Cron Jobs with Python's schedule Library and APScheduler

System cron is great for independent scripts, but when your scheduled task needs to live inside a running Python application — sharing a database pool, an in-memory cache, or application config — an in-process scheduler is often simpler. Python has two popular options: the tiny schedule library for simple cases, and APScheduler for anything that needs real cron syntax or persistence.

Option 1: the schedule library (simple, readable, no cron syntax)

Install with pip install schedule. It uses a fluent, human-readable API instead of cron strings — great for small scripts and simple intervals:

import schedule
import time

def sync_orders():
    print("Syncing orders...")

def send_daily_report():
    print("Sending daily report...")

schedule.every(10).minutes.do(sync_orders)
schedule.every().day.at("09:00").do(send_daily_report)
schedule.every().monday.at("07:30").do(lambda: print("Weekly cleanup"))

while True:
    schedule.run_pending()
    time.sleep(1)

The catch: schedule requires you to keep a process alive running that while True loop — nothing runs unless your script is actively executing. It also has no built-in persistence, so scheduled state resets every time the process restarts, and there's no native way to write full cron expressions like 0 9 * * 1-5.

Option 2: APScheduler (real cron syntax, background execution, persistence)

Install with pip install apscheduler. APScheduler supports three trigger types — interval, date (one-off), and cron — and can run jobs in a background thread inside a long-running app like a Flask or FastAPI service:

from apscheduler.schedulers.background import BackgroundScheduler
from apscheduler.triggers.cron import CronTrigger

scheduler = BackgroundScheduler(timezone="Asia/Kolkata")

def sync_orders():
    print("Syncing orders...")

# Real cron-style fields as keyword arguments
scheduler.add_job(sync_orders, CronTrigger(minute="*/10"))

# 9:00 AM on weekdays — equivalent to cron "0 9 * * 1-5"
scheduler.add_job(
    lambda: print("Weekday report"),
    CronTrigger(hour=9, minute=0, day_of_week="mon-fri"),
)

# Parse a traditional 5-field cron string directly
scheduler.add_job(
    lambda: print("Midnight backup"),
    CronTrigger.from_crontab("0 0 * * *"),
)

scheduler.start()

Persisting jobs across restarts

APScheduler can store job definitions in a database (SQLite, PostgreSQL, Redis) via a job store, so scheduled jobs survive an app restart instead of being redefined only in code:

from apscheduler.schedulers.background import BackgroundScheduler
from apscheduler.jobstores.sqlalchemy import SQLAlchemyJobStore

scheduler = BackgroundScheduler(
    jobstores={'default': SQLAlchemyJobStore(url='sqlite:///jobs.sqlite')}
)
scheduler.start()

Choosing between schedule, APScheduler, and system cron

• schedule — quick scripts, single-server, don't need real cron syntax, comfortable keeping a process alive.
• APScheduler — need real cron expressions, background execution inside a bigger app, or persistence across restarts.
• System cron — jobs are standalone scripts, you want the OS itself (not your app process) to guarantee execution, and you don't need to share Python in-memory state.

A common production pattern on Linux is actually hybrid: use system cron to invoke a lightweight Python entrypoint script for reliability and OS-level guarantees, and use APScheduler only for schedules that must live and adapt inside a running web service (e.g. schedules configurable by end users at runtime).

Frequently Asked Questions