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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...

[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. """
[docs] def __init__(self, obj): self.obj = obj
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 items(self): return iter((k, self.get(k)) for k, v in self.metadata.items())
[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