Python sched Module

last modified March 10, 2025

The sched module in Python is a lightweight tool for scheduling events to run at specific times. It’s great for tasks like periodic jobs or delayed actions in single-threaded apps. This tutorial covers its usage with clear examples.

Unlike threading or multiprocessing, sched is simple and non-blocking, making it ideal for basic timing needs without added complexity.

Basic Usage

This example shows how to schedule a task with a delay.

basic_scheduler.py

import sched import time

def print_message(): print(“Hello, World!”)

scheduler = sched.scheduler(time.time, time.sleep) scheduler.enter(5, 1, print_message) # Run after 5 seconds scheduler.run() # Start the scheduler

Here, scheduler.enter sets the print_message function to run after 5 seconds. scheduler.run executes all scheduled events in order.

Repeating Events

This example creates a task that repeats every 5 seconds.

repeating_events.py

import sched import time

def print_message(): print(f"Tick at {time.ctime()}") scheduler.enter(5, 1, print_message) # Reschedule

scheduler = sched.scheduler(time.time, time.sleep) scheduler.enter(5, 1, print_message) # First run scheduler.run() # Runs indefinitely

The function reschedules itself, forming a loop. Note that scheduler.run blocks until stopped manually.

Priority and Arguments

This example uses priorities and passes arguments to tasks.

priority_arguments.py

import sched import time

def print_message(msg): print(msg)

scheduler = sched.scheduler(time.time, time.sleep) scheduler.enter(5, 2, print_message, (“Low priority”,)) # Priority 2 scheduler.enter(5, 1, print_message, (“High priority”,)) # Priority 1 scheduler.run()

Lower priority numbers run first if times overlap. The argument tuple passes data to the function.

Cancel Scheduled Events

This example cancels a scheduled task before it runs.

cancel_event.py

import sched import time

def print_message(): print(“This won’t run!”)

scheduler = sched.scheduler(time.time, time.sleep) event = scheduler.enter(5, 1, print_message) scheduler.cancel(event) # Remove from queue scheduler.run() # Nothing happens

scheduler.cancel takes an event object and removes it, preventing execution if not yet run.

Advanced: Using Absolute Time

This example schedules a task at an exact time.

absolute_time.py

import sched import time

def print_message(): print(f"Event at {time.ctime()}")

scheduler = sched.scheduler(time.time, time.sleep) run_time = time.time() + 5 # 5 seconds ahead scheduler.enterabs(run_time, 1, print_message) scheduler.run()

scheduler.enterabs uses absolute time (e.g., Unix timestamp) instead of a relative delay.

New Example: Task with Exception Handling

This example safely handles errors in scheduled tasks.

exception_handling.py

import sched import time

def risky_task(): try: result = 10 / 0 # Simulate error except ZeroDivisionError: print(“Caught an error!”)

scheduler = sched.scheduler(time.time, time.sleep) scheduler.enter(3, 1, risky_task) # Run after 3 seconds scheduler.run()

Wrapping tasks in try-except prevents the scheduler from crashing due to unhandled exceptions.

New Example: Scheduled File Cleanup

This example schedules a file deletion task.

file_cleanup.py

import sched import time import os

def cleanup_temp_file(): file = “temp.txt” if os.path.exists(file): os.remove(file) print(f"Deleted {file}") else: print(f"{file} not found")

scheduler = sched.scheduler(time.time, time.sleep) scheduler.enter(5, 1, cleanup_temp_file) scheduler.run()

This simulates a cleanup job, useful for temp files or logs. Check file existence to avoid errors.

Best Practices for sched

• Keep Tasks Light: Use for simple, non-blocking jobs.

• Handle Errors: Add exception handling in tasks.

• Set Priorities: Use priority for same-time events.

• Cancel Events: Remove unneeded tasks to save resources.

• Avoid Blocking: Don’t use for long-running tasks.

• Log Activity: Log events for debugging and monitoring.

Source

Python sched Module Documentation

This tutorial explored the sched module with examples like repeating tasks, priorities, and file cleanup. Follow the best practices for reliable scheduling.

Author

My name is Jan Bodnar, a passionate programmer with years of experience. Since 2007, I’ve written over 1400 articles and 8 e-books, with over eight years teaching programming.

List all Python tutorials.