schedule (Python)
Human-friendly Python job scheduler. Provides a simple fluent API for scheduling Python functions: `schedule.every(10).minutes.do(job)`. Jobs run in the same process via polling loop. Extremely simple alternative to APScheduler or Celery Beat for basic periodic task execution without external dependencies. No daemon process, no persistence, no distributed execution.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Zero dependency library. No external calls. Security depends on what the scheduled functions do.
⚡ Reliability
Best When
You need simple in-process periodic job execution in Python with a human-readable API and no external dependencies.
Avoid When
You need job persistence across restarts, distributed execution, or high reliability — use APScheduler, Celery Beat, or a proper cron daemon.
Use Cases
- • Schedule simple periodic tasks in Python scripts (data fetches, cleanup jobs, health checks) without complex scheduler infrastructure
- • Add basic cron-like scheduling to agent scripts that poll external services at regular intervals
- • Run periodic maintenance tasks in long-running Python processes (servers, agents) with minimal setup
- • Schedule Python functions in development and testing environments where APScheduler is overkill
- • Implement recurring reminder or notification jobs in Python applications that run continuously
Not For
- • Production distributed task scheduling — use Celery, APScheduler, or Temporal for reliability and persistence
- • Jobs that must survive process restarts — schedule runs in-process with no persistence; restarts lose all jobs
- • High-precision timing requirements — schedule polls approximately, not exactly; use asyncio.sleep or APScheduler for precise timing
Interface
Authentication
Pure Python library. No authentication required.
Pricing
MIT license. Created by Daniel Bader.
Agent Metadata
Known Gotchas
- ⚠ schedule requires a polling loop: while True: schedule.run_pending(); time.sleep(1) — forgetting the loop means jobs never run
- ⚠ Jobs run synchronously in the polling thread — long-running jobs block subsequent scheduled jobs; use threading.Thread or asyncio for concurrent execution
- ⚠ No persistence — all scheduled jobs are lost on process restart; any persistent scheduling requires re-registering jobs at startup
- ⚠ Exceptions in job functions are silently swallowed by default — wrap job functions with try/except or use schedule's logger to catch failures
- ⚠ schedule uses approximate polling intervals — the sleep(1) in the loop means job timing can drift by up to 1 second per interval
- ⚠ Thread safety: schedule's default global scheduler is not thread-safe — use separate Scheduler() instances per thread or protect with locks
Alternatives
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Scores are editorial opinions as of 2026-03-06.