ContextQMD
Back to Prefect

workers

docs/v3/api-ref/python/prefect-server-models-workers.mdx

3.6.30.dev317.7 KB
Original Source

prefect.server.models.workers

Functions for interacting with worker ORM objects. Intended for internal use by the Prefect REST API.

Functions

create_work_pool <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L48" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
create_work_pool(db: PrefectDBInterface, session: AsyncSession, work_pool: Union[schemas.core.WorkPool, schemas.actions.WorkPoolCreate]) -> orm_models.WorkPool

Creates a work pool.

If a WorkPool with the same name exists, an error will be thrown.

Args:

  • session: a database session
  • work_pool: a WorkPool model

Returns:

  • orm_models.WorkPool: the newly-created WorkPool

read_work_pool <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L93" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
read_work_pool(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID) -> Optional[orm_models.WorkPool]

Reads a WorkPool by id.

Args:

  • session: A database session
  • work_pool_id: a WorkPool id

Returns:

  • orm_models.WorkPool: the WorkPool

read_work_pool_by_name <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L112" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
read_work_pool_by_name(db: PrefectDBInterface, session: AsyncSession, work_pool_name: str) -> Optional[orm_models.WorkPool]

Reads a WorkPool by name.

Args:

  • session: A database session
  • work_pool_name: a WorkPool name

Returns:

  • orm_models.WorkPool: the WorkPool

read_work_pools <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L131" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
read_work_pools(db: PrefectDBInterface, session: AsyncSession, work_pool_filter: Optional[schemas.filters.WorkPoolFilter] = None, offset: Optional[int] = None, limit: Optional[int] = None) -> Sequence[orm_models.WorkPool]

Read worker configs.

Args:

  • session: A database session
  • offset: Query offset
  • limit: Query limit

Returns: List[orm_models.WorkPool]: worker configs

count_work_pools <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L163" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
count_work_pools(db: PrefectDBInterface, session: AsyncSession, work_pool_filter: Optional[schemas.filters.WorkPoolFilter] = None) -> int

Read worker configs.

Args:

  • session: A database session
  • work_pool_filter: filter criteria to apply to the count

Returns: int: the count of work pools matching the criteria

count_work_pool_active_slots <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L196" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
count_work_pool_active_slots(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID) -> int

Count flow runs in slot-occupying states (Pending, Running) for a given work pool. Does not filter on queue pause status — paused queues may still have running/pending runs consuming resources. This matches the behavior of count_work_pool_slot_holders / get_work_pool_slot_holders.

count_work_pool_active_slots_bulk <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L221" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
count_work_pool_active_slots_bulk(db: PrefectDBInterface, session: AsyncSession, work_pool_ids: Sequence[UUID]) -> dict[UUID, int]

Count active slots for multiple work pools in a single query. Returns a mapping of work_pool_id -> active slot count. Does not filter on queue pause status (see count_work_pool_active_slots).

count_work_queue_active_slots <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L252" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
count_work_queue_active_slots(db: PrefectDBInterface, session: AsyncSession, work_queue_id: UUID) -> int

Count flow runs in slot-occupying states (Pending, Running) for a given work queue under a work pool. Counts by work_queue_id FK only.

count_work_queue_active_slots_bulk <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L274" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
count_work_queue_active_slots_bulk(db: PrefectDBInterface, session: AsyncSession, work_queue_ids: Sequence[UUID]) -> dict[UUID, int]

Count active slots for multiple work queues in a single query. Returns a mapping of work_queue_id -> active slot count.

update_work_pool <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L302" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
update_work_pool(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID, work_pool: schemas.actions.WorkPoolUpdate, emit_status_change: Optional[Callable[[UUID, DateTime, orm_models.WorkPool, orm_models.WorkPool], Awaitable[None]]] = None) -> bool

Update a WorkPool by id.

Args:

  • session: A database session
  • work_pool_id: a WorkPool id
  • worker: the work queue data
  • emit_status_change: function to call when work pool status is changed

Returns:

  • whether or not the worker was updated

delete_work_pool <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L423" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
delete_work_pool(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID) -> bool

Delete a WorkPool by id.

Args:

  • session: A database session
  • work_pool_id: a work pool id

Returns:

  • whether or not the WorkPool was deleted

get_scheduled_flow_runs <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L444" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
get_scheduled_flow_runs(db: PrefectDBInterface, session: AsyncSession, work_pool_ids: Optional[List[UUID]] = None, work_queue_ids: Optional[List[UUID]] = None, scheduled_before: Optional[datetime.datetime] = None, scheduled_after: Optional[datetime.datetime] = None, limit: Optional[int] = None, respect_queue_priorities: Optional[bool] = None) -> Sequence[schemas.responses.WorkerFlowRunResponse]

Get runs from queues in a specific work pool.

Args:

  • session: a database session
  • work_pool_ids: a list of work pool ids
  • work_queue_ids: a list of work pool queue ids
  • scheduled_before: a datetime to filter runs scheduled before
  • scheduled_after: a datetime to filter runs scheduled after
  • respect_queue_priorities: whether or not to respect queue priorities
  • limit: the maximum number of runs to return
  • db: a database interface

Returns:

  • List[WorkerFlowRunResponse]: the runs, as well as related work pool details

create_work_queue <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L496" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
create_work_queue(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID, work_queue: schemas.actions.WorkQueueCreate) -> orm_models.WorkQueue

Creates a work pool queue.

Args:

  • session: a database session
  • work_pool_id: a work pool id
  • work_queue: a WorkQueue action model

Returns:

  • orm_models.WorkQueue: the newly-created WorkQueue

bulk_update_work_queue_priorities <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L553" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
bulk_update_work_queue_priorities(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID, new_priorities: Dict[UUID, int]) -> None

This is a brute force update of all work pool queue priorities for a given work pool.

It loads all queues fully into memory, sorts them, and flushes the update to the orm_models. The algorithm ensures that priorities are unique integers > 0, and makes the minimum number of changes required to satisfy the provided new_priorities. For example, if no queues currently have the provided new_priorities, then they are assigned without affecting other queues. If they are held by other queues, then those queues' priorities are incremented as necessary.

Updating queue priorities is not a common operation (happens on the same scale as queue modification, which is significantly less than reading from queues), so while this implementation is slow, it may suffice and make up for that with extreme simplicity.

read_work_queues <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L619" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
read_work_queues(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID, work_queue_filter: Optional[schemas.filters.WorkQueueFilter] = None, offset: Optional[int] = None, limit: Optional[int] = None) -> Sequence[orm_models.WorkQueue]

Read all work pool queues for a work pool. Results are ordered by ascending priority.

Args:

  • session: a database session
  • work_pool_id: a work pool id
  • work_queue_filter: Filter criteria for work pool queues
  • offset: Query offset
  • limit: Query limit

Returns:

  • List[orm_models.WorkQueue]: the WorkQueues

count_work_queues <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L660" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
count_work_queues(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID, work_queue_filter: Optional[schemas.filters.WorkQueueFilter] = None) -> int

Count work pool queues for a work pool.

read_work_queue <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L679" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
read_work_queue(db: PrefectDBInterface, session: AsyncSession, work_queue_id: Union[UUID, PrefectUUID]) -> Optional[orm_models.WorkQueue]

Read a specific work pool queue.

Args:

  • session: a database session
  • work_queue_id: a work pool queue id

Returns:

  • orm_models.WorkQueue: the WorkQueue

read_work_queue_by_name <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L699" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
read_work_queue_by_name(db: PrefectDBInterface, session: AsyncSession, work_pool_name: str, work_queue_name: str) -> Optional[orm_models.WorkQueue]

Reads a WorkQueue by name.

Args:

  • session: A database session
  • work_pool_name: a WorkPool name
  • work_queue_name: a WorkQueue name

Returns:

  • orm_models.WorkQueue: the WorkQueue

update_work_queue <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L733" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
update_work_queue(db: PrefectDBInterface, session: AsyncSession, work_queue_id: UUID, work_queue: schemas.actions.WorkQueueUpdate, emit_status_change: Optional[Callable[[orm_models.WorkQueue], Awaitable[None]]] = None, default_status: WorkQueueStatus = WorkQueueStatus.NOT_READY) -> bool

Update a work pool queue.

Args:

  • session: a database session
  • work_queue_id: a work pool queue ID
  • work_queue: a WorkQueue model
  • emit_status_change: function to call when work queue status is changed

Returns:

  • whether or not the WorkQueue was updated

delete_work_queue <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L857" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
delete_work_queue(db: PrefectDBInterface, session: AsyncSession, work_queue_id: UUID) -> bool

Delete a work pool queue.

Args:

  • session: a database session
  • work_queue_id: a work pool queue ID

Returns:

  • whether or not the WorkQueue was deleted

read_workers <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L905" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
read_workers(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID, worker_filter: Optional[schemas.filters.WorkerFilter] = None, limit: Optional[int] = None, offset: Optional[int] = None) -> Sequence[orm_models.Worker]

worker_heartbeat <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L934" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
worker_heartbeat(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID, worker_name: str, heartbeat_interval_seconds: Optional[int] = None) -> bool

Record a worker process heartbeat.

Args:

  • session: a database session
  • work_pool_id: a work pool ID
  • worker_name: a worker name

Returns:

  • whether or not the worker was updated

delete_worker <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L984" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
delete_worker(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID, worker_name: str) -> bool

Delete a work pool's worker.

Args:

  • session: a database session
  • work_pool_id: a work pool ID
  • worker_name: a worker name

Returns:

  • whether or not the Worker was deleted

count_work_pool_slot_holders <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L1089" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
count_work_pool_slot_holders(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID) -> int

Counts flow runs in slot-occupying states for a work pool.

get_work_pool_slot_holders <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L1106" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
get_work_pool_slot_holders(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID, work_queue_ids: Optional[List[UUID]] = None, flow_run_limit: Optional[int] = None) -> Sequence[tuple[orm_models.FlowRun, Optional[DateTime]]]

Returns flow runs in slot-occupying states for a work pool.

Each result is a tuple of (FlowRun, slot_acquired_at) where slot_acquired_at is when the current slot-occupying sequence began.

Args:

  • work_pool_id: The work pool to query.
  • work_queue_ids: If provided, only return runs for these queues.
  • flow_run_limit: If provided, cap results per work_queue_id.

count_work_pool_slot_holders_by_queue <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L1159" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
count_work_pool_slot_holders_by_queue(db: PrefectDBInterface, session: AsyncSession, work_pool_id: UUID) -> dict[UUID, int]

Returns {work_queue_id: count} for slot-holding runs in a pool.

count_work_queue_slot_holders <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L1192" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
count_work_queue_slot_holders(db: PrefectDBInterface, session: AsyncSession, work_queue_id: UUID) -> int

Counts flow runs in slot-occupying states for a single work queue.

get_work_queue_slot_holders <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L1213" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
get_work_queue_slot_holders(db: PrefectDBInterface, session: AsyncSession, work_queue_id: UUID, offset: Optional[int] = None, limit: Optional[int] = None) -> Sequence[tuple[orm_models.FlowRun, Optional[DateTime]]]

Returns flow runs in slot-occupying states for a single work queue.

Each result is a tuple of (FlowRun, slot_acquired_at) where slot_acquired_at is when the current slot-occupying sequence began.

emit_work_pool_updated_event <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L1247" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
emit_work_pool_updated_event(session: AsyncSession, work_pool: orm_models.WorkPool, changed_fields: Dict[str, Dict[str, Any]]) -> None

Emit an event when work pool fields are updated.

emit_work_pool_status_event <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/server/models/workers.py#L1267" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>

python
emit_work_pool_status_event(event_id: UUID, occurred: DateTime, pre_update_work_pool: Optional[orm_models.WorkPool], work_pool: orm_models.WorkPool) -> None