Schedules - Python SDK feature guide
This page shows how to do the following:
Schedule a Workflow
How to Schedule a Workflow Execution
Scheduling Workflows is a crucial aspect of any automation process, especially when dealing with time-sensitive tasks. By scheduling a Workflow, you can automate repetitive tasks, reduce the need for manual intervention, and ensure timely execution of your business processes
Use any of the following action to help Schedule a Workflow Execution and take control over your automation process.
Create a Scheduled Workflow
How to create a Scheduled Workflow
The create action enables you to create a new Schedule. When you create a new Schedule, a unique Schedule ID is generated, which you can use to reference the Schedule in other Schedule commands.
To create a Scheduled Workflow Execution in Python, use the create_schedule()
asynchronous method on the Client.
Then pass the Schedule ID and the Schedule object to the method to create a Scheduled Workflow Execution.
Set the action parameter to ScheduleActionStartWorkflow to start a Workflow Execution.
Optionally, you can set the spec parameter to ScheduleSpec to specify the schedule or set the intervals parameter to ScheduleIntervalSpec to specify the interval.
Other options include: cron_expressions, skip, start_at, and jitter.
View the source code
in the context of the rest of the application code.
# ...
async def main():
client = await Client.connect("localhost:7233")
await client.create_schedule(
"workflow-schedule-id",
Schedule(
action=ScheduleActionStartWorkflow(
YourSchedulesWorkflow.run,
"my schedule arg",
id="schedules-workflow-id",
task_queue="schedules-task-queue",
),
spec=ScheduleSpec(
intervals=[ScheduleIntervalSpec(every=timedelta(minutes=2))]
),
state=ScheduleState(note="Here's a note on my Schedule."),
),
)
Backfill a Scheduled Workflow
How to backfill a Scheduled Workflow
The backfill action executes Actions ahead of their specified time range. This command is useful when you need to execute a missed or delayed Action, or when you want to test the Workflow before its scheduled time.
To Backfill a Scheduled Workflow Execution in Python, use the backfill() asynchronous method on the Schedule Handle.
View the source code
in the context of the rest of the application code.
import asyncio
from datetime import datetime, timedelta
from temporalio.client import Client, ScheduleBackfill, ScheduleOverlapPolicy
async def main():
client = await Client.connect("localhost:7233")
handle = client.get_schedule_handle(
"workflow-schedule-id",
)
now = datetime.utcnow()
(
await handle.backfill(
ScheduleBackfill(
start_at=now - timedelta(minutes=10),
end_at=now - timedelta(minutes=9),
overlap=ScheduleOverlapPolicy.ALLOW_ALL,
),
),
)
Delete a Scheduled Workflow
How to delete a Scheduled Workflow
The delete action enables you to delete a Schedule. When you delete a Schedule, it does not affect any Workflows that were started by the Schedule.
To delete a Scheduled Workflow Execution in Python, use the delete() asynchronous method on the Schedule Handle.
View the source code
in the context of the rest of the application code.
async def main():
client = await Client.connect("localhost:7233")
handle = client.get_schedule_handle(
"workflow-schedule-id",
)
await handle.delete()
Describe a Scheduled Workflow
How to describe a Scheduled Workflow
The describe action shows the current Schedule configuration, including information about past, current, and future Workflow Runs. This command is helpful when you want to get a detailed view of the Schedule and its associated Workflow Runs.
To describe a Scheduled Workflow Execution in Python, use the describe() asynchronous method on the Schedule Handle. You can get a complete list of the attributes of the Scheduled Workflow Execution from the ScheduleDescription class.
View the source code
in the context of the rest of the application code.
# ...
async def main():
client = await Client.connect("localhost:7233")
handle = client.get_schedule_handle(
"workflow-schedule-id",
)
desc = await handle.describe()
print(f"Returns the note: {desc.schedule.state.note}")
List a Scheduled Workflow
How to list a Scheduled Workflow
The list action lists all the available Schedules. This command is useful when you want to view a list of all the Schedules and their respective Schedule IDs.
To list all schedules, use the list_schedules() asynchronous method on the Client. If a schedule is added or deleted, it may not be available in the list immediately.
View the source code
in the context of the rest of the application code.
# ...
async def main() -> None:
client = await Client.connect("localhost:7233")
async for schedule in await client.list_schedules():
print(f"List Schedule Info: {schedule.info}.")
Pause a Scheduled Workflow
How to pause a Scheduled Workflow
The pause action enables you to pause and unpause a Schedule. When you pause a Schedule, all the future Workflow Runs associated with the Schedule are temporarily stopped. This command is useful when you want to temporarily halt a Workflow due to maintenance or any other reason.
To pause a Scheduled Workflow Execution in Python, use the pause() asynchronous method on the Schedule Handle.
You can pass a note to the pause() method to provide a reason for pausing the schedule.
View the source code
in the context of the rest of the application code.
# ...
async def main():
client = await Client.connect("localhost:7233")
handle = client.get_schedule_handle(
"workflow-schedule-id",
)
await handle.pause(note="Pausing the schedule for now")
Trigger a Scheduled Workflow
How to trigger a Scheduled Workflow
The trigger action triggers an immediate action with a given Schedule. By default, this action is subject to the Overlap Policy of the Schedule. This command is helpful when you want to execute a Workflow outside of its scheduled time.
To trigger a Scheduled Workflow Execution in Python, use the trigger() asynchronous method on the Schedule Handle.
View the source code
in the context of the rest of the application code.
# ...
async def main():
client = await Client.connect("localhost:7233")
handle = client.get_schedule_handle(
"workflow-schedule-id",
)
await handle.trigger()
Update a Scheduled Workflow
How to update a Scheduled Workflow
The update action enables you to update an existing Schedule. This command is useful when you need to modify the Schedule's configuration, such as changing the start time, end time, or interval.
Create a function that takes ScheduleUpdateInput and returns ScheduleUpdate.
To update a Schedule, use a callback to build the update from the description.
The following example updates the Schedule to use a new argument.
View the source code
in the context of the rest of the application code.
# ...
async def update_schedule_simple(input: ScheduleUpdateInput) -> ScheduleUpdate:
schedule_action = input.description.schedule.action
if isinstance(schedule_action, ScheduleActionStartWorkflow):
schedule_action.args = ["my new schedule arg"]
return ScheduleUpdate(schedule=input.description.schedule)
Temporal Cron Jobs
How to use Temporal Cron Jobs
We recommend using Schedules instead of Cron Jobs. Schedules were built to provide a better developer experience, including more configuration options and the ability to update or pause running Schedules.
A Temporal Cron Job is the series of Workflow Executions that occur when a Cron Schedule is provided in the call to spawn a Workflow Execution.
A Cron Schedule is provided as an option when the call to spawn a Workflow Execution is made.
You can set each Workflow to repeat on a schedule with the cron_schedule option from either the start_workflow() or execute_workflow() asynchronous methods.
View the source code
in the context of the rest of the application code.
# ...
result = await client.execute_workflow(
CronWorkflow.run,
id="your-workflow-id",
task_queue="your-task-queue",
cron_schedule="* * * * *",
)
print(f"Results: {result}")
Start Delay
How to use Start Delay
Use the start_delay to schedule a Workflow Execution at a specific one-time future point rather than on a recurring schedule.
Use the start_delay option in either the start_workflow() or execute_workflow() asynchronous methods in the Client.
async def main():
client = await Client.connect("localhost:7233")
result = await client.execute_workflow(
YourWorkflow.run,
"your name",
id="your-workflow-id",
task_queue="your-task-queue",
start_delay=timedelta(hours=1, minutes=20, seconds=30)
)
print(f"Result: {result}")
if __name__ == "__main__":
asyncio.run(main())