Source code for galaxy.tools.parameters.dynamic_options

"""
Support for generating the options for a SelectToolParameter dynamically (based
on the values of other parameters or other aspects of the current state)
"""
import logging
import os
import re

from six import StringIO

import galaxy.tools
from galaxy.model import (
    HistoryDatasetAssociation,
    HistoryDatasetCollectionAssociation,
    User
)
from galaxy.util import string_as_bool
from . import validation

log = logging.getLogger(__name__)


[docs]class Filter(object): """ A filter takes the current options list and modifies it. """
[docs] @classmethod def from_element(cls, d_option, elem): """Loads the proper filter by the type attribute of elem""" type = elem.get('type', None) assert type is not None, "Required 'type' attribute missing from filter" return filter_types[type.strip()](d_option, elem)
[docs] def __init__(self, d_option, elem): self.dynamic_option = d_option self.elem = elem
[docs] def get_dependency_name(self): """Returns the name of any dependencies, otherwise None""" return None
[docs] def filter_options(self, options, trans, other_values): """Returns a list of options after the filter is applied""" raise TypeError("Abstract Method")
[docs]class StaticValueFilter(Filter): """ Filters a list of options on a column by a static value. Type: static_value Required Attributes: value: static value to compare to column: column in options to compare with Optional Attributes: keep: Keep columns matching value (True) Discard columns matching value (False) """
[docs] def __init__(self, d_option, elem): Filter.__init__(self, d_option, elem) self.value = elem.get("value", None) assert self.value is not None, "Required 'value' attribute missing from filter" column = elem.get("column", None) assert column is not None, "Required 'column' attribute missing from filter, when loading from file" self.column = d_option.column_spec_to_index(column) self.keep = string_as_bool(elem.get("keep", 'True'))
[docs] def filter_options(self, options, trans, other_values): rval = [] filter_value = self.value try: filter_value = User.expand_user_properties(trans.user, filter_value) except Exception: pass for fields in options: if self.keep == (filter_value == fields[self.column]): rval.append(fields) return rval
[docs]class RegexpFilter(Filter): """ Filters a list of options on a column by a regular expression. Type: regexp Required Attributes: value: regular expression to compare to column: column in options to compare with Optional Attributes: keep: Keep columns matching the regexp (True) Discard columns matching the regexp (False) """
[docs] def __init__(self, d_option, elem): Filter.__init__(self, d_option, elem) self.value = elem.get("value", None) assert self.value is not None, "Required 'value' attribute missing from filter" column = elem.get("column", None) assert column is not None, "Required 'column' attribute missing from filter, when loading from file" self.column = d_option.column_spec_to_index(column) self.keep = string_as_bool(elem.get("keep", 'True'))
[docs] def filter_options(self, options, trans, other_values): rval = [] filter_value = self.value try: filter_value = User.expand_user_properties(trans.user, filter_value) except Exception: pass filter_pattern = re.compile(filter_value) for fields in options: if self.keep == (not filter_pattern.match(fields[self.column]) is None): rval.append(fields) return rval
[docs]class DataMetaFilter(Filter): """ Filters a list of options on a column by a dataset metadata value. Type: data_meta When no 'from' source has been specified in the <options> tag, this will populate the options list with (meta_value, meta_value, False). Otherwise, options which do not match the metadata value in the column are discarded. Required Attributes: - ref: Name of input dataset - key: Metadata key to use for comparison - column: column in options to compare with (not required when not associated with input options) Optional Attributes: - multiple: Option values are multiple, split column by separator (True) - separator: When multiple split by this (,) """
[docs] def __init__(self, d_option, elem): Filter.__init__(self, d_option, elem) self.ref_name = elem.get("ref", None) assert self.ref_name is not None, "Required 'ref' attribute missing from filter" d_option.has_dataset_dependencies = True self.key = elem.get("key", None) assert self.key is not None, "Required 'key' attribute missing from filter" self.column = elem.get("column", None) if self.column is None: assert self.dynamic_option.file_fields is None and self.dynamic_option.dataset_ref_name is None, "Required 'column' attribute missing from filter, when loading from file" else: self.column = d_option.column_spec_to_index(self.column) self.multiple = string_as_bool(elem.get("multiple", "False")) self.separator = elem.get("separator", ",")
[docs] def get_dependency_name(self): return self.ref_name
[docs] def filter_options(self, options, trans, other_values): def compare_meta_value(file_value, dataset_value): if isinstance(dataset_value, list): if self.multiple: file_value = file_value.split(self.separator) for value in dataset_value: if value not in file_value: return False return True return file_value in dataset_value if self.multiple: return dataset_value in file_value.split(self.separator) return file_value == dataset_value ref = other_values.get(self.ref_name, None) if isinstance(ref, HistoryDatasetCollectionAssociation): ref = ref.to_hda_representative(self.multiple) is_data = isinstance(ref, galaxy.tools.wrappers.DatasetFilenameWrapper) is_data_list = isinstance(ref, galaxy.tools.wrappers.DatasetListWrapper) or isinstance(ref, list) is_data_or_data_list = is_data or is_data_list if not isinstance(ref, HistoryDatasetAssociation) and not is_data_or_data_list: return [] # not a valid dataset # get the metadata value. for lists (of data sets) and collections # the meta data value of all elements is determined if its the same # for all, if different are found the filter returns an empty list if is_data_list: meta_value = None for single_ref in ref: this_meta_value = single_ref.metadata.get(self.key, None) if this_meta_value == meta_value: continue elif meta_value is None: meta_value = this_meta_value else: # Different values with mismatching metadata, return [] return [] else: meta_value = ref.metadata.get(self.key, None) # if no meta data value could be determined just return a copy # of the original options if meta_value is None: return [(disp_name, optval, selected) for disp_name, optval, selected in options] if self.column is not None: rval = [] for fields in options: if compare_meta_value(fields[self.column], meta_value): rval.append(fields) return rval else: if not self.dynamic_option.columns: self.dynamic_option.columns = { "name" : 0, "value" : 1, "selected" : 2 } self.dynamic_option.largest_index = 2 if not isinstance(meta_value, list): meta_value = [meta_value] for value in meta_value: options.append((value, value, False)) return options
[docs]class ParamValueFilter(Filter): """ Filters a list of options on a column by the value of another input. Type: param_value Required Attributes: - ref: Name of input value - column: column in options to compare with Optional Attributes: - keep: Keep columns matching value (True) Discard columns matching value (False) - ref_attribute: Period (.) separated attribute chain of input (ref) to use as value for filter """
[docs] def __init__(self, d_option, elem): Filter.__init__(self, d_option, elem) self.ref_name = elem.get("ref", None) assert self.ref_name is not None, "Required 'ref' attribute missing from filter" column = elem.get("column", None) assert column is not None, "Required 'column' attribute missing from filter" self.column = d_option.column_spec_to_index(column) self.keep = string_as_bool(elem.get("keep", 'True')) self.ref_attribute = elem.get("ref_attribute", None) if self.ref_attribute: self.ref_attribute = self.ref_attribute.split('.') else: self.ref_attribute = []
[docs] def get_dependency_name(self): return self.ref_name
[docs] def filter_options(self, options, trans, other_values): if trans is not None and trans.workflow_building_mode: return [] ref = other_values.get(self.ref_name, None) for ref_attribute in self.ref_attribute: if not hasattr(ref, ref_attribute): return [] # ref does not have attribute, so we cannot filter, return empty list ref = getattr(ref, ref_attribute) ref = str(ref) rval = [] for fields in options: if self.keep == (fields[self.column] == ref): rval.append(fields) return rval
[docs]class UniqueValueFilter(Filter): """ Filters a list of options to be unique by a column value. Type: unique_value Required Attributes: column: column in options to compare with """
[docs] def __init__(self, d_option, elem): Filter.__init__(self, d_option, elem) column = elem.get("column", None) assert column is not None, "Required 'column' attribute missing from filter" self.column = d_option.column_spec_to_index(column)
[docs] def get_dependency_name(self): return self.dynamic_option.dataset_ref_name
[docs] def filter_options(self, options, trans, other_values): rval = [] skip_list = [] for fields in options: if fields[self.column] not in skip_list: rval.append(fields) skip_list.append(fields[self.column]) return rval
[docs]class MultipleSplitterFilter(Filter): """ Turns a single line of options into multiple lines, by splitting a column and creating a line for each item. Type: multiple_splitter Required Attributes: column: column in options to compare with Optional Attributes: separator: Split column by this (,) """
[docs] def __init__(self, d_option, elem): Filter.__init__(self, d_option, elem) self.separator = elem.get("separator", ",") columns = elem.get("column", None) assert columns is not None, "Required 'column' attribute missing from filter" self.columns = [d_option.column_spec_to_index(column) for column in columns.split(",")]
[docs] def filter_options(self, options, trans, other_values): rval = [] for fields in options: for column in self.columns: for field in fields[column].split(self.separator): rval.append(fields[0:column] + [field] + fields[column + 1:]) return rval
[docs]class AttributeValueSplitterFilter(Filter): """ Filters a list of attribute-value pairs to be unique attribute names. DEPRECATED: just replace with 2 rounds of MultipleSplitterFilter Type: attribute_value_splitter Required Attributes: column: column in options to compare with Optional Attributes: pair_separator: Split column by this (,) name_val_separator: Split name-value pair by this ( whitespace ) """
[docs] def __init__(self, d_option, elem): Filter.__init__(self, d_option, elem) self.pair_separator = elem.get("pair_separator", ",") self.name_val_separator = elem.get("name_val_separator", None) columns = elem.get("column", None) assert columns is not None, "Required 'column' attribute missing from filter" self.columns = [d_option.column_spec_to_index(column) for column in columns.split(",")]
[docs] def filter_options(self, options, trans, other_values): attr_names = [] rval = [] for fields in options: for column in self.columns: for pair in fields[column].split(self.pair_separator): ary = pair.split(self.name_val_separator) if len(ary) == 2: name = ary[0] if name not in attr_names: rval.append(fields[0:column] + [name] + fields[column:]) attr_names.append(name) return rval
[docs]class AdditionalValueFilter(Filter): """ Adds a single static value to an options list. Type: add_value Required Attributes: value: value to appear in select list Optional Attributes: name: Display name to appear in select list (value) index: Index of option list to add value (APPEND) """
[docs] def __init__(self, d_option, elem): Filter.__init__(self, d_option, elem) self.value = elem.get("value", None) assert self.value is not None, "Required 'value' attribute missing from filter" self.name = elem.get("name", None) if self.name is None: self.name = self.value self.index = elem.get("index", None) if self.index is not None: self.index = int(self.index)
[docs] def filter_options(self, options, trans, other_values): rval = list(options) add_value = [] for _ in range(self.dynamic_option.largest_index + 1): add_value.append("") value_col = self.dynamic_option.columns.get('value', 0) name_col = self.dynamic_option.columns.get('name', value_col) # Set name first, then value, in case they are the same column add_value[name_col] = self.name add_value[value_col] = self.value if self.index is not None: rval.insert(self.index, add_value) else: rval.append(add_value) return rval
[docs]class RemoveValueFilter(Filter): """ Removes a value from an options list. Type: remove_value Required Attributes:: value: value to remove from select list or ref: param to refer to or meta_ref: dataset to refer to key: metadata key to compare to """
[docs] def __init__(self, d_option, elem): Filter.__init__(self, d_option, elem) self.value = elem.get("value", None) self.ref_name = elem.get("ref", None) self.meta_ref = elem.get("meta_ref", None) self.metadata_key = elem.get("key", None) assert self.value is not None or self.ref_name is not None or (self.meta_ref is not None and self.metadata_key is not None), ValueError("Required 'value', or 'ref', or 'meta_ref' and 'key' attributes missing from filter") self.multiple = string_as_bool(elem.get("multiple", "False")) self.separator = elem.get("separator", ",")
[docs] def filter_options(self, options, trans, other_values): if trans is not None and trans.workflow_building_mode: return options def compare_value(option_value, filter_value): if isinstance(filter_value, list): if self.multiple: option_value = option_value.split(self.separator) for value in filter_value: if value not in option_value: return False return True return option_value in filter_value if self.multiple: return filter_value in option_value.split(self.separator) return option_value == filter_value value = self.value if value is None: if self.ref_name is not None: value = other_values.get(self.ref_name) else: data_ref = other_values.get(self.meta_ref) if isinstance(data_ref, HistoryDatasetCollectionAssociation): data_ref = data_ref.to_hda_representative() if not isinstance(data_ref, HistoryDatasetAssociation) and not isinstance(data_ref, galaxy.tools.wrappers.DatasetFilenameWrapper): return options # cannot modify options value = data_ref.metadata.get(self.metadata_key, None) # Default to the second column (i.e. 1) since this used to work only on options produced by the data_meta filter value_col = self.dynamic_option.columns.get('value', 1) return [option for option in options if not compare_value(option[value_col], value)]
[docs]class SortByColumnFilter(Filter): """ Sorts an options list by a column Type: sort_by Required Attributes: column: column to sort by """
[docs] def __init__(self, d_option, elem): Filter.__init__(self, d_option, elem) column = elem.get("column", None) assert column is not None, "Required 'column' attribute missing from filter" self.column = d_option.column_spec_to_index(column)
[docs] def filter_options(self, options, trans, other_values): return sorted(options, key=lambda x: x[self.column])
filter_types = dict(data_meta=DataMetaFilter, param_value=ParamValueFilter, static_value=StaticValueFilter, regexp=RegexpFilter, unique_value=UniqueValueFilter, multiple_splitter=MultipleSplitterFilter, attribute_value_splitter=AttributeValueSplitterFilter, add_value=AdditionalValueFilter, remove_value=RemoveValueFilter, sort_by=SortByColumnFilter)
[docs]class DynamicOptions(object): """Handles dynamically generated SelectToolParameter options"""
[docs] def __init__(self, elem, tool_param): def load_from_parameter(from_parameter, transform_lines=None): obj = self.tool_param for field in from_parameter.split('.'): obj = getattr(obj, field) if transform_lines: obj = eval(transform_lines, {'self': self, 'obj': obj}) return self.parse_file_fields(obj) self.tool_param = tool_param self.columns = {} self.filters = [] self.file_fields = None self.largest_index = 0 self.dataset_ref_name = None # True if the options generation depends on one or more other parameters # that are dataset inputs self.has_dataset_dependencies = False self.validators = [] self.converter_safe = True # Parse the <options> tag self.separator = elem.get('separator', '\t') self.line_startswith = elem.get('startswith', None) data_file = elem.get('from_file', None) self.index_file = None self.missing_index_file = None dataset_file = elem.get('from_dataset', None) from_parameter = elem.get('from_parameter', None) self.tool_data_table_name = elem.get('from_data_table', None) # Options are defined from a data table loaded by the app self._tool_data_table = None self.elem = elem self.column_elem = elem.find("column") self.tool_data_table # Need to touch tool data table once to populate self.columns # Options are defined by parsing tabular text data from a data file # on disk, a dataset, or the value of another parameter if not self.tool_data_table_name and (data_file is not None or dataset_file is not None or from_parameter is not None): self.parse_column_definitions(elem) if data_file is not None: data_file = data_file.strip() if not os.path.isabs(data_file): full_path = os.path.join(self.tool_param.tool.app.config.tool_data_path, data_file) if os.path.exists(full_path): self.index_file = data_file with open(full_path) as fh: self.file_fields = self.parse_file_fields(fh) else: self.missing_index_file = data_file elif dataset_file is not None: self.dataset_ref_name = dataset_file self.has_dataset_dependencies = True self.converter_safe = False elif from_parameter is not None: transform_lines = elem.get('transform_lines', None) self.file_fields = list(load_from_parameter(from_parameter, transform_lines)) # Load filters for filter_elem in elem.findall('filter'): self.filters.append(Filter.from_element(self, filter_elem)) # Load Validators for validator in elem.findall('validator'): self.validators.append(validation.Validator.from_element(self.tool_param, validator)) if self.dataset_ref_name: tool_param.data_ref = self.dataset_ref_name
@property def tool_data_table(self): if self.tool_data_table_name: tool_data_table = self.tool_param.tool.app.tool_data_tables.get(self.tool_data_table_name, None) if tool_data_table: # Column definitions are optional, but if provided override those from the table if self.column_elem is not None: self.parse_column_definitions(self.elem) else: self.columns = tool_data_table.columns # Set self.missing_index_file if the index file to # which the tool_data_table refers does not exist. if tool_data_table.missing_index_file: self.missing_index_file = tool_data_table.missing_index_file return tool_data_table return None @property def missing_tool_data_table_name(self): if not self.tool_data_table: log.warning("Data table named '%s' is required by tool but not configured" % self.tool_data_table_name) return self.tool_data_table_name return None
[docs] def parse_column_definitions(self, elem): for column_elem in elem.findall('column'): name = column_elem.get('name', None) assert name is not None, "Required 'name' attribute missing from column def" index = column_elem.get('index', None) assert index is not None, "Required 'index' attribute missing from column def" index = int(index) self.columns[name] = index if index > self.largest_index: self.largest_index = index assert 'value' in self.columns, "Required 'value' column missing from column def" if 'name' not in self.columns: self.columns['name'] = self.columns['value']
[docs] def parse_file_fields(self, reader): rval = [] field_count = None for line in reader: if line.startswith('#') or (self.line_startswith and not line.startswith(self.line_startswith)): continue line = line.rstrip("\n\r") if line: fields = line.split(self.separator) if self.largest_index < len(fields): if not field_count: field_count = len(fields) elif field_count != len(fields): try: name = reader.name except AttributeError: name = "a configuration file" # Perhaps this should be an error, but even a warning is useful. log.warning("Inconsistent number of fields (%i vs %i) in %s using separator %r, check line: %r" % (field_count, len(fields), name, self.separator, line)) rval.append(fields) return rval
[docs] def get_dependency_names(self): """ Return the names of parameters these options depend on -- both data and other param types. """ rval = [] if self.dataset_ref_name: rval.append(self.dataset_ref_name) for filter in self.filters: depend = filter.get_dependency_name() if depend: rval.append(depend) return rval
[docs] def get_fields(self, trans, other_values): if self.dataset_ref_name: dataset = other_values.get(self.dataset_ref_name, None) if not dataset or not hasattr(dataset, 'file_name'): return [] # no valid dataset in history # Ensure parsing dynamic options does not consume more than a megabyte worth memory. path = dataset.file_name if os.path.getsize(path) < 1048576: with open(path) as fh: options = self.parse_file_fields(fh) else: # Pass just the first megabyte to parse_file_fields. log.warning("Attempting to load options from large file, reading just first megabyte") with open(path, 'r') as fh: contents = fh.read(1048576) options = self.parse_file_fields(StringIO(contents)) elif self.tool_data_table: options = self.tool_data_table.get_fields() elif self.file_fields: options = list(self.file_fields) else: options = [] for filter in self.filters: options = filter.filter_options(options, trans, other_values) return options
[docs] def get_fields_by_value(self, value, trans, other_values): """ Return a list of fields with column 'value' matching provided value. """ rval = [] val_index = self.columns['value'] for fields in self.get_fields(trans, other_values): if fields[val_index] == value: rval.append(fields) return rval
[docs] def get_field_by_name_for_value(self, field_name, value, trans, other_values): """ Get contents of field by name for specified value. """ rval = [] if isinstance(field_name, int): field_index = field_name else: assert field_name in self.columns, "Requested '%s' column missing from column def" % field_name field_index = self.columns[field_name] if not isinstance(value, list): value = [value] for val in value: for fields in self.get_fields_by_value(val, trans, other_values): rval.append(fields[field_index]) return rval
[docs] def get_options(self, trans, other_values): rval = [] if self.file_fields is not None or self.tool_data_table is not None or self.dataset_ref_name is not None or self.missing_index_file: options = self.get_fields(trans, other_values) for fields in options: rval.append((fields[self.columns['name']], fields[self.columns['value']], False)) else: for filter in self.filters: rval = filter.filter_options(rval, trans, other_values) return rval
[docs] def column_spec_to_index(self, column_spec): """ Convert a column specification (as read from the config file), to an index. A column specification can just be a number, a column name, or a column alias. """ # Name? if column_spec in self.columns: return self.columns[column_spec] # Int? return int(column_spec)