Asynchronous client implementation for communicating with the Prefect REST API.

Explore the client by communicating with an in-memory webserver — no setup required:

$ # start python REPL with native await functionality
$ python -m asyncio
>>> from prefect.client.orchestration import get_client
>>> async with get_client() as client:
...     response = await client.hello()
...     print(response.json())
👋

prefect.client.orchestration

PrefectClient

An asynchronous client for interacting with the Prefect REST API.

Parameters:

Name	Type	Description	Default
api	Union[str, FastAPI]	the REST API URL or FastAPI application to connect to	required
api_key	str	An optional API key for authentication.	None
api_version	str	The API version this client is compatible with.	None
httpx_settings	dict	An optional dictionary of settings to pass to the underlying httpx.AsyncClient	None

Examples:

Say hello to a Prefect REST API

>>> async with get_client() as client:
>>>     response = await client.hello()
>>>
>>> print(response.json())
👋

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

            # When using an ephemeral server, server-side exceptions can be raised
            # client-side breaking all of our response error code handling. To work
            # around this, we create an ASGI transport with application exceptions
            # disabled instead of using the application directly.
            # refs:
            # - https://github.com/PrefectHQ/prefect/pull/9637
            # - https://github.com/encode/starlette/blob/d3a11205ed35f8e5a58a711db0ff59c86fa7bb31/starlette/middleware/errors.py#L184
            # - https://github.com/tiangolo/fastapi/blob/8cc967a7605d3883bd04ceb5d25cc94ae079612f/fastapi/applications.py#L163-L164
            httpx_settings.setdefault(
                "transport",
                httpx.ASGITransport(
                    app=self._ephemeral_app, raise_app_exceptions=False
                ),
            )
            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, exclude_unset=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("/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 = create_model.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=schemas.actions.BlockTypeUpdate.updatable_fields(),
                    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("/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("/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,
        pull_steps: Optional[List[dict]] = 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,
            pull_steps=pull_steps,
        )

        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")

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

        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_update = 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,
        )

        if getattr(deployment, "work_pool_name", None) is not None:
            deployment_update.work_pool_name = deployment.work_pool_name

        await self._client.patch(
            f"/deployments/{deployment.id}",
            json=deployment_update.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
        """
        try:
            response = await self._client.get(f"/deployments/{deployment_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.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, exclude_unset=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:
            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, exclude_unset=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("/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, exclude_unset=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("/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("/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("/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.
        """
        try:
            response = await self._client.post(
                "/work_pools/",
                json=work_pool.dict(json_compatible=True, exclude_unset=True),
            )
        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 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("/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 create_artifact(
        self,
        artifact: schemas.actions.ArtifactCreate,
    ) -> schemas.core.Artifact:
        """
        Creates an artifact with the provided configuration.

        Args:
            artifact: Desired configuration for the new artifact.
        Returns:
            Information about the newly created artifact.
        """

        response = await self._client.post(
            "/artifacts/",
            json=artifact.dict(json_compatible=True, exclude_unset=True),
        )

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

    async def read_artifacts(
        self,
        *,
        artifact_filter: schemas.filters.ArtifactFilter = None,
        flow_run_filter: schemas.filters.FlowRunFilter = None,
        task_run_filter: schemas.filters.TaskRunFilter = None,
        sort: schemas.sorting.ArtifactSort = None,
        limit: int = None,
        offset: int = 0,
    ) -> List[Artifact]:
        """
        Query the Prefect API for artifacts. Only artifacts matching all criteria will
        be returned.
        Args:
            artifact_filter: filter criteria for artifacts
            flow_run_filter: filter criteria for flow runs
            task_run_filter: filter criteria for task runs
            sort: sort criteria for the artifacts
            limit: limit for the artifact query
            offset: offset for the artifact query
        Returns:
            a list of Artifact model representations of the artifacts
        """
        body = {
            "artifacts": (
                artifact_filter.dict(json_compatible=True) if artifact_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
            ),
            "sort": sort,
            "limit": limit,
            "offset": offset,
        }
        response = await self._client.post("/artifacts/filter", json=body)
        return pydantic.parse_obj_as(List[Artifact], response.json())

    async def read_latest_artifacts(
        self,
        *,
        artifact_filter: schemas.filters.ArtifactCollectionFilter = None,
        flow_run_filter: schemas.filters.FlowRunFilter = None,
        task_run_filter: schemas.filters.TaskRunFilter = None,
        sort: schemas.sorting.ArtifactCollectionSort = None,
        limit: int = None,
        offset: int = 0,
    ) -> List[ArtifactCollection]:
        """
        Query the Prefect API for artifacts. Only artifacts matching all criteria will
        be returned.
        Args:
            artifact_filter: filter criteria for artifacts
            flow_run_filter: filter criteria for flow runs
            task_run_filter: filter criteria for task runs
            sort: sort criteria for the artifacts
            limit: limit for the artifact query
            offset: offset for the artifact query
        Returns:
            a list of Artifact model representations of the artifacts
        """
        body = {
            "artifacts": (
                artifact_filter.dict(json_compatible=True) if artifact_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
            ),
            "sort": sort,
            "limit": limit,
            "offset": offset,
        }
        response = await self._client.post("/artifacts/latest/filter", json=body)
        return pydantic.parse_obj_as(List[ArtifactCollection], response.json())

    async def delete_artifact(self, artifact_id: UUID) -> None:
        """
        Deletes an artifact with the provided id.

        Args:
            artifact_id: The id of the artifact to delete.
        """
        try:
            await self._client.delete(f"/artifacts/{artifact_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_variable_by_name(self, name: str) -> Optional[schemas.core.Variable]:
        """Reads a variable by name. Returns None if no variable is found."""
        try:
            response = await self._client.get(f"/variables/name/{name}")
            return pydantic.parse_obj_as(schemas.core.Variable, response.json())
        except httpx.HTTPStatusError as e:
            if e.response.status_code == status.HTTP_404_NOT_FOUND:
                return None
            else:
                raise

    async def delete_variable_by_name(self, name: str):
        """Deletes a variable by name."""
        try:
            await self._client.delete(f"/variables/name/{name}")
        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_variables(self, limit: int = None) -> List[schemas.core.Variable]:
        """Reads all variables."""
        response = await self._client.post("/variables/filter", json={"limit": limit})
        return pydantic.parse_obj_as(List[schemas.core.Variable], response.json())

    async def read_worker_metadata(self) -> Dict[str, Any]:
        """Reads worker metadata stored in Prefect collection registry."""
        response = await self._client.get("collections/views/aggregate-worker-metadata")
        response.raise_for_status()
        return 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__"

api_url: httpx.URL property

Get the base URL for the API.

api_healthcheck async

Attempts to connect to the API and returns the encountered exception if not successful.

If successful, returns None.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

hello async

Send a GET request to /hello for testing purposes.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

create_flow async

Create a flow in the Prefect API.

Parameters:

Name	Type	Description	Default
flow	Flow	a Flow object	required

Raises:

Type	Description
httpx.RequestError	if a flow was not created for any reason

Returns:

Type	Description
UUID	the ID of the flow in the backend

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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)

create_flow_from_name async

Create a flow in the Prefect API.

Parameters:

Name	Type	Description	Default
flow_name	str	the name of the new flow	required

Raises:

Type	Description
httpx.RequestError	if a flow was not created for any reason

Returns:

Type	Description
UUID	the ID of the flow in the backend

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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)

read_flow async

Query the Prefect API for a flow by id.

Parameters:

Name	Type	Description	Default
flow_id	UUID	the flow ID of interest	required

Returns:

Type	Description
schemas.core.Flow	a Flow model representation of the flow

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_flows async

Query the Prefect API for flows. Only flows matching all criteria will be returned.

Parameters:

Name	Type	Description	Default
flow_filter	schemas.filters.FlowFilter	filter criteria for flows	None
flow_run_filter	schemas.filters.FlowRunFilter	filter criteria for flow runs	None
task_run_filter	schemas.filters.TaskRunFilter	filter criteria for task runs	None
deployment_filter	schemas.filters.DeploymentFilter	filter criteria for deployments	None
work_pool_filter	schemas.filters.WorkPoolFilter	filter criteria for work pools	None
work_queue_filter	schemas.filters.WorkQueueFilter	filter criteria for work pool queues	None
sort	schemas.sorting.FlowSort	sort criteria for the flows	None
limit	int	limit for the flow query	None
offset	int	offset for the flow query	0

Returns:

Type	Description
List[schemas.core.Flow]	a list of Flow model representations of the flows

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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, exclude_unset=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("/flows/filter", json=body)
    return pydantic.parse_obj_as(List[schemas.core.Flow], response.json())

read_flow_by_name async

Query the Prefect API for a flow by name.

Parameters:

Name	Type	Description	Default
flow_name	str	the name of a flow	required

Returns:

Type	Description
schemas.core.Flow	a fully hydrated Flow model

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

create_flow_run_from_deployment async

Create a flow run for a deployment.

Parameters:

Name	Type	Description	Default
deployment_id	UUID	The deployment ID to create the flow run from	required
parameters	Dict[str, Any]	Parameter overrides for this flow run. Merged with the deployment defaults	None
context	dict	Optional run context data	None
state	prefect.states.State	The initial state for the run. If not provided, defaults to Scheduled for now. Should always be a Scheduled type.	None
name	str	An optional name for the flow run. If not provided, the server will generate a name.	None
tags	Iterable[str]	An optional iterable of tags to apply to the flow run; these tags are merged with the deployment's tags.	None
idempotency_key	str	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.	None
parent_task_run_id	UUID	if a subflow run is being created, the placeholder task run identifier in the parent flow	None

Raises:

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

Returns:

Type	Description
FlowRun	The flow run model

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

create_flow_run async

Create a flow run for a flow.

Parameters:

Name	Type	Description	Default
flow	Flow	The flow model to create the flow run for	required
name	str	An optional name for the flow run	None
parameters	Dict[str, Any]	Parameter overrides for this flow run.	None
context	dict	Optional run context data	None
tags	Iterable[str]	a list of tags to apply to this flow run	None
parent_task_run_id	UUID	if a subflow run is being created, the placeholder task run identifier in the parent flow	None
state	prefect.states.State	The initial state for the run. If not provided, defaults to Scheduled for now. Should always be a Scheduled type.	None

Raises:

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

Returns:

Type	Description
FlowRun	The flow run model

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

update_flow_run async

Update a flow run's details.

Parameters:

Name	Type	Description	Default
flow_run_id	UUID	The identifier for the flow run to update.	required
flow_version	Optional[str]	A new version string for the flow run.	None
parameters	Optional[dict]	A dictionary of parameter values for the flow run. This will not be merged with any existing parameters.	None
name	Optional[str]	A new name for the flow run.	None
empirical_policy	Optional[schemas.core.FlowRunPolicy]	A new flow run orchestration policy. This will not be merged with any existing policy.	None
tags	Optional[Iterable[str]]	An iterable of new tags for the flow run. These will not be merged with any existing tags.	None
infrastructure_pid	Optional[str]	The id of flow run as returned by an infrastructure block.	None

Returns:

Type	Description
httpx.Response	an httpx.Response object from the PATCH request

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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),
    )

delete_flow_run async

Delete a flow run by UUID.

Parameters:

Name	Type	Description	Default
flow_run_id	UUID	The flow run UUID of interest.	required

Raises:

Type	Description
prefect.exceptions.ObjectNotFound	If request returns 404
httpx.RequestError	If requests fails

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

create_concurrency_limit async

Create a tag concurrency limit in the Prefect API. These limits govern concurrently running tasks.

Parameters:

Name	Type	Description	Default
tag	str	a tag the concurrency limit is applied to	required
concurrency_limit	int	the maximum number of concurrent task runs for a given tag	required

Raises:

Type	Description
httpx.RequestError	if the concurrency limit was not created for any reason

Returns:

Type	Description
UUID	the ID of the concurrency limit in the backend

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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)

read_concurrency_limit_by_tag async

Read the concurrency limit set on a specific tag.

Parameters:

Name	Type	Description	Default
tag	str	a tag the concurrency limit is applied to	required

Raises:

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

Returns:

Type	Description
	the concurrency limit set on a specific tag

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

read_concurrency_limits async

Lists concurrency limits set on task run tags.

Parameters:

Name	Type	Description	Default
limit	int	the maximum number of concurrency limits returned	required
offset	int	the concurrency limit query offset	required

Returns:

Type	Description
	a list of concurrency limits

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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()
    )

reset_concurrency_limit_by_tag async

Resets the concurrency limit slots set on a specific tag.

Parameters:

Name	Type	Description	Default
tag	str	a tag the concurrency limit is applied to	required
slot_override	Optional[List[Union[UUID, str]]]	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.	None

Raises:

Type	Description
prefect.exceptions.ObjectNotFound	If request returns 404
httpx.RequestError	If request fails

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

delete_concurrency_limit_by_tag async

Delete the concurrency limit set on a specific tag.

Parameters:

Name	Type	Description	Default
tag	str	a tag the concurrency limit is applied to	required

Raises:

Type	Description
prefect.exceptions.ObjectNotFound	If request returns 404
httpx.RequestError	If request fails

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

create_work_queue async

Create a work queue.

Parameters:

Name	Type	Description	Default
name	str	a unique name for the work queue	required
tags	Optional[List[str]]	will be included in the queue. This option will be removed on 2023-02-23.	None
description	Optional[str]	An optional description for the work queue.	None
is_paused	Optional[bool]	Whether or not the work queue is paused.	None
concurrency_limit	Optional[int]	An optional concurrency limit for the work queue.	None
priority	Optional[int]	The queue's priority. Lower values are higher priority (1 is the highest).	None
work_pool_name	Optional[str]	The name of the work pool to use for this queue.	None

Raises:

Type	Description
prefect.exceptions.ObjectAlreadyExists	If request returns 409
httpx.RequestError	If request fails

Returns:

Name	Type	Description
UUID	schemas.core.WorkQueue	The UUID of the newly created workflow

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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 = create_model.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())

read_work_queue_by_name async

Read a work queue by name.

Parameters:

Name	Type	Description	Default
name	str	a unique name for the work queue	required
work_pool_name	str	the name of the work pool the queue belongs to.	None

Raises:

Type	Description
prefect.exceptions.ObjectNotFound	if no work queue is found
httpx.HTTPStatusError	other status errors

Returns:

Type	Description
schemas.core.WorkQueue	schemas.core.WorkQueue: a work queue API object

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

update_work_queue async

Update properties of a work queue.

Parameters:

Name	Type	Description	Default
id	UUID	the ID of the work queue to update	required
**kwargs		the fields to update	{}

Raises:

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

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

get_runs_in_work_queue async

Read flow runs off a work queue.

Parameters:

Name	Type	Description	Default
id	UUID	the id of the work queue to read from	required
limit	int	a limit on the number of runs to return	10
scheduled_before	datetime.datetime	a timestamp; only runs scheduled before this time will be returned. Defaults to now.	None

Raises:

Type	Description
prefect.exceptions.ObjectNotFound	If request returns 404
httpx.RequestError	If request fails

Returns:

Type	Description
List[FlowRun]	List[FlowRun]: a list of FlowRun objects read from the queue

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_work_queue async

Read a work queue.

Parameters:

Name	Type	Description	Default
id	UUID	the id of the work queue to load	required

Raises:

Type	Description
prefect.exceptions.ObjectNotFound	If request returns 404
httpx.RequestError	If request fails

Returns:

Name	Type	Description
WorkQueue	schemas.core.WorkQueue	an instantiated WorkQueue object

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

match_work_queues async

Query the Prefect API for work queues with names with a specific prefix.

Parameters:

Name	Type	Description	Default
prefixes	List[str]	a list of strings used to match work queue name prefixes	required

Returns:

Type	Description
List[schemas.core.WorkQueue]	a list of WorkQueue model representations of the work queues

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

delete_work_queue_by_id async

Delete a work queue by its ID.

Parameters:

Name	Type	Description	Default
id	UUID	the id of the work queue to delete	required

Raises:

Type	Description
prefect.exceptions.ObjectNotFound	If request returns 404
httpx.RequestError	If requests fails

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

create_block_type async

Create a block type in the Prefect API.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

create_block_schema async

Create a block schema in the Prefect API.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

create_block_document async

Create a block document in the Prefect API. This data is used to configure a corresponding Block.

Parameters:

Name	Type	Description	Default
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.	True

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

update_block_document async

Update a block document in the Prefect API.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

delete_block_document async

Delete a block document.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

read_block_type_by_slug async

Read a block type by its slug.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_block_schema_by_checksum async

Look up a block schema checksum

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

update_block_type async

Update a block document in the Prefect API.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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=schemas.actions.BlockTypeUpdate.updatable_fields(),
                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

delete_block_type async

Delete a block type.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

read_block_types async

Read all block types

Raises:

Type	Description
httpx.RequestError	if the block types were not found

Returns:

Type	Description
List[schemas.core.BlockType]	List of BlockTypes.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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("/block_types/filter", json={})
    return pydantic.parse_obj_as(List[schemas.core.BlockType], response.json())

read_block_schemas async

Read all block schemas

Raises:

Type	Description
httpx.RequestError	if a valid block schema was not found

Returns:

Type	Description
List[schemas.core.BlockSchema]	A BlockSchema.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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("/block_schemas/filter", json={})
    return pydantic.parse_obj_as(List[schemas.core.BlockSchema], response.json())

read_block_document async

Read the block document with the specified ID.

Parameters:

Name	Type	Description	Default
block_document_id	UUID	the block document id	required
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.	True

Raises:

Type	Description
httpx.RequestError	if the block document was not found for any reason

Returns:

Type	Description
	A block document or None.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_block_document_by_name async

Read the block document with the specified name that corresponds to a specific block type name.

Parameters:

Name	Type	Description	Default
name	str	The block document name.	required
block_type_slug	str	The block type slug.	required
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.	True

Raises:

Type	Description
httpx.RequestError	if the block document was not found for any reason

Returns:

Type	Description
	A block document or None.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_block_documents async

Read block documents

Parameters:

Name	Type	Description	Default
block_schema_type	Optional[str]	an optional block schema type	None
offset	Optional[int]	an offset	None
limit	Optional[int]	the number of blocks to return	None
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.	True

Returns:

Type	Description
	A list of block documents

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

create_deployment async

Create a deployment.

Parameters:

Name	Type	Description	Default
flow_id	UUID	the flow ID to create a deployment for	required
name	str	the name of the deployment	required
version	str	an optional version string for the deployment	None
schedule	schemas.schedules.SCHEDULE_TYPES	an optional schedule to apply to the deployment	None
tags	List[str]	an optional list of tags to apply to the deployment	None
storage_document_id	UUID	an reference to the storage block document used for the deployed flow	None
infrastructure_document_id	UUID	an reference to the infrastructure block document to use for this deployment	None

Raises:

Type	Description
httpx.RequestError	if the deployment was not created for any reason

Returns:

Type	Description
UUID	the ID of the deployment in the backend

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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,
    pull_steps: Optional[List[dict]] = 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,
        pull_steps=pull_steps,
    )

    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")

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

    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)

read_deployment async

Query the Prefect API for a deployment by id.

Parameters:

Name	Type	Description	Default
deployment_id	UUID	the deployment ID of interest	required

Returns:

Type	Description
schemas.responses.DeploymentResponse	a Deployment model representation of the deployment

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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
    """
    try:
        response = await self._client.get(f"/deployments/{deployment_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.responses.DeploymentResponse.parse_obj(response.json())

read_deployment_by_name async

Query the Prefect API for a deployment by name.

Parameters:

Name	Type	Description	Default
name	str	A deployed flow's name: /	required

Raises:

Type	Description
prefect.exceptions.ObjectNotFound	If request returns 404
httpx.RequestError	If request fails

Returns:

Type	Description
schemas.responses.DeploymentResponse	a Deployment model representation of the deployment

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_deployments async

Query the Prefect API for deployments. Only deployments matching all the provided criteria will be returned.

Parameters:

Name	Type	Description	Default
flow_filter	schemas.filters.FlowFilter	filter criteria for flows	None
flow_run_filter	schemas.filters.FlowRunFilter	filter criteria for flow runs	None
task_run_filter	schemas.filters.TaskRunFilter	filter criteria for task runs	None
deployment_filter	schemas.filters.DeploymentFilter	filter criteria for deployments	None
work_pool_filter	schemas.filters.WorkPoolFilter	filter criteria for work pools	None
work_queue_filter	schemas.filters.WorkQueueFilter	filter criteria for work pool queues	None
limit	int	a limit for the deployment query	None
offset	int	an offset for the deployment query	0

Returns:

Type	Description
List[schemas.responses.DeploymentResponse]	a list of Deployment model representations of the deployments

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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, exclude_unset=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()
    )

delete_deployment async

Delete deployment by id.

Parameters:

Name	Type	Description	Default
deployment_id	UUID	The deployment id of interest.	required

Raises:

Type	Description
prefect.exceptions.ObjectNotFound	If request returns 404
httpx.RequestError	If requests fails

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

read_flow_run async

Query the Prefect API for a flow run by id.

Parameters:

Name	Type	Description	Default
flow_run_id	UUID	the flow run ID of interest	required

Returns:

Type	Description
FlowRun	a Flow Run model representation of the flow run

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

resume_flow_run async

Resumes a paused flow run.

Parameters:

Name	Type	Description	Default
flow_run_id	UUID	the flow run ID of interest	required

Returns:

Type	Description
OrchestrationResult	an OrchestrationResult model representation of state orchestration output

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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:
        raise

    return OrchestrationResult.parse_obj(response.json())

read_flow_runs async

Query the Prefect API for flow runs. Only flow runs matching all criteria will be returned.

Parameters:

Name	Type	Description	Default
flow_filter	schemas.filters.FlowFilter	filter criteria for flows	None
flow_run_filter	schemas.filters.FlowRunFilter	filter criteria for flow runs	None
task_run_filter	schemas.filters.TaskRunFilter	filter criteria for task runs	None
deployment_filter	schemas.filters.DeploymentFilter	filter criteria for deployments	None
work_pool_filter	schemas.filters.WorkPoolFilter	filter criteria for work pools	None
work_queue_filter	schemas.filters.WorkQueueFilter	filter criteria for work pool queues	None
sort	schemas.sorting.FlowRunSort	sort criteria for the flow runs	None
limit	int	limit for the flow run query	None
offset	int	offset for the flow run query	0

Returns:

Type	Description
List[FlowRun]	a list of Flow Run model representations of the flow runs

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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, exclude_unset=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("/flow_runs/filter", json=body)
    return pydantic.parse_obj_as(List[FlowRun], response.json())

set_flow_run_state async

Set the state of a flow run.

Parameters:

Name	Type	Description	Default
flow_run_id	UUID	the id of the flow run	required
state	prefect.states.State	the state to set	required
force	bool	if True, disregard orchestration logic when setting the state, forcing the Prefect API to accept the state	False

Returns:

Type	Description
OrchestrationResult	an OrchestrationResult model representation of state orchestration output

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_flow_run_states async

Query for the states of a flow run

Parameters:

Name	Type	Description	Default
flow_run_id	UUID	the id of the flow run	required

Returns:

Type	Description
List[prefect.states.State]	a list of State model representations of the flow run states

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

create_task_run async

Create a task run

Parameters:

Name	Type	Description	Default
task	Task	The Task to run	required
flow_run_id	UUID	The flow run id with which to associate the task run	required
dynamic_key	str	A key unique to this particular run of a Task within the flow	required
name	str	An optional name for the task run	None
extra_tags	Iterable[str]	an optional list of extra tags to apply to the task run in addition to task.tags	None
state	prefect.states.State	The initial state for the run. If not provided, defaults to Pending for now. Should always be a Scheduled type.	None
task_inputs	Dict[str, List[Union[schemas.core.TaskRunResult, schemas.core.Parameter, schemas.core.Constant]]]	the set of inputs passed to the task	None

Returns:

Type	Description
TaskRun	The created task run.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_task_run async

Query the Prefect API for a task run by id.

Parameters:

Name	Type	Description	Default
task_run_id	UUID	the task run ID of interest	required

Returns:

Type	Description
TaskRun	a Task Run model representation of the task run

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_task_runs async

Query the Prefect API for task runs. Only task runs matching all criteria will be returned.

Parameters:

Name	Type	Description	Default
flow_filter	schemas.filters.FlowFilter	filter criteria for flows	None
flow_run_filter	schemas.filters.FlowRunFilter	filter criteria for flow runs	None
task_run_filter	schemas.filters.TaskRunFilter	filter criteria for task runs	None
deployment_filter	schemas.filters.DeploymentFilter	filter criteria for deployments	None
sort	schemas.sorting.TaskRunSort	sort criteria for the task runs	None
limit	int	a limit for the task run query	None
offset	int	an offset for the task run query	0

Returns:

Type	Description
List[TaskRun]	a list of Task Run model representations of the task runs

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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, exclude_unset=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("/task_runs/filter", json=body)
    return pydantic.parse_obj_as(List[TaskRun], response.json())

set_task_run_state async

Set the state of a task run.

Parameters:

Name	Type	Description	Default
task_run_id	UUID	the id of the task run	required
state	prefect.states.State	the state to set	required
force	bool	if True, disregard orchestration logic when setting the state, forcing the Prefect API to accept the state	False

Returns:

Type	Description
OrchestrationResult	an OrchestrationResult model representation of state orchestration output

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_task_run_states async

Query for the states of a task run

Parameters:

Name	Type	Description	Default
task_run_id	UUID	the id of the task run	required

Returns:

Type	Description
List[prefect.states.State]	a list of State model representations of the task run states

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

create_logs async

Create logs for a flow or task run

Parameters:

Name	Type	Description	Default
logs	Iterable[Union[LogCreate, dict]]	An iterable of LogCreate objects or already json-compatible dicts	required

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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("/logs/", json=serialized_logs)

create_flow_run_notification_policy async

Create a notification policy for flow runs

Parameters:

Name	Type	Description	Default
block_document_id	UUID	The block document UUID	required
is_active	bool	Whether the notification policy is active	True
tags	List[str]	List of flow tags	None
state_names	List[str]	List of state names	None
message_template	Optional[str]	Notification message template	None

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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)

read_flow_run_notification_policies async

Query the Prefect API for flow run notification policies. Only policies matching all criteria will be returned.

Parameters:

Name	Type	Description	Default
flow_run_notification_policy_filter	FlowRunNotificationPolicyFilter	filter criteria for notification policies	required
limit	Optional[int]	a limit for the notification policies query	None
offset	int	an offset for the notification policies query	0

Returns:

Type	Description
List[FlowRunNotificationPolicy]	a list of FlowRunNotificationPolicy model representations of the notification policies

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_logs async

Read flow and task run logs.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

resolve_datadoc async

Recursively decode possibly nested data documents.

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

Parameters:

Name	Type	Description	Default
datadoc	DataDocument	The data document to resolve	required

Returns:

Type	Description
Any	a decoded object, the innermost data

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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)

send_worker_heartbeat async

Sends a worker heartbeat for a given work pool.

Parameters:

Name	Type	Description	Default
work_pool_name	str	The name of the work pool to heartbeat against.	required
worker_name	str	The name of the worker sending the heartbeat.	required

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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},
    )

read_workers_for_work_pool async

Reads workers for a given work pool.

Parameters:

Name	Type	Description	Default
work_pool_name	str	The name of the work pool for which to get member workers.	required
worker_filter	Optional[schemas.filters.WorkerFilter]	Criteria by which to filter workers.	None
limit	Optional[int]	Limit for the worker query.	None
offset	Optional[int]	Limit for the worker query.	None

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

read_work_pool async

Reads information for a given work pool

Parameters:

Name	Type	Description	Default
work_pool_name	str	The name of the work pool to for which to get information.	required

Returns:

Type	Description
schemas.core.WorkPool	Information about the requested work pool.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

read_work_pools async

Reads work pools.

Parameters:

Name	Type	Description	Default
limit	Optional[int]	Limit for the work pool query.	None
offset	int	Offset for the work pool query.	0
work_pool_filter	Optional[WorkPoolFilter]	Criteria by which to filter work pools.	None

Returns:

Type	Description
List[WorkPool]	A list of work pools.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

create_work_pool async

Creates a work pool with the provided configuration.

Parameters:

Name	Type	Description	Default
work_pool	schemas.actions.WorkPoolCreate	Desired configuration for the new work pool.	required

Returns:

Type	Description
schemas.core.WorkPool	Information about the newly created work pool.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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.
    """
    try:
        response = await self._client.post(
            "/work_pools/",
            json=work_pool.dict(json_compatible=True, exclude_unset=True),
        )
    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 pydantic.parse_obj_as(WorkPool, response.json())

delete_work_pool async

Deletes a work pool.

Parameters:

Name	Type	Description	Default
work_pool_name	str	Name of the work pool to delete.	required

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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

read_work_queues async

Retrieves queues for a work pool.

Parameters:

Name	Type	Description	Default
work_pool_name	Optional[str]	Name of the work pool for which to get queues.	None
work_queue_filter	Optional[WorkQueueFilter]	Criteria by which to filter queues.	None
limit	Optional[int]	Limit for the queue query.	None
offset	Optional[int]	Limit for the queue query.	None

Returns:

Type	Description
List[schemas.core.WorkQueue]	List of queues for the specified work pool.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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("/work_queues/filter", json=json)

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

get_scheduled_flow_runs_for_work_pool async

Retrieves scheduled flow runs for the provided set of work pool queues.

Parameters:

Name	Type	Description	Default
work_pool_name	str	The name of the work pool that the work pool queues are associated with.	required
work_queue_names	Optional[List[str]]	The names of the work pool queues from which to get scheduled flow runs.	None
scheduled_before	Optional[datetime.datetime]	Datetime used to filter returned flow runs. Flow runs scheduled for after the given datetime string will not be returned.	None

Returns:

Type	Description
List[WorkerFlowRunResponse]	A list of worker flow run responses containing information about the
List[WorkerFlowRunResponse]	retrieved flow runs.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

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())

create_artifact async

Creates an artifact with the provided configuration.

Parameters:

Name	Type	Description	Default
artifact	schemas.actions.ArtifactCreate	Desired configuration for the new artifact.	required

Returns:

Type	Description
schemas.core.Artifact	Information about the newly created artifact.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

async def create_artifact(
    self,
    artifact: schemas.actions.ArtifactCreate,
) -> schemas.core.Artifact:
    """
    Creates an artifact with the provided configuration.

    Args:
        artifact: Desired configuration for the new artifact.
    Returns:
        Information about the newly created artifact.
    """

    response = await self._client.post(
        "/artifacts/",
        json=artifact.dict(json_compatible=True, exclude_unset=True),
    )

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

read_artifacts async

Query the Prefect API for artifacts. Only artifacts matching all criteria will be returned.

Parameters:

Name	Type	Description	Default
artifact_filter	schemas.filters.ArtifactFilter	filter criteria for artifacts	None
flow_run_filter	schemas.filters.FlowRunFilter	filter criteria for flow runs	None
task_run_filter	schemas.filters.TaskRunFilter	filter criteria for task runs	None
sort	schemas.sorting.ArtifactSort	sort criteria for the artifacts	None
limit	int	limit for the artifact query	None
offset	int	offset for the artifact query	0

Returns:

Type	Description
List[Artifact]	a list of Artifact model representations of the artifacts

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

async def read_artifacts(
    self,
    *,
    artifact_filter: schemas.filters.ArtifactFilter = None,
    flow_run_filter: schemas.filters.FlowRunFilter = None,
    task_run_filter: schemas.filters.TaskRunFilter = None,
    sort: schemas.sorting.ArtifactSort = None,
    limit: int = None,
    offset: int = 0,
) -> List[Artifact]:
    """
    Query the Prefect API for artifacts. Only artifacts matching all criteria will
    be returned.
    Args:
        artifact_filter: filter criteria for artifacts
        flow_run_filter: filter criteria for flow runs
        task_run_filter: filter criteria for task runs
        sort: sort criteria for the artifacts
        limit: limit for the artifact query
        offset: offset for the artifact query
    Returns:
        a list of Artifact model representations of the artifacts
    """
    body = {
        "artifacts": (
            artifact_filter.dict(json_compatible=True) if artifact_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
        ),
        "sort": sort,
        "limit": limit,
        "offset": offset,
    }
    response = await self._client.post("/artifacts/filter", json=body)
    return pydantic.parse_obj_as(List[Artifact], response.json())

read_latest_artifacts async

Query the Prefect API for artifacts. Only artifacts matching all criteria will be returned.

Parameters:

Name	Type	Description	Default
artifact_filter	schemas.filters.ArtifactCollectionFilter	filter criteria for artifacts	None
flow_run_filter	schemas.filters.FlowRunFilter	filter criteria for flow runs	None
task_run_filter	schemas.filters.TaskRunFilter	filter criteria for task runs	None
sort	schemas.sorting.ArtifactCollectionSort	sort criteria for the artifacts	None
limit	int	limit for the artifact query	None
offset	int	offset for the artifact query	0

Returns:

Type	Description
List[ArtifactCollection]	a list of Artifact model representations of the artifacts

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

async def read_latest_artifacts(
    self,
    *,
    artifact_filter: schemas.filters.ArtifactCollectionFilter = None,
    flow_run_filter: schemas.filters.FlowRunFilter = None,
    task_run_filter: schemas.filters.TaskRunFilter = None,
    sort: schemas.sorting.ArtifactCollectionSort = None,
    limit: int = None,
    offset: int = 0,
) -> List[ArtifactCollection]:
    """
    Query the Prefect API for artifacts. Only artifacts matching all criteria will
    be returned.
    Args:
        artifact_filter: filter criteria for artifacts
        flow_run_filter: filter criteria for flow runs
        task_run_filter: filter criteria for task runs
        sort: sort criteria for the artifacts
        limit: limit for the artifact query
        offset: offset for the artifact query
    Returns:
        a list of Artifact model representations of the artifacts
    """
    body = {
        "artifacts": (
            artifact_filter.dict(json_compatible=True) if artifact_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
        ),
        "sort": sort,
        "limit": limit,
        "offset": offset,
    }
    response = await self._client.post("/artifacts/latest/filter", json=body)
    return pydantic.parse_obj_as(List[ArtifactCollection], response.json())

delete_artifact async

Deletes an artifact with the provided id.

Parameters:

Name	Type	Description	Default
artifact_id	UUID	The id of the artifact to delete.	required

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

async def delete_artifact(self, artifact_id: UUID) -> None:
    """
    Deletes an artifact with the provided id.

    Args:
        artifact_id: The id of the artifact to delete.
    """
    try:
        await self._client.delete(f"/artifacts/{artifact_id}")
    except httpx.HTTPStatusError as e:
        if e.response.status_code == 404:
            raise prefect.exceptions.ObjectNotFound(http_exc=e) from e
        else:
            raise

read_variable_by_name async

Reads a variable by name. Returns None if no variable is found.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

async def read_variable_by_name(self, name: str) -> Optional[schemas.core.Variable]:
    """Reads a variable by name. Returns None if no variable is found."""
    try:
        response = await self._client.get(f"/variables/name/{name}")
        return pydantic.parse_obj_as(schemas.core.Variable, response.json())
    except httpx.HTTPStatusError as e:
        if e.response.status_code == status.HTTP_404_NOT_FOUND:
            return None
        else:
            raise

delete_variable_by_name async

Deletes a variable by name.

Source code in /home/runner/work/docs/docs/prefect_source/src/prefect/client/orchestration.py

async def delete_variable_by_name(self, name: str):
    """Deletes a variable by name."""
    try:
        await self._client.delete(f"/variables/name/{name}")
    except httpx.HTTPStatusError as e:
        if e.response.status_code == 404: