Hatchet Python SDK Reference
This is the Python SDK reference, documenting methods available for interacting with Hatchet resources. Check out the user guide for an introduction for getting your first tasks running.
The Hatchet Python Client
Main client for interacting with the Hatchet SDK.
This class provides access to various client interfaces and utility methods for working with Hatchet workers, workflows, tasks, and our various feature clients.
Methods:
| Name | Description |
|---|---|
worker | Create a Hatchet worker on which to run workflows. |
workflow | Define a Hatchet workflow, which can then declare tasks and be run, scheduled, and so on. |
task | A decorator to transform a function into a standalone Hatchet task that runs as part of a workflow. |
durable_task | A decorator to transform a function into a standalone Hatchet durable task that runs as part of a workflow. |
Attributes
cron
The cron client is a client for managing cron workflows within Hatchet.
event
The event client, which you can use to push events to Hatchet.
logs
The logs client is a client for interacting with Hatchet’s logs API.
metrics
The metrics client is a client for reading metrics out of Hatchet’s metrics API.
rate_limits
The rate limits client is a wrapper for Hatchet’s gRPC API that makes it easier to work with rate limits in Hatchet.
runs
The runs client is a client for interacting with task and workflow runs within Hatchet.
scheduled
The scheduled client is a client for managing scheduled workflows within Hatchet.
workers
The workers client is a client for managing workers programmatically within Hatchet.
workflows
The workflows client is a client for managing workflows programmatically within Hatchet.
Note that workflows are the declaration, not the individual runs. If you’re looking for runs, use the RunsClient instead.
tenant_id
The tenant id you’re operating in.
namespace
The current namespace you’re interacting with.
Functions
worker
Create a Hatchet worker on which to run workflows.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
name | str | The name of the worker. | required |
slots | int | The number of workflow slots on the worker. In other words, the number of concurrent tasks the worker can run at any point in time | 100 |
durable_slots | int | The number of durable workflow slots on the worker. In other words, the number of concurrent tasks the worker can run at any point in time that are durable. | 1000 |
labels | dict[str, Union[str, int]] | A dictionary of labels to assign to the worker. For more details, view examples on affinity and worker labels. | {} |
workflows | list[BaseWorkflow[Any]] | A list of workflows to register on the worker, as a shorthand for calling register_workflow on each or register_workflows on all of them. | [] |
lifespan | LifespanFn | None | A lifespan function to run on the worker. This function will be called when the worker is started, and can be used to perform any setup or teardown tasks. | None |
Returns:
| Type | Description |
|---|---|
Worker | The created Worker object, which exposes an instance method start which can be called to start the worker. |
workflow
Define a Hatchet workflow, which can then declare tasks and be run, scheduled, and so on.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
name | str | The name of the workflow. | required |
description | str | None | A description for the workflow | None |
input_validator | Type[TWorkflowInput] | None | A Pydantic model to use as a validator for the input to the tasks in the workflow. If no validator is provided, defaults to an EmptyModel under the hood. The EmptyModel is a Pydantic model with no fields specified, and with the extra config option set to "allow". | None |
on_events | list[str] | A list of event triggers for the workflow - events which cause the workflow to be run. | [] |
on_crons | list[str] | A list of cron triggers for the workflow. | [] |
version | str | None | A version for the workflow | None |
sticky | StickyStrategy | None | A sticky strategy for the workflow | None |
default_priority | int | The priority of the workflow. Higher values will cause this workflow to have priority in scheduling over other, lower priority ones. | 1 |
concurrency | ConcurrencyExpression | list[ConcurrencyExpression] | None | A concurrency object controlling the concurrency settings for this workflow. | None |
task_defaults | TaskDefaults | A TaskDefaults object controlling the default task settings for this workflow. | TaskDefaults() |
Returns:
| Type | Description |
|---|---|
Workflow[EmptyModel] | Workflow[TWorkflowInput] | The created Workflow object, which can be used to declare tasks, run the workflow, and so on. |
task
A decorator to transform a function into a standalone Hatchet task that runs as part of a workflow.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
name | str | The name of the task. If not specified, defaults to the name of the function being wrapped by the task decorator. | required |
description | str | None | An optional description for the task. | None |
input_validator | Type[TWorkflowInput] | None | A Pydantic model to use as a validator for the input to the task. If no validator is provided, defaults to an EmptyModel. | None |
on_events | list[str] | A list of event triggers for the task - events which cause the task to be run. | [] |
on_crons | list[str] | A list of cron triggers for the task. | [] |
version | str | None | A version for the task. | None |
sticky | StickyStrategy | None | A sticky strategy for the task. | None |
default_priority | int | The priority of the task. Higher values will cause this task to have priority in scheduling. | 1 |
concurrency | ConcurrencyExpression | list[ConcurrencyExpression] | None | A concurrency object controlling the concurrency settings for this task. | None |
schedule_timeout | Duration | The maximum time allowed for scheduling the task. | DEFAULT_SCHEDULE_TIMEOUT |
execution_timeout | Duration | The maximum time allowed for executing the task. | DEFAULT_EXECUTION_TIMEOUT |
retries | int | The number of times to retry the task before failing. | 0 |
rate_limits | list[RateLimit] | A list of rate limit configurations for the task. | [] |
desired_worker_labels | dict[str, DesiredWorkerLabel] | A dictionary of desired worker labels that determine to which worker the task should be assigned. | {} |
backoff_factor | float | None | The backoff factor for controlling exponential backoff in retries. | None |
backoff_max_seconds | int | None | The maximum number of seconds to allow retries with exponential backoff to continue. | None |
Returns:
| Type | Description |
|---|---|
Callable[[Callable[[EmptyModel, Context], R]], Standalone[EmptyModel, R]] | Callable[[Callable[[TWorkflowInput, Context], R]], Standalone[TWorkflowInput, R]] | A decorator which creates a Standalone task object. |
durable_task
A decorator to transform a function into a standalone Hatchet durable task that runs as part of a workflow.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
name | str | The name of the task. If not specified, defaults to the name of the function being wrapped by the task decorator. | required |
description | str | None | An optional description for the task. | None |
input_validator | Type[TWorkflowInput] | None | A Pydantic model to use as a validator for the input to the task. If no validator is provided, defaults to an EmptyModel. | None |
on_events | list[str] | A list of event triggers for the task - events which cause the task to be run. | [] |
on_crons | list[str] | A list of cron triggers for the task. | [] |
version | str | None | A version for the task. | None |
sticky | StickyStrategy | None | A sticky strategy for the task. | None |
default_priority | int | The priority of the task. Higher values will cause this task to have priority in scheduling. | 1 |
concurrency | ConcurrencyExpression | None | A concurrency object controlling the concurrency settings for this task. | None |
schedule_timeout | Duration | The maximum time allowed for scheduling the task. | DEFAULT_SCHEDULE_TIMEOUT |
execution_timeout | Duration | The maximum time allowed for executing the task. | DEFAULT_EXECUTION_TIMEOUT |
retries | int | The number of times to retry the task before failing. | 0 |
rate_limits | list[RateLimit] | A list of rate limit configurations for the task. | [] |
desired_worker_labels | dict[str, DesiredWorkerLabel] | A dictionary of desired worker labels that determine to which worker the task should be assigned. | {} |
backoff_factor | float | None | The backoff factor for controlling exponential backoff in retries. | None |
backoff_max_seconds | int | None | The maximum number of seconds to allow retries with exponential backoff to continue. | None |
Returns:
| Type | Description |
|---|---|
Callable[[Callable[[EmptyModel, DurableContext], R]], Standalone[EmptyModel, R]] | Callable[[Callable[[TWorkflowInput, DurableContext], R]], Standalone[TWorkflowInput, R]] | A decorator which creates a Standalone task object. |