Logging

Schedule logs messages to the Python logger named schedule at DEBUG level. To receive logs from Schedule, set the logging level to DEBUG.

import schedule
import logging

logging.basicConfig()
schedule_logger = logging.getLogger('schedule')
schedule_logger.setLevel(level=logging.DEBUG)

def job():
    print("Hello, Logs")

schedule.every().second.do(job)

schedule.run_all()

schedule.clear()

This will result in the following log messages:

DEBUG:schedule:Running *all* 1 jobs with 0s delay in between
DEBUG:schedule:Running job Job(interval=1, unit=seconds, do=job, args=(), kwargs={})
Hello, Logs
DEBUG:schedule:Deleting *all* jobs

Customize logging

The easiest way to add reusable logging to jobs is to implement a decorator that handles logging. As an example, below code adds the print_elapsed_time decorator:

import functools
import time
import schedule

# This decorator can be applied to any job function to log the elapsed time of each job
def print_elapsed_time(func):
    @functools.wraps(func)
    def wrapper(*args, **kwargs):
        start_timestamp = time.time()
        print('LOG: Running job "%s"' % func.__name__)
        result = func(*args, **kwargs)
        print('LOG: Job "%s" completed in %d seconds' % (func.__name__, time.time() - start_timestamp))
        return result

    return wrapper


@print_elapsed_time
def job():
    print('Hello, Logs')
    time.sleep(5)

schedule.every().second.do(job)

schedule.run_all()

This outputs:

LOG: Running job "job"
Hello, Logs
LOG: Job "job" completed in 5 seconds