enviPy-bayer/epapi/v1/interfaces/iuclid/projections.py

from uuid import UUID

from epdb.logic import PackageManager
from epdb.models import Pathway

from epapi.v1.errors import EPAPINotFoundError, EPAPIPermissionDeniedError

from .dto import (
    PathwayCompoundDTO,
    PathwayEdgeDTO,
    PathwayExportDTO,
    PathwayModelInfoDTO,
    PathwayNodeDTO,
    PathwayScenarioDTO,
)


def get_pathway_for_iuclid_export(user, pathway_uuid: UUID) -> PathwayExportDTO:
    """Return pathway data projected into DTOs for the IUCLID export consumer."""
    try:
        pathway = (
            Pathway.objects.select_related("package", "setting", "setting__model")
            .prefetch_related(
                "node_set__default_node_label__compound__external_identifiers__database",
                "node_set__scenarios",
                "edge_set__start_nodes__default_node_label__compound",
                "edge_set__end_nodes__default_node_label__compound",
            )
            .get(uuid=pathway_uuid)
        )
    except Pathway.DoesNotExist:
        raise EPAPINotFoundError(f"Pathway with UUID {pathway_uuid} not found")

    if not user or user.is_anonymous or not PackageManager.readable(user, pathway.package):
        raise EPAPIPermissionDeniedError("Insufficient permissions to access this pathway.")

    nodes: list[PathwayNodeDTO] = []
    edges: list[PathwayEdgeDTO] = []
    compounds_by_pk: dict[int, PathwayCompoundDTO] = {}
    root_compound_pks: list[int] = []

    for node in pathway.node_set.all().order_by("depth", "pk"):
        cs = node.default_node_label
        if cs is None:
            continue
        compound = cs.compound

        cas_number = None
        ec_number = None
        for ext_id in compound.external_identifiers.all():
            db_name = ext_id.database.name if ext_id.database else None
            if db_name == "CAS" and cas_number is None:
                cas_number = ext_id.identifier_value
            elif db_name == "EC" and ec_number is None:
                ec_number = ext_id.identifier_value

        ai_for_node = []
        scenario_entries: list[PathwayScenarioDTO] = []
        for scenario in sorted(node.get_scenarios(), key=lambda item: item.pk):
            ai_for_scenario = list(scenario.get_additional_information(direct_only=True))
            ai_for_node.extend(ai_for_scenario)
            scenario_entries.append(
                PathwayScenarioDTO(
                    scenario_uuid=scenario.uuid,
                    name=scenario.name,
                    additional_info=ai_for_scenario,
                )
            )

        nodes.append(
            PathwayNodeDTO(
                node_uuid=node.uuid,
                compound_pk=compound.pk,
                name=compound.name,
                depth=node.depth,
                smiles=cs.smiles,
                cas_number=cas_number,
                ec_number=ec_number,
                additional_info=ai_for_node,
                scenarios=scenario_entries,
            )
        )

        if node.depth == 0 and compound.pk not in root_compound_pks:
            root_compound_pks.append(compound.pk)

        if compound.pk not in compounds_by_pk:
            compounds_by_pk[compound.pk] = PathwayCompoundDTO(
                pk=compound.pk,
                name=compound.name,
                smiles=cs.smiles,
                cas_number=cas_number,
                ec_number=ec_number,
            )

    for edge in pathway.edge_set.all():
        start_compounds = {
            n.default_node_label.compound.pk
            for n in edge.start_nodes.all()
            if n.default_node_label is not None
        }
        end_compounds = {
            n.default_node_label.compound.pk
            for n in edge.end_nodes.all()
            if n.default_node_label is not None
        }

        probability = None
        if edge.kv and edge.kv.get("probability") is not None:
            try:
                probability = float(edge.kv.get("probability"))
            except (TypeError, ValueError):
                probability = None

        edges.append(
            PathwayEdgeDTO(
                edge_uuid=edge.uuid,
                start_compound_pks=sorted(start_compounds),
                end_compound_pks=sorted(end_compounds),
                probability=probability,
            )
        )

    model_info = None
    if pathway.setting and pathway.setting.model:
        model = pathway.setting.model
        model_info = PathwayModelInfoDTO(
            model_name=model.get_name(),
            model_uuid=model.uuid,
            software_name="enviPath",
            software_version=None,
        )

    return PathwayExportDTO(
        pathway_uuid=pathway.uuid,
        pathway_name=pathway.get_name(),
        compounds=list(compounds_by_pk.values()),
        nodes=nodes,
        edges=edges,
        root_compound_pks=root_compound_pks,
        model_info=model_info,
    )