---
id: apscheduler
version: "3.11.3"
license: MIT
license_treatment: permissive
maintenance: active
---

# APScheduler — In-process task scheduler with Cron-like capabilities

License: permissive · Maintenance: active · Popularity: top 1,000 on PyPI

## Install

pip install apscheduler
uv add apscheduler
poetry add apscheduler

## Description

.. image:: https://github.com/agronholm/apscheduler/workflows/Python%20codeqa/test/badge.svg?branch=3.x
  :target: https://github.com/agronholm/apscheduler/actions?query=workflow%3A%22Python+codeqa%2Ftest%22+branch%3A3.x
  :alt: Build Status
.. image:: https://coveralls.io/repos/github/agronholm/apscheduler/badge.svg?branch=3.x
  :target: https://coveralls.io/github/agronholm/apscheduler?branch=3.x
  :alt: Code Coverage
.. image:: https://readthedocs.org/projects/apscheduler/badge/?version=3.x
  :target: https://apscheduler.readthedocs.io/en/master/?badge=3.x
  :alt: Documentation

Advanced Python Scheduler (APScheduler) is a Python library that lets you schedule your Python code
to be executed later, either just once or periodically. You can add new jobs or remove old ones on
the fly as you please. If you store your jobs in a database, they will also survive scheduler
restarts and maintain their state. When the scheduler is restarted, it will then run all the jobs
it should have run while it was offline [#f1]_.

Among other things, APScheduler can be used as a cross-platform, application specific replacement
to platform specific schedulers, such as the cron daemon or the...

## AI interpretation — verify before relying

APScheduler is an in-process task scheduler that lets you run Python code on a schedule—once, at intervals, or using cron expressions—with support for persistent job storage and multiple execution frameworks.

Verdict: APScheduler is a mature, well-maintained production-grade scheduler with no known vulnerabilities, minimal dependencies, and broad framework integration. Its permissive MIT license and active development make it a reliable choice for embedding scheduling into Python applications.

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