Warning
This document is for an old release of Galaxy. You can alternatively view this page in the latest release if it exists or view the top of the latest release's documentation.
Source code for galaxy.tools.wrappers
import logging
import os
import shlex
import tempfile
from functools import total_ordering
from typing import (
Any,
cast,
Dict,
Iterable,
Iterator,
KeysView,
List,
Optional,
Sequence,
Tuple,
TYPE_CHECKING,
Union,
)
from galaxy import exceptions
from galaxy.model import (
DatasetCollection,
DatasetCollectionElement,
DatasetCollectionInstance,
DatasetInstance,
HasTags,
HistoryDatasetCollectionAssociation,
)
from galaxy.model.none_like import NoneDataset
from galaxy.security.object_wrapper import wrap_with_safe_string
from galaxy.tools.parameters.wrapped_json import (
data_collection_input_to_staging_path_and_source_path,
data_input_to_staging_path_and_source_path,
)
from galaxy.util import filesystem_safe_string
if TYPE_CHECKING:
from galaxy.datatypes.registry import Registry
from galaxy.job_execution.compute_environment import ComputeEnvironment
from galaxy.model.metadata import MetadataCollection
from galaxy.tools import Tool
from galaxy.tools.parameters.basic import (
SelectToolParameter,
ToolParameter,
)
log = logging.getLogger(__name__)
# Fields in tool config files corresponding to paths (e.g .loc or .len)
# must have one of the following field names, and all such fields are
# assumed to be paths. This is to allow remote ComputeEnvironments (such
# as one used by Pulsar) to determine what values to rewrite or transfer.
PATH_ATTRIBUTES = ["len_path", "path"]
[docs]class ToolParameterValueWrapper:
"""
Base class for object that Wraps a Tool Parameter and Value.
"""
value: Union[str, List[str]]
input: "ToolParameter"
def __bool__(self) -> bool:
return bool(self.value)
__nonzero__ = __bool__
[docs] def get_display_text(self, quote: bool = True) -> str:
"""
Returns a string containing the value that would be displayed to the user in the tool interface.
When quote is True (default), the string is escaped for e.g. command-line usage.
"""
rval = self.input.value_to_display_text(self.value) or ""
if quote:
return shlex.quote(rval)
return rval
[docs]class RawObjectWrapper(ToolParameterValueWrapper):
"""
Wraps an object so that __str__ returns module_name:class_name.
"""
def __bool__(self) -> bool:
return bool(
self.obj
) # FIXME: would it be safe/backwards compatible to rename .obj to .value, so that we can just inherit this method?
__nonzero__ = __bool__
def __str__(self) -> str:
try:
return f"{self.obj.__module__}:{self.obj.__class__.__name__}"
except Exception:
# Most likely None, which lacks __module__.
return str(self.obj)
def __getattr__(self, key: Any) -> Any:
return getattr(self.obj, key)
[docs]@total_ordering
class InputValueWrapper(ToolParameterValueWrapper):
"""
Wraps an input so that __str__ gives the "param_dict" representation.
"""
[docs] def __init__(
self,
input: "ToolParameter",
value: str,
other_values: Optional[Dict[str, str]] = None,
) -> None:
self.input = input
self.value = value
self._other_values: Dict[str, str] = other_values or {}
def _get_cast_value(self, other: Any) -> Union[str, int, float, bool, None]:
if self.input.type == "boolean" and isinstance(other, str):
return str(self)
# For backward compatibility, allow `$wrapper != ""` for optional non-text param
if self.input.optional and self.value is None:
if isinstance(other, str):
return str(self)
else:
return None
cast_table = {
"text": str,
"integer": int,
"float": float,
"boolean": bool,
}
return cast(Union[str, int, float, bool], cast_table.get(self.input.type, str)(self))
def __eq__(self, other: Any) -> bool:
return bool(self._get_cast_value(other) == other)
def __ne__(self, other: Any) -> bool:
return not self == other
def __str__(self) -> str:
to_param_dict_string = self.input.to_param_dict_string(self.value, self._other_values)
if isinstance(to_param_dict_string, list):
return ",".join(to_param_dict_string)
else:
return to_param_dict_string
def __iter__(self) -> Iterable[str]:
to_param_dict_string = self.input.to_param_dict_string(self.value, self._other_values)
if not isinstance(to_param_dict_string, list):
return iter([to_param_dict_string])
else:
return iter(to_param_dict_string)
def __getattr__(self, key: Any) -> Any:
return getattr(self.value, key)
def __gt__(self, other: Any) -> bool:
return bool(self._get_cast_value(other) > other)
def __int__(self) -> int:
return int(float(self))
def __float__(self) -> float:
return float(str(self))
[docs]class SelectToolParameterWrapper(ToolParameterValueWrapper):
"""
Wraps a SelectTooParameter so that __str__ returns the selected value, but all other
attributes are accessible.
"""
input: "SelectToolParameter"
[docs] class SelectToolParameterFieldWrapper:
"""
Provide access to any field by name or index for this particular value.
Only applicable for dynamic_options selects, which have more than simple 'options' defined (name, value, selected).
"""
[docs] def __init__(
self,
input: "SelectToolParameter",
value: Union[str, List[str]],
other_values: Optional[Dict[str, str]],
compute_environment: Optional["ComputeEnvironment"],
) -> None:
self._input = input
self._value = value
self._other_values = other_values
self._fields: Dict[str, str] = {}
self._compute_environment = compute_environment
def __getattr__(self, name: str) -> Any:
if name not in self._fields:
self._fields[name] = self._input.options.get_field_by_name_for_value(
name, self._value, None, self._other_values
)
values = map(str, self._fields[name])
if name in PATH_ATTRIBUTES and self._compute_environment:
# If we infer this is a path, rewrite it if needed.
new_values = []
for value in values:
rewrite_value = self._compute_environment.unstructured_path_rewrite(value)
if rewrite_value:
new_values.append(rewrite_value)
else:
new_values.append(value)
return self._input.separator.join(new_values)
return self._input.separator.join(values)
[docs] def __init__(
self,
input: "SelectToolParameter",
value: Union[str, List[str]],
other_values: Optional[Dict[str, str]] = None,
compute_environment: Optional["ComputeEnvironment"] = None,
):
self.input = input
self.value = value
self.input.value_label = input.value_to_display_text(value)
self._other_values = other_values or {}
self.compute_environment = compute_environment
self.fields = self.SelectToolParameterFieldWrapper(input, value, other_values, self.compute_environment)
def __eq__(self, other: Any) -> bool:
if isinstance(other, str):
if other == "" and self.value in (None, []):
# Allow $wrapper == '' for select (self.value is None) and multiple select (self.value is []) params
return True
return str(self) == other
else:
return super().__eq__(other)
def __ne__(self, other: Any) -> bool:
return not self == other
def __str__(self) -> str:
# Assuming value is never a path - otherwise would need to pass
# along following argument value_map=self._path_rewriter.
return str(self.input.to_param_dict_string(self.value, other_values=self._other_values))
def __add__(self, x: Any) -> str:
return f"{self}{x}"
def __getattr__(self, key: Any) -> Any:
return getattr(self.input, key)
def __iter__(self) -> Iterable[str]:
if not self.input.multiple:
raise Exception("Tried to iterate over a non-multiple parameter.")
return self.value.__iter__()
[docs]class DatasetFilenameWrapper(ToolParameterValueWrapper):
"""
Wraps a dataset so that __str__ returns the filename, but all other
attributes are accessible.
"""
false_path: Optional[str]
[docs] class MetadataWrapper:
"""
Wraps a Metadata Collection to return MetadataParameters wrapped
according to the metadata spec. Methods implemented to match behavior
of a Metadata Collection.
"""
[docs] def __init__(
self,
dataset: DatasetInstance,
compute_environment: Optional["ComputeEnvironment"] = None,
) -> None:
self.dataset = dataset
self.metadata: "MetadataCollection" = dataset.metadata
self.compute_environment = compute_environment
def __getattr__(self, name: str) -> Any:
rval = self.metadata.get(name, None)
if name in self.metadata.spec:
if rval is None:
rval = self.metadata.spec[name].no_value
metadata_param = self.metadata.spec[name].param
from galaxy.model.metadata import FileParameter
rval = metadata_param.to_safe_string(rval)
if isinstance(metadata_param, FileParameter) and self.compute_environment:
rewrite = self.compute_environment.input_metadata_rewrite(self.dataset, rval)
if rewrite is not None:
rval = rewrite
# Store this value, so we don't need to recalculate if needed
# again
setattr(self, name, rval)
else:
# escape string value of non-defined metadata value
rval = wrap_with_safe_string(rval)
return rval
def __bool__(self) -> bool:
return bool(self.metadata.__nonzero__())
__nonzero__ = __bool__
def __iter__(self) -> Iterator[Any]:
return self.metadata.__iter__()
[docs] def get(self, key: str, default: Any = None) -> Any:
try:
return getattr(self, key)
except Exception:
return default
[docs] def items(self) -> Iterator[Tuple[str, Any]]:
return iter((k, self.get(k)) for k, v in self.metadata.items())
[docs] def __init__(
self,
dataset: Optional[DatasetInstance],
datatypes_registry: Optional["Registry"] = None,
tool: Optional["Tool"] = None,
name: Optional[str] = None,
compute_environment: Optional["ComputeEnvironment"] = None,
identifier: Optional[str] = None,
io_type: str = "input",
formats: Optional[List[str]] = None,
) -> None:
if not dataset:
try:
# TODO: allow this to work when working with grouping
ext = tool.inputs[name].extensions[0] # type: ignore[union-attr]
except Exception:
ext = "data"
self.dataset = cast(
DatasetInstance,
wrap_with_safe_string(
NoneDataset(datatypes_registry=datatypes_registry, ext=ext),
no_wrap_classes=ToolParameterValueWrapper,
),
)
else:
# Tool wrappers should not normally be accessing .dataset directly,
# so we will wrap it and keep the original around for file paths
# Should we name this .value to maintain consistency with most other ToolParameterValueWrapper?
if formats:
direct_match, target_ext, converted_dataset = dataset.find_conversion_destination(formats)
if not direct_match and target_ext and converted_dataset:
dataset = converted_dataset
self.unsanitized: DatasetInstance = dataset
self.dataset = wrap_with_safe_string(dataset, no_wrap_classes=ToolParameterValueWrapper)
assert dataset
self.metadata = self.MetadataWrapper(dataset, compute_environment)
if isinstance(dataset, HasTags):
self.groups = {tag.user_value.lower() for tag in dataset.tags if tag.user_tname == "group"}
else:
# May be a 'FakeDatasetAssociation'
self.groups = set()
self.compute_environment = compute_environment
# TODO: lazy initialize this...
self.__io_type = io_type
if self.__io_type == "input":
path_rewrite = compute_environment and dataset and compute_environment.input_path_rewrite(dataset)
if path_rewrite:
self.false_path = path_rewrite
else:
self.false_path = None
else:
path_rewrite = compute_environment and compute_environment.output_path_rewrite(dataset)
if path_rewrite:
self.false_path = path_rewrite
else:
self.false_path = None
self.datatypes_registry = datatypes_registry
self._element_identifier = identifier
@property
def element_identifier(self) -> str:
identifier = self._element_identifier
if identifier is None:
identifier = self.name
return identifier
@property
def file_ext(self) -> str:
return str(
getattr(
self.unsanitized.datatype,
"file_ext_export_alias",
self.dataset.extension,
)
)
@property
def name_and_ext(self) -> str:
return f"{self.element_identifier}.{self.file_ext}"
[docs] def get_staging_path(self, invalid_chars: Sequence[str] = ("/",)) -> str:
"""
Strip leading dots, unicode null chars, replace `/` with `_`, truncate at 255 characters.
Not safe for commandline use, would need additional sanitization.
"""
max_len = 254 - len(self.file_ext)
safe_element_identifier = filesystem_safe_string(
self.element_identifier, max_len=max_len, invalid_chars=invalid_chars
)
return f"{safe_element_identifier}.{self.file_ext}"
@property
def all_metadata_files(self) -> List[Tuple[str, str]]:
return self.unsanitized.get_metadata_file_paths_and_extensions() if self else []
[docs] def serialize(self, invalid_chars: Sequence[str] = ("/",)) -> Dict[str, Any]:
return data_input_to_staging_path_and_source_path(self, invalid_chars=invalid_chars) if self else {}
@property
def is_collection(self) -> bool:
return False
[docs] def is_of_type(self, *exts: str) -> bool:
datatypes = []
if not self.datatypes_registry:
raise Exception("datatypes_registry is required to use 'is_of_type'.")
for e in exts:
datatype = self.datatypes_registry.get_datatype_by_extension(e)
if datatype is not None:
datatypes.append(datatype)
else:
log.warning(
f"Datatype class not found for extension '{e}', which is used as parameter of 'is_of_type()' method"
)
return self.dataset.datatype.matches_any(datatypes)
def __str__(self) -> str:
if self.false_path is not None:
return self.false_path
else:
return str(self.unsanitized.file_name)
def __getattr__(self, key: Any) -> Any:
if self.false_path is not None and key == "file_name":
# Path to dataset was rewritten for this job.
return self.false_path
elif key == "extra_files_path":
if self.__io_type == "input":
path_rewrite = self.compute_environment and self.compute_environment.input_extra_files_rewrite(
self.unsanitized
)
else:
path_rewrite = self.compute_environment and self.compute_environment.output_extra_files_rewrite(
self.unsanitized
)
if path_rewrite:
return path_rewrite
else:
try:
# Assume it is an output and that this wrapper
# will be set with correct "files_path" for this
# job.
return self.files_path
except AttributeError:
# Otherwise, we have an input - delegate to model and
# object store to find the static location of this
# directory.
try:
return self.unsanitized.extra_files_path
except exceptions.ObjectNotFound:
# NestedObjectstore raises an error here
# instead of just returning a non-existent
# path like DiskObjectStore.
raise
elif key == "serialize":
return self.serialize
else:
return getattr(self.dataset, key)
def __bool__(self) -> bool:
return bool(self.dataset)
__nonzero__ = __bool__
[docs]class HasDatasets:
job_working_directory: Optional[str]
def __iter__(self) -> Iterator[Any]:
pass
def _dataset_wrapper(self, dataset: DatasetInstance, **kwargs: Any) -> DatasetFilenameWrapper:
return DatasetFilenameWrapper(dataset, **kwargs)
[docs] def paths_as_file(self, sep: str = "\n") -> str:
contents = sep.join(map(str, self))
with tempfile.NamedTemporaryFile(
mode="w+", prefix="gx_file_list", dir=self.job_working_directory, delete=False
) as fh:
fh.write(contents)
filepath = fh.name
return filepath
[docs]class DatasetListWrapper(List[DatasetFilenameWrapper], ToolParameterValueWrapper, HasDatasets):
""" """
[docs] def __init__(
self,
job_working_directory: Optional[str],
datasets: Union[
Sequence[
Union[
None,
DatasetInstance,
DatasetCollectionInstance,
DatasetCollectionElement,
]
],
DatasetInstance,
],
**kwargs: Any,
) -> None:
self._dataset_elements_cache: Dict[str, List[DatasetFilenameWrapper]] = {}
if not isinstance(datasets, Sequence):
datasets = [datasets]
def to_wrapper(
dataset: Union[
None,
DatasetInstance,
DatasetCollectionInstance,
DatasetCollectionElement,
]
) -> DatasetFilenameWrapper:
if isinstance(dataset, DatasetCollectionElement):
dataset2 = dataset.dataset_instance
kwargs["identifier"] = dataset.element_identifier
else:
dataset2 = dataset
return self._dataset_wrapper(dataset2, **kwargs)
list.__init__(self, map(to_wrapper, datasets))
self.job_working_directory = job_working_directory
[docs] @staticmethod
def to_dataset_instances(
dataset_instance_sources: Any,
) -> List[Union[None, DatasetInstance]]:
dataset_instances: List[Optional[DatasetInstance]] = []
if not isinstance(dataset_instance_sources, list):
dataset_instance_sources = [dataset_instance_sources]
for dataset_instance_source in dataset_instance_sources:
if dataset_instance_source is None:
dataset_instances.append(dataset_instance_source)
elif getattr(dataset_instance_source, "history_content_type", None) == "dataset":
dataset_instances.append(dataset_instance_source)
elif hasattr(dataset_instance_source, "child_collection"):
dataset_instances.extend(dataset_instance_source.child_collection.dataset_elements)
else:
dataset_instances.extend(dataset_instance_source.collection.dataset_elements)
return dataset_instances
[docs] def get_datasets_for_group(self, group: str) -> List[DatasetFilenameWrapper]:
group = str(group).lower()
if not self._dataset_elements_cache.get(group):
wrappers = []
for element in self:
if any(t for t in element.tags if t.user_tname.lower() == "group" and t.value.lower() == group):
wrappers.append(element)
self._dataset_elements_cache[group] = wrappers
return self._dataset_elements_cache[group]
[docs] def serialize(self, invalid_chars: Sequence[str] = ("/",)) -> List[Dict[str, Any]]:
return [v.serialize(invalid_chars) for v in self]
def __str__(self) -> str:
return ",".join(map(str, self))
def __bool__(self) -> bool:
# Fail `#if $param` checks in cheetah if optional input is not provided
return any(self)
__nonzero__ = __bool__
[docs]class DatasetCollectionWrapper(ToolParameterValueWrapper, HasDatasets):
name: Optional[str]
collection: DatasetCollection
[docs] def __init__(
self,
job_working_directory: Optional[str],
has_collection: Union[None, DatasetCollectionElement, HistoryDatasetCollectionAssociation],
datatypes_registry: "Registry",
**kwargs: Any,
) -> None:
super().__init__()
self.job_working_directory = job_working_directory
self._dataset_elements_cache: Dict[str, List[DatasetFilenameWrapper]] = {}
self._element_identifiers_extensions_paths_and_metadata_files: Optional[List[List[Any]]] = None
self.datatypes_registry = datatypes_registry
kwargs["datatypes_registry"] = datatypes_registry
self.kwargs = kwargs
if has_collection is None:
self.__input_supplied = False
return
else:
self.__input_supplied = True
if isinstance(has_collection, HistoryDatasetCollectionAssociation):
collection = has_collection.collection
self.name = has_collection.name
elif isinstance(has_collection, DatasetCollectionElement):
collection = has_collection.child_collection
self.name = has_collection.element_identifier
else:
collection = has_collection
self.name = None
self.collection = collection
elements = collection.elements
element_instances = {}
element_instance_list = []
for dataset_collection_element in elements:
element_object = dataset_collection_element.element_object
element_identifier = dataset_collection_element.element_identifier
if dataset_collection_element.is_collection:
element_wrapper: Union[DatasetCollectionWrapper, DatasetFilenameWrapper] = DatasetCollectionWrapper(
job_working_directory, dataset_collection_element, **kwargs
)
else:
element_wrapper = self._dataset_wrapper(element_object, identifier=element_identifier, **kwargs)
element_instances[element_identifier] = element_wrapper
element_instance_list.append(element_wrapper)
self.__element_instances = element_instances
self.__element_instance_list = element_instance_list
[docs] def get_datasets_for_group(self, group: str) -> List[DatasetFilenameWrapper]:
group = str(group).lower()
if not self._dataset_elements_cache.get(group):
wrappers = []
for element in self.collection.dataset_elements:
if any(
t
for t in element.dataset_instance.tags
if t.user_tname.lower() == "group" and t.value.lower() == group
):
wrappers.append(
self._dataset_wrapper(
element.element_object, identifier=element.element_identifier, **self.kwargs
)
)
self._dataset_elements_cache[group] = wrappers
return self._dataset_elements_cache[group]
[docs] def keys(self) -> Union[List[str], KeysView[Any]]:
if not self.__input_supplied:
return []
return self.__element_instances.keys()
@property
def is_collection(self) -> bool:
return True
@property
def element_identifier(self) -> Optional[str]:
return self.name
@property
def all_paths(self) -> List[str]:
return [path for _, _, path, _ in self.element_identifiers_extensions_paths_and_metadata_files]
@property
def all_metadata_files(self) -> List[List[str]]:
return [
metadata_files for _, _, _, metadata_files in self.element_identifiers_extensions_paths_and_metadata_files
]
@property
def element_identifiers_extensions_paths_and_metadata_files(
self,
) -> List[List[Any]]:
if self._element_identifiers_extensions_paths_and_metadata_files is None:
if self.collection:
result = self.collection.element_identifiers_extensions_paths_and_metadata_files
self._element_identifiers_extensions_paths_and_metadata_files = result
return result
else:
return []
return self._element_identifiers_extensions_paths_and_metadata_files
[docs] def get_all_staging_paths(
self,
invalid_chars: Sequence[str] = ("/",),
include_collection_name: bool = False,
) -> List[str]:
safe_element_identifiers = []
for element_identifiers, extension, *_ in self.element_identifiers_extensions_paths_and_metadata_files:
datatype = self.datatypes_registry.get_datatype_by_extension(extension)
if datatype:
extension = getattr(datatype, "file_ext_export_alias", extension)
current_element_identifiers = []
for element_identifier in element_identifiers:
max_len = 254 - len(extension)
if include_collection_name:
max_len = max_len - (len(self.name or "") + 1)
assert max_len >= 1, "Could not stage element, element identifier is too long"
current_element_identifier = filesystem_safe_string(
element_identifier, max_len=max_len, invalid_chars=invalid_chars
)
if include_collection_name and self.name:
current_element_identifier = f"{filesystem_safe_string(self.name, invalid_chars=invalid_chars)}{os.path.sep}{current_element_identifier}"
current_element_identifiers.append(current_element_identifier)
safe_element_identifiers.append(f"{os.path.sep.join(current_element_identifiers)}.{extension}")
return safe_element_identifiers
[docs] def serialize(
self,
invalid_chars: Sequence[str] = ("/",),
include_collection_name: bool = False,
) -> List[Dict[str, Any]]:
return data_collection_input_to_staging_path_and_source_path(
self,
invalid_chars=invalid_chars,
include_collection_name=include_collection_name,
)
@property
def is_input_supplied(self) -> bool:
return self.__input_supplied
def __getitem__(self, key: Union[str, int]) -> Union[None, "DatasetCollectionWrapper", DatasetFilenameWrapper]:
if not self.__input_supplied:
return None
if isinstance(key, int):
return self.__element_instance_list[key]
else:
return self.__element_instances[key]
def __getattr__(self, key: str) -> Union[None, "DatasetCollectionWrapper", DatasetFilenameWrapper]:
if not self.__input_supplied:
return None
try:
return self.__element_instances[key]
except KeyError:
raise AttributeError()
def __iter__(
self,
) -> Iterator[Union["DatasetCollectionWrapper", DatasetFilenameWrapper]]:
if not self.__input_supplied:
return [].__iter__()
return self.__element_instance_list.__iter__()
def __bool__(self) -> bool:
# Fail `#if $param` checks in cheetah is optional input
# not specified or if resulting collection is empty.
return self.__input_supplied and bool(self.__element_instance_list)
__nonzero__ = __bool__
[docs]class ElementIdentifierMapper:
"""Track mapping of dataset collection elements datasets to element identifiers."""
[docs] def __init__(self, input_datasets: Optional[Dict[str, Any]] = None) -> None:
if input_datasets is not None:
self.identifier_key_dict = {v: f"{k}|__identifier__" for k, v in input_datasets.items()}
else:
self.identifier_key_dict = {}
[docs] def identifier(self, dataset_value: str, input_values: Dict[str, str]) -> Optional[str]:
identifier_key = self.identifier_key_dict.get(dataset_value, None)
element_identifier = None
if identifier_key:
element_identifier = input_values.get(identifier_key, None)
return element_identifier