APScheduler is a task scheduling library for Python that handles both job queuing and task scheduling across single-process and distributed deployments.
The tool addresses the need to execute tasks at specific times or intervals, whether as one-off jobs, recurring schedules, or queued work. It provides multiple scheduling mechanisms including cron-style patterns, fixed intervals, calendar-based scheduling at consistent times of day, and one-off execution. The library supports both synchronous and asynchronous execution models, making it compatible with traditional thread-based applications as well as asyncio and Trio-based systems. For distributed scenarios, multiple scheduler and worker instances can share a persistent data store and coordinate through an event broker, enabling horizontal scaling and high availability.
The tool suits projects ranging from simple single-process applications to large multi-node deployments. It works with WSGI and ASGI web frameworks. Persistent storage backends include PostgreSQL, MySQL, SQLite, and MongoDB. Event brokers for multi-instance coordination support PostgreSQL, Redis, and MQTT. Beyond basic scheduling, the tool offers job concurrency limits per task, maximum lateness constraints, and jitter to spread load. Custom scheduling logic can be implemented through user-defined trigger classes.
The project maintains active test coverage and documentation. Development follows a structured release process with pre-release versions clearly marked as unsuitable for production use. The codebase supports multiple Python async frameworks and integrates with common web application patterns, indicating ongoing attention to compatibility across the Python ecosystem.
