orchestration.py

import datetime
import warnings
from contextlib import AsyncExitStack
from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Union
from uuid import UUID

import httpcore
import httpx
import pendulum
import pydantic
from asgi_lifespan import LifespanManager
from fastapi import FastAPI, status

import prefect
import prefect.exceptions
import prefect.server.schemas as schemas
import prefect.settings
import prefect.states
from prefect._internal.compatibility.deprecated import deprecated_callable
from prefect.client.schemas import FlowRun, OrchestrationResult, TaskRun
from prefect.deprecated.data_documents import DataDocument
from prefect.logging import get_logger
from prefect.server.schemas.actions import (
    FlowRunNotificationPolicyCreate,
    LogCreate,
    WorkQueueCreate,
    WorkQueueUpdate,
)
from prefect.server.schemas.core import (
    BlockDocument,
    BlockSchema,
    BlockType,
    FlowRunNotificationPolicy,
    QueueFilter,
    WorkPool,
    WorkQueue,
)
from prefect.server.schemas.filters import (
    FlowRunNotificationPolicyFilter,
    LogFilter,
    WorkPoolFilter,
    WorkQueueFilter,
)
from prefect.server.schemas.responses import WorkerFlowRunResponse
from prefect.settings import (
    PREFECT_API_DATABASE_CONNECTION_URL,
    PREFECT_API_ENABLE_HTTP2,
    PREFECT_API_KEY,
    PREFECT_API_REQUEST_TIMEOUT,
    PREFECT_API_TLS_INSECURE_SKIP_VERIFY,
    PREFECT_API_URL,
    PREFECT_CLOUD_API_URL,
)
from prefect.utilities.collections import AutoEnum

if TYPE_CHECKING:
    from prefect.flows import Flow
    from prefect.tasks import Task

from prefect.client.base import PrefectHttpxClient, app_lifespan_context


class ServerType(AutoEnum):
    EPHEMERAL = AutoEnum.auto()
    SERVER = AutoEnum.auto()
    CLOUD = AutoEnum.auto()


def get_client(httpx_settings: dict = None) -> "PrefectClient":
    """
    Retrieve a HTTP client for communicating with the Prefect REST API.

    The client must be context managed; for example:

    ```python
    async with get_client() as client:
        await client.hello()
    ```
    """
    ctx = prefect.context.get_settings_context()
    api = PREFECT_API_URL.value()
    if not api:
        # create an ephemeral API if none was provided
        from prefect.server.api.server import create_app

        api = create_app(ctx.settings, ephemeral=True)

    return PrefectClient(
        api,
        api_key=PREFECT_API_KEY.value(),
        httpx_settings=httpx_settings,
    )


class PrefectClient:
    """
    An asynchronous client for interacting with the [Prefect REST API](/api-ref/rest-api/).

    Args:
        api: the REST API URL or FastAPI application to connect to
        api_key: An optional API key for authentication.
        api_version: The API version this client is compatible with.
        httpx_settings: An optional dictionary of settings to pass to the underlying
            `httpx.AsyncClient`

    Examples:

        Say hello to a Prefect REST API

        <div class="terminal">
        ```
        >>> async with get_client() as client:
        >>>     response = await client.hello()
        >>>
        >>> print(response.json())
        👋
        ```
        </div>
    """

    def __init__(
        self,
        api: Union[str, FastAPI],
        *,
        api_key: str = None,
        api_version: str = None,
        httpx_settings: dict = None,
    ) -> None:
        httpx_settings = httpx_settings.copy() if httpx_settings else {}
        httpx_settings.setdefault("headers", {})

        if PREFECT_API_TLS_INSECURE_SKIP_VERIFY:
            httpx_settings.setdefault("verify", False)

        if api_version is None:
            # deferred import to avoid importing the entire server unless needed
            from prefect.server.api.server import SERVER_API_VERSION

            api_version = SERVER_API_VERSION
        httpx_settings["headers"].setdefault("X-PREFECT-API-VERSION", api_version)
        if api_key:
            httpx_settings["headers"].setdefault("Authorization", f"Bearer {api_key}")

        # Context management
        self._exit_stack = AsyncExitStack()
        self._ephemeral_app: Optional[FastAPI] = None
        self.manage_lifespan = True
        self.server_type: ServerType

        # Only set if this client started the lifespan of the application
        self._ephemeral_lifespan: Optional[LifespanManager] = None

        self._closed = False
        self._started = False

        # Connect to an external application
        if isinstance(api, str):
            if httpx_settings.get("app"):
                raise ValueError(
                    "Invalid httpx settings: `app` cannot be set when providing an "
                    "api url. `app` is only for use with ephemeral instances. Provide "
                    "it as the `api` parameter instead."
                )
            httpx_settings.setdefault("base_url", api)

            # See https://www.python-httpx.org/advanced/#pool-limit-configuration
            httpx_settings.setdefault(
                "limits",
                httpx.Limits(
                    # We see instability when allowing the client to open many connections at once.
                    # Limiting concurrency results in more stable performance.
                    max_connections=16,
                    max_keepalive_connections=8,
                    # The Prefect Cloud LB will keep connections alive for 30s.
                    # Only allow the client to keep connections alive for 25s.
                    keepalive_expiry=25,
                ),
            )

            # See https://www.python-httpx.org/http2/
            # Enabling HTTP/2 support on the client does not necessarily mean that your requests
            # and responses will be transported over HTTP/2, since both the client and the server
            # need to support HTTP/2. If you connect to a server that only supports HTTP/1.1 the
            # client will use a standard HTTP/1.1 connection instead.
            httpx_settings.setdefault("http2", PREFECT_API_ENABLE_HTTP2.value())

            self.server_type = (
                ServerType.CLOUD
                if api.startswith(PREFECT_CLOUD_API_URL.value())
                else ServerType.SERVER
            )

        # Connect to an in-process application
        elif isinstance(api, FastAPI):
            self._ephemeral_app = api
            self.server_type = ServerType.EPHEMERAL
            httpx_settings.setdefault("app", self._ephemeral_app)
            httpx_settings.setdefault("base_url", "http://ephemeral-prefect/api")

        else:
            raise TypeError(
                f"Unexpected type {type(api).__name__!r} for argument `api`. Expected"
                " 'str' or 'FastAPI'"
            )

        # See https://www.python-httpx.org/advanced/#timeout-configuration
        httpx_settings.setdefault(
            "timeout",
            httpx.Timeout(
                connect=PREFECT_API_REQUEST_TIMEOUT.value(),
                read=PREFECT_API_REQUEST_TIMEOUT.value(),
                write=PREFECT_API_REQUEST_TIMEOUT.value(),
                pool=PREFECT_API_REQUEST_TIMEOUT.value(),
            ),
        )

        self._client = PrefectHttpxClient(
            **httpx_settings,
        )

        # See https://www.python-httpx.org/advanced/#custom-transports
        #
        # If we're using an HTTP/S client (not the ephemeral client), adjust the
        # transport to add retries _after_ it is instantiated. If we alter the transport
        # before instantiation, the transport will not be aware of proxies unless we
        # reproduce all of the logic to make it so.
        #
        # Only alter the transport to set our default of 3 retries, don't modify any
        # transport a user may have provided via httpx_settings.
        #
        # Making liberal use of getattr and isinstance checks here to avoid any
        # surprises if the internals of httpx or httpcore change on us
        if isinstance(api, str) and not httpx_settings.get("transport"):
            transport_for_url = getattr(self._client, "_transport_for_url", None)
            if callable(transport_for_url):
                server_transport = transport_for_url(httpx.URL(api))
                if isinstance(server_transport, httpx.AsyncHTTPTransport):
                    pool = getattr(server_transport, "_pool", None)
                    if isinstance(pool, httpcore.AsyncConnectionPool):
                        pool._retries = 3

        self.logger = get_logger("client")

    @property
    def api_url(self) -> httpx.URL:
        """
        Get the base URL for the API.
        """
        return self._client.base_url

    # API methods ----------------------------------------------------------------------

    async def api_healthcheck(self) -> Optional[Exception]:
        """
        Attempts to connect to the API and returns the encountered exception if not
        successful.

        If successful, returns `None`.
        """
        try:
            await self._client.get("/health")
            return None
        except Exception as exc:
            return exc

    async def hello(self) -> httpx.Response:
        """
        Send a GET request to /hello for testing purposes.
        """
        return await self._client.get("/hello")

    async def create_flow(self, flow: "Flow") -> UUID:
        """
        Create a flow in the Prefect API.

        Args:
            flow: a [Flow][prefect.flows.Flow] object

        Raises:
            httpx.RequestError: if a flow was not created for any reason

        Returns:
            the ID of the flow in the backend
        """
        return await self.create_flow_from_name(flow.name)

    async def create_flow_from_name(self, flow_name: str) -> UUID:
        """
        Create a flow in the Prefect API.

        Args:
            flow_name: the name of the new flow

        Raises:
            httpx.RequestError: if a flow was not created for any reason

        Returns:
            the ID of the flow in the backend
        """
        flow_data = schemas.actions.FlowCreate(name=flow_name)
        response = await self._client.post(
            "/flows/", json=flow_data.dict(json_compatible=True)
        )

        flow_id = response.json().get("id")
        if not flow_id:
            raise httpx.RequestError(f"Malformed response: {response}")

        # Return the id of the created flow
        return UUID(flow_id)

    async def read_flow(self, flow_id: UUID) -> schemas.core.Flow:
        """
        Query the Prefect API for a flow by id.

        Args:
            flow_id: the flow ID of interest

        Returns:
            a [Flow model][prefect.server.schemas.core.Flow] representation of the flow
        """
        response = await self._client.get(f"/flows/{flow_id}")
        return schemas.core.Flow.parse_obj(response.json())

    async def read_flows(
        self,
        *,
        flow_filter: schemas.filters.FlowFilter = None,
        flow_run_filter: schemas.filters.FlowRunFilter = None,
        task_run_filter: schemas.filters.TaskRunFilter = None,
        deployment_filter: schemas.filters.DeploymentFilter = None,
        work_pool_filter: schemas.filters.WorkPoolFilter = None,
        work_queue_filter: schemas.filters.WorkQueueFilter = None,
        sort: schemas.sorting.FlowSort = None,
        limit: int = None,
        offset: int = 0,
    ) -> List[schemas.core.Flow]:
        """
        Query the Prefect API for flows. Only flows matching all criteria will
        be returned.

        Args:
            flow_filter: filter criteria for flows
            flow_run_filter: filter criteria for flow runs
            task_run_filter: filter criteria for task runs
            deployment_filter: filter criteria for deployments
            work_pool_filter: filter criteria for work pools
            work_queue_filter: filter criteria for work pool queues
            sort: sort criteria for the flows
            limit: limit for the flow query
            offset: offset for the flow query

        Returns:
            a list of Flow model representations of the flows
        """
        body = {
            "flows": flow_filter.dict(json_compatible=True) if flow_filter else None,
            "flow_runs": (
                flow_run_filter.dict(json_compatible=True) if flow_run_filter else None
            ),
            "task_runs": (
                task_run_filter.dict(json_compatible=True) if task_run_filter else None
            ),
            "deployments": (
                deployment_filter.dict(json_compatible=True)
                if deployment_filter
                else None
            ),
            "work_pools": (
                work_pool_filter.dict(json_compatible=True)
                if work_pool_filter
                else None
            ),
            "work_queues": (
                work_queue_filter.dict(json_compatible=True)
                if work_queue_filter
                else None
            ),
            "sort": sort,
            "limit": limit,
            "offset": offset,
        }

        response = await self._client.post(f"/flows/filter", json=body)
        return pydantic.parse_obj_as(List[schemas.core.Flow], response.json())

    async def read_flow_by_name(
        self,
        flow_name: str,
    ) -> schemas.core.Flow:
        """
        Query the Prefect API for a flow by name.

        Args:
            flow_name: the name of a flow

        Returns:
            a fully hydrated Flow model
        """
        response = await self._client.get(f"/flows/name/{flow_name}")
        return schemas.core.Flow.parse_obj(response.json())

    async def create_flow_run_from_deployment(
        self,
        deployment_id: UUID,
        *,
        parameters: Dict[str, Any] = None,
        context: dict = None,
        state: prefect.states.State = None,
        name: str = None,
        tags: Iterable[str] = None,
        idempotency_key: str = None,
        parent_task_run_id: UUID = None,
    ) -> FlowRun:
        """
        Create a flow run for a deployment.

        Args:
            deployment_id: The deployment ID to create the flow run from
            parameters: Parameter overrides for this flow run. Merged with the
                deployment defaults
            context: Optional run context data
            state: The initial state for the run. If not provided, defaults to
                `Scheduled` for now. Should always be a `Scheduled` type.
            name: An optional name for the flow run. If not provided, the server will
                generate a name.
            tags: An optional iterable of tags to apply to the flow run; these tags
                are merged with the deployment's tags.
            idempotency_key: Optional idempotency key for creation of the flow run.
                If the key matches the key of an existing flow run, the existing run will
                be returned instead of creating a new one.
            parent_task_run_id: if a subflow run is being created, the placeholder task
                run identifier in the parent flow

        Raises:
            httpx.RequestError: if the Prefect API does not successfully create a run for any reason

        Returns:
            The flow run model
        """
        parameters = parameters or {}
        context = context or {}
        state = state or prefect.states.Scheduled()
        tags = tags or []

        flow_run_create = schemas.actions.DeploymentFlowRunCreate(
            parameters=parameters,
            context=context,
            state=state.to_state_create(),
            tags=tags,
            name=name,
            idempotency_key=idempotency_key,
            parent_task_run_id=parent_task_run_id,
        )

        response = await self._client.post(
            f"/deployments/{deployment_id}/create_flow_run",
            json=flow_run_create.dict(json_compatible=True),
        )
        return FlowRun.parse_obj(response.json())

    async def create_flow_run(
        self,
        flow: "Flow",
        name: str = None,
        parameters: Dict[str, Any] = None,
        context: dict = None,
        tags: Iterable[str] = None,
        parent_task_run_id: UUID = None,
        state: "prefect.states.State" = None,
    ) -> FlowRun:
        """
        Create a flow run for a flow.

        Args:
            flow: The flow model to create the flow run for
            name: An optional name for the flow run
            parameters: Parameter overrides for this flow run.
            context: Optional run context data
            tags: a list of tags to apply to this flow run
            parent_task_run_id: if a subflow run is being created, the placeholder task
                run identifier in the parent flow
            state: The initial state for the run. If not provided, defaults to
                `Scheduled` for now. Should always be a `Scheduled` type.

        Raises:
            httpx.RequestError: if the Prefect API does not successfully create a run for any reason

        Returns:
            The flow run model
        """
        parameters = parameters or {}
        context = context or {}

        if state is None:
            state = prefect.states.Pending()

        # Retrieve the flow id
        flow_id = await self.create_flow(flow)

        flow_run_create = schemas.actions.FlowRunCreate(
            flow_id=flow_id,
            flow_version=flow.version,
            name=name,
            parameters=parameters,
            context=context,
            tags=list(tags or []),
            parent_task_run_id=parent_task_run_id,
            state=state.to_state_create(),
            empirical_policy=schemas.core.FlowRunPolicy(
                retries=flow.retries,
                retry_delay=flow.retry_delay_seconds,
            ),
        )

        flow_run_create_json = flow_run_create.dict(json_compatible=True)
        response = await self._client.post("/flow_runs/", json=flow_run_create_json)
        flow_run = FlowRun.parse_obj(response.json())

        # Restore the parameters to the local objects to retain expectations about
        # Python objects
        flow_run.parameters = parameters

        return flow_run

    async def update_flow_run(
        self,
        flow_run_id: UUID,
        flow_version: Optional[str] = None,
        parameters: Optional[dict] = None,
        name: Optional[str] = None,
        tags: Optional[Iterable[str]] = None,
        empirical_policy: Optional[schemas.core.FlowRunPolicy] = None,
        infrastructure_pid: Optional[str] = None,
    ) -> httpx.Response:
        """
        Update a flow run's details.

        Args:
            flow_run_id: The identifier for the flow run to update.
            flow_version: A new version string for the flow run.
            parameters: A dictionary of parameter values for the flow run. This will not
                be merged with any existing parameters.
            name: A new name for the flow run.
            empirical_policy: A new flow run orchestration policy. This will not be
                merged with any existing policy.
            tags: An iterable of new tags for the flow run. These will not be merged with
                any existing tags.
            infrastructure_pid: The id of flow run as returned by an
                infrastructure block.

        Returns:
            an `httpx.Response` object from the PATCH request
        """
        params = {}
        if flow_version is not None:
            params["flow_version"] = flow_version
        if parameters is not None:
            params["parameters"] = parameters
        if name is not None:
            params["name"] = name
        if tags is not None:
            params["tags"] = tags
        if empirical_policy is not None:
            params["empirical_policy"] = empirical_policy
        if infrastructure_pid:
            params["infrastructure_pid"] = infrastructure_pid

        flow_run_data = schemas.actions.FlowRunUpdate(**params)

        return await self._client.patch(
            f"/flow_runs/{flow_run_id}",
            json=flow_run_data.dict(json_compatible=True, exclude_unset=True),
        )

    async def delete_flow_run(
        self,
        flow_run_id: UUID,
    ) -> None:
        """
        Delete a flow run by UUID.

        Args:
            flow_run_id: The flow run UUID of interest.
        Raises:
            prefect.exceptions.ObjectNotFound: If request returns 404
            httpx.RequestError: If requests fails
        """
        try:
            await self._client.delete(f"/flow_runs/{flow_run_id}"),
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

    async def create_concurrency_limit(
        self,
        tag: str,
        concurrency_limit: int,
    ) -> UUID:
        """
        Create a tag concurrency limit in the Prefect API. These limits govern concurrently
        running tasks.

        Args:
            tag: a tag the concurrency limit is applied to
            concurrency_limit: the maximum number of concurrent task runs for a given tag

        Raises:
            httpx.RequestError: if the concurrency limit was not created for any reason

        Returns:
            the ID of the concurrency limit in the backend
        """

        concurrency_limit_create = schemas.actions.ConcurrencyLimitCreate(
            tag=tag,
            concurrency_limit=concurrency_limit,
        )
        response = await self._client.post(
            "/concurrency_limits/",
            json=concurrency_limit_create.dict(json_compatible=True),
        )

        concurrency_limit_id = response.json().get("id")

        if not concurrency_limit_id:
            raise httpx.RequestError(f"Malformed response: {response}")

        return UUID(concurrency_limit_id)

    async def read_concurrency_limit_by_tag(
        self,
        tag: str,
    ):
        """
        Read the concurrency limit set on a specific tag.

        Args:
            tag: a tag the concurrency limit is applied to

        Raises:
            prefect.exceptions.ObjectNotFound: If request returns 404
            httpx.RequestError: if the concurrency limit was not created for any reason

        Returns:
            the concurrency limit set on a specific tag
        """
        try:
            response = await self._client.get(
                f"/concurrency_limits/tag/{tag}",
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

        concurrency_limit_id = response.json().get("id")

        if not concurrency_limit_id:
            raise httpx.RequestError(f"Malformed response: {response}")

        concurrency_limit = schemas.core.ConcurrencyLimit.parse_obj(response.json())
        return concurrency_limit

    async def read_concurrency_limits(
        self,
        limit: int,
        offset: int,
    ):
        """
        Lists concurrency limits set on task run tags.

        Args:
            limit: the maximum number of concurrency limits returned
            offset: the concurrency limit query offset

        Returns:
            a list of concurrency limits
        """

        body = {
            "limit": limit,
            "offset": offset,
        }

        response = await self._client.post("/concurrency_limits/filter", json=body)
        return pydantic.parse_obj_as(
            List[schemas.core.ConcurrencyLimit], response.json()
        )

    async def reset_concurrency_limit_by_tag(
        self,
        tag: str,
        slot_override: Optional[List[Union[UUID, str]]] = None,
    ):
        """
        Resets the concurrency limit slots set on a specific tag.

        Args:
            tag: a tag the concurrency limit is applied to
            slot_override: a list of task run IDs that are currently using a
                concurrency slot, please check that any task run IDs included in
                `slot_override` are currently running, otherwise those concurrency
                slots will never be released.

        Raises:
            prefect.exceptions.ObjectNotFound: If request returns 404
            httpx.RequestError: If request fails

        """
        if slot_override is not None:
            slot_override = [str(slot) for slot in slot_override]

        try:
            await self._client.post(
                f"/concurrency_limits/tag/{tag}/reset",
                json=dict(slot_override=slot_override),
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

    async def delete_concurrency_limit_by_tag(
        self,
        tag: str,
    ):
        """
        Delete the concurrency limit set on a specific tag.

        Args:
            tag: a tag the concurrency limit is applied to

        Raises:
            prefect.exceptions.ObjectNotFound: If request returns 404
            httpx.RequestError: If request fails

        """
        try:
            await self._client.delete(
                f"/concurrency_limits/tag/{tag}",
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

    async def create_work_queue(
        self,
        name: str,
        tags: Optional[List[str]] = None,
        description: Optional[str] = None,
        is_paused: Optional[bool] = None,
        concurrency_limit: Optional[int] = None,
        priority: Optional[int] = None,
        work_pool_name: Optional[str] = None,
    ) -> schemas.core.WorkQueue:
        """
        Create a work queue.

        Args:
            name: a unique name for the work queue
            tags: DEPRECATED: an optional list of tags to filter on; only work scheduled with these tags
                will be included in the queue. This option will be removed on 2023-02-23.
            description: An optional description for the work queue.
            is_paused: Whether or not the work queue is paused.
            concurrency_limit: An optional concurrency limit for the work queue.
            priority: The queue's priority. Lower values are higher priority (1 is the highest).
            work_pool_name: The name of the work pool to use for this queue.

        Raises:
            prefect.exceptions.ObjectAlreadyExists: If request returns 409
            httpx.RequestError: If request fails

        Returns:
            UUID: The UUID of the newly created workflow
        """
        if tags:
            warnings.warn(
                (
                    "The use of tags for creating work queue filters is deprecated."
                    " This option will be removed on 2023-02-23."
                ),
                DeprecationWarning,
            )
            filter = QueueFilter(tags=tags)
        else:
            filter = None
        create_model = WorkQueueCreate(name=name, filter=filter)
        if description is not None:
            create_model.description = description
        if is_paused is not None:
            create_model.is_paused = is_paused
        if concurrency_limit is not None:
            create_model.concurrency_limit = concurrency_limit
        if priority is not None:
            create_model.priority = priority
        data = WorkQueueCreate(name=name, filter=filter).dict(json_compatible=True)
        try:
            if work_pool_name is not None:
                response = await self._client.post(
                    f"/work_pools/{work_pool_name}/queues", json=data
                )
            else:
                response = await self._client.post("/work_queues/", json=data)
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_409_CONFLICT:
                raise prefect.exceptions.ObjectAlreadyExists(http_exc=e) from e
            elif e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise
        return schemas.core.WorkQueue.parse_obj(response.json())

    async def read_work_queue_by_name(
        self,
        name: str,
        work_pool_name: Optional[str] = None,
    ) -> schemas.core.WorkQueue:
        """
        Read a work queue by name.

        Args:
            name (str): a unique name for the work queue
            work_pool_name (str, optional): the name of the work pool
                the queue belongs to.

        Raises:
            prefect.exceptions.ObjectNotFound: if no work queue is found
            httpx.HTTPStatusError: other status errors

        Returns:
            schemas.core.WorkQueue: a work queue API object
        """
        try:
            if work_pool_name is not None:
                response = await self._client.get(
                    f"/work_pools/{work_pool_name}/queues/{name}"
                )
            else:
                response = await self._client.get(f"/work_queues/name/{name}")
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

        return schemas.core.WorkQueue.parse_obj(response.json())

    async def update_work_queue(self, id: UUID, **kwargs):
        """
        Update properties of a work queue.

        Args:
            id: the ID of the work queue to update
            **kwargs: the fields to update

        Raises:
            ValueError: if no kwargs are provided
            prefect.exceptions.ObjectNotFound: if request returns 404
            httpx.RequestError: if the request fails

        """
        if not kwargs:
            raise ValueError("No fields provided to update.")

        data = WorkQueueUpdate(**kwargs).dict(json_compatible=True, exclude_unset=True)
        try:
            await self._client.patch(f"/work_queues/{id}", json=data)
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

    async def get_runs_in_work_queue(
        self,
        id: UUID,
        limit: int = 10,
        scheduled_before: datetime.datetime = None,
    ) -> List[FlowRun]:
        """
        Read flow runs off a work queue.

        Args:
            id: the id of the work queue to read from
            limit: a limit on the number of runs to return
            scheduled_before: a timestamp; only runs scheduled before this time will be returned.
                Defaults to now.

        Raises:
            prefect.exceptions.ObjectNotFound: If request returns 404
            httpx.RequestError: If request fails

        Returns:
            List[FlowRun]: a list of FlowRun objects read from the queue
        """
        if scheduled_before is None:
            scheduled_before = pendulum.now()

        try:
            response = await self._client.post(
                f"/work_queues/{id}/get_runs",
                json={
                    "limit": limit,
                    "scheduled_before": scheduled_before.isoformat(),
                },
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise
        return pydantic.parse_obj_as(List[FlowRun], response.json())

    async def read_work_queue(
        self,
        id: UUID,
    ) -> schemas.core.WorkQueue:
        """
        Read a work queue.

        Args:
            id: the id of the work queue to load

        Raises:
            prefect.exceptions.ObjectNotFound: If request returns 404
            httpx.RequestError: If request fails

        Returns:
            WorkQueue: an instantiated WorkQueue object
        """
        try:
            response = await self._client.get(f"/work_queues/{id}")
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise
        return schemas.core.WorkQueue.parse_obj(response.json())

    async def match_work_queues(
        self,
        prefixes: List[str],
    ) -> List[schemas.core.WorkQueue]:
        """
        Query the Prefect API for work queues with names with a specific prefix.

        Args:
            prefixes: a list of strings used to match work queue name prefixes

        Returns:
            a list of WorkQueue model representations
                of the work queues
        """
        page_length = 100
        current_page = 0
        work_queues = []

        while True:
            new_queues = await self.read_work_queues(
                offset=current_page * page_length,
                limit=page_length,
                work_queue_filter=schemas.filters.WorkQueueFilter(
                    name=schemas.filters.WorkQueueFilterName(startswith_=prefixes)
                ),
            )
            if not new_queues:
                break
            work_queues += new_queues
            current_page += 1

        return work_queues

    async def delete_work_queue_by_id(
        self,
        id: UUID,
    ):
        """
        Delete a work queue by its ID.

        Args:
            id: the id of the work queue to delete

        Raises:
            prefect.exceptions.ObjectNotFound: If request returns 404
            httpx.RequestError: If requests fails
        """
        try:
            await self._client.delete(
                f"/work_queues/{id}",
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

    async def create_block_type(
        self, block_type: schemas.actions.BlockTypeCreate
    ) -> BlockType:
        """
        Create a block type in the Prefect API.
        """
        try:
            response = await self._client.post(
                "/block_types/",
                json=block_type.dict(
                    json_compatible=True, exclude_unset=True, exclude={"id"}
                ),
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_409_CONFLICT:
                raise prefect.exceptions.ObjectAlreadyExists(http_exc=e) from e
            else:
                raise
        return BlockType.parse_obj(response.json())

    async def create_block_schema(
        self, block_schema: schemas.actions.BlockSchemaCreate
    ) -> BlockSchema:
        """
        Create a block schema in the Prefect API.
        """
        try:
            response = await self._client.post(
                "/block_schemas/",
                json=block_schema.dict(
                    json_compatible=True,
                    exclude_unset=True,
                    exclude={"id", "block_type", "checksum"},
                ),
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_409_CONFLICT:
                raise prefect.exceptions.ObjectAlreadyExists(http_exc=e) from e
            else:
                raise
        return BlockSchema.parse_obj(response.json())

    async def create_block_document(
        self,
        block_document: Union[BlockDocument, schemas.actions.BlockDocumentCreate],
        include_secrets: bool = True,
    ) -> BlockDocument:
        """
        Create a block document in the Prefect API. This data is used to configure a
        corresponding Block.

        Args:
            include_secrets (bool): whether to include secret values
                on the stored Block, corresponding to Pydantic's `SecretStr` and
                `SecretBytes` fields. Note Blocks may not work as expected if
                this is set to `False`.
        """
        if isinstance(block_document, BlockDocument):
            block_document = schemas.actions.BlockDocumentCreate.parse_obj(
                block_document.dict(
                    json_compatible=True,
                    include_secrets=include_secrets,
                    exclude_unset=True,
                    exclude={"id", "block_schema", "block_type"},
                ),
            )

        try:
            response = await self._client.post(
                "/block_documents/",
                json=block_document.dict(
                    json_compatible=True,
                    include_secrets=include_secrets,
                    exclude_unset=True,
                    exclude={"id", "block_schema", "block_type"},
                ),
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_409_CONFLICT:
                raise prefect.exceptions.ObjectAlreadyExists(http_exc=e) from e
            else:
                raise
        return BlockDocument.parse_obj(response.json())

    async def update_block_document(
        self,
        block_document_id: UUID,
        block_document: schemas.actions.BlockDocumentUpdate,
    ):
        """
        Update a block document in the Prefect API.
        """
        try:
            await self._client.patch(
                f"/block_documents/{block_document_id}",
                json=block_document.dict(
                    json_compatible=True,
                    exclude_unset=True,
                    include={"data", "merge_existing_data", "block_schema_id"},
                    include_secrets=True,
                ),
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

    async def delete_block_document(self, block_document_id: UUID):
        """
        Delete a block document.
        """
        try:
            await self._client.delete(f"/block_documents/{block_document_id}")
        except httpx.HTTPStatusError as e:
            if e.response.status_code == 404:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

    async def read_block_type_by_slug(self, slug: str) -> BlockType:
        """
        Read a block type by its slug.
        """
        try:
            response = await self._client.get(f"/block_types/slug/{slug}")
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise
        return BlockType.parse_obj(response.json())

    async def read_block_schema_by_checksum(
        self, checksum: str, version: Optional[str] = None
    ) -> schemas.core.BlockSchema:
        """
        Look up a block schema checksum
        """
        try:
            url = f"/block_schemas/checksum/{checksum}"
            if version is not None:
                url = f"{url}?version={version}"
            response = await self._client.get(url)
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise
        return schemas.core.BlockSchema.parse_obj(response.json())

    async def update_block_type(
        self, block_type_id: UUID, block_type: schemas.actions.BlockTypeUpdate
    ):
        """
        Update a block document in the Prefect API.
        """
        try:
            await self._client.patch(
                f"/block_types/{block_type_id}",
                json=block_type.dict(
                    json_compatible=True,
                    exclude_unset=True,
                    include={
                        "logo_url",
                        "documentation_url",
                        "description",
                        "code_example",
                    },
                    include_secrets=True,
                ),
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

    async def delete_block_type(self, block_type_id: UUID):
        """
        Delete a block type.
        """
        try:
            await self._client.delete(f"/block_types/{block_type_id}")
        except httpx.HTTPStatusError as e:
            if e.response.status_code == 404:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            elif (
                e.response.status_code == status.HTTP_403_FORBIDDEN
                and e.response.json()["detail"]
                == "protected block types cannot be deleted."
            ):
                raise prefect.exceptions.ProtectedBlockError(
                    "Protected block types cannot be deleted."
                ) from e
            else:
                raise

    async def read_block_types(self) -> List[schemas.core.BlockType]:
        """
        Read all block types
        Raises:
            httpx.RequestError: if the block types were not found

        Returns:
            List of BlockTypes.
        """
        response = await self._client.post(f"/block_types/filter", json={})
        return pydantic.parse_obj_as(List[schemas.core.BlockType], response.json())

    async def read_block_schemas(self) -> List[schemas.core.BlockSchema]:
        """
        Read all block schemas
        Raises:
            httpx.RequestError: if a valid block schema was not found

        Returns:
            A BlockSchema.
        """
        response = await self._client.post(f"/block_schemas/filter", json={})
        return pydantic.parse_obj_as(List[schemas.core.BlockSchema], response.json())

    async def read_block_document(
        self,
        block_document_id: UUID,
        include_secrets: bool = True,
    ):
        """
        Read the block document with the specified ID.

        Args:
            block_document_id: the block document id
            include_secrets (bool): whether to include secret values
                on the Block, corresponding to Pydantic's `SecretStr` and
                `SecretBytes` fields. These fields are automatically obfuscated
                by Pydantic, but users can additionally choose not to receive
                their values from the API. Note that any business logic on the
                Block may not work if this is `False`.

        Raises:
            httpx.RequestError: if the block document was not found for any reason

        Returns:
            A block document or None.
        """
        try:
            response = await self._client.get(
                f"/block_documents/{block_document_id}",
                params=dict(include_secrets=include_secrets),
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise
        return BlockDocument.parse_obj(response.json())

    async def read_block_document_by_name(
        self,
        name: str,
        block_type_slug: str,
        include_secrets: bool = True,
    ):
        """
        Read the block document with the specified name that corresponds to a
        specific block type name.

        Args:
            name: The block document name.
            block_type_slug: The block type slug.
            include_secrets (bool): whether to include secret values
                on the Block, corresponding to Pydantic's `SecretStr` and
                `SecretBytes` fields. These fields are automatically obfuscated
                by Pydantic, but users can additionally choose not to receive
                their values from the API. Note that any business logic on the
                Block may not work if this is `False`.

        Raises:
            httpx.RequestError: if the block document was not found for any reason

        Returns:
            A block document or None.
        """
        try:
            response = await self._client.get(
                f"/block_types/slug/{block_type_slug}/block_documents/name/{name}",
                params=dict(include_secrets=include_secrets),
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise
        return BlockDocument.parse_obj(response.json())

    async def read_block_documents(
        self,
        block_schema_type: Optional[str] = None,
        offset: Optional[int] = None,
        limit: Optional[int] = None,
        include_secrets: bool = True,
    ):
        """
        Read block documents

        Args:
            block_schema_type: an optional block schema type
            offset: an offset
            limit: the number of blocks to return
            include_secrets (bool): whether to include secret values
                on the Block, corresponding to Pydantic's `SecretStr` and
                `SecretBytes` fields. These fields are automatically obfuscated
                by Pydantic, but users can additionally choose not to receive
                their values from the API. Note that any business logic on the
                Block may not work if this is `False`.

        Returns:
            A list of block documents
        """
        response = await self._client.post(
            "/block_documents/filter",
            json=dict(
                block_schema_type=block_schema_type,
                offset=offset,
                limit=limit,
                include_secrets=include_secrets,
            ),
        )
        return pydantic.parse_obj_as(List[BlockDocument], response.json())

    async def create_deployment(
        self,
        flow_id: UUID,
        name: str,
        version: str = None,
        schedule: schemas.schedules.SCHEDULE_TYPES = None,
        parameters: Dict[str, Any] = None,
        description: str = None,
        work_queue_name: str = None,
        work_pool_name: str = None,
        tags: List[str] = None,
        storage_document_id: UUID = None,
        manifest_path: str = None,
        path: str = None,
        entrypoint: str = None,
        infrastructure_document_id: UUID = None,
        infra_overrides: Dict[str, Any] = None,
        parameter_openapi_schema: dict = None,
        is_schedule_active: Optional[bool] = None,
    ) -> UUID:
        """
        Create a deployment.

        Args:
            flow_id: the flow ID to create a deployment for
            name: the name of the deployment
            version: an optional version string for the deployment
            schedule: an optional schedule to apply to the deployment
            tags: an optional list of tags to apply to the deployment
            storage_document_id: an reference to the storage block document
                used for the deployed flow
            infrastructure_document_id: an reference to the infrastructure block document
                to use for this deployment

        Raises:
            httpx.RequestError: if the deployment was not created for any reason

        Returns:
            the ID of the deployment in the backend
        """
        deployment_create = schemas.actions.DeploymentCreate(
            flow_id=flow_id,
            name=name,
            version=version,
            schedule=schedule,
            parameters=dict(parameters or {}),
            tags=list(tags or []),
            work_queue_name=work_queue_name,
            description=description,
            storage_document_id=storage_document_id,
            path=path,
            entrypoint=entrypoint,
            manifest_path=manifest_path,  # for backwards compat
            infrastructure_document_id=infrastructure_document_id,
            infra_overrides=infra_overrides or {},
            parameter_openapi_schema=parameter_openapi_schema,
            is_schedule_active=is_schedule_active,
        )

        if work_pool_name is not None:
            deployment_create.work_pool_name = work_pool_name

        # Exclude newer fields that are not set to avoid compatibility issues
        exclude = {
            field
            for field in ["work_pool_name", "work_queue_name"]
            if field not in deployment_create.__fields_set__
        }

        if deployment_create.is_schedule_active is None:
            exclude.add("is_schedule_active")

        json = deployment_create.dict(json_compatible=True, exclude=exclude)
        response = await self._client.post(
            "/deployments/",
            json=json,
        )
        deployment_id = response.json().get("id")
        if not deployment_id:
            raise httpx.RequestError(f"Malformed response: {response}")

        return UUID(deployment_id)

    async def update_deployment(
        self,
        deployment: schemas.core.Deployment,
        schedule: schemas.schedules.SCHEDULE_TYPES = None,
        is_schedule_active: bool = None,
    ):
        deployment_create = schemas.actions.DeploymentUpdate(
            version=deployment.version,
            schedule=schedule if schedule is not None else deployment.schedule,
            is_schedule_active=(
                is_schedule_active
                if is_schedule_active is not None
                else deployment.is_schedule_active
            ),
            description=deployment.description,
            work_queue_name=deployment.work_queue_name,
            tags=deployment.tags,
            manifest_path=deployment.manifest_path,
            path=deployment.path,
            entrypoint=deployment.entrypoint,
            parameters=deployment.parameters,
            storage_document_id=deployment.storage_document_id,
            infrastructure_document_id=deployment.infrastructure_document_id,
            infra_overrides=deployment.infra_overrides,
        )

        response = await self._client.patch(
            f"/deployments/{deployment.id}",
            json=deployment_create.dict(json_compatible=True),
        )

    async def _create_deployment_from_schema(
        self, schema: schemas.actions.DeploymentCreate
    ) -> UUID:
        """
        Create a deployment from a prepared `DeploymentCreate` schema.
        """
        # TODO: We are likely to remove this method once we have considered the
        #       packaging interface for deployments further.
        response = await self._client.post(
            "/deployments/", json=schema.dict(json_compatible=True)
        )
        deployment_id = response.json().get("id")
        if not deployment_id:
            raise httpx.RequestError(f"Malformed response: {response}")

        return UUID(deployment_id)

    async def read_deployment(
        self,
        deployment_id: UUID,
    ) -> schemas.responses.DeploymentResponse:
        """
        Query the Prefect API for a deployment by id.

        Args:
            deployment_id: the deployment ID of interest

        Returns:
            a [Deployment model][prefect.server.schemas.core.Deployment] representation of the deployment
        """
        response = await self._client.get(f"/deployments/{deployment_id}")
        return schemas.responses.DeploymentResponse.parse_obj(response.json())

    async def read_deployment_by_name(
        self,
        name: str,
    ) -> schemas.responses.DeploymentResponse:
        """
        Query the Prefect API for a deployment by name.

        Args:
            name: A deployed flow's name: <FLOW_NAME>/<DEPLOYMENT_NAME>

        Raises:
            prefect.exceptions.ObjectNotFound: If request returns 404
            httpx.RequestError: If request fails

        Returns:
            a Deployment model representation of the deployment
        """
        try:
            response = await self._client.get(f"/deployments/name/{name}")
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

        return schemas.responses.DeploymentResponse.parse_obj(response.json())

    async def read_deployments(
        self,
        *,
        flow_filter: schemas.filters.FlowFilter = None,
        flow_run_filter: schemas.filters.FlowRunFilter = None,
        task_run_filter: schemas.filters.TaskRunFilter = None,
        deployment_filter: schemas.filters.DeploymentFilter = None,
        work_pool_filter: schemas.filters.WorkPoolFilter = None,
        work_queue_filter: schemas.filters.WorkQueueFilter = None,
        limit: int = None,
        sort: schemas.sorting.DeploymentSort = None,
        offset: int = 0,
    ) -> List[schemas.responses.DeploymentResponse]:
        """
        Query the Prefect API for deployments. Only deployments matching all
        the provided criteria will be returned.

        Args:
            flow_filter: filter criteria for flows
            flow_run_filter: filter criteria for flow runs
            task_run_filter: filter criteria for task runs
            deployment_filter: filter criteria for deployments
            work_pool_filter: filter criteria for work pools
            work_queue_filter: filter criteria for work pool queues
            limit: a limit for the deployment query
            offset: an offset for the deployment query

        Returns:
            a list of Deployment model representations
                of the deployments
        """
        body = {
            "flows": flow_filter.dict(json_compatible=True) if flow_filter else None,
            "flow_runs": (
                flow_run_filter.dict(json_compatible=True) if flow_run_filter else None
            ),
            "task_runs": (
                task_run_filter.dict(json_compatible=True) if task_run_filter else None
            ),
            "deployments": (
                deployment_filter.dict(json_compatible=True)
                if deployment_filter
                else None
            ),
            "work_pools": (
                work_pool_filter.dict(json_compatible=True)
                if work_pool_filter
                else None
            ),
            "work_pool_queues": (
                work_queue_filter.dict(json_compatible=True)
                if work_queue_filter
                else None
            ),
            "limit": limit,
            "offset": offset,
            "sort": sort,
        }

        response = await self._client.post("/deployments/filter", json=body)
        return pydantic.parse_obj_as(
            List[schemas.responses.DeploymentResponse], response.json()
        )

    async def delete_deployment(
        self,
        deployment_id: UUID,
    ):
        """
        Delete deployment by id.

        Args:
            deployment_id: The deployment id of interest.
        Raises:
            prefect.exceptions.ObjectNotFound: If request returns 404
            httpx.RequestError: If requests fails
        """
        try:
            await self._client.delete(f"/deployments/{deployment_id}")
        except httpx.HTTPStatusError as e:
            if e.response.status_code == 404:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

    async def read_flow_run(self, flow_run_id: UUID) -> FlowRun:
        """
        Query the Prefect API for a flow run by id.

        Args:
            flow_run_id: the flow run ID of interest

        Returns:
            a Flow Run model representation of the flow run
        """
        try:
            response = await self._client.get(f"/flow_runs/{flow_run_id}")
        except httpx.HTTPStatusError as e:
            if e.response.status_code == 404:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise
        return FlowRun.parse_obj(response.json())

    async def resume_flow_run(self, flow_run_id: UUID) -> OrchestrationResult:
        """
        Resumes a paused flow run.

        Args:
            flow_run_id: the flow run ID of interest

        Returns:
            an OrchestrationResult model representation of state orchestration output
        """
        try:
            response = await self._client.post(f"/flow_runs/{flow_run_id}/resume")
        except httpx.HTTPStatusError as e:
            raise

        return OrchestrationResult.parse_obj(response.json())

    async def read_flow_runs(
        self,
        *,
        flow_filter: schemas.filters.FlowFilter = None,
        flow_run_filter: schemas.filters.FlowRunFilter = None,
        task_run_filter: schemas.filters.TaskRunFilter = None,
        deployment_filter: schemas.filters.DeploymentFilter = None,
        work_pool_filter: schemas.filters.WorkPoolFilter = None,
        work_queue_filter: schemas.filters.WorkQueueFilter = None,
        sort: schemas.sorting.FlowRunSort = None,
        limit: int = None,
        offset: int = 0,
    ) -> List[FlowRun]:
        """
        Query the Prefect API for flow runs. Only flow runs matching all criteria will
        be returned.

        Args:
            flow_filter: filter criteria for flows
            flow_run_filter: filter criteria for flow runs
            task_run_filter: filter criteria for task runs
            deployment_filter: filter criteria for deployments
            work_pool_filter: filter criteria for work pools
            work_queue_filter: filter criteria for work pool queues
            sort: sort criteria for the flow runs
            limit: limit for the flow run query
            offset: offset for the flow run query

        Returns:
            a list of Flow Run model representations
                of the flow runs
        """
        body = {
            "flows": flow_filter.dict(json_compatible=True) if flow_filter else None,
            "flow_runs": (
                flow_run_filter.dict(json_compatible=True) if flow_run_filter else None
            ),
            "task_runs": (
                task_run_filter.dict(json_compatible=True) if task_run_filter else None
            ),
            "deployments": (
                deployment_filter.dict(json_compatible=True)
                if deployment_filter
                else None
            ),
            "work_pools": (
                work_pool_filter.dict(json_compatible=True)
                if work_pool_filter
                else None
            ),
            "work_pool_queues": (
                work_queue_filter.dict(json_compatible=True)
                if work_queue_filter
                else None
            ),
            "sort": sort,
            "limit": limit,
            "offset": offset,
        }

        response = await self._client.post(f"/flow_runs/filter", json=body)
        return pydantic.parse_obj_as(List[FlowRun], response.json())

    async def set_flow_run_state(
        self,
        flow_run_id: UUID,
        state: "prefect.states.State",
        force: bool = False,
    ) -> OrchestrationResult:
        """
        Set the state of a flow run.

        Args:
            flow_run_id: the id of the flow run
            state: the state to set
            force: if True, disregard orchestration logic when setting the state,
                forcing the Prefect API to accept the state

        Returns:
            an OrchestrationResult model representation of state orchestration output
        """
        state_create = state.to_state_create()
        state_create.state_details.flow_run_id = flow_run_id
        try:
            response = await self._client.post(
                f"/flow_runs/{flow_run_id}/set_state",
                json=dict(state=state_create.dict(json_compatible=True), force=force),
            )
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

        return OrchestrationResult.parse_obj(response.json())

    async def read_flow_run_states(
        self, flow_run_id: UUID
    ) -> List[prefect.states.State]:
        """
        Query for the states of a flow run

        Args:
            flow_run_id: the id of the flow run

        Returns:
            a list of State model representations
                of the flow run states
        """
        response = await self._client.get(
            "/flow_run_states/", params=dict(flow_run_id=str(flow_run_id))
        )
        return pydantic.parse_obj_as(List[prefect.states.State], response.json())

    async def set_task_run_name(self, task_run_id: UUID, name: str):
        task_run_data = schemas.actions.TaskRunUpdate(name=name)
        return await self._client.patch(
            f"/task_runs/{task_run_id}",
            json=task_run_data.dict(json_compatible=True, exclude_unset=True),
        )

    async def create_task_run(
        self,
        task: "Task",
        flow_run_id: UUID,
        dynamic_key: str,
        name: str = None,
        extra_tags: Iterable[str] = None,
        state: prefect.states.State = None,
        task_inputs: Dict[
            str,
            List[
                Union[
                    schemas.core.TaskRunResult,
                    schemas.core.Parameter,
                    schemas.core.Constant,
                ]
            ],
        ] = None,
    ) -> TaskRun:
        """
        Create a task run

        Args:
            task: The Task to run
            flow_run_id: The flow run id with which to associate the task run
            dynamic_key: A key unique to this particular run of a Task within the flow
            name: An optional name for the task run
            extra_tags: an optional list of extra tags to apply to the task run in
                addition to `task.tags`
            state: The initial state for the run. If not provided, defaults to
                `Pending` for now. Should always be a `Scheduled` type.
            task_inputs: the set of inputs passed to the task

        Returns:
            The created task run.
        """
        tags = set(task.tags).union(extra_tags or [])

        if state is None:
            state = prefect.states.Pending()

        task_run_data = schemas.actions.TaskRunCreate(
            name=name,
            flow_run_id=flow_run_id,
            task_key=task.task_key,
            dynamic_key=dynamic_key,
            tags=list(tags),
            task_version=task.version,
            empirical_policy=schemas.core.TaskRunPolicy(
                retries=task.retries,
                retry_delay=task.retry_delay_seconds,
                retry_jitter_factor=task.retry_jitter_factor,
            ),
            state=state.to_state_create(),
            task_inputs=task_inputs or {},
        )

        response = await self._client.post(
            "/task_runs/", json=task_run_data.dict(json_compatible=True)
        )
        return TaskRun.parse_obj(response.json())

    async def read_task_run(self, task_run_id: UUID) -> TaskRun:
        """
        Query the Prefect API for a task run by id.

        Args:
            task_run_id: the task run ID of interest

        Returns:
            a Task Run model representation of the task run
        """
        response = await self._client.get(f"/task_runs/{task_run_id}")
        return TaskRun.parse_obj(response.json())

    async def read_task_runs(
        self,
        *,
        flow_filter: schemas.filters.FlowFilter = None,
        flow_run_filter: schemas.filters.FlowRunFilter = None,
        task_run_filter: schemas.filters.TaskRunFilter = None,
        deployment_filter: schemas.filters.DeploymentFilter = None,
        sort: schemas.sorting.TaskRunSort = None,
        limit: int = None,
        offset: int = 0,
    ) -> List[TaskRun]:
        """
        Query the Prefect API for task runs. Only task runs matching all criteria will
        be returned.

        Args:
            flow_filter: filter criteria for flows
            flow_run_filter: filter criteria for flow runs
            task_run_filter: filter criteria for task runs
            deployment_filter: filter criteria for deployments
            sort: sort criteria for the task runs
            limit: a limit for the task run query
            offset: an offset for the task run query

        Returns:
            a list of Task Run model representations
                of the task runs
        """
        body = {
            "flows": flow_filter.dict(json_compatible=True) if flow_filter else None,
            "flow_runs": (
                flow_run_filter.dict(json_compatible=True) if flow_run_filter else None
            ),
            "task_runs": (
                task_run_filter.dict(json_compatible=True) if task_run_filter else None
            ),
            "deployments": (
                deployment_filter.dict(json_compatible=True)
                if deployment_filter
                else None
            ),
            "sort": sort,
            "limit": limit,
            "offset": offset,
        }
        response = await self._client.post(f"/task_runs/filter", json=body)
        return pydantic.parse_obj_as(List[TaskRun], response.json())

    async def set_task_run_state(
        self,
        task_run_id: UUID,
        state: prefect.states.State,
        force: bool = False,
    ) -> OrchestrationResult:
        """
        Set the state of a task run.

        Args:
            task_run_id: the id of the task run
            state: the state to set
            force: if True, disregard orchestration logic when setting the state,
                forcing the Prefect API to accept the state

        Returns:
            an OrchestrationResult model representation of state orchestration output
        """
        state_create = state.to_state_create()
        state_create.state_details.task_run_id = task_run_id
        response = await self._client.post(
            f"/task_runs/{task_run_id}/set_state",
            json=dict(state=state_create.dict(json_compatible=True), force=force),
        )
        return OrchestrationResult.parse_obj(response.json())

    async def read_task_run_states(
        self, task_run_id: UUID
    ) -> List[prefect.states.State]:
        """
        Query for the states of a task run

        Args:
            task_run_id: the id of the task run

        Returns:
            a list of State model representations of the task run states
        """
        response = await self._client.get(
            "/task_run_states/", params=dict(task_run_id=str(task_run_id))
        )
        return pydantic.parse_obj_as(List[prefect.states.State], response.json())

    async def create_logs(self, logs: Iterable[Union[LogCreate, dict]]) -> None:
        """
        Create logs for a flow or task run

        Args:
            logs: An iterable of `LogCreate` objects or already json-compatible dicts
        """
        serialized_logs = [
            log.dict(json_compatible=True) if isinstance(log, LogCreate) else log
            for log in logs
        ]
        await self._client.post(f"/logs/", json=serialized_logs)

    async def create_flow_run_notification_policy(
        self,
        block_document_id: UUID,
        is_active: bool = True,
        tags: List[str] = None,
        state_names: List[str] = None,
        message_template: Optional[str] = None,
    ) -> UUID:
        """
        Create a notification policy for flow runs

        Args:
            block_document_id: The block document UUID
            is_active: Whether the notification policy is active
            tags: List of flow tags
            state_names: List of state names
            message_template: Notification message template
        """
        if tags is None:
            tags = []
        if state_names is None:
            state_names = []

        policy = FlowRunNotificationPolicyCreate(
            block_document_id=block_document_id,
            is_active=is_active,
            tags=tags,
            state_names=state_names,
            message_template=message_template,
        )
        response = await self._client.post(
            "/flow_run_notification_policies/",
            json=policy.dict(json_compatible=True),
        )

        policy_id = response.json().get("id")
        if not policy_id:
            raise httpx.RequestError(f"Malformed response: {response}")

        return UUID(policy_id)

    async def read_flow_run_notification_policies(
        self,
        flow_run_notification_policy_filter: FlowRunNotificationPolicyFilter,
        limit: Optional[int] = None,
        offset: int = 0,
    ) -> List[FlowRunNotificationPolicy]:
        """
        Query the Prefect API for flow run notification policies. Only policies matching all criteria will
        be returned.

        Args:
            flow_run_notification_policy_filter: filter criteria for notification policies
            limit: a limit for the notification policies query
            offset: an offset for the notification policies query

        Returns:
            a list of FlowRunNotificationPolicy model representations
                of the notification policies
        """
        body = {
            "flow_run_notification_policy_filter": (
                flow_run_notification_policy_filter.dict(json_compatible=True)
                if flow_run_notification_policy_filter
                else None
            ),
            "limit": limit,
            "offset": offset,
        }
        response = await self._client.post(
            "/flow_run_notification_policies/filter", json=body
        )
        return pydantic.parse_obj_as(List[FlowRunNotificationPolicy], response.json())

    async def read_logs(
        self,
        log_filter: LogFilter = None,
        limit: int = None,
        offset: int = None,
        sort: schemas.sorting.LogSort = schemas.sorting.LogSort.TIMESTAMP_ASC,
    ) -> None:
        """
        Read flow and task run logs.
        """
        body = {
            "logs": log_filter.dict(json_compatible=True) if log_filter else None,
            "limit": limit,
            "offset": offset,
            "sort": sort,
        }

        response = await self._client.post(f"/logs/filter", json=body)
        return pydantic.parse_obj_as(List[schemas.core.Log], response.json())

    async def resolve_datadoc(self, datadoc: DataDocument) -> Any:
        """
        Recursively decode possibly nested data documents.

        "server" encoded documents will be retrieved from the server.

        Args:
            datadoc: The data document to resolve

        Returns:
            a decoded object, the innermost data
        """
        if not isinstance(datadoc, DataDocument):
            raise TypeError(
                f"`resolve_datadoc` received invalid type {type(datadoc).__name__}"
            )

        async def resolve_inner(data):
            if isinstance(data, bytes):
                try:
                    data = DataDocument.parse_raw(data)
                except pydantic.ValidationError:
                    return data

            if isinstance(data, DataDocument):
                return await resolve_inner(data.decode())

            return data

        return await resolve_inner(datadoc)

    async def send_worker_heartbeat(self, work_pool_name: str, worker_name: str):
        """
        Sends a worker heartbeat for a given work pool.

        Args:
            work_pool_name: The name of the work pool to heartbeat against.
            worker_name: The name of the worker sending the heartbeat.
        """
        await self._client.post(
            f"/work_pools/{work_pool_name}/workers/heartbeat",
            json={"name": worker_name},
        )

    async def read_workers_for_work_pool(
        self,
        work_pool_name: str,
        worker_filter: Optional[schemas.filters.WorkerFilter] = None,
        offset: Optional[int] = None,
        limit: Optional[int] = None,
    ) -> List[schemas.core.Worker]:
        """
        Reads workers for a given work pool.

        Args:
            work_pool_name: The name of the work pool for which to get
                member workers.
            worker_filter: Criteria by which to filter workers.
            limit: Limit for the worker query.
            offset: Limit for the worker query.
        """
        response = await self._client.post(
            f"/work_pools/{work_pool_name}/workers/filter",
            json={
                "worker_filter": (
                    worker_filter.dict(json_compatible=True, exclude_unset=True)
                    if worker_filter
                    else None
                ),
                "offset": offset,
                "limit": limit,
            },
        )

        return pydantic.parse_obj_as(List[schemas.core.Worker], response.json())

    async def read_work_pool(self, work_pool_name: str) -> schemas.core.WorkPool:
        """
        Reads information for a given work pool

        Args:
            work_pool_name: The name of the work pool to for which to get
                information.

        Returns:
            Information about the requested work pool.
        """
        try:
            response = await self._client.get(f"/work_pools/{work_pool_name}")
            return pydantic.parse_obj_as(WorkPool, response.json())
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

    async def read_work_pools(
        self,
        limit: Optional[int] = None,
        offset: int = 0,
        work_pool_filter: Optional[WorkPoolFilter] = None,
    ) -> List[WorkPool]:
        """
        Reads work pools.

        Args:
            limit: Limit for the work pool query.
            offset: Offset for the work pool query.
            work_pool_filter: Criteria by which to filter work pools.

        Returns:
            A list of work pools.
        """

        body = {
            "limit": limit,
            "offset": offset,
            "work_pools": (
                work_pool_filter.dict(json_compatible=True)
                if work_pool_filter
                else None
            ),
        }
        response = await self._client.post("/work_pools/filter", json=body)
        return pydantic.parse_obj_as(List[WorkPool], response.json())

    async def create_work_pool(
        self,
        work_pool: schemas.actions.WorkPoolCreate,
    ) -> schemas.core.WorkPool:
        """
        Creates a work pool with the provided configuration.

        Args:
            work_pool: Desired configuration for the new work pool.

        Returns:
            Information about the newly created work pool.
        """
        response = await self._client.post(
            "/work_pools/",
            json=work_pool.dict(json_compatible=True, exclude_unset=True),
        )

        return pydantic.parse_obj_as(WorkPool, response.json())

    async def update_work_pool(
        self,
        work_pool_name: str,
        work_pool: schemas.actions.WorkPoolUpdate,
    ):
        await self._client.patch(
            f"/work_pools/{work_pool_name}",
            json=work_pool.dict(json_compatible=True, exclude_unset=True),
        )

    async def delete_work_pool(
        self,
        work_pool_name: str,
    ):
        """
        Deletes a work pool.

        Args:
            work_pool_name: Name of the work pool to delete.
        """
        try:
            await self._client.delete(f"/work_pools/{work_pool_name}")
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
            else:
                raise

    async def read_work_queues(
        self,
        work_pool_name: Optional[str] = None,
        work_queue_filter: Optional[WorkQueueFilter] = None,
        limit: Optional[int] = None,
        offset: Optional[int] = None,
    ) -> List[schemas.core.WorkQueue]:
        """
        Retrieves queues for a work pool.

        Args:
            work_pool_name: Name of the work pool for which to get queues.
            work_queue_filter: Criteria by which to filter queues.
            limit: Limit for the queue query.
            offset: Limit for the queue query.

        Returns:
            List of queues for the specified work pool.
        """
        json = {
            "work_queues": (
                work_queue_filter.dict(json_compatible=True, exclude_unset=True)
                if work_queue_filter
                else None
            ),
            "limit": limit,
            "offset": offset,
        }

        if work_pool_name:
            try:
                response = await self._client.post(
                    f"/work_pools/{work_pool_name}/queues/filter",
                    json=json,
                )
            except httpx.HTTPStatusError as e:
                if e.response.status_code == status.HTTP_404_NOT_FOUND:
                    raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
                else:
                    raise
        else:
            response = await self._client.post(f"/work_queues/filter", json=json)

        return pydantic.parse_obj_as(List[WorkQueue], response.json())

    async def get_scheduled_flow_runs_for_work_pool(
        self,
        work_pool_name: str,
        work_queue_names: Optional[List[str]] = None,
        scheduled_before: Optional[datetime.datetime] = None,
    ) -> List[WorkerFlowRunResponse]:
        """
        Retrieves scheduled flow runs for the provided set of work pool queues.

        Args:
            work_pool_name: The name of the work pool that the work pool
                queues are associated with.
            work_queue_names: The names of the work pool queues from which
                to get scheduled flow runs.
            scheduled_before: Datetime used to filter returned flow runs. Flow runs
                scheduled for after the given datetime string will not be returned.

        Returns:
            A list of worker flow run responses containing information about the
            retrieved flow runs.
        """
        body: Dict[str, Any] = {}
        if work_queue_names is not None:
            body["work_queue_names"] = list(work_queue_names)
        if scheduled_before:
            body["scheduled_before"] = str(scheduled_before)

        response = await self._client.post(
            f"/work_pools/{work_pool_name}/get_scheduled_flow_runs",
            json=body,
        )

        return pydantic.parse_obj_as(List[WorkerFlowRunResponse], response.json())

    async def __aenter__(self):
        """
        Start the client.

        If the client is already started, this will raise an exception.

        If the client is already closed, this will raise an exception. Use a new client
        instance instead.
        """
        if self._closed:
            # httpx.AsyncClient does not allow reuse so we will not either.
            raise RuntimeError(
                "The client cannot be started again after closing. "
                "Retrieve a new client with `get_client()` instead."
            )

        if self._started:
            # httpx.AsyncClient does not allow reentrancy so we will not either.
            raise RuntimeError("The client cannot be started more than once.")

        await self._exit_stack.__aenter__()

        # Enter a lifespan context if using an ephemeral application.
        # See https://github.com/encode/httpx/issues/350
        if self._ephemeral_app and self.manage_lifespan:
            self._ephemeral_lifespan = await self._exit_stack.enter_async_context(
                app_lifespan_context(self._ephemeral_app)
            )

        if self._ephemeral_app:
            self.logger.debug(
                "Using ephemeral application with database at "
                f"{PREFECT_API_DATABASE_CONNECTION_URL.value()}"
            )
        else:
            self.logger.debug(f"Connecting to API at {self.api_url}")

        # Enter the httpx client's context
        await self._exit_stack.enter_async_context(self._client)

        self._started = True

        return self

    async def __aexit__(self, *exc_info):
        """
        Shutdown the client.
        """
        self._closed = True
        return await self._exit_stack.__aexit__(*exc_info)

    def __enter__(self):
        raise RuntimeError(
            "The `PrefectClient` must be entered with an async context. Use 'async "
            "with PrefectClient(...)' not 'with PrefectClient(...)'"
        )

    def __exit__(self, *_):
        assert False, "This should never be called but must be defined for __enter__"


@deprecated_callable(start_date="Feb 2023", help="Use `PrefectClient` instead.")
class OrionClient(PrefectClient):
    """
    Deprecated. Use `PrefectClient` instead.
    """