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Source code for galaxy.managers.datatypes

from typing import (
    Dict,
    List,
    Optional,
    Union,
)

from pydantic.tools import parse_obj_as

from galaxy.datatypes._schema import (
    DatatypeConverterList,
    DatatypeDetails,
    DatatypesCombinedMap,
    DatatypesEDAMDetailsDict,
    DatatypesMap,
    DatatypeVisualizationMapping,
    DatatypeVisualizationMappingsList,
)
from galaxy.datatypes.data import Data
from galaxy.datatypes.registry import Registry


[docs] def view_index( datatypes_registry: Registry, extension_only: Optional[bool] = True, upload_only: Optional[bool] = True ) -> Union[List[DatatypeDetails], List[str]]: if extension_only: if upload_only: return datatypes_registry.upload_file_formats else: return list(datatypes_registry.datatypes_by_extension) else: rval = [] for datatype_info_dict in datatypes_registry.datatype_info_dicts: if upload_only and not datatype_info_dict.get("display_in_upload"): continue rval.append(datatype_info_dict) return rval
[docs] def view_mapping(datatypes_registry: Registry) -> DatatypesMap: ext_to_class_name: Dict[str, str] = {} classes = [] for k, v in datatypes_registry.datatypes_by_extension.items(): c = v.__class__ ext_to_class_name[k] = f"{c.__module__}.{c.__name__}" classes.append(c) class_to_classes: Dict[str, Dict[str, bool]] = {} def visit_bases(types, cls): for base in cls.__bases__: if issubclass(base, Data): types.add(f"{base.__module__}.{base.__name__}") visit_bases(types, base) for c in classes: n = f"{c.__module__}.{c.__name__}" types = {n} visit_bases(types, c) class_to_classes[n] = dict.fromkeys(types, True) return DatatypesMap(ext_to_class_name=ext_to_class_name, class_to_classes=class_to_classes)
[docs] def view_types_and_mapping( datatypes_registry: Registry, extension_only: Optional[bool] = True, upload_only: Optional[bool] = True ) -> DatatypesCombinedMap: return DatatypesCombinedMap( datatypes=view_index(datatypes_registry, extension_only, upload_only), datatypes_mapping=view_mapping(datatypes_registry), )
[docs] def view_sniffers(datatypes_registry: Registry) -> List[str]: rval: List[str] = [] for sniffer_elem in datatypes_registry.sniffer_elems: datatype = sniffer_elem.get("type") if datatype is not None: rval.append(datatype) return rval
[docs] def view_converters(datatypes_registry: Registry) -> DatatypeConverterList: converters = [] for source_type, targets in datatypes_registry.datatype_converters.items(): for target_type in targets: converters.append( { "source": source_type, "target": target_type, "tool_id": targets[target_type].id, } ) return parse_obj_as(DatatypeConverterList, converters)
def _get_edam_details(datatypes_registry: Registry, edam_ids: Dict[str, str]) -> Dict[str, Dict]: details_dict = {} for format, edam_iri in edam_ids.items(): edam_details = datatypes_registry.edam.get(edam_iri, {}) details_dict[format] = { "prefix_IRI": edam_iri, "label": edam_details.get("label", None), "definition": edam_details.get("definition", None), } return details_dict
[docs] def view_edam_formats( datatypes_registry: Registry, detailed: Optional[bool] = False ) -> Union[Dict[str, str], Dict[str, Dict[str, str]]]: if detailed: return _get_edam_details(datatypes_registry, datatypes_registry.edam_formats) else: return datatypes_registry.edam_formats
[docs] def view_edam_data( datatypes_registry: Registry, detailed: Optional[bool] = False ) -> Union[Dict[str, str], Dict[str, Dict[str, str]]]: if detailed: return _get_edam_details(datatypes_registry, datatypes_registry.edam_data) else: return datatypes_registry.edam_data
[docs] def view_visualization_mappings( datatypes_registry: Registry, datatype: Optional[str] = None ) -> DatatypeVisualizationMappingsList: """ Get datatype visualization mappings from the registry. Args: datatypes_registry: The datatypes registry datatype: If provided, return only the mapping for this datatype extension Returns: A list of datatype visualization mappings """ mappings = [] # Get all mappings all_mappings = datatypes_registry.get_all_visualization_mappings() # Filter for a specific datatype if requested if datatype and datatype in all_mappings: mapping_info = all_mappings[datatype] mappings.append( { "datatype": datatype, "visualization": mapping_info["visualization"], } ) elif not datatype: for dt, mapping_info in all_mappings.items(): mappings.append( { "datatype": dt, "visualization": mapping_info["visualization"], } ) return parse_obj_as(DatatypeVisualizationMappingsList, mappings)
__all__ = ( "DatatypeConverterList", "DatatypeDetails", "DatatypesCombinedMap", "DatatypesEDAMDetailsDict", "DatatypesMap", "DatatypeVisualizationMapping", "DatatypeVisualizationMappingsList", "view_index", "view_mapping", "view_types_and_mapping", "view_sniffers", "view_converters", "view_edam_formats", "view_edam_data", "view_visualization_mappings", )