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Logging
=======
Schedule logs messages to the Python logger named ``schedule`` at ``DEBUG`` level.
To receive logs from Schedule, set the logging level to ``DEBUG``.
.. code-block:: python
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:
.. code-block:: text
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:
.. code-block:: python
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:
.. code-block:: text
LOG: Running job "job"
Hello, Logs
LOG: Job "job" completed in 5 seconds
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