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Source code for galaxy.tools.wrappers
import logging
import tempfile
from collections import OrderedDict
from functools import total_ordering
from six import string_types, text_type
from six.moves import shlex_quote
from galaxy import exceptions
from galaxy.model.none_like import NoneDataset
from galaxy.util.object_wrapper import wrap_with_safe_string
log = logging.getLogger(__name__)
# Fields in .log files corresponding to paths, 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) determine what values to
# rewrite or transfer...
PATH_ATTRIBUTES = ["path"]
[docs]class ToolParameterValueWrapper(object):
"""
Base class for object that Wraps a Tool Parameter and Value.
"""
def __bool__(self):
return bool(self.value)
__nonzero__ = __bool__
[docs] def get_display_text(self, quote=True):
"""
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):
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):
try:
return "%s:%s" % (self.obj.__module__, self.obj.__class__.__name__)
except Exception:
# Most likely None, which lacks __module__.
return str(self.obj)
def __getattr__(self, key):
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, value, other_values={}):
self.input = input
self.value = value
self._other_values = other_values
def _get_cast_value(self, other):
if self.input.type == 'boolean' and isinstance(other, string_types):
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, string_types):
return str(self)
else:
return None
cast = {
'text': str,
'integer': int,
'float': float,
'boolean': bool,
}
return cast.get(self.input.type, str)(self)
def __eq__(self, other):
return self._get_cast_value(other) == other
def __ne__(self, other):
return not self == other
def __str__(self):
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):
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):
return getattr(self.value, key)
def __gt__(self, other):
return self._get_cast_value(other) > other
def __int__(self):
return int(float(self))
def __float__(self):
return float(str(self))
[docs]class SelectToolParameterWrapper(ToolParameterValueWrapper):
"""
Wraps a SelectTooParameter so that __str__ returns the selected value, but all other
attributes are accessible.
"""
[docs] class SelectToolParameterFieldWrapper(object):
"""
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, value, other_values, compute_environment):
self._input = input
self._value = value
self._other_values = other_values
self._fields = {}
self._compute_environment = compute_environment
def __getattr__(self, name):
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)
values = new_values
return self._input.separator.join(values)
[docs] def __init__(self, input, value, other_values={}, compute_environment=None):
self.input = input
self.value = value
self.input.value_label = input.value_to_display_text(value)
self._other_values = other_values
self.compute_environment = compute_environment
self.fields = self.SelectToolParameterFieldWrapper(input, value, other_values, self.compute_environment)
def __eq__(self, other):
if isinstance(other, string_types):
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(SelectToolParameterWrapper, self) == other
def __ne__(self, other):
return not self == other
def __str__(self):
# Assuming value is never a path - otherwise would need to pass
# along following argument value_map=self._path_rewriter.
return self.input.to_param_dict_string(self.value, other_values=self._other_values)
def __add__(self, x):
return '%s%s' % (self, x)
def __getattr__(self, key):
return getattr(self.input, key)
def __iter__(self):
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.
"""
[docs] class MetadataWrapper(object):
"""
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, compute_environment=None):
self.dataset = dataset
self.metadata = dataset.metadata
self.compute_environment = compute_environment
def __getattr__(self, name):
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):
return self.metadata.__nonzero__()
__nonzero__ = __bool__
def __iter__(self):
return self.metadata.__iter__()
[docs] def get(self, key, default=None):
try:
return getattr(self, key)
except Exception:
return default
[docs] def __init__(self, dataset, datatypes_registry=None, tool=None, name=None, compute_environment=None, identifier=None, io_type="input", formats=None):
if not dataset:
try:
# TODO: allow this to work when working with grouping
ext = tool.inputs[name].extensions[0]
except Exception:
ext = 'data'
self.dataset = 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:
target_ext, converted_dataset = dataset.find_conversion_destination(formats)
if target_ext and converted_dataset:
dataset = converted_dataset
self.unsanitized = dataset
self.dataset = wrap_with_safe_string(dataset, no_wrap_classes=ToolParameterValueWrapper)
self.metadata = self.MetadataWrapper(dataset, compute_environment)
if hasattr(dataset, 'tags'):
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):
identifier = self._element_identifier
if identifier is None:
identifier = self.name
return identifier
@property
def is_collection(self):
return False
[docs] def is_of_type(self, *exts):
datatypes = []
for e in exts:
datatype = self.datatypes_registry.get_datatype_by_extension(e)
if datatype is not None:
datatypes.append(datatype)
else:
log.warning("Datatype class not found for extension '%s', which is used as parameter of 'is_of_type()' method" % (e))
return self.dataset.datatype.matches_any(datatypes)
def __str__(self):
if self.false_path is not None:
return self.false_path
else:
return self.unsanitized.file_name
def __getattr__(self, key):
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
else:
return getattr(self.dataset, key)
def __bool__(self):
return bool(self.dataset)
__nonzero__ = __bool__
[docs]class HasDatasets(object):
def _dataset_wrapper(self, dataset, **kwargs):
return DatasetFilenameWrapper(dataset, **kwargs)
[docs] def paths_as_file(self, sep="\n"):
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, ToolParameterValueWrapper, HasDatasets):
"""
"""
[docs] def __init__(self, job_working_directory, datasets, **kwargs):
self._dataset_elements_cache = {}
if not isinstance(datasets, list):
datasets = [datasets]
def to_wrapper(dataset):
if hasattr(dataset, "dataset_instance"):
element = dataset
dataset = element.dataset_instance
kwargs["identifier"] = element.element_identifier
return self._dataset_wrapper(dataset, **kwargs)
list.__init__(self, map(to_wrapper, datasets))
self.job_working_directory = job_working_directory
[docs] @staticmethod
def to_dataset_instances(dataset_instance_sources):
dataset_instances = []
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):
group = text_type(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]
def __str__(self):
return ','.join(map(str, self))
def __bool__(self):
# Fail `#if $param` checks in cheetah if optional input is not provided
return any(self)
__nonzero__ = __bool__
[docs]class DatasetCollectionWrapper(ToolParameterValueWrapper, HasDatasets):
[docs] def __init__(self, job_working_directory, has_collection, **kwargs):
super(DatasetCollectionWrapper, self).__init__()
self.job_working_directory = job_working_directory
self._dataset_elements_cache = {}
self.kwargs = kwargs
if has_collection is None:
self.__input_supplied = False
return
else:
self.__input_supplied = True
if hasattr(has_collection, "name"):
# It is a HistoryDatasetCollectionAssociation
collection = has_collection.collection
self.name = has_collection.name
elif hasattr(has_collection, "child_collection"):
# It is a DatasetCollectionElement instance referencing another collection
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 = OrderedDict()
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 = 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):
group = text_type(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):
if not self.__input_supplied:
return []
return self.__element_instances.keys()
@property
def is_collection(self):
return True
@property
def element_identifier(self):
return self.name
@property
def is_input_supplied(self):
return self.__input_supplied
def __getitem__(self, key):
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):
if not self.__input_supplied:
return None
try:
return self.__element_instances[key]
except KeyError:
raise AttributeError()
def __iter__(self):
if not self.__input_supplied:
return [].__iter__()
return self.__element_instance_list.__iter__()
def __bool__(self):
# 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(object):
"""Track mapping of dataset collection elements datasets to element identifiers."""
[docs] def __init__(self, input_datasets=None):
if input_datasets is not None:
self.identifier_key_dict = dict((v, "%s|__identifier__" % k) for k, v in input_datasets.items())
else:
self.identifier_key_dict = {}
[docs] def identifier(self, dataset_value, input_values):
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