Warning
The v4.0 series is provided as a pre-release and may change in a backwards incompatible fashion without any migration pathway, so do NOT use this release in production!
Advanced Python Scheduler (APScheduler) is a task scheduler and task queue system for Python. It can be used solely as a job queuing system if you have no need for task scheduling. It scales both up and down, and is suitable for both trivial, single-process use cases as well as large deployments spanning multiple nodes. Multiple schedulers and workers can be deployed to use a shared data store to provide both a degree of high availability and horizontal scaling.
APScheduler comes in both synchronous and asynchronous flavors, making it a good fit for both traditional, thread-based applications, and asynchronous (asyncio or Trio) applications. Documentation and examples are provided for integrating with either WSGI or ASGI compatible web applications.
Support is provided for persistent storage of schedules and jobs. This means that they can be shared among multiple scheduler/worker instances and will survive process and node restarts.
The built-in persistent data store back-ends are:
The built-in event brokers (needed in scenarios with multiple schedulers and/or workers):
The built-in scheduling mechanisms (triggers) are:
Different scheduling mechanisms can even be combined with so-called combining triggers (see the documentation for details).
You can also implement your custom scheduling logic by building your own trigger class. These will be treated no differently than the built-in ones.
Other notable features include:
Documentation can be found here.
The source can be browsed at Github.
A bug tracker is provided by GitHub.
If you have problems or other questions, you can either:
apscheduler
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