from __future__ import annotations

import warnings
from collections.abc import Sequence
from typing import Any, ClassVar, Literal, overload

from cognite.client import CogniteClient
from cognite.client import data_modeling as dm
from cognite.client.data_classes.data_modeling.instances import InstanceAggregationResultList, InstanceSort

from cognite.powerops.client._generated.v1._api._core import (
    DEFAULT_LIMIT_READ,
    instantiate_classes,
    Aggregations,
    NodeAPI,
    SequenceNotStr,
)
from cognite.powerops.client._generated.v1.data_classes._core import (
    DEFAULT_INSTANCE_SPACE,
    DEFAULT_QUERY_LIMIT,
    QueryStepFactory,
    QueryBuilder,
    QueryUnpacker,
    ViewPropertyId,
)
from cognite.powerops.client._generated.v1.data_classes._task_dispatcher_output import (
    TaskDispatcherOutputQuery,
    _TASKDISPATCHEROUTPUT_PROPERTIES_BY_FIELD,
    _create_task_dispatcher_output_filter,
)
from cognite.powerops.client._generated.v1.data_classes import (
    DomainModel,
    DomainModelCore,
    DomainModelWrite,
    ResourcesWriteResult,
    TaskDispatcherOutput,
    TaskDispatcherOutputWrite,
    TaskDispatcherOutputFields,
    TaskDispatcherOutputList,
    TaskDispatcherOutputWriteList,
    TaskDispatcherOutputTextFields,
    Alert,
    FunctionInput,
    TaskDispatcherInput,
)
from cognite.powerops.client._generated.v1._api.task_dispatcher_output_alerts import TaskDispatcherOutputAlertsAPI
from cognite.powerops.client._generated.v1._api.task_dispatcher_output_process_sub_tasks import TaskDispatcherOutputProcessSubTasksAPI
from cognite.powerops.client._generated.v1._api.task_dispatcher_output_query import TaskDispatcherOutputQueryAPI


class TaskDispatcherOutputAPI(NodeAPI[TaskDispatcherOutput, TaskDispatcherOutputWrite, TaskDispatcherOutputList, TaskDispatcherOutputWriteList]):
    _view_id = dm.ViewId("power_ops_core", "TaskDispatcherOutput", "1")
    _properties_by_field: ClassVar[dict[str, str]] = _TASKDISPATCHEROUTPUT_PROPERTIES_BY_FIELD
    _class_type = TaskDispatcherOutput
    _class_list = TaskDispatcherOutputList
    _class_write_list = TaskDispatcherOutputWriteList

    def __init__(self, client: CogniteClient):
        super().__init__(client=client)

        self.alerts_edge = TaskDispatcherOutputAlertsAPI(client)
        self.process_sub_tasks_edge = TaskDispatcherOutputProcessSubTasksAPI(client)

    def __call__(
        self,
        workflow_execution_id: str | list[str] | None = None,
        workflow_execution_id_prefix: str | None = None,
        min_workflow_step: int | None = None,
        max_workflow_step: int | None = None,
        function_name: str | list[str] | None = None,
        function_name_prefix: str | None = None,
        function_call_id: str | list[str] | None = None,
        function_call_id_prefix: str | None = None,
        function_input: str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference | Sequence[str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference] | None = None,
        external_id_prefix: str | None = None,
        space: str | list[str] | None = None,
        limit: int = DEFAULT_QUERY_LIMIT,
        filter: dm.Filter | None = None,
    ) -> TaskDispatcherOutputQueryAPI[TaskDispatcherOutput, TaskDispatcherOutputList]:
        """Query starting at task dispatcher outputs.

        Args:
            workflow_execution_id: The workflow execution id to filter on.
            workflow_execution_id_prefix: The prefix of the workflow execution id to filter on.
            min_workflow_step: The minimum value of the workflow step to filter on.
            max_workflow_step: The maximum value of the workflow step to filter on.
            function_name: The function name to filter on.
            function_name_prefix: The prefix of the function name to filter on.
            function_call_id: The function call id to filter on.
            function_call_id_prefix: The prefix of the function call id to filter on.
            function_input: The function input to filter on.
            external_id_prefix: The prefix of the external ID to filter on.
            space: The space to filter on.
            limit: Maximum number of task dispatcher outputs to return. Defaults to 25.
                Set to -1, float("inf") or None to return all items.
            filter: (Advanced) If the filtering available in the above is not sufficient, you can write
                your own filtering which will be ANDed with the filter above.

        Returns:
            A query API for task dispatcher outputs.

        """
        warnings.warn(
            "This method is deprecated and will soon be removed. "
            "Use the .select() method instead.",
            UserWarning,
            stacklevel=2,
        )
        has_data = dm.filters.HasData(views=[self._view_id])
        filter_ = _create_task_dispatcher_output_filter(
            self._view_id,
            workflow_execution_id,
            workflow_execution_id_prefix,
            min_workflow_step,
            max_workflow_step,
            function_name,
            function_name_prefix,
            function_call_id,
            function_call_id_prefix,
            function_input,
            external_id_prefix,
            space,
            (filter and dm.filters.And(filter, has_data)) or has_data,
        )
        return TaskDispatcherOutputQueryAPI(
            self._client, QueryBuilder(), self._class_type, self._class_list, None, filter_, limit
        )

    def apply(
        self,
        task_dispatcher_output: TaskDispatcherOutputWrite | Sequence[TaskDispatcherOutputWrite],
        replace: bool = False,
        write_none: bool = False,
    ) -> ResourcesWriteResult:
        """Add or update (upsert) task dispatcher outputs.

        Args:
            task_dispatcher_output: Task dispatcher output or
                sequence of task dispatcher outputs to upsert.
            replace (bool): How do we behave when a property value exists? Do we replace all matching and
                existing values with the supplied values (true)?
                Or should we merge in new values for properties together with the existing values (false)?
                Note: This setting applies for all nodes or edges specified in the ingestion call.
            write_none (bool): This method, will by default, skip properties that are set to None.
                However, if you want to set properties to None,
                you can set this parameter to True. Note this only applies to properties that are nullable.
        Returns:
            Created instance(s), i.e., nodes, edges, and time series.

        Examples:

            Create a new task_dispatcher_output:

                >>> from cognite.powerops.client._generated.v1 import PowerOpsModelsV1Client
                >>> from cognite.powerops.client._generated.v1.data_classes import TaskDispatcherOutputWrite
                >>> client = PowerOpsModelsV1Client()
                >>> task_dispatcher_output = TaskDispatcherOutputWrite(
                ...     external_id="my_task_dispatcher_output", ...
                ... )
                >>> result = client.task_dispatcher_output.apply(task_dispatcher_output)

        """
        warnings.warn(
            "The .apply method is deprecated and will be removed in v1.0. "
            "Please use the .upsert method on the client instead. This means instead of "
            "`my_client.task_dispatcher_output.apply(my_items)` please use `my_client.upsert(my_items)`."
            "The motivation is that all apply methods are the same, and having one apply method per API "
            " class encourages users to create items in small batches, which is inefficient."
            "In addition, .upsert method is more descriptive of what the method does.",
            UserWarning,
            stacklevel=2,
        )
        return self._apply(task_dispatcher_output, replace, write_none)

    def delete(self, external_id: str | SequenceNotStr[str], space: str = DEFAULT_INSTANCE_SPACE) -> dm.InstancesDeleteResult:
        """Delete one or more task dispatcher output.

        Args:
            external_id: External id of the task dispatcher output to delete.
            space: The space where all the task dispatcher output are located.

        Returns:
            The instance(s), i.e., nodes and edges which has been deleted. Empty list if nothing was deleted.

        Examples:

            Delete task_dispatcher_output by id:

                >>> from cognite.powerops.client._generated.v1 import PowerOpsModelsV1Client
                >>> client = PowerOpsModelsV1Client()
                >>> client.task_dispatcher_output.delete("my_task_dispatcher_output")
        """
        warnings.warn(
            "The .delete method is deprecated and will be removed in v1.0. "
            "Please use the .delete method on the client instead. This means instead of "
            "`my_client.task_dispatcher_output.delete(my_ids)` please use `my_client.delete(my_ids)`."
            "The motivation is that all delete methods are the same, and having one delete method per API "
            " class encourages users to delete items in small batches, which is inefficient.",
            UserWarning,
            stacklevel=2,
        )
        return self._delete(external_id, space)

    @overload
    def retrieve(
        self,
        external_id: str | dm.NodeId | tuple[str, str],
        space: str = DEFAULT_INSTANCE_SPACE,
        retrieve_connections: Literal["skip", "identifier", "full"] = "skip",
    ) -> TaskDispatcherOutput | None: ...

    @overload
    def retrieve(
        self,
        external_id: SequenceNotStr[str | dm.NodeId | tuple[str, str]],
        space: str = DEFAULT_INSTANCE_SPACE,
        retrieve_connections: Literal["skip", "identifier", "full"] = "skip",
    ) -> TaskDispatcherOutputList: ...

    def retrieve(
        self,
        external_id: str | dm.NodeId | tuple[str, str] | SequenceNotStr[str | dm.NodeId | tuple[str, str]],
        space: str = DEFAULT_INSTANCE_SPACE,
        retrieve_connections: Literal["skip", "identifier", "full"] = "skip",
    ) -> TaskDispatcherOutput | TaskDispatcherOutputList | None:
        """Retrieve one or more task dispatcher outputs by id(s).

        Args:
            external_id: External id or list of external ids of the task dispatcher outputs.
            space: The space where all the task dispatcher outputs are located.
            retrieve_connections: Whether to retrieve `function_input`, `alerts` and `process_sub_tasks` for the task
            dispatcher outputs. Defaults to 'skip'.'skip' will not retrieve any connections, 'identifier' will only
            retrieve the identifier of the connected items, and 'full' will retrieve the full connected items.

        Returns:
            The requested task dispatcher outputs.

        Examples:

            Retrieve task_dispatcher_output by id:

                >>> from cognite.powerops.client._generated.v1 import PowerOpsModelsV1Client
                >>> client = PowerOpsModelsV1Client()
                >>> task_dispatcher_output = client.task_dispatcher_output.retrieve(
                ...     "my_task_dispatcher_output"
                ... )

        """
        return self._retrieve(
            external_id,
            space,
            retrieve_connections=retrieve_connections,
        )

    def search(
        self,
        query: str,
        properties: TaskDispatcherOutputTextFields | SequenceNotStr[TaskDispatcherOutputTextFields] | None = None,
        workflow_execution_id: str | list[str] | None = None,
        workflow_execution_id_prefix: str | None = None,
        min_workflow_step: int | None = None,
        max_workflow_step: int | None = None,
        function_name: str | list[str] | None = None,
        function_name_prefix: str | None = None,
        function_call_id: str | list[str] | None = None,
        function_call_id_prefix: str | None = None,
        function_input: str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference | Sequence[str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference] | None = None,
        external_id_prefix: str | None = None,
        space: str | list[str] | None = None,
        limit: int = DEFAULT_LIMIT_READ,
        filter: dm.Filter | None = None,
        sort_by: TaskDispatcherOutputFields | SequenceNotStr[TaskDispatcherOutputFields] | None = None,
        direction: Literal["ascending", "descending"] = "ascending",
        sort: InstanceSort | list[InstanceSort] | None = None,
    ) -> TaskDispatcherOutputList:
        """Search task dispatcher outputs

        Args:
            query: The search query,
            properties: The property to search, if nothing is passed all text fields will be searched.
            workflow_execution_id: The workflow execution id to filter on.
            workflow_execution_id_prefix: The prefix of the workflow execution id to filter on.
            min_workflow_step: The minimum value of the workflow step to filter on.
            max_workflow_step: The maximum value of the workflow step to filter on.
            function_name: The function name to filter on.
            function_name_prefix: The prefix of the function name to filter on.
            function_call_id: The function call id to filter on.
            function_call_id_prefix: The prefix of the function call id to filter on.
            function_input: The function input to filter on.
            external_id_prefix: The prefix of the external ID to filter on.
            space: The space to filter on.
            limit: Maximum number of task dispatcher outputs to return. Defaults to 25.
                Set to -1, float("inf") or None to return all items.
            filter: (Advanced) If the filtering available in the above is not sufficient,
                you can write your own filtering which will be ANDed with the filter above.
            sort_by: The property to sort by.
            direction: The direction to sort by, either 'ascending' or 'descending'.
            sort: (Advanced) If sort_by and direction are not sufficient, you can write your own sorting.
                This will override the sort_by and direction. This allows you to sort by multiple fields and
                specify the direction for each field as well as how to handle null values.

        Returns:
            Search results task dispatcher outputs matching the query.

        Examples:

           Search for 'my_task_dispatcher_output' in all text properties:

                >>> from cognite.powerops.client._generated.v1 import PowerOpsModelsV1Client
                >>> client = PowerOpsModelsV1Client()
                >>> task_dispatcher_outputs = client.task_dispatcher_output.search(
                ...     'my_task_dispatcher_output'
                ... )

        """
        filter_ = _create_task_dispatcher_output_filter(
            self._view_id,
            workflow_execution_id,
            workflow_execution_id_prefix,
            min_workflow_step,
            max_workflow_step,
            function_name,
            function_name_prefix,
            function_call_id,
            function_call_id_prefix,
            function_input,
            external_id_prefix,
            space,
            filter,
        )
        return self._search(
            query=query,
            properties=properties,
            filter_=filter_,
            limit=limit,
            sort_by=sort_by,  # type: ignore[arg-type]
            direction=direction,
            sort=sort,
        )

    @overload
    def aggregate(
        self,
        aggregate: Aggregations | dm.aggregations.MetricAggregation,
        group_by: None = None,
        property: TaskDispatcherOutputFields | SequenceNotStr[TaskDispatcherOutputFields] | None = None,
        query: str | None = None,
        search_property: TaskDispatcherOutputTextFields | SequenceNotStr[TaskDispatcherOutputTextFields] | None = None,
        workflow_execution_id: str | list[str] | None = None,
        workflow_execution_id_prefix: str | None = None,
        min_workflow_step: int | None = None,
        max_workflow_step: int | None = None,
        function_name: str | list[str] | None = None,
        function_name_prefix: str | None = None,
        function_call_id: str | list[str] | None = None,
        function_call_id_prefix: str | None = None,
        function_input: str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference | Sequence[str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference] | None = None,
        external_id_prefix: str | None = None,
        space: str | list[str] | None = None,
        limit: int = DEFAULT_LIMIT_READ,
        filter: dm.Filter | None = None,
    ) -> dm.aggregations.AggregatedNumberedValue: ...

    @overload
    def aggregate(
        self,
        aggregate: SequenceNotStr[Aggregations | dm.aggregations.MetricAggregation],
        group_by: None = None,
        property: TaskDispatcherOutputFields | SequenceNotStr[TaskDispatcherOutputFields] | None = None,
        query: str | None = None,
        search_property: TaskDispatcherOutputTextFields | SequenceNotStr[TaskDispatcherOutputTextFields] | None = None,
        workflow_execution_id: str | list[str] | None = None,
        workflow_execution_id_prefix: str | None = None,
        min_workflow_step: int | None = None,
        max_workflow_step: int | None = None,
        function_name: str | list[str] | None = None,
        function_name_prefix: str | None = None,
        function_call_id: str | list[str] | None = None,
        function_call_id_prefix: str | None = None,
        function_input: str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference | Sequence[str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference] | None = None,
        external_id_prefix: str | None = None,
        space: str | list[str] | None = None,
        limit: int = DEFAULT_LIMIT_READ,
        filter: dm.Filter | None = None,
    ) -> list[dm.aggregations.AggregatedNumberedValue]: ...

    @overload
    def aggregate(
        self,
        aggregate: Aggregations
        | dm.aggregations.MetricAggregation
        | SequenceNotStr[Aggregations | dm.aggregations.MetricAggregation],
        group_by: TaskDispatcherOutputFields | SequenceNotStr[TaskDispatcherOutputFields],
        property: TaskDispatcherOutputFields | SequenceNotStr[TaskDispatcherOutputFields] | None = None,
        query: str | None = None,
        search_property: TaskDispatcherOutputTextFields | SequenceNotStr[TaskDispatcherOutputTextFields] | None = None,
        workflow_execution_id: str | list[str] | None = None,
        workflow_execution_id_prefix: str | None = None,
        min_workflow_step: int | None = None,
        max_workflow_step: int | None = None,
        function_name: str | list[str] | None = None,
        function_name_prefix: str | None = None,
        function_call_id: str | list[str] | None = None,
        function_call_id_prefix: str | None = None,
        function_input: str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference | Sequence[str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference] | None = None,
        external_id_prefix: str | None = None,
        space: str | list[str] | None = None,
        limit: int = DEFAULT_LIMIT_READ,
        filter: dm.Filter | None = None,
    ) -> InstanceAggregationResultList: ...

    def aggregate(
        self,
        aggregate: Aggregations
        | dm.aggregations.MetricAggregation
        | SequenceNotStr[Aggregations | dm.aggregations.MetricAggregation],
        group_by: TaskDispatcherOutputFields | SequenceNotStr[TaskDispatcherOutputFields] | None = None,
        property: TaskDispatcherOutputFields | SequenceNotStr[TaskDispatcherOutputFields] | None = None,
        query: str | None = None,
        search_property: TaskDispatcherOutputTextFields | SequenceNotStr[TaskDispatcherOutputTextFields] | None = None,
        workflow_execution_id: str | list[str] | None = None,
        workflow_execution_id_prefix: str | None = None,
        min_workflow_step: int | None = None,
        max_workflow_step: int | None = None,
        function_name: str | list[str] | None = None,
        function_name_prefix: str | None = None,
        function_call_id: str | list[str] | None = None,
        function_call_id_prefix: str | None = None,
        function_input: str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference | Sequence[str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference] | None = None,
        external_id_prefix: str | None = None,
        space: str | list[str] | None = None,
        limit: int = DEFAULT_LIMIT_READ,
        filter: dm.Filter | None = None,
    ) -> (
        dm.aggregations.AggregatedNumberedValue
        | list[dm.aggregations.AggregatedNumberedValue]
        | InstanceAggregationResultList
    ):
        """Aggregate data across task dispatcher outputs

        Args:
            aggregate: The aggregation to perform.
            group_by: The property to group by when doing the aggregation.
            property: The property to perform aggregation on.
            query: The query to search for in the text field.
            search_property: The text field to search in.
            workflow_execution_id: The workflow execution id to filter on.
            workflow_execution_id_prefix: The prefix of the workflow execution id to filter on.
            min_workflow_step: The minimum value of the workflow step to filter on.
            max_workflow_step: The maximum value of the workflow step to filter on.
            function_name: The function name to filter on.
            function_name_prefix: The prefix of the function name to filter on.
            function_call_id: The function call id to filter on.
            function_call_id_prefix: The prefix of the function call id to filter on.
            function_input: The function input to filter on.
            external_id_prefix: The prefix of the external ID to filter on.
            space: The space to filter on.
            limit: Maximum number of task dispatcher outputs to return. Defaults to 25.
                Set to -1, float("inf") or None to return all items.
            filter: (Advanced) If the filtering available in the above is not sufficient, you can write
                your own filtering which will be ANDed with the filter above.

        Returns:
            Aggregation results.

        Examples:

            Count task dispatcher outputs in space `my_space`:

                >>> from cognite.powerops.client._generated.v1 import PowerOpsModelsV1Client
                >>> client = PowerOpsModelsV1Client()
                >>> result = client.task_dispatcher_output.aggregate("count", space="my_space")

        """

        filter_ = _create_task_dispatcher_output_filter(
            self._view_id,
            workflow_execution_id,
            workflow_execution_id_prefix,
            min_workflow_step,
            max_workflow_step,
            function_name,
            function_name_prefix,
            function_call_id,
            function_call_id_prefix,
            function_input,
            external_id_prefix,
            space,
            filter,
        )
        return self._aggregate(
            aggregate=aggregate,
            group_by=group_by,  # type: ignore[arg-type]
            properties=property,  # type: ignore[arg-type]
            query=query,
            search_properties=search_property,  # type: ignore[arg-type]
            limit=limit,
            filter=filter_,
        )

    def histogram(
        self,
        property: TaskDispatcherOutputFields,
        interval: float,
        query: str | None = None,
        search_property: TaskDispatcherOutputTextFields | SequenceNotStr[TaskDispatcherOutputTextFields] | None = None,
        workflow_execution_id: str | list[str] | None = None,
        workflow_execution_id_prefix: str | None = None,
        min_workflow_step: int | None = None,
        max_workflow_step: int | None = None,
        function_name: str | list[str] | None = None,
        function_name_prefix: str | None = None,
        function_call_id: str | list[str] | None = None,
        function_call_id_prefix: str | None = None,
        function_input: str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference | Sequence[str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference] | None = None,
        external_id_prefix: str | None = None,
        space: str | list[str] | None = None,
        limit: int = DEFAULT_LIMIT_READ,
        filter: dm.Filter | None = None,
    ) -> dm.aggregations.HistogramValue:
        """Produces histograms for task dispatcher outputs

        Args:
            property: The property to use as the value in the histogram.
            interval: The interval to use for the histogram bins.
            query: The query to search for in the text field.
            search_property: The text field to search in.
            workflow_execution_id: The workflow execution id to filter on.
            workflow_execution_id_prefix: The prefix of the workflow execution id to filter on.
            min_workflow_step: The minimum value of the workflow step to filter on.
            max_workflow_step: The maximum value of the workflow step to filter on.
            function_name: The function name to filter on.
            function_name_prefix: The prefix of the function name to filter on.
            function_call_id: The function call id to filter on.
            function_call_id_prefix: The prefix of the function call id to filter on.
            function_input: The function input to filter on.
            external_id_prefix: The prefix of the external ID to filter on.
            space: The space to filter on.
            limit: Maximum number of task dispatcher outputs to return.
                Defaults to 25. Set to -1, float("inf") or None to return all items.
            filter: (Advanced) If the filtering available in the above is not sufficient,
                you can write your own filtering which will be ANDed with the filter above.

        Returns:
            Bucketed histogram results.

        """
        filter_ = _create_task_dispatcher_output_filter(
            self._view_id,
            workflow_execution_id,
            workflow_execution_id_prefix,
            min_workflow_step,
            max_workflow_step,
            function_name,
            function_name_prefix,
            function_call_id,
            function_call_id_prefix,
            function_input,
            external_id_prefix,
            space,
            filter,
        )
        return self._histogram(
            property,
            interval,
            query,
            search_property,  # type: ignore[arg-type]
            limit,
            filter_,
        )

    def select(self) -> TaskDispatcherOutputQuery:
        """Start selecting from task dispatcher outputs."""
        return TaskDispatcherOutputQuery(self._client)

    def _query(
        self,
        filter_: dm.Filter | None,
        limit: int,
        retrieve_connections: Literal["skip", "identifier", "full"],
        sort: list[InstanceSort] | None = None,
    ) -> list[dict[str, Any]]:
        builder = QueryBuilder()
        factory = QueryStepFactory(builder.create_name, view_id=self._view_id, edge_connection_property="end_node")
        builder.append(factory.root(
            filter=filter_,
            sort=sort,
            limit=limit,
            has_container_fields=True,
        ))
        builder.extend(
            factory.from_edge(
                Alert._view_id,
                "outwards",
                ViewPropertyId(self._view_id, "alerts"),
                include_end_node=retrieve_connections == "full",
                has_container_fields=True,
            )
        )
        builder.extend(
            factory.from_edge(
                FunctionInput._view_id,
                "outwards",
                ViewPropertyId(self._view_id, "processSubTasks"),
                include_end_node=retrieve_connections == "full",
                has_container_fields=True,
            )
        )
        if retrieve_connections == "full":
            builder.extend(
                factory.from_direct_relation(
                    TaskDispatcherInput._view_id,
                    ViewPropertyId(self._view_id, "functionInput"),
                    has_container_fields=True,
                )
            )
        unpack_edges: Literal["skip", "identifier"] = "identifier" if retrieve_connections == "identifier" else "skip"
        builder.execute_query(self._client, remove_not_connected=True if unpack_edges == "skip" else False)
        return QueryUnpacker(builder, edges=unpack_edges).unpack()


    def list(
        self,
        workflow_execution_id: str | list[str] | None = None,
        workflow_execution_id_prefix: str | None = None,
        min_workflow_step: int | None = None,
        max_workflow_step: int | None = None,
        function_name: str | list[str] | None = None,
        function_name_prefix: str | None = None,
        function_call_id: str | list[str] | None = None,
        function_call_id_prefix: str | None = None,
        function_input: str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference | Sequence[str | tuple[str, str] | dm.NodeId | dm.DirectRelationReference] | None = None,
        external_id_prefix: str | None = None,
        space: str | list[str] | None = None,
        limit: int = DEFAULT_LIMIT_READ,
        filter: dm.Filter | None = None,
        sort_by: TaskDispatcherOutputFields | Sequence[TaskDispatcherOutputFields] | None = None,
        direction: Literal["ascending", "descending"] = "ascending",
        sort: InstanceSort | list[InstanceSort] | None = None,
        retrieve_connections: Literal["skip", "identifier", "full"] = "skip",
    ) -> TaskDispatcherOutputList:
        """List/filter task dispatcher outputs

        Args:
            workflow_execution_id: The workflow execution id to filter on.
            workflow_execution_id_prefix: The prefix of the workflow execution id to filter on.
            min_workflow_step: The minimum value of the workflow step to filter on.
            max_workflow_step: The maximum value of the workflow step to filter on.
            function_name: The function name to filter on.
            function_name_prefix: The prefix of the function name to filter on.
            function_call_id: The function call id to filter on.
            function_call_id_prefix: The prefix of the function call id to filter on.
            function_input: The function input to filter on.
            external_id_prefix: The prefix of the external ID to filter on.
            space: The space to filter on.
            limit: Maximum number of task dispatcher outputs to return.
                Defaults to 25. Set to -1, float("inf") or None to return all items.
            filter: (Advanced) If the filtering available in the above is not sufficient,
                you can write your own filtering which will be ANDed with the filter above.
            sort_by: The property to sort by.
            direction: The direction to sort by, either 'ascending' or 'descending'.
            sort: (Advanced) If sort_by and direction are not sufficient, you can write your own sorting.
                This will override the sort_by and direction. This allowos you to sort by multiple fields and
                specify the direction for each field as well as how to handle null values.
            retrieve_connections: Whether to retrieve `function_input`, `alerts` and `process_sub_tasks` for the task
            dispatcher outputs. Defaults to 'skip'.'skip' will not retrieve any connections, 'identifier' will only
            retrieve the identifier of the connected items, and 'full' will retrieve the full connected items.

        Returns:
            List of requested task dispatcher outputs

        Examples:

            List task dispatcher outputs and limit to 5:

                >>> from cognite.powerops.client._generated.v1 import PowerOpsModelsV1Client
                >>> client = PowerOpsModelsV1Client()
                >>> task_dispatcher_outputs = client.task_dispatcher_output.list(limit=5)

        """
        filter_ = _create_task_dispatcher_output_filter(
            self._view_id,
            workflow_execution_id,
            workflow_execution_id_prefix,
            min_workflow_step,
            max_workflow_step,
            function_name,
            function_name_prefix,
            function_call_id,
            function_call_id_prefix,
            function_input,
            external_id_prefix,
            space,
            filter,
        )
        sort_input =  self._create_sort(sort_by, direction, sort)  # type: ignore[arg-type]
        if retrieve_connections == "skip":
            return self._list(limit=limit,  filter=filter_, sort=sort_input)
        values = self._query(filter_, limit, retrieve_connections, sort_input)
        return self._class_list(instantiate_classes(self._class_type, values, "list"))
