API reference¶

Data structures¶

class apscheduler.Task(*, id, func, executor, max_running_jobs=None, misfire_grace_time=None, state=None)¶

Represents a callable and its surrounding configuration parameters.

Variables:

id (str) – the unique identifier of this task
func (Callable) – the callable that is called when this task is run
max_running_jobs (int | None) – maximum number of instances of this task that are allowed to run concurrently
misfire_grace_time (timedelta | None) – maximum number of seconds the run time of jobs created for this task are allowed to be late, compared to the scheduled run time

class apscheduler.Schedule(*, id, task_id, trigger, args=(), kwargs=(), coalesce=CoalescePolicy.latest, misfire_grace_time=None, max_jitter=None, tags=(), next_fire_time=None, last_fire_time=None, acquired_by=None, acquired_until=None)¶

Represents a schedule on which a task will be run.

Variables:

id (str) – the unique identifier of this schedule
task_id (str) – unique identifier of the task to be run on this schedule
args (tuple) – positional arguments to pass to the task callable
kwargs (dict[str, Any]) – keyword arguments to pass to the task callable
coalesce (CoalescePolicy) – determines what to do when processing the schedule if multiple fire times have become due for this schedule since the last processing
misfire_grace_time (timedelta | None) – maximum number of seconds the scheduled job’s actual run time is allowed to be late, compared to the scheduled run time
max_jitter (timedelta | None) – maximum number of seconds to randomly add to the scheduled time for each job created from this schedule
tags (frozenset[str]) – strings that can be used to categorize and filter the schedule and its derivative jobs
conflict_policy (ConflictPolicy) – determines what to do if a schedule with the same ID already exists in the data store
next_fire_time (datetime) – the next time the task will be run
last_fire_time (datetime | None) – the last time the task was scheduled to run
acquired_by (str | None) – ID of the scheduler that has acquired this schedule for processing
acquired_until (str | None) – the time after which other schedulers are free to acquire the schedule for processing even if it is still marked as acquired

class apscheduler.Job(*, id=NOTHING, task_id, args=(), kwargs=(), schedule_id=None, scheduled_fire_time=None, jitter=NOTHING, start_deadline=None, result_expiration_time=datetime.timedelta(0), tags=(), created_at=NOTHING, started_at=None, acquired_by=None, acquired_until=None)¶

Represents a queued request to run a task.

Variables:

id (UUID) – autogenerated unique identifier of the job
task_id (str) – unique identifier of the task to be run
args (tuple) – positional arguments to pass to the task callable
kwargs (dict[str, Any]) – keyword arguments to pass to the task callable
schedule_id (str) – unique identifier of the associated schedule (if the job was derived from a schedule)
scheduled_fire_time (datetime | None) – the time the job was scheduled to run at (if the job was derived from a schedule; includes jitter)
jitter (timedelta | None) – the time that was randomly added to the calculated scheduled run time (if the job was derived from a schedule)
start_deadline (datetime | None) – if the job is started in the worker after this time, it is considered to be misfired and will be aborted
result_expiration_time (timedelta) – minimum amount of time to keep the result available for fetching in the data store
tags (frozenset[str]) – strings that can be used to categorize and filter the job
created_at (datetime) – the time at which the job was created
started_at (datetime | None) – the time at which the execution of the job was started
acquired_by (str | None) – the unique identifier of the worker that has acquired the job for execution
acquired_until (str | None) – the time after which other workers are free to acquire the job for processing even if it is still marked as acquired

property original_scheduled_time: datetime | None¶

The scheduled time without any jitter included.

Return type:: datetime | None

class apscheduler.JobInfo(*, job_id, task_id, schedule_id, scheduled_fire_time, jitter, start_deadline, tags)¶

Contains information about the currently running job.

This information is available in the thread or task where a job is currently being run, available from current_job.

Variables:

job_id (UUID) – the unique identifier of the job
task_id (str) – the unique identifier of the task that is being run
schedule_id (str | None) – the unique identifier of the schedule that the job was derived from (if any)
scheduled_fire_time (datetime | None) – the time the job was scheduled to run at (if the job was derived from a schedule; includes jitter)
jitter (timedelta) – the time that was randomly added to the calculated scheduled run time (if the job was derived from a schedule)
start_deadline (datetime | None) – if the job is started in the worker after this time, it is considered to be misfired and will be aborted
tags (frozenset[str]) – strings that can be used to categorize and filter the job

class apscheduler.JobResult(*, job_id, outcome, finished_at=NOTHING, expires_at, exception=None, return_value=None)¶

Represents the result of running a job.

Variables:

job_id (UUID) – the unique identifier of the job
outcome (JobOutcome) – indicates how the job ended
finished_at (datetime) – the time when the job ended
exception (BaseException | None) – the exception object if the job ended due to an exception being raised
return_value – the return value from the task function (if the job ran to completion successfully)

class apscheduler.RetrySettings(*, stop=<tenacity.stop.stop_after_delay object>, wait=<tenacity.wait.wait_exponential object>)¶

Settings for retrying an operation with Tenacity.

Parameters:

stop (stop_base) – defines when to stop trying
wait (wait_base) – defines how long to wait between attempts

Schedulers¶

class apscheduler.schedulers.sync.Scheduler(data_store=None, event_broker=None, *, identity=None, role=SchedulerRole.both, job_executors=None, default_job_executor=None, logger=None)¶

A synchronous scheduler implementation.

start_in_background()¶

Launch the scheduler in a new thread.

This method registers atexit hooks to shut down the scheduler and wait for the thread to finish.

Raises:: RuntimeError – if the scheduler is not in the stopped state
Return type:: None

property state: RunState¶

The current running state of the scheduler.

Return type:: RunState

subscribe(callback, event_types=None, *, one_shot=False)¶

Subscribe to events.

To unsubscribe, call the Subscription.unsubscribe() method on the returned object.

Parameters:

callback – callable to be called with the event object when an event is published
event_types – an iterable of concrete Event classes to subscribe to
one_shot – if True, automatically unsubscribe after the first matching event

class apscheduler.schedulers.async_.AsyncScheduler(*, data_store=NOTHING, event_broker=NOTHING, identity=None, role=SchedulerRole.both, max_concurrent_jobs=100, job_executors=None, default_job_executor=None, logger=<Logger apscheduler.schedulers.async_ (WARNING)>)¶

An asynchronous (AnyIO based) scheduler implementation.

Parameters:

data_store – the data store for tasks, schedules and jobs
event_broker – the event broker to use for publishing an subscribing events
max_concurrent_jobs – Maximum number of jobs the worker will run at once
role – specifies what the scheduler should be doing when running
process_schedules – True to process due schedules in this scheduler

async add_job(func_or_task_id, *, args=None, kwargs=None, job_executor=None, tags=None, result_expiration_time=0)¶

Add a job to the data store.

Parameters:

func_or_task_id (str | Callable) –
job_executor (str | None) – name of the job executor to run the task with
args (Iterable | None) – positional arguments to call the target callable with
kwargs (Mapping[str, Any] | None) – keyword arguments to call the target callable with
job_executor – name of the job executor to run the task with
tags (Iterable[str] | None) – strings that can be used to categorize and filter the job
result_expiration_time (timedelta | float) – the minimum time (as seconds, or timedelta) to keep the result of the job available for fetching (the result won’t be saved at all if that time is 0)

Return type:

UUID

Returns:

the ID of the newly created job

async add_schedule(func_or_task_id, trigger, *, id=None, args=None, kwargs=None, job_executor=None, coalesce=CoalescePolicy.latest, misfire_grace_time=None, max_jitter=None, tags=None, conflict_policy=ConflictPolicy.do_nothing)¶

Schedule a task to be run one or more times in the future.

Parameters:

func_or_task_id (str | Callable) – either a callable or an ID of an existing task definition
trigger (Trigger) – determines the times when the task should be run
id (str | None) – an explicit identifier for the schedule (if omitted, a random, UUID based ID will be assigned)
args (Iterable | None) – positional arguments to be passed to the task function
kwargs (Mapping[str, Any] | None) – keyword arguments to be passed to the task function
job_executor (str | None) – name of the job executor to run the task with
coalesce (CoalescePolicy) – determines what to do when processing the schedule if multiple fire times have become due for this schedule since the last processing
misfire_grace_time (float | timedelta | None) – maximum number of seconds the scheduled job’s actual run time is allowed to be late, compared to the scheduled run time
max_jitter (float | timedelta | None) – maximum number of seconds to randomly add to the scheduled time for each job created from this schedule
tags (Iterable[str] | None) – strings that can be used to categorize and filter the schedule and its derivative jobs
conflict_policy (ConflictPolicy) – determines what to do if a schedule with the same ID already exists in the data store

Return type:

str

Returns:

the ID of the newly added schedule

async get_job_result(job_id, *, wait=True)¶

Retrieve the result of a job.

Parameters:

job_id (UUID) – the ID of the job
wait (bool) – if True, wait until the job has ended (one way or another), False to raise an exception if the result is not yet available

Raises:

JobLookupError – if wait=False and the job result does not exist in the data store

Return type:

JobResult

async get_next_event(event_types)¶

Wait until the next event matching one of the given types arrives.

Parameters:: event_types – an event class or an iterable event classes to subscribe to

async get_schedule(id)¶

Retrieve a schedule from the data store.

Parameters:: id (str) – the unique identifier of the schedule
Raises:: ScheduleLookupError – if the schedule could not be found
Return type:: Schedule

async get_schedules()¶

Retrieve all schedules from the data store.

Returns:: a list of schedules, in an unspecified order

async remove_schedule(id)¶

Remove the given schedule from the data store.

Parameters:: id (str) – the unique identifier of the schedule
Return type:: None

async run_job(func_or_task_id, *, args=None, kwargs=None, job_executor=None, tags=())¶

Convenience method to add a job and then return its result.

If the job raised an exception, that exception will be reraised here.

Parameters:

func_or_task_id (str | Callable) – either a callable or an ID of an existing task definition
args (Iterable | None) – positional arguments to be passed to the task function
kwargs (Mapping[str, Any] | None) – keyword arguments to be passed to the task function
job_executor (str | None) – name of the job executor to run the task with
tags (Iterable[str] | None) – strings that can be used to categorize and filter the job

Return type:

Any

Returns:

the return value of the task function

async run_until_stopped(*, task_status=<anyio._core._tasks._IgnoredTaskStatus object>)¶

Run the scheduler until explicitly stopped.

Return type:: None

property state: RunState¶

The current running state of the scheduler.

Return type:: RunState

async stop()¶

Signal the scheduler that it should stop processing schedules.

This method does not wait for the scheduler to actually stop. For that, see wait_until_stopped().

Return type:: None

subscribe(callback, event_types=None, *, one_shot=False, is_async=True)¶

Subscribe to events.

To unsubscribe, call the Subscription.unsubscribe() method on the returned object.

Parameters:

callback – callable to be called with the event object when an event is published
event_types – an event class or an iterable event classes to subscribe to
one_shot – if True, automatically unsubscribe after the first matching event
is_async – True if the (synchronous) callback should be called on the event loop thread, False if it should be called in a worker thread. If callback is a coroutine function, this flag is ignored.

async wait_until_stopped()¶

Wait until the scheduler is in the “stopped” or “stopping” state.

If the scheduler is already stopped or in the process of stopping, this method returns immediately. Otherwise, it waits until the scheduler posts the SchedulerStopped event.

Return type:: None

Workers¶

Data stores¶

class apscheduler.abc.DataStore¶

Asynchronous version of DataStore. Expected to work on asyncio.

abstract async acquire_jobs(worker_id, limit=None)¶

Acquire unclaimed jobs for execution.

This method claims up to the requested number of jobs for the given worker and returns them.

Parameters:

worker_id (str) – unique identifier of the worker
limit (int | None) – maximum number of jobs to claim and return

Return type:

list[Job]

Returns:

the list of claimed jobs

abstract async acquire_schedules(scheduler_id, limit)¶

Acquire unclaimed due schedules for processing.

This method claims up to the requested number of schedules for the given scheduler and returns them.

Parameters:

scheduler_id – unique identifier of the scheduler
limit – maximum number of schedules to claim

Returns:

the list of claimed schedules

abstract async add_job(job)¶

Add a job to be executed by an eligible worker.

Parameters:: job (Job) – the job object
Return type:: None

abstract async add_schedule(schedule, conflict_policy)¶

Add or update the given schedule in the data store.

Parameters:

schedule (Schedule) – schedule to be added
conflict_policy (ConflictPolicy) – policy that determines what to do if there is an existing schedule with the same ID

Return type:

None

abstract async add_task(task)¶

Add the given task to the store.

If a task with the same ID already exists, it replaces the old one but does NOT affect task accounting (# of running jobs).

Parameters:: task (Task) – the task to be added
Return type:: None

abstract async get_job_result(job_id)¶

Retrieve the result of a job.

The result is removed from the store after retrieval.

Parameters:: job_id (UUID) – the identifier of the job
Return type:: JobResult | None
Returns:: the result, or None if the result was not found

abstract async get_jobs(ids=None)¶

Get the list of pending jobs.

Parameters:: ids (Iterable[UUID] | None) – a specific set of job IDs to return, or None to return all jobs
Return type:: list[Job]
Returns:: the list of matching pending jobs, in the order they will be given to workers

abstract async get_next_schedule_run_time()¶

Return the earliest upcoming run time of all the schedules in the store, or None if there are no active schedules.

Return type:: datetime | None

abstract async get_schedules(ids=None)¶

Get schedules from the data store.

Parameters:: ids – a specific set of schedule IDs to return, or None to return all schedules
Returns:: the list of matching schedules, in unspecified order

abstract async get_task(task_id)¶

Get an existing task definition.

Parameters:: task_id (str) – ID of the task to be returned
Return type:: Task
Returns:: the matching task
Raises:: TaskLookupError – if no matching task was found

abstract async get_tasks()¶

Get all the tasks in this store.

Returns:: a list of tasks, sorted by ID

abstract async release_job(worker_id, task_id, result)¶

Release the claim on the given job and record the result.

Parameters:

worker_id (str) – unique identifier of the worker
task_id (str) – the job’s task ID
result (JobResult) – the result of the job

Return type:

None

abstract async release_schedules(scheduler_id, schedules)¶

Release the claims on the given schedules and update them on the store.

Parameters:

scheduler_id – unique identifier of the scheduler
schedules – the previously claimed schedules

abstract async remove_schedules(ids)¶

Remove schedules from the data store.

Parameters:: ids (Iterable[str]) – a specific set of schedule IDs to remove
Return type:: None

abstract async remove_task(task_id)¶

Remove the task with the given ID.

Parameters:: task_id (str) – ID of the task to be removed
Raises:: TaskLookupError – if no matching task was found
Return type:: None

abstract async start(exit_stack, event_broker)¶

Start the event broker.

Parameters:

exit_stack (AsyncExitStack) – an asynchronous exit stack which will be processed when the scheduler is shut down
event_broker (EventBroker) – the event broker shared between the scheduler, worker (if any) and this data store

Return type:

None

class apscheduler.datastores.memory.MemoryDataStore(tasks=NOTHING, schedules=NOTHING, schedules_by_id=NOTHING, schedules_by_task_id=NOTHING, jobs=NOTHING, jobs_by_id=NOTHING, jobs_by_task_id=NOTHING, job_results=NOTHING, *, lock_expiration_delay=30)¶

Stores scheduler data in memory, without serializing it.

Can be shared between multiple schedulers within the same event loop.

async acquire_jobs(worker_id, limit=None)¶

Acquire unclaimed jobs for execution.

This method claims up to the requested number of jobs for the given worker and returns them.

Parameters:

worker_id (str) – unique identifier of the worker
limit (int | None) – maximum number of jobs to claim and return

Return type:

list[Job]

Returns:

the list of claimed jobs

async acquire_schedules(scheduler_id, limit)¶

Acquire unclaimed due schedules for processing.

This method claims up to the requested number of schedules for the given scheduler and returns them.

Parameters:

scheduler_id – unique identifier of the scheduler
limit – maximum number of schedules to claim

Returns:

the list of claimed schedules

async add_job(job)¶

Add a job to be executed by an eligible worker.

Parameters:: job (Job) – the job object
Return type:: None

async add_schedule(schedule, conflict_policy)¶

Add or update the given schedule in the data store.

Parameters:

schedule (Schedule) – schedule to be added
conflict_policy (ConflictPolicy) – policy that determines what to do if there is an existing schedule with the same ID

Return type:

None

async add_task(task)¶

Add the given task to the store.

If a task with the same ID already exists, it replaces the old one but does NOT affect task accounting (# of running jobs).

Parameters:: task (Task) – the task to be added
Return type:: None

async get_job_result(job_id)¶

Retrieve the result of a job.

The result is removed from the store after retrieval.

Parameters:: job_id (UUID) – the identifier of the job
Return type:: JobResult | None
Returns:: the result, or None if the result was not found

async get_jobs(ids=None)¶

Get the list of pending jobs.

Parameters:: ids (Iterable[UUID] | None) – a specific set of job IDs to return, or None to return all jobs
Return type:: list[Job]
Returns:: the list of matching pending jobs, in the order they will be given to workers

async get_next_schedule_run_time()¶

Return the earliest upcoming run time of all the schedules in the store, or None if there are no active schedules.

Return type:: datetime | None

async get_schedules(ids=None)¶

Get schedules from the data store.

Parameters:: ids – a specific set of schedule IDs to return, or None to return all schedules
Returns:: the list of matching schedules, in unspecified order

async get_task(task_id)¶

Get an existing task definition.

Parameters:: task_id (str) – ID of the task to be returned
Return type:: Task
Returns:: the matching task
Raises:: TaskLookupError – if no matching task was found

async get_tasks()¶

Get all the tasks in this store.

Returns:: a list of tasks, sorted by ID

async release_job(worker_id, task_id, result)¶

Release the claim on the given job and record the result.

Parameters:

worker_id (str) – unique identifier of the worker
task_id (str) – the job’s task ID
result (JobResult) – the result of the job

Return type:

None

async release_schedules(scheduler_id, schedules)¶

Release the claims on the given schedules and update them on the store.

Parameters:

scheduler_id – unique identifier of the scheduler
schedules – the previously claimed schedules

async remove_schedules(ids)¶

Remove schedules from the data store.

Parameters:: ids (Iterable[str]) – a specific set of schedule IDs to remove
Return type:: None

async remove_task(task_id)¶

Remove the task with the given ID.

Parameters:: task_id (str) – ID of the task to be removed
Raises:: TaskLookupError – if no matching task was found
Return type:: None

class apscheduler.datastores.sqlalchemy.SQLAlchemyDataStore(engine, schema=None, max_poll_time=1, max_idle_time=60, *, retry_settings=RetrySettings(stop=<tenacity.stop.stop_after_delay object>, wait=<tenacity.wait.wait_exponential object>), lock_expiration_delay=30, serializer=NOTHING, start_from_scratch=False)¶

Uses a relational database to store data.

When started, this data store creates the appropriate tables on the given database if they’re not already present.

Operations are retried (in accordance to retry_settings) when an operation raises sqlalchemy.OperationalError.

This store has been tested to work with PostgreSQL (asyncpg driver) and MySQL (asyncmy driver).

Parameters:

engine (Engine | AsyncEngine) – an asynchronous SQLAlchemy engine
schema (str | None) – a database schema name to use, if not the default

async acquire_jobs(worker_id, limit=None)¶

Acquire unclaimed jobs for execution.

This method claims up to the requested number of jobs for the given worker and returns them.

Parameters:

worker_id (str) – unique identifier of the worker
limit (int | None) – maximum number of jobs to claim and return

Return type:

list[Job]

Returns:

the list of claimed jobs

async acquire_schedules(scheduler_id, limit)¶

Acquire unclaimed due schedules for processing.

This method claims up to the requested number of schedules for the given scheduler and returns them.

Parameters:

scheduler_id – unique identifier of the scheduler
limit – maximum number of schedules to claim

Returns:

the list of claimed schedules

async add_job(job)¶

Add a job to be executed by an eligible worker.

Parameters:: job (Job) – the job object
Return type:: None

async add_schedule(schedule, conflict_policy)¶

Add or update the given schedule in the data store.

Parameters:

schedule (Schedule) – schedule to be added
conflict_policy (ConflictPolicy) – policy that determines what to do if there is an existing schedule with the same ID

Return type:

None

async add_task(task)¶

Add the given task to the store.

If a task with the same ID already exists, it replaces the old one but does NOT affect task accounting (# of running jobs).

Parameters:: task (Task) – the task to be added
Return type:: None

classmethod from_url(url, **options)¶

Create a new asynchronous SQLAlchemy data store.

Parameters:

url – an SQLAlchemy URL to pass to create_engine() (must use an async dialect like asyncpg or asyncmy)
kwargs – keyword arguments to pass to the initializer of this class

Returns:

the newly created data store

async get_job_result(job_id)¶

Retrieve the result of a job.

The result is removed from the store after retrieval.

Parameters:: job_id (UUID) – the identifier of the job
Return type:: JobResult | None
Returns:: the result, or None if the result was not found

async get_jobs(ids=None)¶

Get the list of pending jobs.

Parameters:: ids (Iterable[UUID] | None) – a specific set of job IDs to return, or None to return all jobs
Return type:: list[Job]
Returns:: the list of matching pending jobs, in the order they will be given to workers

async get_next_schedule_run_time()¶

Return the earliest upcoming run time of all the schedules in the store, or None if there are no active schedules.

Return type:: datetime | None

async get_schedules(ids=None)¶

Get schedules from the data store.

Parameters:: ids – a specific set of schedule IDs to return, or None to return all schedules
Returns:: the list of matching schedules, in unspecified order

async get_task(task_id)¶

Get an existing task definition.

Parameters:: task_id (str) – ID of the task to be returned
Return type:: Task
Returns:: the matching task
Raises:: TaskLookupError – if no matching task was found

async get_tasks()¶

Get all the tasks in this store.

Returns:: a list of tasks, sorted by ID

async release_job(worker_id, task_id, result)¶

Release the claim on the given job and record the result.

Parameters:

worker_id (str) – unique identifier of the worker
task_id (str) – the job’s task ID
result (JobResult) – the result of the job

Return type:

None

async release_schedules(scheduler_id, schedules)¶

Release the claims on the given schedules and update them on the store.

Parameters:

scheduler_id – unique identifier of the scheduler
schedules – the previously claimed schedules

async remove_schedules(ids)¶

Remove schedules from the data store.

Parameters:: ids (Iterable[str]) – a specific set of schedule IDs to remove
Return type:: None

async remove_task(task_id)¶

Remove the task with the given ID.

Parameters:: task_id (str) – ID of the task to be removed
Raises:: TaskLookupError – if no matching task was found
Return type:: None

async start(exit_stack, event_broker)¶

Start the event broker.

Parameters:

exit_stack (AsyncExitStack) – an asynchronous exit stack which will be processed when the scheduler is shut down
event_broker (EventBroker) – the event broker shared between the scheduler, worker (if any) and this data store

Return type:

None

class apscheduler.datastores.mongodb.MongoDBDataStore(client, *, retry_settings=RetrySettings(stop=<tenacity.stop.stop_after_delay object>, wait=<tenacity.wait.wait_exponential object>), lock_expiration_delay=30, serializer=NOTHING, start_from_scratch=False, database='apscheduler')¶

Uses a MongoDB server to store data.

When started, this data store creates the appropriate indexes on the given database if they’re not already present.

Operations are retried (in accordance to retry_settings) when an operation raises pymongo.errors.ConnectionFailure.

Parameters:

client (MongoClient) – a PyMongo client
database (str) – name of the database to use

async acquire_jobs(worker_id, limit=None)¶

Acquire unclaimed jobs for execution.

This method claims up to the requested number of jobs for the given worker and returns them.

Parameters:

worker_id (str) – unique identifier of the worker
limit (int | None) – maximum number of jobs to claim and return

Return type:

list[Job]

Returns:

the list of claimed jobs

async acquire_schedules(scheduler_id, limit)¶

Acquire unclaimed due schedules for processing.

This method claims up to the requested number of schedules for the given scheduler and returns them.

Parameters:

scheduler_id – unique identifier of the scheduler
limit – maximum number of schedules to claim

Returns:

the list of claimed schedules

async add_job(job)¶

Add a job to be executed by an eligible worker.

Parameters:: job (Job) – the job object
Return type:: None

async add_schedule(schedule, conflict_policy)¶

Add or update the given schedule in the data store.

Parameters:

schedule (Schedule) – schedule to be added
conflict_policy (ConflictPolicy) – policy that determines what to do if there is an existing schedule with the same ID

Return type:

None

async add_task(task)¶

Add the given task to the store.

If a task with the same ID already exists, it replaces the old one but does NOT affect task accounting (# of running jobs).

Parameters:: task (Task) – the task to be added
Return type:: None

async get_job_result(job_id)¶

Retrieve the result of a job.

The result is removed from the store after retrieval.

Parameters:: job_id (UUID) – the identifier of the job
Return type:: JobResult | None
Returns:: the result, or None if the result was not found

async get_jobs(ids=None)¶

Get the list of pending jobs.

Parameters:: ids (Iterable[UUID] | None) – a specific set of job IDs to return, or None to return all jobs
Return type:: list[Job]
Returns:: the list of matching pending jobs, in the order they will be given to workers

async get_next_schedule_run_time()¶

Return the earliest upcoming run time of all the schedules in the store, or None if there are no active schedules.

Return type:: datetime | None

async get_schedules(ids=None)¶

Get schedules from the data store.

Parameters:: ids – a specific set of schedule IDs to return, or None to return all schedules
Returns:: the list of matching schedules, in unspecified order

async get_task(task_id)¶

Get an existing task definition.

Parameters:: task_id (str) – ID of the task to be returned
Return type:: Task
Returns:: the matching task
Raises:: TaskLookupError – if no matching task was found

async get_tasks()¶

Get all the tasks in this store.

Returns:: a list of tasks, sorted by ID

async release_job(worker_id, task_id, result)¶

Release the claim on the given job and record the result.

Parameters:

worker_id (str) – unique identifier of the worker
task_id (str) – the job’s task ID
result (JobResult) – the result of the job

Return type:

None

async release_schedules(scheduler_id, schedules)¶

Release the claims on the given schedules and update them on the store.

Parameters:

scheduler_id – unique identifier of the scheduler
schedules – the previously claimed schedules

async remove_schedules(ids)¶

Remove schedules from the data store.

Parameters:: ids (Iterable[str]) – a specific set of schedule IDs to remove
Return type:: None

async remove_task(task_id)¶

Remove the task with the given ID.

Parameters:: task_id (str) – ID of the task to be removed
Raises:: TaskLookupError – if no matching task was found
Return type:: None

async start(exit_stack, event_broker)¶

Start the event broker.

Parameters:

exit_stack (AsyncExitStack) – an asynchronous exit stack which will be processed when the scheduler is shut down
event_broker (EventBroker) – the event broker shared between the scheduler, worker (if any) and this data store

Return type:

None

Event brokers¶

class apscheduler.abc.EventBroker¶

Interface for objects that can be used to publish notifications to interested subscribers.

abstract async publish(event)¶

Publish an event.

Return type:: None

abstract async publish_local(event)¶

Publish an event, but only to local subscribers.

Return type:: None

abstract async start(exit_stack)¶

Start the event broker.

Parameters:: exit_stack (AsyncExitStack) – an asynchronous exit stack which will be processed when the scheduler is shut down
Return type:: None

abstract subscribe(callback, event_types=None, *, is_async=True, one_shot=False)¶

Subscribe to events from this event broker.

Parameters:

callback – callable to be called with the event object when an event is published
event_types – an iterable of concrete Event classes to subscribe to
is_async – True if the (synchronous) callback should be called on the event loop thread, False if it should be called in a worker thread. If the callback is a coroutine function, this flag is ignored.
one_shot – if True, automatically unsubscribe after the first matching event

class apscheduler.eventbrokers.local.LocalEventBroker¶

Asynchronous, local event broker.

This event broker only broadcasts within the process it runs in, and is therefore not suitable for multi-node or multiprocess use cases.

Does not serialize events.

async publish(event)¶

Publish an event.

Return type:: None

class apscheduler.eventbrokers.asyncpg.AsyncpgEventBroker(connection_factory, *, retry_settings=RetrySettings(stop=<tenacity.stop.stop_after_delay object>, wait=<tenacity.wait.wait_exponential object>), serializer=NOTHING, channel='apscheduler', max_idle_time=10)¶

An asynchronous, asyncpg based event broker that uses a PostgreSQL server to broadcast events using its NOTIFY mechanism.

Parameters:

connection_factory (Callable[[], Awaitable[Connection]]) – a callable that creates an asyncpg connection
channel (str) – the NOTIFY channel to use
max_idle_time (float) – maximum time to let the connection go idle, before sending a SELECT 1 query to prevent a connection timeout

classmethod from_async_sqla_engine(engine, options=None, **kwargs)¶

Create a new asyncpg event broker from an SQLAlchemy engine.

The engine will only be used to create the appropriate options for asyncpg.connect().

Parameters:

engine (AsyncEngine) – an asynchronous SQLAlchemy engine using asyncpg as the driver
options (Mapping[str, Any] | None) – extra keyword arguments passed to asyncpg.connect() (will override any automatically generated arguments based on the engine)
kwargs (Any) – keyword arguments to pass to the initializer of this class

Return type:

AsyncpgEventBroker

Returns:

the newly created event broker

classmethod from_dsn(dsn, options=None, **kwargs)¶

Create a new asyncpg event broker from an existing asyncpg connection pool.

Parameters:

dsn – data source name, passed as first positional argument to asyncpg.connect()
options – keyword arguments passed to asyncpg.connect()
kwargs – keyword arguments to pass to the initializer of this class

Returns:

the newly created event broker

async publish(event)¶

Publish an event.

Return type:: None

async start(exit_stack)¶

Start the event broker.

Parameters:: exit_stack (AsyncExitStack) – an asynchronous exit stack which will be processed when the scheduler is shut down
Return type:: None

class apscheduler.eventbrokers.mqtt.MQTTEventBroker(client=NOTHING, *, retry_settings=RetrySettings(stop=<tenacity.stop.stop_after_delay object>, wait=<tenacity.wait.wait_exponential object>), serializer=NOTHING, host='localhost', port=1883, topic='apscheduler', subscribe_qos=0, publish_qos=0)¶

An event broker that uses an MQTT (v3.1 or v5) broker to broadcast events.

Requires the paho-mqtt library to be installed.

Parameters:

client (Client) – a paho-mqtt client
host (str) – host name or IP address to connect to
port (int) – TCP port number to connect to
topic (str) – topic on which to send the messages
subscribe_qos (int) – MQTT QoS to use for subscribing messages
publish_qos (int) – MQTT QoS to use for publishing messages

async publish(event)¶

Publish an event.

Return type:: None

async start(exit_stack)¶

Start the event broker.

Parameters:: exit_stack (AsyncExitStack) – an asynchronous exit stack which will be processed when the scheduler is shut down
Return type:: None

class apscheduler.eventbrokers.redis.RedisEventBroker(client, *, retry_settings=RetrySettings(stop=<tenacity.stop.stop_after_delay object>, wait=<tenacity.wait.wait_exponential object>), serializer=NOTHING, channel='apscheduler', stop_check_interval=1)¶

An event broker that uses a Redis server to broadcast events.

Requires the redis library to be installed.

Parameters:

client (Redis | RedisCluster) – an asynchronous Redis client
channel (str) – channel on which to send the messages
stop_check_interval (float) – interval (in seconds) on which the channel listener should check if it should stop (higher values mean slower reaction time but less CPU use)

classmethod from_url(url, **kwargs)¶

Create a new event broker from a URL.

Parameters:

url (str) – a Redis URL (`redis://...`)
kwargs – keyword arguments to pass to the initializer of this class

Return type:

RedisEventBroker

Returns:

the newly created event broker

async publish(event)¶

Publish an event.

Return type:: None

async start(exit_stack)¶

Start the event broker.

Parameters:: exit_stack (AsyncExitStack) – an asynchronous exit stack which will be processed when the scheduler is shut down
Return type:: None

Serializers¶

class apscheduler.abc.Serializer¶

Interface for classes that implement (de)serialization.

abstract deserialize(serialized)¶

Restore a previously serialized object from bytestring

Parameters:: serialized (bytes) – a bytestring previously received from serialize()
Return type:: Any
Returns:: a copy of the original object

abstract serialize(obj)¶

Turn the given object into a bytestring.

Return type:: bytes
Returns:: a bytestring that can be later restored using deserialize()

class apscheduler.serializers.cbor.CBORSerializer(*, type_tag=4664, dump_options=NOTHING, load_options=NOTHING)¶

Serializes objects using CBOR (RFC 8949).

Can serialize types not normally CBOR serializable, if they implement __getstate__() and __setstate__().

Parameters:

type_tag – CBOR tag number for indicating arbitrary serialized object
dump_options – keyword arguments passed to cbor2.dumps()
load_options – keyword arguments passed to cbor2.loads()

deserialize(serialized)¶

Restore a previously serialized object from bytestring

Parameters:: serialized (bytes) – a bytestring previously received from serialize()
Returns:: a copy of the original object

serialize(obj)¶

Turn the given object into a bytestring.

Return type:: bytes
Returns:: a bytestring that can be later restored using deserialize()

class apscheduler.serializers.json.JSONSerializer(*, magic_key='_apscheduler_json', dump_options=NOTHING, load_options=NOTHING)¶

Serializes objects using JSON.

Can serialize types not normally CBOR serializable, if they implement __getstate__() and __setstate__(). These objects are serialized into dicts that contain the necessary information for deserialization in magic_key.

Parameters:

magic_key – name of a specially handled dict key that indicates that a dict contains a serialized instance of an arbitrary type
dump_options – keyword arguments passed to json.dumps()
load_options – keyword arguments passed to json.loads()

deserialize(serialized)¶

Restore a previously serialized object from bytestring

Parameters:: serialized (bytes) – a bytestring previously received from serialize()
Returns:: a copy of the original object

serialize(obj)¶

Turn the given object into a bytestring.

Return type:: bytes
Returns:: a bytestring that can be later restored using deserialize()

class apscheduler.serializers.pickle.PickleSerializer(*, protocol=4)¶

Uses the pickle module to (de)serialize objects.

As this serialization method is native to Python, it is able to serialize a wide range of types, at the expense of being insecure. Do not use this serializer unless you can fully trust the entire system to not have maliciously injected data. Such data can be made to call arbitrary functions with arbitrary arguments on unpickling.

Parameters:: protocol (int) – the pickle protocol number to use

deserialize(serialized)¶

Restore a previously serialized object from bytestring

Parameters:: serialized (bytes) – a bytestring previously received from serialize()
Returns:: a copy of the original object

serialize(obj)¶

Turn the given object into a bytestring.

Return type:: bytes
Returns:: a bytestring that can be later restored using deserialize()

Triggers¶

class apscheduler.abc.Trigger(*args, **kwds)¶

Abstract base class that defines the interface that every trigger must implement.

abstract next()¶

Return the next datetime to fire on.

If no such datetime can be calculated, None is returned. :raises apscheduler.exceptions.MaxIterationsReached:

Return type:: datetime | None

class apscheduler.triggers.date.DateTrigger(run_time)¶

Triggers once on the given date/time.

Parameters:: run_time (datetime | str | None) – the date/time to run the job at

next()¶

Return the next datetime to fire on.

If no such datetime can be calculated, None is returned. :raises apscheduler.exceptions.MaxIterationsReached:

Return type:: datetime | None

class apscheduler.triggers.interval.IntervalTrigger(*, weeks=0, days=0, hours=0, minutes=0, seconds=0, microseconds=0, start_time=NOTHING, end_time=None)¶

Triggers on specified intervals.

The first trigger time is on start_time which is the moment the trigger was created unless specifically overridden. If end_time is specified, the last trigger time will be at or before that time. If no end_time has been given, the trigger will produce new trigger times as long as the resulting datetimes are valid datetimes in Python.

Parameters:

weeks (float) – number of weeks to wait
days (float) – number of days to wait
hours (float) – number of hours to wait
minutes (float) – number of minutes to wait
seconds (float) – number of seconds to wait
microseconds (float) – number of microseconds to wait
start_time (datetime | str | None) – first trigger date/time (defaults to current date/time if omitted)
end_time (datetime | str | None) – latest possible date/time to trigger on

next()¶

Return the next datetime to fire on.

If no such datetime can be calculated, None is returned. :raises apscheduler.exceptions.MaxIterationsReached:

Return type:: datetime | None

class apscheduler.triggers.calendarinterval.CalendarIntervalTrigger(*, years=0, months=0, weeks=0, days=0, hour=0, minute=0, second=0, start_date=NOTHING, end_date=None, timezone='local')¶

Runs the task on specified calendar-based intervals always at the same exact time of day.

When calculating the next date, the years and months parameters are first added to the previous date while keeping the day of the month constant. This is repeated until the resulting date is valid. After that, the weeks and days parameters are added to that date. Finally, the date is combined with the given time (hour, minute, second) to form the final datetime.

This means that if the days or weeks parameters are not used, the task will always be executed on the same day of the month at the same wall clock time, assuming the date and time are valid.

If the resulting datetime is invalid due to a daylight saving forward shift, the date is discarded and the process moves on to the next date. If instead the datetime is ambiguous due to a backward DST shift, the earlier of the two resulting datetimes is used.

If no previous run time is specified when requesting a new run time (like when starting for the first time or resuming after being paused), start_date is used as a reference and the next valid datetime equal to or later than the current time will be returned. Otherwise, the next valid datetime starting from the previous run time is returned, even if it’s in the past.

Warning

Be wary of setting a start date near the end of the month (29. – 31.) if you have months specified in your interval, as this will skip the months when those days do not exist. Likewise, setting the start date on the leap day (February 29th) and having years` defined may cause some years to be skipped.

Users are also discouraged from using a time inside the target timezone’s DST switching period (typically around 2 am) since a date could either be skipped or repeated due to the specified wall clock time either occurring twice or not at all.

Parameters:

years (int) – number of years to wait
months (int) – number of months to wait
weeks (int) – number of weeks to wait
days (int) – number of days to wait
hour (int) – hour to run the task at
minute (int) – minute to run the task at
second (int) – second to run the task at
start_date (date | str | None) – first date to trigger on (defaults to current date if omitted)
end_date (date | str | None) – latest possible date to trigger on
timezone (str | tzinfo | None) – time zone to use for calculating the next fire time

next()¶

Return the next datetime to fire on.

If no such datetime can be calculated, None is returned. :raises apscheduler.exceptions.MaxIterationsReached:

Return type:: datetime | None

class apscheduler.triggers.combining.AndTrigger(triggers, threshold=1, max_iterations=10000)¶

Fires on times produced by the enclosed triggers whenever the fire times are within the given threshold.

If the produced fire times are not within the given threshold of each other, the trigger(s) that produced the earliest fire time will be asked for their next fire time and the iteration is restarted. If instead all the triggers agree on a fire time, all the triggers are asked for their next fire times and the earliest of the previously produced fire times will be returned.

This trigger will be finished when any of the enclosed trigger has finished.

Parameters:

triggers – triggers to combine
threshold – maximum time difference between the next fire times of the triggers in order for the earliest of them to be returned from next() (in seconds, or as timedelta)
max_iterations – maximum number of iterations of fire time calculations before giving up

next()¶

Return the next datetime to fire on.

If no such datetime can be calculated, None is returned. :raises apscheduler.exceptions.MaxIterationsReached:

Return type:: datetime | None

class apscheduler.triggers.combining.OrTrigger(triggers)¶

Fires on every fire time of every trigger in chronological order. If two or more triggers produce the same fire time, it will only be used once.

This trigger will be finished when none of the enclosed triggers can produce any new fire times.

Parameters:: triggers – triggers to combine

next()¶

Return the next datetime to fire on.

If no such datetime can be calculated, None is returned. :raises apscheduler.exceptions.MaxIterationsReached:

Return type:: datetime | None

class apscheduler.triggers.cron.CronTrigger(*, year=None, month=None, day=None, week=None, day_of_week=None, hour=None, minute=None, second=None, start_time=NOTHING, end_time=None, timezone=NOTHING)¶

Triggers when current time matches all specified time constraints, similarly to how the UNIX cron scheduler works.

Parameters:

year (int | str | None) – 4-digit year
month (int | str | None) – month (1-12)
day (int | str | None) – day of the (1-31)
week (int | str | None) – ISO week (1-53)
day_of_week (int | str | None) – number or name of weekday (0-7 or sun,mon,tue,wed,thu,fri,sat, sun)
hour (int | str | None) – hour (0-23)
minute (int | str | None) – minute (0-59)
second (int | str | None) – second (0-59)
start_time (datetime | str | None) – earliest possible date/time to trigger on (defaults to current time)
end_time (datetime | None) – latest possible date/time to trigger on
timezone (str | tzinfo | None) – time zone to use for the date/time calculations (defaults to the local timezone)

Note

The first weekday is always monday.

classmethod from_crontab(expr, timezone='local')¶

Create a CronTrigger from a standard crontab expression.

See https://en.wikipedia.org/wiki/Cron for more information on the format accepted here.

Parameters:

expr (str) – minute, hour, day of month, month, day of week
timezone (str | tzinfo) – time zone to use for the date/time calculations (defaults to local timezone if omitted)

Return type:

CronTrigger

next()¶

Return the next datetime to fire on.

If no such datetime can be calculated, None is returned. :raises apscheduler.exceptions.MaxIterationsReached:

Return type:: datetime | None

Events¶

class apscheduler.Event(*, timestamp=NOTHING)¶

Base class for all events.

Variables:: timestamp – the time when the event occurrent

class apscheduler.DataStoreEvent(*, timestamp=NOTHING)¶: Base class for events originating from a data store.

class apscheduler.TaskAdded(*, timestamp=NOTHING, task_id)¶

Signals that a new task was added to the store.

Variables:: task_id – ID of the task that was added

class apscheduler.TaskUpdated(*, timestamp=NOTHING, task_id)¶

Signals that a task was updated in a data store.

Variables:: task_id – ID of the task that was updated

class apscheduler.TaskRemoved(*, timestamp=NOTHING, task_id)¶

Signals that a task was removed from the store.

Variables:: task_id – ID of the task that was removed

class apscheduler.ScheduleAdded(*, timestamp=NOTHING, schedule_id, next_fire_time)¶

Signals that a new schedule was added to the store.

Variables:

schedule_id – ID of the schedule that was added
next_fire_time – the first run time calculated for the schedule

class apscheduler.ScheduleUpdated(*, timestamp=NOTHING, schedule_id, next_fire_time)¶

Signals that a schedule has been updated in the store.

Variables:

schedule_id – ID of the schedule that was updated
next_fire_time – the next time the schedule will run

class apscheduler.ScheduleRemoved(*, timestamp=NOTHING, schedule_id)¶

Signals that a schedule was removed from the store.

Variables:: schedule_id – ID of the schedule that was removed

class apscheduler.JobAdded(*, timestamp=NOTHING, job_id, task_id, schedule_id, tags)¶

Signals that a new job was added to the store.

Variables:

job_id – ID of the job that was added
task_id – ID of the task the job would run
schedule_id – ID of the schedule the job was created from
tags – the set of tags collected from the associated task and schedule

class apscheduler.JobRemoved(*, timestamp=NOTHING, job_id)¶

Signals that a job was removed from the store.

Variables:: job_id – ID of the job that was removed

class apscheduler.ScheduleDeserializationFailed(*, timestamp=NOTHING, schedule_id, exception)¶

Signals that the deserialization of a schedule has failed.

Variables:

schedule_id – ID of the schedule that failed to deserialize
exception – the exception that was raised during deserialization

class apscheduler.JobDeserializationFailed(*, timestamp=NOTHING, job_id, exception)¶

Signals that the deserialization of a job has failed.

Variables:

job_id – ID of the job that failed to deserialize
exception – the exception that was raised during deserialization

class apscheduler.SchedulerEvent(*, timestamp=NOTHING)¶: Base class for events originating from a scheduler.

class apscheduler.SchedulerStarted(*, timestamp=NOTHING)¶

class apscheduler.SchedulerStopped(*, timestamp=NOTHING, exception=None)¶

Signals that a scheduler has stopped.

Variables:: exception – the exception that caused the scheduler to stop, if any

class apscheduler.JobAcquired(*, timestamp=NOTHING, job_id, worker_id)¶

Signals that a worker has acquired a job for processing.

Parameters:

job_id (UUID | str) – the ID of the job that was acquired
worker_id (str) – the ID of the worker that acquired the job

class apscheduler.JobReleased(*, timestamp=NOTHING, job_id, worker_id, outcome, exception_type=None, exception_message=None, exception_traceback=None)¶

Signals that a worker has finished processing of a job.

Parameters:

job_id (UUID | str) – the ID of the job that was released
worker_id (str) – the ID of the worker that released the job
outcome (TEnum | str) – the outcome of the job
exception_type (str | None) – the fully qualified name of the exception if outcome is JobOutcome.error
exception_message (str | None) – the result of str(exception) if outcome is JobOutcome.error
exception_traceback (list[str] | None) – the traceback lines from the exception if outcome is JobOutcome.error

Enumerated types¶

class apscheduler.RunState(value)¶

Used to track the running state of schedulers and workers.

Values:

starting: not running yet, but in the process of starting
started: running
stopping: still running but in the process of shutting down
stopped: not running

class apscheduler.JobOutcome(value)¶

Used to indicate how the execution of a job ended.

Values:

success: the job completed successfully
error: the job raised an exception
missed_start_deadline: the job’s execution was delayed enough for it to miss its deadline
cancelled: the job’s execution was cancelled

class apscheduler.ConflictPolicy(value)¶

Used to indicate what to do when trying to add a schedule whose ID conflicts with an existing schedule.

Values:

replace: replace the existing schedule with a new one
do_nothing: keep the existing schedule as-is and drop the new schedule
exception: raise an exception if a conflict is detected

class apscheduler.CoalescePolicy(value)¶

Used to indicate how to queue jobs for a schedule that has accumulated multiple run times since the last scheduler iteration.

Values:

earliest: run once, with the earliest fire time
latest: run once, with the latest fire time
all: submit one job for every accumulated fire time

Context variables¶

See the contextvars module for information on how to work with context variables.

apscheduler.current_scheduler the current scheduler: ContextVar[Union[Scheduler, AsyncScheduler]]¶

apscheduler.current_worker the current scheduler: ContextVar[Union[Worker, AsyncWorker]]¶

apscheduler.current_job information on the job being currently run: ContextVar[JobInfo]¶

Exceptions¶

exception apscheduler.TaskLookupError(task_id)¶: Raised by a data store when it cannot find the requested task.

exception apscheduler.ScheduleLookupError(schedule_id)¶: Raised by a scheduler when it cannot find the requested schedule.

exception apscheduler.JobLookupError(job_id)¶: Raised when the job store cannot find a job for update or removal.

exception apscheduler.JobResultNotReady(job_id)¶: Raised by get_job_result() if the job result is not ready.

exception apscheduler.JobCancelled¶: Raised by get_job_result() if the job was cancelled.

exception apscheduler.JobDeadlineMissed¶: Raised by get_job_result() if the job failed to start within the allotted time.

exception apscheduler.ConflictingIdError(schedule_id)¶: Raised when trying to add a schedule to a store that already contains a schedule by that ID, and the conflict policy of exception is used.

exception apscheduler.SerializationError¶: Raised when a serializer fails to serialize the given object.

exception apscheduler.DeserializationError¶: Raised when a serializer fails to deserialize the given object.

exception apscheduler.MaxIterationsReached¶: Raised when a trigger has reached its maximum number of allowed computation iterations when trying to calculate the next fire time.

API reference¶

Data structures¶

Schedulers¶

Workers¶

Data stores¶

Event brokers¶

Serializers¶

Triggers¶

Events¶

Enumerated types¶

Context variables¶

Exceptions¶

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