration': FieldInfo(annotation=Union[int, float, NoneType], required=False, default=None), 'export_association_id': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'history_id': FieldInfo(annotation=int, required=True), 'include_deleted': FieldInfo(annotation=bool, required=False, default=False, title='Include deleted', description='Include file contents for deleted datasets (if include_files is True).'), 'include_files': FieldInfo(annotation=bool, required=False, default=True, description='include materialized files in export when available'), 'include_hidden': FieldInfo(annotation=bool, required=False, default=False, title='Include hidden', description='Include file contents for hidden datasets (if include_files is True).'), 'model_store_format': FieldInfo(annotation=ModelStoreFormat, required=False, default=<ModelStoreFormat.TAR_DOT_GZ: 'tar.gz'>, description='format of model store to export'), 'short_term_storage_request_id': FieldInfo(annotation=UUID, required=True), 'user': FieldInfo(annotation=RequestUser, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.GenerateHistoryContentDownload(*, model_store_format: ModelStoreFormat = ModelStoreFormat.TAR_DOT_GZ, include_files: bool = True, include_deleted: bool = False, include_hidden: bool = False, short_term_storage_request_id: UUID, duration: int | float | None = None, content_type: HistoryContentType, content_id: int, user: RequestUser)

Bases: ShortTermStoreExportPayload

content_type: HistoryContentType

content_id: int

user: RequestUser

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'content_id': FieldInfo(annotation=int, required=True), 'content_type': FieldInfo(annotation=HistoryContentType, required=True), 'duration': FieldInfo(annotation=Union[int, float, NoneType], required=False, default=None), 'include_deleted': FieldInfo(annotation=bool, required=False, default=False, title='Include deleted', description='Include file contents for deleted datasets (if include_files is True).'), 'include_files': FieldInfo(annotation=bool, required=False, default=True, description='include materialized files in export when available'), 'include_hidden': FieldInfo(annotation=bool, required=False, default=False, title='Include hidden', description='Include file contents for hidden datasets (if include_files is True).'), 'model_store_format': FieldInfo(annotation=ModelStoreFormat, required=False, default=<ModelStoreFormat.TAR_DOT_GZ: 'tar.gz'>, description='format of model store to export'), 'short_term_storage_request_id': FieldInfo(annotation=UUID, required=True), 'user': FieldInfo(annotation=RequestUser, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.BcoGenerationTaskParametersMixin(*, bco_merge_history_metadata: bool = False, bco_override_environment_variables: Dict[str, str] | None = None, bco_override_empirical_error: Dict[str, str] | None = None, bco_override_algorithmic_error: Dict[str, str] | None = None, bco_override_xref: List[XrefItem] | None = None, galaxy_url: str)

Bases: BcoGenerationParametersMixin

galaxy_url: str

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'bco_merge_history_metadata': FieldInfo(annotation=bool, required=False, default=False, description='When reading tags/annotations to generate BCO object include history metadata.'), 'bco_override_algorithmic_error': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override algorithmic error for 'error domain' when generating BioCompute object."), 'bco_override_empirical_error': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override empirical error for 'error domain' when generating BioCompute object."), 'bco_override_environment_variables': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override environment variables for 'execution_domain' when generating BioCompute object."), 'bco_override_xref': FieldInfo(annotation=Union[List[galaxy.schema.bco.description_domain.XrefItem], NoneType], required=False, default=None, description="Override xref for 'description domain' when generating BioCompute object."), 'galaxy_url': FieldInfo(annotation=str, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.GenerateInvocationDownload(*, bco_merge_history_metadata: bool = False, bco_override_environment_variables: Dict[str, str] | None = None, bco_override_empirical_error: Dict[str, str] | None = None, bco_override_algorithmic_error: Dict[str, str] | None = None, bco_override_xref: List[XrefItem] | None = None, galaxy_url: str, model_store_format: ModelStoreFormat = ModelStoreFormat.TAR_DOT_GZ, include_files: bool = True, include_deleted: bool = False, include_hidden: bool = False, short_term_storage_request_id: UUID, duration: int | float | None = None, invocation_id: int, user: RequestUser)

Bases: ShortTermStoreExportPayload, BcoGenerationTaskParametersMixin

invocation_id: int

user: RequestUser

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'bco_merge_history_metadata': FieldInfo(annotation=bool, required=False, default=False, description='When reading tags/annotations to generate BCO object include history metadata.'), 'bco_override_algorithmic_error': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override algorithmic error for 'error domain' when generating BioCompute object."), 'bco_override_empirical_error': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override empirical error for 'error domain' when generating BioCompute object."), 'bco_override_environment_variables': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override environment variables for 'execution_domain' when generating BioCompute object."), 'bco_override_xref': FieldInfo(annotation=Union[List[galaxy.schema.bco.description_domain.XrefItem], NoneType], required=False, default=None, description="Override xref for 'description domain' when generating BioCompute object."), 'duration': FieldInfo(annotation=Union[int, float, NoneType], required=False, default=None), 'galaxy_url': FieldInfo(annotation=str, required=True), 'include_deleted': FieldInfo(annotation=bool, required=False, default=False, title='Include deleted', description='Include file contents for deleted datasets (if include_files is True).'), 'include_files': FieldInfo(annotation=bool, required=False, default=True, description='include materialized files in export when available'), 'include_hidden': FieldInfo(annotation=bool, required=False, default=False, title='Include hidden', description='Include file contents for hidden datasets (if include_files is True).'), 'invocation_id': FieldInfo(annotation=int, required=True), 'model_store_format': FieldInfo(annotation=ModelStoreFormat, required=False, default=<ModelStoreFormat.TAR_DOT_GZ: 'tar.gz'>, description='format of model store to export'), 'short_term_storage_request_id': FieldInfo(annotation=UUID, required=True), 'user': FieldInfo(annotation=RequestUser, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.WriteInvocationTo(*, bco_merge_history_metadata: bool = False, bco_override_environment_variables: Dict[str, str] | None = None, bco_override_empirical_error: Dict[str, str] | None = None, bco_override_algorithmic_error: Dict[str, str] | None = None, bco_override_xref: List[XrefItem] | None = None, galaxy_url: str, model_store_format: ModelStoreFormat = ModelStoreFormat.TAR_DOT_GZ, include_files: bool = True, include_deleted: bool = False, include_hidden: bool = False, target_uri: str, invocation_id: int, user: RequestUser)

Bases: WriteStoreToPayload, BcoGenerationTaskParametersMixin

invocation_id: int

user: RequestUser

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'bco_merge_history_metadata': FieldInfo(annotation=bool, required=False, default=False, description='When reading tags/annotations to generate BCO object include history metadata.'), 'bco_override_algorithmic_error': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override algorithmic error for 'error domain' when generating BioCompute object."), 'bco_override_empirical_error': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override empirical error for 'error domain' when generating BioCompute object."), 'bco_override_environment_variables': FieldInfo(annotation=Union[Dict[str, str], NoneType], required=False, default=None, description="Override environment variables for 'execution_domain' when generating BioCompute object."), 'bco_override_xref': FieldInfo(annotation=Union[List[galaxy.schema.bco.description_domain.XrefItem], NoneType], required=False, default=None, description="Override xref for 'description domain' when generating BioCompute object."), 'galaxy_url': FieldInfo(annotation=str, required=True), 'include_deleted': FieldInfo(annotation=bool, required=False, default=False, title='Include deleted', description='Include file contents for deleted datasets (if include_files is True).'), 'include_files': FieldInfo(annotation=bool, required=False, default=True, description='include materialized files in export when available'), 'include_hidden': FieldInfo(annotation=bool, required=False, default=False, title='Include hidden', description='Include file contents for hidden datasets (if include_files is True).'), 'invocation_id': FieldInfo(annotation=int, required=True), 'model_store_format': FieldInfo(annotation=ModelStoreFormat, required=False, default=<ModelStoreFormat.TAR_DOT_GZ: 'tar.gz'>, description='format of model store to export'), 'target_uri': FieldInfo(annotation=str, required=True, title='Target URI', description='Galaxy Files URI to write mode store content to.'), 'user': FieldInfo(annotation=RequestUser, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.WriteHistoryContentTo(*, model_store_format: ModelStoreFormat = ModelStoreFormat.TAR_DOT_GZ, include_files: bool = True, include_deleted: bool = False, include_hidden: bool = False, target_uri: str, content_type: HistoryContentType, content_id: int, user: RequestUser)

Bases: WriteStoreToPayload

content_type: HistoryContentType

content_id: int

user: RequestUser

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'content_id': FieldInfo(annotation=int, required=True), 'content_type': FieldInfo(annotation=HistoryContentType, required=True), 'include_deleted': FieldInfo(annotation=bool, required=False, default=False, title='Include deleted', description='Include file contents for deleted datasets (if include_files is True).'), 'include_files': FieldInfo(annotation=bool, required=False, default=True, description='include materialized files in export when available'), 'include_hidden': FieldInfo(annotation=bool, required=False, default=False, title='Include hidden', description='Include file contents for hidden datasets (if include_files is True).'), 'model_store_format': FieldInfo(annotation=ModelStoreFormat, required=False, default=<ModelStoreFormat.TAR_DOT_GZ: 'tar.gz'>, description='format of model store to export'), 'target_uri': FieldInfo(annotation=str, required=True, title='Target URI', description='Galaxy Files URI to write mode store content to.'), 'user': FieldInfo(annotation=RequestUser, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.WriteHistoryTo(*, model_store_format: ModelStoreFormat = ModelStoreFormat.TAR_DOT_GZ, include_files: bool = True, include_deleted: bool = False, include_hidden: bool = False, target_uri: str, history_id: int, user: RequestUser, export_association_id: int | None = None)

Bases: WriteStoreToPayload

history_id: int

user: RequestUser

export_association_id: int | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'export_association_id': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'history_id': FieldInfo(annotation=int, required=True), 'include_deleted': FieldInfo(annotation=bool, required=False, default=False, title='Include deleted', description='Include file contents for deleted datasets (if include_files is True).'), 'include_files': FieldInfo(annotation=bool, required=False, default=True, description='include materialized files in export when available'), 'include_hidden': FieldInfo(annotation=bool, required=False, default=False, title='Include hidden', description='Include file contents for hidden datasets (if include_files is True).'), 'model_store_format': FieldInfo(annotation=ModelStoreFormat, required=False, default=<ModelStoreFormat.TAR_DOT_GZ: 'tar.gz'>, description='format of model store to export'), 'target_uri': FieldInfo(annotation=str, required=True, title='Target URI', description='Galaxy Files URI to write mode store content to.'), 'user': FieldInfo(annotation=RequestUser, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.ImportModelStoreTaskRequest(*, user: RequestUser, history_id: int | None = None, source_uri: str, for_library: bool, model_store_format: ModelStoreFormat | None = None)

Bases: Model

user: RequestUser

history_id: int | None

source_uri: str

for_library: bool

model_store_format: ModelStoreFormat | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'for_library': FieldInfo(annotation=bool, required=True), 'history_id': FieldInfo(annotation=Union[int, NoneType], required=False, default=None), 'model_store_format': FieldInfo(annotation=Union[ModelStoreFormat, NoneType], required=False, default=None), 'source_uri': FieldInfo(annotation=str, required=True), 'user': FieldInfo(annotation=RequestUser, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.MaterializeDatasetInstanceTaskRequest(*, history_id: int, user: RequestUser, source: DatasetSourceType, content: int)

Bases: Model

history_id: int

user: RequestUser

source: DatasetSourceType

content: int

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'content': FieldInfo(annotation=int, required=True, title='Content', description='Depending on the `source` it can be:\n- The decoded id of the source library dataset\n- The decoded id of the HDA\n'), 'history_id': FieldInfo(annotation=int, required=True), 'source': FieldInfo(annotation=DatasetSourceType, required=True, title='Source', description='The source of the content. Can be other history element to be copied or library elements.'), 'user': FieldInfo(annotation=RequestUser, required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.ComputeDatasetHashTaskRequest(*, dataset_id: int, extra_files_path: str | None = None, hash_function: HashFunctionNameEnum, user: RequestUser | None = None)

Bases: Model

dataset_id: int

extra_files_path: str | None

hash_function: HashFunctionNameEnum

user: RequestUser | None

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'dataset_id': FieldInfo(annotation=int, required=True), 'extra_files_path': FieldInfo(annotation=Union[str, NoneType], required=False, default=None), 'hash_function': FieldInfo(annotation=HashFunctionNameEnum, required=True), 'user': FieldInfo(annotation=Union[RequestUser, NoneType], required=False, default=None)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

class galaxy.schema.tasks.PurgeDatasetsTaskRequest(*, dataset_ids: List[int])

Bases: Model

dataset_ids: List[int]

model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}

A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {'populate_by_name': True, 'protected_namespaces': (), 'use_enum_values': True}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[Dict[str, FieldInfo]] = {'dataset_ids': FieldInfo(annotation=List[int], required=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.

This replaces Model.__fields__ from Pydantic V1.

galaxy.schema.types module

galaxy.schema.types.strip_tzinfo(v: datetime, info: ValidationInfo) → datetime