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prefect.workers.process

Module containing the Process worker used for executing flow runs as subprocesses. To start a Process worker, run the following command: 
prefect worker start --pool 'my-work-pool' --type process
Replace my-work-pool with the name of the work pool you want the worker to poll for flow runs. For more information about work pools and workers, checkout out the Prefect docs.

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Classes

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ProcessJobConfiguration

Methods:

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from_template_and_values 

from_template_and_values(cls, base_job_template: dict[str, Any], values: dict[str, Any], client: 'PrefectClient | None' = None)
Creates a valid worker configuration object from the provided base configuration and overrides. Important: this method expects that the base_job_template was already validated server-side.

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is_using_a_runner 

is_using_a_runner(self) -> bool

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json_template 

json_template(cls) -> dict[str, Any]
Returns a dict with job configuration as keys and the corresponding templates as values Defaults to using the job configuration parameter name as the template variable name. e.g. 
{
    key1: '{{ key1 }}',     # default variable template
    key2: '{{ template2 }}', # `template2` specifically provide as template
}

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prepare_for_flow_run 

prepare_for_flow_run(self, flow_run: 'FlowRun', deployment: 'DeploymentResponse | None' = None, flow: 'APIFlow | None' = None, work_pool: 'WorkPool | None' = None, worker_name: str | None = None) -> None

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prepare_for_flow_run 

prepare_for_flow_run(self, flow_run: 'FlowRun', deployment: 'DeploymentResponse | None' = None, flow: 'APIFlow | None' = None, work_pool: 'WorkPool | None' = None, worker_name: str | None = None) -> None
Prepare the job configuration for a flow run. This method is called by the worker before starting a flow run. It should be used to set any configuration values that are dependent on the flow run. Args:
  • flow_run: The flow run to be executed.
  • deployment: The deployment that the flow run is associated with.
  • flow: The flow that the flow run is associated with.
  • work_pool: The work pool that the flow run is running in.
  • worker_name: The name of the worker that is submitting the flow run.

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validate_working_dir 

validate_working_dir(cls, v: Path | str | None) -> Path | None

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ProcessVariables

Methods:

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model_json_schema 

model_json_schema(cls, by_alias: bool = True, ref_template: str = '#/definitions/{model}', schema_generator: Type[GenerateJsonSchema] = GenerateJsonSchema, mode: Literal['validation', 'serialization'] = 'validation') -> dict[str, Any]
TODO: stop overriding this method - use GenerateSchema in ConfigDict instead?

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ProcessWorkerResult

Contains information about the final state of a completed process

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ProcessWorker

Methods:

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run 

run(self, flow_run: 'FlowRun', configuration: ProcessJobConfiguration, task_status: Optional[anyio.abc.TaskStatus[int]] = None) -> ProcessWorkerResult

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start 

start(self, run_once: bool = False, with_healthcheck: bool = False, printer: Callable[..., None] = print) -> None
Starts the worker and runs the main worker loops. By default, the worker will run loops to poll for scheduled/cancelled flow runs and sync with the Prefect API server. If run_once is set, the worker will only run each loop once and then return. If with_healthcheck is set, the worker will start a healthcheck server which can be used to determine if the worker is still polling for flow runs and restart the worker if necessary. Args:
  • run_once: If set, the worker will only run each loop once then return.
  • with_healthcheck: If set, the worker will start a healthcheck server.
  • printer: A print-like function where logs will be reported.