FAQ.rst

Frequently Asked Questions

Frequently asked questions on the usage of schedule.

How to execute jobs in parallel?

I am trying to execute 50 items every 10 seconds, but from the my logs it says it executes every item in 10 second schedule serially, is there a work around?

By default, schedule executes all jobs serially. The reasoning behind this is that it would be difficult to find a model for parallel execution that makes everyone happy.

You can work around this restriction by running each of the jobs in its own thread:

import threading
import time
import schedule


def job():
    print("I'm running on thread %s" % threading.current_thread())


def run_threaded(job_func):
    job_thread = threading.Thread(target=job_func)
    job_thread.start()


schedule.every(10).seconds.do(run_threaded, job)
schedule.every(10).seconds.do(run_threaded, job)
schedule.every(10).seconds.do(run_threaded, job)
schedule.every(10).seconds.do(run_threaded, job)
schedule.every(10).seconds.do(run_threaded, job)


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

If you want tighter control on the number of threads use a shared jobqueue and one or more worker threads:

import Queue
import time
import threading
import schedule


def job():
    print("I'm working")


def worker_main():
    while 1:
        job_func = jobqueue.get()
        job_func()
        jobqueue.task_done()

jobqueue = Queue.Queue()

schedule.every(10).seconds.do(jobqueue.put, job)
schedule.every(10).seconds.do(jobqueue.put, job)
schedule.every(10).seconds.do(jobqueue.put, job)
schedule.every(10).seconds.do(jobqueue.put, job)
schedule.every(10).seconds.do(jobqueue.put, job)

worker_thread = threading.Thread(target=worker_main)
worker_thread.start()

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

This model also makes sense for a distributed application where the workers are separate processes that receive jobs from a distributed work queue. I like using beanstalkd with the beanstalkc Python library.

How to continuously run the scheduler without blocking the main thread?

Run the scheduler in a separate thread. Mrwhick wrote up a nice solution in to this problem here (look for run_continuously())

Does schedule support timezones?

Vanilla schedule doesn't support timezones at the moment. If you need this functionality please check out @imiric's work here. He added timezone support to schedule using python-dateutil.

What if my task throws an exception?

Schedule doesn't catch exceptions that happen during job execution. Therefore any exceptions thrown during job execution will bubble up and interrupt schedule's run_xyz function.

If you want to guard against exceptions you can wrap your job function in a decorator like this:

import functools

def catch_exceptions(cancel_on_failure=False):
    def catch_exceptions_decorator(job_func):
        @functools.wraps(job_func)
        def wrapper(*args, **kwargs):
            try:
                return job_func(*args, **kwargs)
            except:
                import traceback
                print(traceback.format_exc())
                if cancel_on_failure:
                    return schedule.CancelJob
        return wrapper
    return catch_exceptions_decorator

@catch_exceptions(cancel_on_failure=True)
def bad_task():
    return 1 / 0

schedule.every(5).minutes.do(bad_task)

Another option would be to subclass Schedule like @mplewis did in this example.

How can I run a job only once?

def job_that_executes_once():
    # Do some work ...
    return schedule.CancelJob

schedule.every().day.at('22:30').do(job_that_executes_once)

How can I cancel several jobs at once?

You can cancel the scheduling of a group of jobs selecting them by a unique identifier.

def greet(name):
    print('Hello {}'.format(name))

schedule.every().day.do(greet, 'Andrea').tag('daily-tasks', 'friend')
schedule.every().hour.do(greet, 'John').tag('hourly-tasks', 'friend')
schedule.every().hour.do(greet, 'Monica').tag('hourly-tasks', 'customer')
schedule.every().day.do(greet, 'Derek').tag('daily-tasks', 'guest')

schedule.clear('daily-tasks')

Will prevent every job tagged as daily-tasks from running again.

I'm getting an AttributeError: 'module' object has no attribute 'every' when I try to use schedule. How can I fix this?

This happens if your code imports the wrong schedule module. Make sure you don't have a schedule.py file in your project that overrides the schedule module provided by this library.

How can I add generic logging to my scheduled jobs?

The easiest way to add generic logging functionality to your schedule job functions is to implement a decorator that handles logging in a reusable way:

import functools
import time

import schedule


# This decorator can be applied to
def with_logging(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        print('LOG: Running job "%s"' % func.__name__)
        result = func(*args, **kwargs)
        print('LOG: Job "%s" completed' % func.__name__)
        return result
    return wrapper

@with_logging
def job():
    print('Hello, World.')

schedule.every(3).seconds.do(job)

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

How to run a job at random intervals?

def my_job():
    # This job will execute every 5 to 10 seconds.
    print('Foo')

schedule.every(5).to(10).seconds.do(my_job)

How can I pass arguments to the job function?

do() passes extra arguments to the job function:

def greet(name):
    print('Hello', name)

schedule.every(2).seconds.do(greet, name='Alice')
schedule.every(4).seconds.do(greet, name='Bob')

How can I make sure long-running jobs are always executed on time?

Schedule does not account for the time it takes the job function to execute. To guarantee a stable execution schedule you need to move long-running jobs off the main-thread (where the scheduler runs). See "How to execute jobs in parallel?" in the FAQ for a sample implementation.