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galaxy.model package

Galaxy data model classes

Naming: try to use class names that have a distinct plural form so that the relationship cardinalities are obvious (e.g. prefer Dataset to Data)

exception galaxy.model.NoConverterException(value)

Bases: exceptions.Exception

__init__(value)

exception galaxy.model.ConverterDependencyException(value)

Bases: exceptions.Exception

__init__(value)

galaxy.model.set_datatypes_registry(d_registry)

Set up datatypes_registry

class galaxy.model.HasTags

Bases: object

dict_collection_visible_keys = ['tags']

dict_element_visible_keys = ['tags']

to_dict(*args, **kwargs)

make_tag_string_list()

copy_tags_from(target_user, source)

class galaxy.model.HasName

get_display_name()

These objects have a name attribute can be either a string or a unicode object. If string, convert to unicode object assuming ‘utf-8’ format.

class galaxy.model.UsesCreateAndUpdateTime

seconds_since_updated

seconds_since_created

class galaxy.model.JobLike

add_metric(plugin, metric_name, metric_value)

metrics

set_streams(stdout, stderr)

log_str()

class galaxy.model.User(email=None, password=None)

Bases: object, galaxy.util.dictifiable.Dictifiable

use_pbkdf2 = True

Data for a Galaxy user or admin and relations to their histories, credentials, and roles.

dict_collection_visible_keys = ['id', 'email', 'username', 'deleted', 'active', 'last_password_change']

dict_element_visible_keys = ['id', 'email', 'username', 'total_disk_usage', 'nice_total_disk_usage', 'deleted', 'active', 'last_password_change']

__init__(email=None, password=None)

extra_preferences

set_password_cleartext(cleartext)

Set user password to the digest of cleartext.

check_password(cleartext)

Check if cleartext matches user password when hashed.

system_user_pwent(real_system_username)

Gives the system user pwent entry based on e-mail or username depending on the value in real_system_username

all_roles()

Return a unique list of Roles associated with this user or any of their groups.

all_roles_exploiting_cache()

get_disk_usage(nice_size=False)

Return byte count of disk space used by user or a human-readable string if nice_size is True.

set_disk_usage(bytes)

Manually set the disk space used by a user to bytes.

total_disk_usage

Return byte count of disk space used by user or a human-readable string if nice_size is True.

adjust_total_disk_usage(amount)

nice_total_disk_usage

Return byte count of disk space used in a human-readable string.

calculate_disk_usage()

Return byte count total of disk space used by all non-purged, non-library HDAs in non-purged histories.

calculate_and_set_disk_usage()

Calculates and sets user disk usage.

static user_template_environment(user)

>>> env = User.user_template_environment(None)
>>> env['__user_email__']
'Anonymous'
>>> env['__user_id__']
'Anonymous'
>>> user = User('foo@example.com')
>>> user.id = 6
>>> user.username = 'foo2'
>>> env = User.user_template_environment(user)
>>> env['__user_id__']
'6'
>>> env['__user_name__']
'foo2'

static expand_user_properties(user, in_string)

class galaxy.model.PasswordResetToken(user, token=None)

Bases: object

__init__(user, token=None)

class galaxy.model.BaseJobMetric(plugin, metric_name, metric_value)

Bases: object

__init__(plugin, metric_name, metric_value)

class galaxy.model.JobMetricText(plugin, metric_name, metric_value)

Bases: galaxy.model.BaseJobMetric

class galaxy.model.JobMetricNumeric(plugin, metric_name, metric_value)

Bases: galaxy.model.BaseJobMetric

class galaxy.model.TaskMetricText(plugin, metric_name, metric_value)

Bases: galaxy.model.BaseJobMetric

class galaxy.model.TaskMetricNumeric(plugin, metric_name, metric_value)

Bases: galaxy.model.BaseJobMetric

class galaxy.model.Job

Bases: object, galaxy.model.JobLike, galaxy.model.UsesCreateAndUpdateTime, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ['id', 'state', 'exit_code', 'update_time', 'create_time']

dict_element_visible_keys = ['id', 'state', 'exit_code', 'update_time', 'create_time']

A job represents a request to run a tool given input datasets, tool parameters, and output datasets.

states = <galaxy.util.bunch.Bunch object>

terminal_states = ['ok', 'error', 'deleted']

non_ready_states = ['new', 'resubmitted', 'upload', 'waiting', 'queued', 'running']

job states where the job hasn’t finished and the model may still change

__init__()

finished

get_external_output_metadata()

The external_output_metadata is currently a reference from Job to JobExternalOutputMetadata. It exists for a job but not a task.

get_session_id()

get_user_id()

get_tool_id()

get_tool_version()

get_command_line()

get_dependencies()

get_param_filename()

get_parameters()

get_copied_from_job_id()

get_input_datasets()

get_output_datasets()

get_input_library_datasets()

get_output_library_datasets()

get_state()

get_info()

get_job_runner_name()

get_job_runner_external_id()

get_post_job_actions()

get_imported()

get_handler()

get_params()

get_user()

get_id()

get_tasks()

get_id_tag()

Return a tag that can be useful in identifying a Job. This returns the Job’s get_id

set_session_id(session_id)

set_user_id(user_id)

set_tool_id(tool_id)

set_tool_version(tool_version)

set_command_line(command_line)

set_dependencies(dependencies)

set_param_filename(param_filename)

set_parameters(parameters)

set_copied_from_job_id(job_id)

set_input_datasets(input_datasets)

set_output_datasets(output_datasets)

set_input_library_datasets(input_library_datasets)

set_output_library_datasets(output_library_datasets)

set_info(info)

set_runner_name(job_runner_name)

get_job()

set_runner_external_id(job_runner_external_id)

set_post_job_actions(post_job_actions)

set_imported(imported)

set_handler(handler)

set_params(params)

add_parameter(name, value)

add_input_dataset(name, dataset=None, dataset_id=None)

add_output_dataset(name, dataset)

add_input_dataset_collection(name, dataset_collection)

add_output_dataset_collection(name, dataset_collection_instance)

add_implicit_output_dataset_collection(name, dataset_collection)

add_input_library_dataset(name, dataset)

add_output_library_dataset(name, dataset)

add_post_job_action(pja)

set_state(state)

Save state history

get_param_values(app, ignore_errors=False)

Read encoded parameter values from the database and turn back into a dict of tool parameter values.

raw_param_dict()

check_if_output_datasets_deleted()

Return true if all of the output datasets associated with this job are in the deleted state

mark_deleted(track_jobs_in_database=False)

Mark this job as deleted, and mark any output datasets as discarded.

to_dict(view='collection', system_details=False)

set_final_state(final_state)

get_destination_configuration(config, key, default=None)

Get a destination parameter that can be defaulted back in specified config if it needs to be applied globally.

class galaxy.model.Task(job, working_directory, prepare_files_cmd)

Bases: object, galaxy.model.JobLike

A task represents a single component of a job.

states = <galaxy.util.bunch.Bunch object>

__init__(job, working_directory, prepare_files_cmd)

get_param_values(app)

Read encoded parameter values from the database and turn back into a dict of tool parameter values.

get_id()

get_id_tag()

Return an id tag suitable for identifying the task. This combines the task’s job id and the task’s own id.

get_command_line()

get_parameters()

get_state()

get_info()

get_working_directory()

get_task_runner_name()

get_task_runner_external_id()

get_job()

get_stdout()

get_stderr()

get_prepare_input_files_cmd()

get_external_output_metadata()

The external_output_metadata is currently a backref to JobExternalOutputMetadata. It exists for a job but not a task, and when a task is cancelled its corresponding parent Job will be cancelled. So None is returned now, but that could be changed to self.get_job().get_external_output_metadata().

get_job_runner_name()

Since runners currently access Tasks the same way they access Jobs, this method just refers to this instance’s runner.

get_job_runner_external_id()

Runners will use the same methods to get information about the Task class as they will about the Job class, so this method just returns the task’s external id.

get_session_id()

set_id(id)

set_command_line(command_line)

set_parameters(parameters)

set_state(state)

set_info(info)

set_working_directory(working_directory)

set_task_runner_name(task_runner_name)

set_job_runner_external_id(task_runner_external_id)

set_task_runner_external_id(task_runner_external_id)

set_job(job)

set_stdout(stdout)

set_stderr(stderr)

set_prepare_input_files_cmd(prepare_input_files_cmd)

class galaxy.model.JobParameter(name, value)

Bases: object

__init__(name, value)

copy()

class galaxy.model.JobToInputDatasetAssociation(name, dataset)

Bases: object

__init__(name, dataset)

class galaxy.model.JobToOutputDatasetAssociation(name, dataset)

Bases: object

__init__(name, dataset)

class galaxy.model.JobToInputDatasetCollectionAssociation(name, dataset_collection)

Bases: object

__init__(name, dataset_collection)

class galaxy.model.JobToOutputDatasetCollectionAssociation(name, dataset_collection_instance)

Bases: object

__init__(name, dataset_collection_instance)

class galaxy.model.JobToImplicitOutputDatasetCollectionAssociation(name, dataset_collection)

Bases: object

__init__(name, dataset_collection)

class galaxy.model.JobToInputLibraryDatasetAssociation(name, dataset)

Bases: object

__init__(name, dataset)

class galaxy.model.JobToOutputLibraryDatasetAssociation(name, dataset)

Bases: object

__init__(name, dataset)

class galaxy.model.JobStateHistory(job)

Bases: object

__init__(job)

class galaxy.model.ImplicitlyCreatedDatasetCollectionInput(name, input_dataset_collection)

Bases: object

__init__(name, input_dataset_collection)

class galaxy.model.ImplicitCollectionJobs(id=None, populated_state=None)

Bases: object

populated_states = <galaxy.util.bunch.Bunch object>

__init__(id=None, populated_state=None)

job_list

class galaxy.model.ImplicitCollectionJobsJobAssociation

Bases: object

__init__()

class galaxy.model.PostJobAction(action_type, workflow_step, output_name=None, action_arguments=None)

Bases: object

__init__(action_type, workflow_step, output_name=None, action_arguments=None)

class galaxy.model.PostJobActionAssociation(pja, job=None, job_id=None)

Bases: object

__init__(pja, job=None, job_id=None)

class galaxy.model.JobExternalOutputMetadata(job=None, dataset=None)

Bases: object

__init__(job=None, dataset=None)

dataset

class galaxy.model.JobExportHistoryArchive(job=None, history=None, dataset=None, compressed=False, history_attrs_filename=None, datasets_attrs_filename=None, jobs_attrs_filename=None)

Bases: object

__init__(job=None, history=None, dataset=None, compressed=False, history_attrs_filename=None, datasets_attrs_filename=None, jobs_attrs_filename=None)

up_to_date

Return False, if a new export should be generated for corresponding history.

ready

preparing

export_name

class galaxy.model.JobImportHistoryArchive(job=None, history=None, archive_dir=None)

Bases: object

__init__(job=None, history=None, archive_dir=None)

class galaxy.model.GenomeIndexToolData(job=None, params=None, dataset=None, deferred_job=None, transfer_job=None, fasta_path=None, created_time=None, modified_time=None, dbkey=None, user=None, indexer=None)

Bases: object

__init__(job=None, params=None, dataset=None, deferred_job=None, transfer_job=None, fasta_path=None, created_time=None, modified_time=None, dbkey=None, user=None, indexer=None)

class galaxy.model.DeferredJob(state=None, plugin=None, params=None)

Bases: object

states = <galaxy.util.bunch.Bunch object>

__init__(state=None, plugin=None, params=None)

get_check_interval()

set_check_interval(seconds)

check_interval

get_last_check()

set_last_check(seconds)

last_check

is_check_time

class galaxy.model.Group(name=None)

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ['id', 'name']

dict_element_visible_keys = ['id', 'name']

__init__(name=None)

class galaxy.model.UserGroupAssociation(user, group)

Bases: object

__init__(user, group)

galaxy.model.is_hda(d)

class galaxy.model.History(id=None, name=None, user=None)

Bases: galaxy.model.HasTags, galaxy.util.dictifiable.Dictifiable, galaxy.model.item_attrs.UsesAnnotations, galaxy.model.HasName

dict_collection_visible_keys = ['id', 'name', 'published', 'deleted']

dict_element_visible_keys = ['id', 'name', 'genome_build', 'deleted', 'purged', 'update_time', 'published', 'importable', 'slug', 'empty']

default_name = 'Unnamed history'

__init__(id=None, name=None, user=None)

empty

add_galaxy_session(galaxy_session, association=None)

add_dataset(dataset, parent_id=None, genome_build=None, set_hid=True, quota=True)

add_datasets(sa_session, datasets, parent_id=None, genome_build=None, set_hid=True, quota=True, flush=False)

Optimized version of add_dataset above that minimizes database interactions when adding many datasets to history at once.

add_dataset_collection(history_dataset_collection, set_hid=True)

copy(name=None, target_user=None, activatable=False, all_datasets=False)

Return a copy of this history using the given name and target_user. If activatable, copy only non-deleted datasets. If all_datasets, copy non-deleted, deleted, and purged datasets.

activatable_datasets

to_dict(view='collection', value_mapper=None)

latest_export

unhide_datasets()

resume_paused_jobs()

disk_size

Return the size in bytes of this history by summing the ‘total_size’s of all non-purged, unique datasets within it.

disk_nice_size

Returns human readable size of history on disk.

active_datasets_and_roles

active_visible_datasets_and_roles

active_visible_dataset_collections

active_contents

Return all active contents ordered by hid.

contents_iter(**kwds)

Fetch filtered list of contents of history.

class galaxy.model.HistoryUserShareAssociation

Bases: object

__init__()

class galaxy.model.UserRoleAssociation(user, role)

Bases: object

__init__(user, role)

class galaxy.model.GroupRoleAssociation(group, role)

Bases: object

__init__(group, role)

class galaxy.model.Role(name='', description='', type='system', deleted=False)

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ['id', 'name']

dict_element_visible_keys = ['id', 'name', 'description', 'type']

private_id = None

types = <galaxy.util.bunch.Bunch object>

__init__(name='', description='', type='system', deleted=False)

class galaxy.model.UserQuotaAssociation(user, quota)

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_element_visible_keys = ['user']

__init__(user, quota)

class galaxy.model.GroupQuotaAssociation(group, quota)

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_element_visible_keys = ['group']

__init__(group, quota)

class galaxy.model.Quota(name='', description='', amount=0, operation='=')

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ['id', 'name']

dict_element_visible_keys = ['id', 'name', 'description', 'bytes', 'operation', 'display_amount', 'default', 'users', 'groups']

valid_operations = ('+', '-', '=')

__init__(name='', description='', amount=0, operation='=')

get_amount()

set_amount(amount)

amount

display_amount

class galaxy.model.DefaultQuotaAssociation(type, quota)

Bases: galaxy.model.Quota, galaxy.util.dictifiable.Dictifiable

dict_element_visible_keys = ['type']

types = <galaxy.util.bunch.Bunch object>

__init__(type, quota)

class galaxy.model.DatasetPermissions(action, dataset, role=None, role_id=None)

Bases: object

__init__(action, dataset, role=None, role_id=None)

class galaxy.model.LibraryPermissions(action, library_item, role)

Bases: object

__init__(action, library_item, role)

class galaxy.model.LibraryFolderPermissions(action, library_item, role)

Bases: object

__init__(action, library_item, role)

class galaxy.model.LibraryDatasetPermissions(action, library_item, role)

Bases: object

__init__(action, library_item, role)

class galaxy.model.LibraryDatasetDatasetAssociationPermissions(action, library_item, role)

Bases: object

__init__(action, library_item, role)

class galaxy.model.DefaultUserPermissions(user, action, role)

Bases: object

__init__(user, action, role)

class galaxy.model.DefaultHistoryPermissions(history, action, role)

Bases: object

__init__(history, action, role)

class galaxy.model.StorableObject(id, **kwargs)

Bases: object

__init__(id, **kwargs)

class galaxy.model.Dataset(id=None, state=None, external_filename=None, extra_files_path=None, file_size=None, purgable=True, uuid=None)

Bases: galaxy.model.StorableObject

states = <galaxy.util.bunch.Bunch object>

non_ready_states = ('new', 'upload', 'queued', 'running', 'setting_metadata')

ready_states = ('discarded', 'ok', 'failed_metadata', 'paused', 'error', 'empty')

valid_input_states = ('ok', 'failed_metadata', 'upload', 'paused', 'running', 'setting_metadata', 'new', 'queued', 'empty')

terminal_states = ('ok', 'empty', 'error', 'discarded', 'failed_metadata')

conversion_messages = <galaxy.util.bunch.Bunch object>

permitted_actions = <galaxy.util.bunch.Bunch object>

file_path = '/tmp/'

object_store = None

engine = None

__init__(id=None, state=None, external_filename=None, extra_files_path=None, file_size=None, purgable=True, uuid=None)

in_ready_state()

get_file_name()

set_file_name(filename)

file_name

get_extra_files_path()

set_extra_files_path(extra_files_path)

extra_files_path

get_size(nice_size=False)

Returns the size of the data on disk

set_size()

Sets the size of the data on disk

get_total_size()

set_total_size()

has_data()

Detects whether there is any data

mark_deleted()

user_can_purge

full_delete()

Remove the file and extra files, marks deleted and purged

get_access_roles(trans)

get_manage_permissions_roles(trans)

has_manage_permissions_roles(trans)

galaxy.model.datatype_for_extension(extension, datatypes_registry=None)

class galaxy.model.DatasetInstance(id=None, hid=None, name=None, info=None, blurb=None, peek=None, tool_version=None, extension=None, dbkey=None, metadata=None, history=None, dataset=None, deleted=False, designation=None, parent_id=None, validation_errors=None, visible=True, create_dataset=False, sa_session=None, extended_metadata=None, flush=True)

Bases: object

A base class for all ‘dataset instances’, HDAs, LDAs, etc

states = <galaxy.util.bunch.Bunch object>

conversion_messages = <galaxy.util.bunch.Bunch object>

permitted_actions = <galaxy.util.bunch.Bunch object>

__init__(id=None, hid=None, name=None, info=None, blurb=None, peek=None, tool_version=None, extension=None, dbkey=None, metadata=None, history=None, dataset=None, deleted=False, designation=None, parent_id=None, validation_errors=None, visible=True, create_dataset=False, sa_session=None, extended_metadata=None, flush=True)

update()

ext

get_dataset_state()

raw_set_dataset_state(state)

set_dataset_state(state)

state

get_file_name()

set_file_name(filename)

file_name

extra_files_path

datatype

get_metadata()

set_metadata(bunch)

metadata

get_dbkey()

set_dbkey(value)

dbkey

change_datatype(new_ext)

get_size(nice_size=False)

Returns the size of the data on disk

set_size()

Sets and gets the size of the data on disk

get_total_size()

set_total_size()

has_data()

Detects whether there is any data

get_raw_data()

Returns the full data. To stream it open the file_name and read/write as needed

write_from_stream(stream)

Writes data from a stream

set_raw_data(data)

Saves the data on the disc

get_mime()

Returns the mime type of the data

set_peek()

init_meta(copy_from=None)

set_meta(**kwd)

missing_meta(**kwd)

as_display_type(type, **kwd)

display_peek()

display_name()

display_info()

get_converted_files_by_type(file_type)

get_converted_dataset_deps(trans, target_ext)

Returns dict of { “dependency” => HDA }

get_converted_dataset(trans, target_ext, target_context=None, history=None)

Return converted dataset(s) if they exist, along with a dict of dependencies. If not converted yet, do so and return None (the first time). If unconvertible, raise exception.

copy_attributes(new_dataset)

Copies attributes to a new datasets, used for implicit conversions

get_metadata_dataset(dataset_ext)

Returns an HDA that points to a metadata file which contains a converted data with the requested extension.

clear_associated_files(metadata_safe=False, purge=False)

get_converter_types()

can_convert_to(format)

find_conversion_destination(accepted_formats, **kwd)

Returns ( target_ext, existing converted dataset )

add_validation_error(validation_error)

extend_validation_errors(validation_errors)

mark_deleted()

mark_undeleted()

mark_unhidden()

undeletable()

is_ok

is_pending

Return true if the dataset is neither ready nor in error

source_library_dataset

source_dataset_chain

creating_job

get_display_applications(trans)

get_visualizations()

get_datasources(trans)

Returns datasources for dataset; if datasources are not available due to indexing, indexing is started. Return value is a dictionary with entries of type (<datasource_type> : {<datasource_name>, <indexing_message>}).

convert_dataset(trans, target_type)

Converts a dataset to the target_type and returns a message indicating status of the conversion. None is returned to indicate that dataset was converted successfully.

class galaxy.model.HistoryDatasetAssociation(hid=None, history=None, copied_from_history_dataset_association=None, copied_from_library_dataset_dataset_association=None, sa_session=None, **kwd)

Bases: galaxy.model.DatasetInstance, galaxy.model.HasTags, galaxy.util.dictifiable.Dictifiable, galaxy.model.item_attrs.UsesAnnotations, galaxy.model.HasName

Resource class that creates a relation between a dataset and a user history.

__init__(hid=None, history=None, copied_from_history_dataset_association=None, copied_from_library_dataset_dataset_association=None, sa_session=None, **kwd)

Create a a new HDA and associate it with the given history.

copy(parent_id=None, copy_tags=None)

Create a copy of this HDA.

copy_tags_to(copy_tags=None)

copy_attributes(new_dataset)

to_library_dataset_dataset_association(trans, target_folder, replace_dataset=None, parent_id=None, user=None, roles=None, ldda_message='', element_identifier=None)

Copy this HDA to a library optionally replacing an existing LDDA.

clear_associated_files(metadata_safe=False, purge=False)

get_access_roles(trans)

Return The access roles associated with this HDA’s dataset.

quota_amount(user)

Return the disk space used for this HDA relevant to user quotas.

If the user has multiple instances of this dataset, it will not affect their disk usage statistic.

to_dict(view='collection', expose_dataset_path=False)

Return attributes of this HDA that are exposed using the API.

history_content_type

content_type = u'dataset'

type_id

class galaxy.model.HistoryDatasetAssociationHistory(history_dataset_association_id, name, dbkey, update_time, version, extension, extended_metadata_id, metadata)

Bases: object

__init__(history_dataset_association_id, name, dbkey, update_time, version, extension, extended_metadata_id, metadata)

class galaxy.model.HistoryDatasetAssociationDisplayAtAuthorization(hda=None, user=None, site=None)

Bases: object

__init__(hda=None, user=None, site=None)

class galaxy.model.HistoryDatasetAssociationSubset(hda, subset, location)

Bases: object

__init__(hda, subset, location)

class galaxy.model.Library(name=None, description=None, synopsis=None, root_folder=None)

Bases: object, galaxy.util.dictifiable.Dictifiable, galaxy.model.HasName

permitted_actions = <galaxy.util.bunch.Bunch object>

dict_collection_visible_keys = ['id', 'name']

dict_element_visible_keys = ['id', 'deleted', 'name', 'description', 'synopsis', 'root_folder_id', 'create_time']

__init__(name=None, description=None, synopsis=None, root_folder=None)

to_dict(view='collection', value_mapper=None)

We prepend an F to folders.

get_active_folders(folder, folders=None)

get_access_roles(trans)

class galaxy.model.LibraryFolder(name=None, description=None, item_count=0, order_id=None)

Bases: object, galaxy.util.dictifiable.Dictifiable, galaxy.model.HasName

dict_element_visible_keys = ['id', 'parent_id', 'name', 'description', 'item_count', 'genome_build', 'update_time', 'deleted']

__init__(name=None, description=None, item_count=0, order_id=None)

add_library_dataset(library_dataset, genome_build=None)

add_folder(folder)

activatable_library_datasets

to_dict(view='collection', value_mapper=None)

library_path

parent_library

class galaxy.model.LibraryDataset(folder=None, order_id=None, name=None, info=None, library_dataset_dataset_association=None, **kwd)

Bases: object

upload_options = [('upload_file', 'Upload files'), ('upload_directory', 'Upload directory of files'), ('upload_paths', 'Upload files from filesystem paths'), ('import_from_history', 'Import datasets from your current history')]

__init__(folder=None, order_id=None, name=None, info=None, library_dataset_dataset_association=None, **kwd)

set_library_dataset_dataset_association(ldda)

get_info()

set_info(info)

info

get_name()

set_name(name)

name

display_name()

to_dict(view='collection')

class galaxy.model.LibraryDatasetDatasetAssociation(copied_from_history_dataset_association=None, copied_from_library_dataset_dataset_association=None, library_dataset=None, user=None, sa_session=None, **kwd)

Bases: galaxy.model.DatasetInstance, galaxy.model.HasName

__init__(copied_from_history_dataset_association=None, copied_from_library_dataset_dataset_association=None, library_dataset=None, user=None, sa_session=None, **kwd)

to_history_dataset_association(target_history, parent_id=None, add_to_history=False)

copy(parent_id=None, target_folder=None)

clear_associated_files(metadata_safe=False, purge=False)

get_access_roles(trans)

get_manage_permissions_roles(trans)

has_manage_permissions_roles(trans)

to_dict(view='collection')

class galaxy.model.ExtendedMetadata(data)

Bases: object

__init__(data)

class galaxy.model.ExtendedMetadataIndex(extended_metadata, path, value)

Bases: object

__init__(extended_metadata, path, value)

class galaxy.model.LibraryInfoAssociation(library, form_definition, info, inheritable=False)

Bases: object

__init__(library, form_definition, info, inheritable=False)

class galaxy.model.LibraryFolderInfoAssociation(folder, form_definition, info, inheritable=False)

Bases: object

__init__(folder, form_definition, info, inheritable=False)

class galaxy.model.LibraryDatasetDatasetInfoAssociation(library_dataset_dataset_association, form_definition, info)

Bases: object

__init__(library_dataset_dataset_association, form_definition, info)

inheritable

class galaxy.model.ValidationError(message=None, err_type=None, attributes=None)

Bases: object

__init__(message=None, err_type=None, attributes=None)

class galaxy.model.DatasetToValidationErrorAssociation(dataset, validation_error)

Bases: object

__init__(dataset, validation_error)

class galaxy.model.ImplicitlyConvertedDatasetAssociation(id=None, parent=None, dataset=None, file_type=None, deleted=False, purged=False, metadata_safe=True)

Bases: object

__init__(id=None, parent=None, dataset=None, file_type=None, deleted=False, purged=False, metadata_safe=True)

clear(purge=False, delete_dataset=True)

class galaxy.model.DatasetCollection(id=None, collection_type=None, populated=True, element_count=None)

Bases: object, galaxy.util.dictifiable.Dictifiable, galaxy.model.item_attrs.UsesAnnotations

dict_collection_visible_keys = ['id', 'collection_type']

dict_element_visible_keys = ['id', 'collection_type']

populated_states = <galaxy.util.bunch.Bunch object>

__init__(id=None, collection_type=None, populated=True, element_count=None)

dataset_states_and_extensions_summary

populated_optimized

populated

waiting_for_elements

mark_as_populated()

handle_population_failed(message)

finalize()

dataset_instances

dataset_elements

state

validate()

copy(destination=None, element_destination=None)

replace_failed_elements(replacements)

set_from_dict(new_data)

has_subcollections

class galaxy.model.DatasetCollectionInstance(collection=None, deleted=False)

Bases: object, galaxy.model.HasName

__init__(collection=None, deleted=False)

state

populated

dataset_instances

display_name()

set_from_dict(new_data)

Set object attributes to the values in dictionary new_data limiting to only those keys in dict_element_visible_keys.

Returns a dictionary of the keys, values that have been changed.

class galaxy.model.HistoryDatasetCollectionAssociation(id=None, hid=None, collection=None, history=None, name=None, deleted=False, visible=True, copied_from_history_dataset_collection_association=None, implicit_output_name=None, implicit_input_collections=[])

Bases: galaxy.model.DatasetCollectionInstance, galaxy.model.HasTags, galaxy.util.dictifiable.Dictifiable, galaxy.model.item_attrs.UsesAnnotations

Associates a DatasetCollection with a History.

editable_keys = ('name', 'deleted', 'visible')

__init__(id=None, hid=None, collection=None, history=None, name=None, deleted=False, visible=True, copied_from_history_dataset_collection_association=None, implicit_output_name=None, implicit_input_collections=[])

history_content_type

content_type = u'dataset_collection'

type_id

job_source_type

job_source_id

to_hda_representative(multiple=False)

to_dict(view='collection')

add_implicit_input_collection(name, history_dataset_collection)

find_implicit_input_collection(name)

copy(element_destination=None)

Create a copy of this history dataset collection association. Copy underlying collection.

class galaxy.model.LibraryDatasetCollectionAssociation(id=None, collection=None, name=None, deleted=False, folder=None)

Bases: galaxy.model.DatasetCollectionInstance

Associates a DatasetCollection with a library folder.

editable_keys = ('name', 'deleted')

__init__(id=None, collection=None, name=None, deleted=False, folder=None)

to_dict(view='collection')

class galaxy.model.DatasetCollectionElement(id=None, collection=None, element=None, element_index=None, element_identifier=None)

Bases: object, galaxy.util.dictifiable.Dictifiable

Associates a DatasetInstance (hda or ldda) with a DatasetCollection.

dict_collection_visible_keys = ['id', 'element_type', 'element_index', 'element_identifier']

dict_element_visible_keys = ['id', 'element_type', 'element_index', 'element_identifier']

UNINITIALIZED_ELEMENT = <object object>

__init__(id=None, collection=None, element=None, element_index=None, element_identifier=None)

element_type

is_collection

element_object

dataset_instance

dataset

first_dataset_instance()

dataset_instances

copy_to_collection(collection, destination=None, element_destination=None)

class galaxy.model.Event(message=None, history=None, user=None, galaxy_session=None)

Bases: object

__init__(message=None, history=None, user=None, galaxy_session=None)

class galaxy.model.GalaxySession(id=None, user=None, remote_host=None, remote_addr=None, referer=None, current_history=None, session_key=None, is_valid=False, prev_session_id=None, last_action=None)

Bases: object

__init__(id=None, user=None, remote_host=None, remote_addr=None, referer=None, current_history=None, session_key=None, is_valid=False, prev_session_id=None, last_action=None)

add_history(history, association=None)

get_disk_usage()

set_disk_usage(bytes)

total_disk_usage

class galaxy.model.GalaxySessionToHistoryAssociation(galaxy_session, history)

Bases: object

__init__(galaxy_session, history)

class galaxy.model.UCI

Bases: object

__init__()

class galaxy.model.StoredWorkflow

Bases: galaxy.model.HasTags, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ['id', 'name', 'published', 'deleted']

dict_element_visible_keys = ['id', 'name', 'published', 'deleted']

__init__()

show_in_tool_panel(user_id)

copy_tags_from(target_user, source_workflow)

to_dict(view='collection', value_mapper=None)

class galaxy.model.Workflow(uuid=None)

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ['name', 'has_cycles', 'has_errors']

dict_element_visible_keys = ['name', 'has_cycles', 'has_errors']

input_step_types = ['data_input', 'data_collection_input', 'parameter_input']

__init__(uuid=None)

has_outputs_defined()

Returns true or false indicating whether or not a workflow has outputs defined.

to_dict(view='collection', value_mapper=None)

steps_by_id

step_by_index(order_index)

input_steps

workflow_outputs

top_level_workflow

If this workflow is not attached to stored workflow directly, recursively grab its parents until it is the top level workflow which must have a stored workflow associated with it.

top_level_stored_workflow

If this workflow is not attached to stored workflow directly, recursively grab its parents until it is the top level workflow which must have a stored workflow associated with it and then grab that stored workflow.

copy()

Copy a workflow (without user information) for a new StoredWorkflow object.

log_str()

class galaxy.model.WorkflowStep

Bases: object

__init__()

unique_workflow_outputs

content_id

input_connections_by_name

setup_input_connections_by_name()

create_or_update_workflow_output(output_name, label, uuid)

workflow_output_for(output_name)

copy_to(copied_step, step_mapping)

log_str()

class galaxy.model.WorkflowStepConnection

Bases: object

NON_DATA_CONNECTION = '__NO_INPUT_OUTPUT_NAME__'

__init__()

set_non_data_connection()

non_data_connection

copy()

class galaxy.model.WorkflowOutput(workflow_step, output_name=None, label=None, uuid=None)

Bases: object

__init__(workflow_step, output_name=None, label=None, uuid=None)

copy(copied_step)

class galaxy.model.StoredWorkflowUserShareAssociation

Bases: object

__init__()

class galaxy.model.StoredWorkflowMenuEntry

Bases: object

__init__()

class galaxy.model.WorkflowInvocation

Bases: object, galaxy.model.UsesCreateAndUpdateTime, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ['id', 'update_time', 'workflow_id', 'history_id', 'uuid', 'state']

dict_element_visible_keys = ['id', 'update_time', 'workflow_id', 'history_id', 'uuid', 'state']

states = <galaxy.util.bunch.Bunch object>

__init__()

create_subworkflow_invocation_for_step(step)

attach_subworkflow_invocation_for_step(step, subworkflow_invocation)

get_subworkflow_invocation_for_step(step)

get_subworkflow_invocation_association_for_step(step)

active

Indicates the workflow invocation is somehow active - and in particular valid actions may be performed on its WorkflowInvocationSteps.

cancel()

fail()

step_states_by_step_id()

step_invocations_by_step_id()

step_invocation_for_step_id(step_id)

static poll_active_workflow_ids(sa_session, scheduler=None, handler=None)

add_output(workflow_output, step, output_object)

to_dict(view='collection', value_mapper=None, step_details=False, legacy_job_state=False)

update()

add_input(content, step_id)

has_input_for_step(step_id)

class galaxy.model.WorkflowInvocationToSubworkflowInvocationAssociation

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ['id', 'workflow_step_id', 'workflow_invocation_id', 'subworkflow_invocation_id']

dict_element_visible_keys = ['id', 'workflow_step_id', 'workflow_invocation_id', 'subworkflow_invocation_id']

class galaxy.model.WorkflowInvocationStep

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ['id', 'update_time', 'job_id', 'workflow_step_id', 'state', 'action']

dict_element_visible_keys = ['id', 'update_time', 'job_id', 'workflow_step_id', 'state', 'action']

states = <galaxy.util.bunch.Bunch object>

update()

is_new

add_output(output_name, output_object)

jobs

to_dict(view='collection', value_mapper=None)

class galaxy.model.WorkflowInvocationStepJobAssociation

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ('id', 'job_id', 'workflow_invocation_step_id')

dict_element_visible_keys = ('id', 'job_id', 'workflow_invocation_step_id')

class galaxy.model.WorkflowRequest

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ['id', 'name', 'type', 'state', 'history_id', 'workflow_id']

dict_element_visible_keys = ['id', 'name', 'type', 'state', 'history_id', 'workflow_id']

to_dict(view='collection', value_mapper=None)

class galaxy.model.WorkflowRequestInputParameter(name=None, value=None, type=None)

Bases: object, galaxy.util.dictifiable.Dictifiable

Workflow-related parameters not tied to steps or inputs.

dict_collection_visible_keys = ['id', 'name', 'value', 'type']

types = <galaxy.util.bunch.Bunch object>

__init__(name=None, value=None, type=None)

class galaxy.model.WorkflowRequestStepState(workflow_step=None, name=None, value=None)

Bases: object, galaxy.util.dictifiable.Dictifiable

Workflow step value parameters.

dict_collection_visible_keys = ['id', 'name', 'value', 'workflow_step_id']

__init__(workflow_step=None, name=None, value=None)

class galaxy.model.WorkflowRequestToInputDatasetAssociation

Bases: object, galaxy.util.dictifiable.Dictifiable

Workflow step input dataset parameters.

dict_collection_visible_keys = ['id', 'workflow_invocation_id', 'workflow_step_id', 'dataset_id', 'name']

class galaxy.model.WorkflowRequestToInputDatasetCollectionAssociation

Bases: object, galaxy.util.dictifiable.Dictifiable

Workflow step input dataset collection parameters.

dict_collection_visible_keys = ['id', 'workflow_invocation_id', 'workflow_step_id', 'dataset_collection_id', 'name']

class galaxy.model.WorkflowRequestInputStepParmeter

Bases: object, galaxy.util.dictifiable.Dictifiable

Workflow step parameter inputs.

dict_collection_visible_keys = ['id', 'workflow_invocation_id', 'workflow_step_id', 'parameter_value']

class galaxy.model.WorkflowInvocationOutputDatasetAssociation

Bases: object, galaxy.util.dictifiable.Dictifiable

Represents links to output datasets for the workflow.

dict_collection_visible_keys = ['id', 'workflow_invocation_id', 'workflow_step_id', 'dataset_id', 'name']

class galaxy.model.WorkflowInvocationOutputDatasetCollectionAssociation

Bases: object, galaxy.util.dictifiable.Dictifiable

Represents links to output dataset collections for the workflow.

dict_collection_visible_keys = ['id', 'workflow_invocation_id', 'workflow_step_id', 'dataset_collection_id', 'name']

class galaxy.model.WorkflowInvocationStepOutputDatasetAssociation

Bases: object, galaxy.util.dictifiable.Dictifiable

Represents links to output datasets for the workflow.

dict_collection_visible_keys = ['id', 'workflow_invocation_step_id', 'dataset_id', 'output_name']

class galaxy.model.WorkflowInvocationStepOutputDatasetCollectionAssociation

Bases: object, galaxy.util.dictifiable.Dictifiable

Represents links to output dataset collections for the workflow.

dict_collection_visible_keys = ['id', 'workflow_invocation_step_id', 'dataset_collection_id', 'output_name']

class galaxy.model.MetadataFile(dataset=None, name=None)

Bases: galaxy.model.StorableObject

__init__(dataset=None, name=None)

file_name

class galaxy.model.FormDefinition(name=None, desc=None, fields=[], form_definition_current=None, form_type=None, layout=None)

Bases: object, galaxy.util.dictifiable.Dictifiable

supported_field_types = [<class 'galaxy.web.form_builder.AddressField'>, <class 'galaxy.web.form_builder.CheckboxField'>, <class 'galaxy.web.form_builder.PasswordField'>, <class 'galaxy.web.form_builder.SelectField'>, <class 'galaxy.web.form_builder.TextArea'>, <class 'galaxy.web.form_builder.TextField'>, <class 'galaxy.web.form_builder.WorkflowField'>, <class 'galaxy.web.form_builder.WorkflowMappingField'>, <class 'galaxy.web.form_builder.HistoryField'>]

types = <galaxy.util.bunch.Bunch object>

dict_collection_visible_keys = ['id', 'name']

dict_element_visible_keys = ['id', 'name', 'desc', 'form_definition_current_id', 'fields', 'layout']

__init__(name=None, desc=None, fields=[], form_definition_current=None, form_type=None, layout=None)

to_dict(user=None, values=None, security=None)

grid_fields(grid_index)

class galaxy.model.FormDefinitionCurrent(form_definition=None)

Bases: object

__init__(form_definition=None)

class galaxy.model.FormValues(form_def=None, content=None)

Bases: object

__init__(form_def=None, content=None)

class galaxy.model.UserAddress(user=None, desc=None, name=None, institution=None, address=None, city=None, state=None, postal_code=None, country=None, phone=None)

Bases: object

__init__(user=None, desc=None, name=None, institution=None, address=None, city=None, state=None, postal_code=None, country=None, phone=None)

to_dict(trans)

class galaxy.model.UserOpenID(user=None, session=None, openid=None)

Bases: object

__init__(user=None, session=None, openid=None)

class galaxy.model.Page

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_element_visible_keys = ['id', 'title', 'latest_revision_id', 'slug', 'published', 'importable', 'deleted']

__init__()

to_dict(view='element')

class galaxy.model.PageRevision

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_element_visible_keys = ['id', 'page_id', 'title', 'content']

__init__()

to_dict(view='element')

class galaxy.model.PageUserShareAssociation

Bases: object

__init__()

class galaxy.model.Visualization(id=None, user=None, type=None, title=None, dbkey=None, slug=None, latest_revision=None)

Bases: object

__init__(id=None, user=None, type=None, title=None, dbkey=None, slug=None, latest_revision=None)

copy(user=None, title=None)

Provide copy of visualization with only its latest revision.

class galaxy.model.VisualizationRevision(visualization=None, title=None, dbkey=None, config=None)

Bases: object

__init__(visualization=None, title=None, dbkey=None, config=None)

copy(visualization=None)

Returns a copy of this object.

class galaxy.model.VisualizationUserShareAssociation

Bases: object

__init__()

class galaxy.model.TransferJob(state=None, path=None, info=None, pid=None, socket=None, params=None)

Bases: object

states = <galaxy.util.bunch.Bunch object>

terminal_states = ['error', 'done']

__init__(state=None, path=None, info=None, pid=None, socket=None, params=None)

class galaxy.model.Tag(id=None, type=None, parent_id=None, name=None)

Bases: object

__init__(id=None, type=None, parent_id=None, name=None)

class galaxy.model.ItemTagAssociation(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

Bases: object, galaxy.util.dictifiable.Dictifiable

dict_collection_visible_keys = ['id', 'user_tname', 'user_value']

dict_element_visible_keys = ['id', 'user_tname', 'user_value']

__init__(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

copy(cls=None)

class galaxy.model.HistoryTagAssociation(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

class galaxy.model.DatasetTagAssociation(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

class galaxy.model.HistoryDatasetAssociationTagAssociation(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

class galaxy.model.LibraryDatasetDatasetAssociationTagAssociation(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

class galaxy.model.PageTagAssociation(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

class galaxy.model.WorkflowStepTagAssociation(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

class galaxy.model.StoredWorkflowTagAssociation(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

class galaxy.model.VisualizationTagAssociation(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

class galaxy.model.HistoryDatasetCollectionTagAssociation(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

class galaxy.model.LibraryDatasetCollectionTagAssociation(id=None, user=None, item_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

class galaxy.model.ToolTagAssociation(id=None, user=None, tool_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

__init__(id=None, user=None, tool_id=None, tag_id=None, user_tname=None, value=None)

class galaxy.model.WorkRequestTagAssociation(id=None, user=None, workflow_request_id=None, tag_id=None, user_tname=None, value=None)

Bases: galaxy.model.ItemTagAssociation

__init__(id=None, user=None, workflow_request_id=None, tag_id=None, user_tname=None, value=None)

class galaxy.model.HistoryAnnotationAssociation

Bases: object

class galaxy.model.HistoryDatasetAssociationAnnotationAssociation

Bases: object

class galaxy.model.StoredWorkflowAnnotationAssociation

Bases: object

class galaxy.model.WorkflowStepAnnotationAssociation

Bases: object

class galaxy.model.PageAnnotationAssociation

Bases: object

class galaxy.model.VisualizationAnnotationAssociation

Bases: object

class galaxy.model.HistoryDatasetCollectionAnnotationAssociation

Bases: object

class galaxy.model.LibraryDatasetCollectionAnnotationAssociation

Bases: object

class galaxy.model.ItemRatingAssociation(id=None, user=None, item=None, rating=0)

Bases: object

__init__(id=None, user=None, item=None, rating=0)

set_item(item)

Set association’s item.

class galaxy.model.HistoryRatingAssociation(id=None, user=None, item=None, rating=0)

Bases: galaxy.model.ItemRatingAssociation

set_item(history)

class galaxy.model.HistoryDatasetAssociationRatingAssociation(id=None, user=None, item=None, rating=0)

Bases: galaxy.model.ItemRatingAssociation

set_item(history_dataset_association)

class galaxy.model.StoredWorkflowRatingAssociation(id=None, user=None, item=None, rating=0)

Bases: galaxy.model.ItemRatingAssociation

set_item(stored_workflow)

class galaxy.model.PageRatingAssociation(id=None, user=None, item=None, rating=0)

Bases: galaxy.model.ItemRatingAssociation

set_item(page)

class galaxy.model.VisualizationRatingAssociation(id=None, user=None, item=None, rating=0)

Bases: galaxy.model.ItemRatingAssociation

set_item(visualization)

class galaxy.model.HistoryDatasetCollectionRatingAssociation(id=None, user=None, item=None, rating=0)

Bases: galaxy.model.ItemRatingAssociation

set_item(dataset_collection)

class galaxy.model.LibraryDatasetCollectionRatingAssociation(id=None, user=None, item=None, rating=0)

Bases: galaxy.model.ItemRatingAssociation

set_item(dataset_collection)

class galaxy.model.DataManagerHistoryAssociation(id=None, history=None, user=None)

Bases: object

__init__(id=None, history=None, user=None)

class galaxy.model.DataManagerJobAssociation(id=None, job=None, data_manager_id=None)

Bases: object

__init__(id=None, job=None, data_manager_id=None)

class galaxy.model.UserPreference(name=None, value=None)

Bases: object

__init__(name=None, value=None)

class galaxy.model.UserAction(id=None, create_time=None, user_id=None, session_id=None, action=None, params=None, context=None)

Bases: object

__init__(id=None, create_time=None, user_id=None, session_id=None, action=None, params=None, context=None)

class galaxy.model.APIKeys(id=None, user_id=None, key=None)

Bases: object

__init__(id=None, user_id=None, key=None)

galaxy.model.copy_list(lst, *args, **kwds)

Subpackages

• galaxy.model.migrate package
  • Submodules
  • galaxy.model.migrate.check module
• galaxy.model.orm package
  • Submodules
  • galaxy.model.orm.engine_factory module
  • galaxy.model.orm.logging_connection_proxy module
  • galaxy.model.orm.now module
  • galaxy.model.orm.scripts module
• galaxy.model.tool_shed_install package
  • Subpackages
    • galaxy.model.tool_shed_install.migrate package
      • Submodules
      • galaxy.model.tool_shed_install.migrate.check module
  • Submodules
  • galaxy.model.tool_shed_install.mapping module

Submodules

galaxy.model.base module

Shared model and mapping code between Galaxy and Tool Shed, trying to generalize to generic database connections.

class galaxy.model.base.ModelMapping(model_modules, engine)

Bases: galaxy.util.bunch.Bunch

__init__(model_modules, engine)

Session

For backward compat., deprecated.

galaxy.model.base.versioned_objects(iter)

galaxy.model.base.versioned_session(session)

galaxy.model.custom_types module

class galaxy.model.custom_types.JSONType(*args, **kwargs)

Bases: sqlalchemy.sql.type_api.TypeDecorator

Represents an immutable structure as a json-encoded string.

If default is, for example, a dict, then a NULL value in the database will be exposed as an empty dict.

impl

alias of LargeBinary

process_bind_param(value, dialect)

process_result_value(value, dialect)

load_dialect_impl(dialect)

copy_value(value)

compare_values(x, y)

class galaxy.model.custom_types.MutationObj

Bases: sqlalchemy.ext.mutable.Mutable

Mutable JSONType for SQLAlchemy from original gist: https://gist.github.com/dbarnett/1730610

Using minor changes from this fork of the gist: https://gist.github.com/miracle2k/52a031cced285ba9b8cd

And other minor changes to make it work for us.

classmethod coerce(key, value)

class galaxy.model.custom_types.MutationDict

Bases: galaxy.model.custom_types.MutationObj, dict

classmethod coerce(key, value)

Convert plain dictionary to MutationDict

class galaxy.model.custom_types.MutationList

Bases: galaxy.model.custom_types.MutationObj, list

classmethod coerce(key, value)

Convert plain list to MutationList

append(value)

insert(idx, value)

extend(values)

pop(*args, **kw)

remove(value)

galaxy.model.custom_types.total_size(o, handlers={}, verbose=False)

Returns the approximate memory footprint an object and all of its contents.

Automatically finds the contents of the following builtin containers and their subclasses: tuple, list, deque, dict, set and frozenset. To search other containers, add handlers to iterate over their contents:

handlers = {SomeContainerClass: iter,

OtherContainerClass: OtherContainerClass.get_elements}

Recipe from: https://code.activestate.com/recipes/577504-compute-memory-footprint-of-an-object-and-its-cont/

class galaxy.model.custom_types.MetadataType(*args, **kwargs)

Bases: galaxy.model.custom_types.JSONType

Backward compatible metadata type. Can read pickles or JSON, but always writes in JSON.

process_bind_param(value, dialect)

process_result_value(value, dialect)

class galaxy.model.custom_types.UUIDType(*args, **kwargs)

Bases: sqlalchemy.sql.type_api.TypeDecorator

Platform-independent UUID type.

Based on http://docs.sqlalchemy.org/en/rel_0_8/core/types.html#backend-agnostic-guid-type Changed to remove sqlalchemy 0.8 specific code

CHAR(32), storing as stringified hex values.

impl

alias of CHAR

load_dialect_impl(dialect)

process_bind_param(value, dialect)

process_result_value(value, dialect)

class galaxy.model.custom_types.TrimmedString(*args, **kwargs)

Bases: sqlalchemy.sql.type_api.TypeDecorator

impl

alias of String

process_bind_param(value, dialect)

Automatically truncate string values

galaxy.model.item_attrs module

exception galaxy.model.item_attrs.RuntimeException

Bases: exceptions.Exception

class galaxy.model.item_attrs.UsesItemRatings

Mixin for getting and setting item ratings.

Class makes two assumptions: (1) item-rating association table is named <item_class>RatingAssocation (2) item-rating association table has a column with a foreign key referencing item table that contains the item’s id.

get_ave_item_rating_data(db_session, item, webapp_model=None)

Returns the average rating for an item.

rate_item(db_session, user, item, rating, webapp_model=None)

Rate an item. Return type is <item_class>RatingAssociation.

get_user_item_rating(db_session, user, item, webapp_model=None)

Returns user’s rating for an item. Return type is <item_class>RatingAssociation.

class galaxy.model.item_attrs.UsesAnnotations

Mixin for getting and setting item annotations.

get_item_annotation_str(db_session, user, item)

Returns a user’s annotation string for an item.

get_item_annotation_obj(db_session, user, item)

Returns a user’s annotation object for an item.

add_item_annotation(db_session, user, item, annotation)

Add or update an item’s annotation; a user can only have a single annotation for an item.

delete_item_annotation(db_session, user, item)

copy_item_annotation(db_session, source_user, source_item, target_user, target_item)

Copy an annotation from a user/item source to a user/item target.

galaxy.model.mapping module

Details of how the data model objects are mapped onto the relational database are encapsulated here.

galaxy.model.mapping.simple_mapping(model, **kwds)

galaxy.model.mapping.tag_mapping(tag_association_class, backref_name)

galaxy.model.mapping.annotation_mapping(annotation_class, **kwds)

galaxy.model.mapping.rating_mapping(rating_class, **kwds)

galaxy.model.mapping.db_next_hid(self)

Override __next_hid to generate from the database in a concurrency safe way. Loads the next history ID from the DB and returns it. It also saves the future next_id into the DB.

Return type:int Returns:the next history id

galaxy.model.mapping.init(file_path, url, engine_options=None, create_tables=False, map_install_models=False, database_query_profiling_proxy=False, object_store=None, trace_logger=None, use_pbkdf2=True, slow_query_log_threshold=0)

Connect mappings to the database

galaxy.model.mapping.now()

Return a new datetime representing UTC day and time.

galaxy.model.metadata module

Galaxy Metadata

class galaxy.model.metadata.Statement(target)

Bases: object

This class inserts its target into a list in the surrounding class. the data.Data class has a metaclass which executes these statements. This is how we shove the metadata element spec into the class.

__init__(target)

classmethod process(element)

class galaxy.model.metadata.MetadataCollection(parent)

Bases: object

MetadataCollection is not a collection at all, but rather a proxy to the real metadata which is stored as a Dictionary. This class handles processing the metadata elements when they are set and retrieved, returning default values in cases when metadata is not set.

__init__(parent)

get_parent()

set_parent(parent)

parent

spec

get(key, default=None)

items()

remove_key(name)

element_is_set(name)

get_metadata_parameter(name, **kwd)

make_dict_copy(to_copy)

Makes a deep copy of input iterable to_copy according to self.spec

from_JSON_dict(filename=None, path_rewriter=None, json_dict=None)

to_JSON_dict(filename=None)

class galaxy.model.metadata.MetadataSpecCollection(dict=None)

Bases: galaxy.util.odict.odict

A simple extension of dict which allows cleaner access to items and allows the values to be iterated over directly as if it were a list. append() is also implemented for simplicity and does not “append”.

__init__(dict=None)

append(item)

iter()

class galaxy.model.metadata.MetadataParameter(spec)

Bases: object

__init__(spec)

get_field(value=None, context=None, other_values=None, **kwd)

to_string(value)

to_safe_string(value)

make_copy(value, target_context=None, source_context=None)

classmethod marshal(value)

This method should/can be overridden to convert the incoming value to whatever type it is supposed to be.

validate(value)

Throw an exception if the value is invalid.

unwrap(form_value)

Turns a value into its storable form.

wrap(value, session)

Turns a value into its usable form.

from_external_value(value, parent)

Turns a value read from an external dict into its value to be pushed directly into the metadata dict.

to_external_value(value)

Turns a value read from a metadata into its value to be pushed directly into the external dict.

class galaxy.model.metadata.MetadataElementSpec(datatype, name=None, desc=None, param=<class 'galaxy.model.metadata.MetadataParameter'>, default=None, no_value=None, visible=True, set_in_upload=False, **kwargs)

Bases: object

Defines a metadata element and adds it to the metadata_spec (which is a MetadataSpecCollection) of datatype.

__init__(datatype, name=None, desc=None, param=<class 'galaxy.model.metadata.MetadataParameter'>, default=None, no_value=None, visible=True, set_in_upload=False, **kwargs)

get(name, default=None)

wrap(value, session)

Turns a stored value into its usable form.

unwrap(value)

Turns an incoming value into its storable form.

galaxy.model.metadata.MetadataElement = <galaxy.model.metadata.Statement object>

MetadataParameter sub-classes.

class galaxy.model.metadata.SelectParameter(spec)

Bases: galaxy.model.metadata.MetadataParameter

__init__(spec)

to_string(value)

get_field(value=None, context=None, other_values=None, values=None, **kwd)

wrap(value, session)

classmethod marshal(value)

class galaxy.model.metadata.DBKeyParameter(spec)

Bases: galaxy.model.metadata.SelectParameter

get_field(value=None, context=None, other_values=None, values=None, **kwd)

class galaxy.model.metadata.RangeParameter(spec)

Bases: galaxy.model.metadata.SelectParameter

__init__(spec)

get_field(value=None, context=None, other_values=None, values=None, **kwd)

classmethod marshal(value)

class galaxy.model.metadata.ColumnParameter(spec)

Bases: galaxy.model.metadata.RangeParameter

get_field(value=None, context=None, other_values=None, values=None, **kwd)

class galaxy.model.metadata.ColumnTypesParameter(spec)

Bases: galaxy.model.metadata.MetadataParameter

to_string(value)

class galaxy.model.metadata.ListParameter(spec)

Bases: galaxy.model.metadata.MetadataParameter

to_string(value)

class galaxy.model.metadata.DictParameter(spec)

Bases: galaxy.model.metadata.MetadataParameter

to_string(value)

to_safe_string(value)

class galaxy.model.metadata.PythonObjectParameter(spec)

Bases: galaxy.model.metadata.MetadataParameter

to_string(value)

get_field(value=None, context=None, other_values=None, **kwd)

classmethod marshal(value)

class galaxy.model.metadata.FileParameter(spec)

Bases: galaxy.model.metadata.MetadataParameter

to_string(value)

to_safe_string(value)

get_field(value=None, context=None, other_values=None, **kwd)

wrap(value, session)

make_copy(value, target_context, source_context)

classmethod marshal(value)

from_external_value(value, parent, path_rewriter=None)

Turns a value read from a external dict into its value to be pushed directly into the metadata dict.

to_external_value(value)

Turns a value read from a metadata into its value to be pushed directly into the external dict.

new_file(dataset=None, **kwds)

class galaxy.model.metadata.MetadataTempFile(**kwds)

Bases: object

tmp_dir = 'database/tmp'

__init__(**kwds)

file_name

to_JSON()

classmethod from_JSON(json_dict)

classmethod is_JSONified_value(value)

classmethod cleanup_from_JSON_dict_filename(filename)

class galaxy.model.metadata.JobExternalOutputMetadataWrapper(job)

Bases: object

Class with methods allowing set_meta() to be called externally to the Galaxy head. This class allows access to external metadata filenames for all outputs associated with a job. We will use JSON as the medium of exchange of information, except for the DatasetInstance object which will use pickle (in the future this could be JSONified as well)

__init__(job)

get_output_filenames_by_dataset(dataset, sa_session)

get_dataset_metadata_key(dataset)

invalidate_external_metadata(datasets, sa_session)

setup_external_metadata(datasets, sa_session, exec_dir=None, tmp_dir=None, dataset_files_path=None, output_fnames=None, config_root=None, config_file=None, datatypes_config=None, job_metadata=None, compute_tmp_dir=None, include_command=True, max_metadata_value_size=0, kwds=None)

external_metadata_set_successfully(dataset, sa_session)

cleanup_external_metadata(sa_session)

set_job_runner_external_pid(pid, sa_session)

galaxy.model.search module

The GQL (Galaxy Query Language) search engine parsers a simple ‘SQL-Like’ query syntax to obtain items from the Galaxy installations. Rather then allow/force the user to do queries on the Galaxy schema, it uses a small set of ‘Views’ which are simple table representations of complex galaxy ideas. So while a history and its tags may exist in seperate tables in the real schema, in GQL they exist in the same view

Example Queries:

select name, id, file_size from hda

select name from hda

select name, model_class from ldda

select * from history

select * from workflow

select id, name from history where name=’Unnamed history’

select * from history where name=’Unnamed history’

class galaxy.model.search.ViewField(name, sqlalchemy_field=None, handler=None, post_filter=None, id_decode=False)

Bases: object

A ViewField defines a field in a view that filter operations can be applied to These filter operations are either handled with standard sqlalchemy filter calls, or passed to specialized handlers (such as when a table join would be needed to do the filtering)

Parameters:

sqlalchemy_field - Simple filtering using existing table columns, the argument is an sqlalchemy column

that the right hand value will be compared against

handler - Requires more specialized code to do filtering, usually requires a table join in order to

process the conditional

post_filter - Unable to do simple sqlalchemy based table filtering, filter is applied to loaded object

Thus methods avalible to the object can be used for filtering. example: a library folder must climb its chain of parents to find out which library it belongs to

__init__(name, sqlalchemy_field=None, handler=None, post_filter=None, id_decode=False)

class galaxy.model.search.ViewQueryBaseClass

Bases: object

FIELDS = {}

VIEW_NAME = 'undefined'

__init__()

decode_query_ids(trans, conditional)

filter(left, operator, right)

search(trans)

get_results(force_query=False)

galaxy.model.search.library_extended_metadata_filter(view, left, operator, right)

galaxy.model.search.ldda_parent_library_filter(item, left, operator, right)

class galaxy.model.search.LibraryDatasetDatasetView

Bases: galaxy.model.search.ViewQueryBaseClass

VIEW_NAME = 'library_dataset_dataset'

FIELDS = {'parent_library_id': <galaxy.model.search.ViewField object>, 'extended_metadata': <galaxy.model.search.ViewField object>, 'name': <galaxy.model.search.ViewField object>, 'data_type': <galaxy.model.search.ViewField object>, 'deleted': <galaxy.model.search.ViewField object>, 'id': <galaxy.model.search.ViewField object>}

search(trans)

class galaxy.model.search.LibraryView

Bases: galaxy.model.search.ViewQueryBaseClass

VIEW_NAME = 'library'

FIELDS = {'deleted': <galaxy.model.search.ViewField object>, 'name': <galaxy.model.search.ViewField object>, 'id': <galaxy.model.search.ViewField object>}

search(trans)

galaxy.model.search.library_folder_parent_library_id_filter(item, left, operator, right)

galaxy.model.search.library_path_filter(item, left, operator, right)

class galaxy.model.search.LibraryFolderView

Bases: galaxy.model.search.ViewQueryBaseClass

VIEW_NAME = 'library_folder'

FIELDS = {'parent_id': <galaxy.model.search.ViewField object>, 'library_path': <galaxy.model.search.ViewField object>, 'name': <galaxy.model.search.ViewField object>, 'parent_library_id': <galaxy.model.search.ViewField object>, 'id': <galaxy.model.search.ViewField object>}

search(trans)

galaxy.model.search.library_dataset_name_filter(item, left, operator, right)

class galaxy.model.search.LibraryDatasetView

Bases: galaxy.model.search.ViewQueryBaseClass

VIEW_NAME = 'library_dataset'

FIELDS = {'folder_id': <galaxy.model.search.ViewField object>, 'name': <galaxy.model.search.ViewField object>, 'id': <galaxy.model.search.ViewField object>}

search(trans)

class galaxy.model.search.ToolView

Bases: galaxy.model.search.ViewQueryBaseClass

VIEW_NAME = 'tool'

FIELDS = {'tool_id': <galaxy.model.search.ViewField object>, 'id': <galaxy.model.search.ViewField object>}

search(trans)

galaxy.model.search.history_dataset_handle_tag(view, left, operator, right)

galaxy.model.search.history_dataset_extended_metadata_filter(view, left, operator, right)

class galaxy.model.search.HistoryDatasetView

Bases: galaxy.model.search.ViewQueryBaseClass

DOMAIN = 'history_dataset'

FIELDS = {'tag': <galaxy.model.search.ViewField object>, 'extended_metadata': <galaxy.model.search.ViewField object>, 'name': <galaxy.model.search.ViewField object>, 'deleted': <galaxy.model.search.ViewField object>, 'history_id': <galaxy.model.search.ViewField object>, 'copied_from_hda_id': <galaxy.model.search.ViewField object>, 'id': <galaxy.model.search.ViewField object>, 'copied_from_ldda_id': <galaxy.model.search.ViewField object>}

search(trans)

galaxy.model.search.history_handle_tag(view, left, operator, right)

galaxy.model.search.history_handle_annotation(view, left, operator, right)

class galaxy.model.search.HistoryView

Bases: galaxy.model.search.ViewQueryBaseClass

DOMAIN = 'history'

FIELDS = {'deleted': <galaxy.model.search.ViewField object>, 'annotation': <galaxy.model.search.ViewField object>, 'tag': <galaxy.model.search.ViewField object>, 'name': <galaxy.model.search.ViewField object>, 'id': <galaxy.model.search.ViewField object>}

search(trans)

galaxy.model.search.workflow_tag_handler(view, left, operator, right)

class galaxy.model.search.WorkflowView

Bases: galaxy.model.search.ViewQueryBaseClass

DOMAIN = 'workflow'

FIELDS = {'deleted': <galaxy.model.search.ViewField object>, 'tag': <galaxy.model.search.ViewField object>, 'name': <galaxy.model.search.ViewField object>, 'id': <galaxy.model.search.ViewField object>}

search(trans)

galaxy.model.search.job_param_filter(view, left, operator, right)

galaxy.model.search.job_input_hda_filter(view, left, operator, right)

galaxy.model.search.job_input_ldda_filter(view, left, operator, right)

galaxy.model.search.job_output_hda_filter(view, left, operator, right)

class galaxy.model.search.JobView

Bases: galaxy.model.search.ViewQueryBaseClass

DOMAIN = 'job'

FIELDS = {'output_hda': <galaxy.model.search.ViewField object>, 'input_ldda': <galaxy.model.search.ViewField object>, 'param': <galaxy.model.search.ViewField object>, 'state': <galaxy.model.search.ViewField object>, 'input_hda': <galaxy.model.search.ViewField object>, 'tool_name': <galaxy.model.search.ViewField object>}

search(trans)

class galaxy.model.search.PageView

Bases: galaxy.model.search.ViewQueryBaseClass

DOMAIN = 'page'

FIELDS = {'deleted': <galaxy.model.search.ViewField object>, 'title': <galaxy.model.search.ViewField object>, 'id': <galaxy.model.search.ViewField object>, 'slug': <galaxy.model.search.ViewField object>}

search(trans)

class galaxy.model.search.PageRevisionView

Bases: galaxy.model.search.ViewQueryBaseClass

DOMAIN = 'page_revision'

FIELDS = {'page_id': <galaxy.model.search.ViewField object>, 'id': <galaxy.model.search.ViewField object>, 'title': <galaxy.model.search.ViewField object>}

search(trans)

class galaxy.model.search.GalaxyQuery(field_list, table_name, conditional)

Bases: object

This class represents a data structure of a compiled GQL query

__init__(field_list, table_name, conditional)

class galaxy.model.search.GalaxyQueryComparison(left, operator, right)

Bases: object

This class represents the data structure of the comparison arguments of a compiled GQL query (ie where name=’Untitled History’)

__init__(left, operator, right)

class galaxy.model.search.GalaxyQueryAnd(left, right)

Bases: object

This class represents the data structure of the comparison arguments of a compiled GQL query (ie where name=’Untitled History’)

__init__(left, right)

exception galaxy.model.search.GalaxyParseError

Bases: exceptions.Exception

class galaxy.model.search.SearchQuery(view, query)

Bases: object

__init__(view, query)

decode_query_ids(trans)

process(trans)

item_to_api_value(item)

class galaxy.model.search.GalaxySearchEngine

Bases: object

Primary class for searching. Parses GQL (Galaxy Query Language) queries and returns a ‘SearchQuery’ class

__init__()

query(query_text)

galaxy.model.util module

Utility helpers related to the model

galaxy.model.util.pgcalc(sa_session, id, dryrun=False)

Utility method for quickly recalculating user disk usage in postgres.

TODO: Check against the recently updated versions of sqlalchemy if this ‘special’ postgresql version is even necessary.