Frequently asked questions on the usage of schedule
.
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.
Run the scheduler in a separate thread. Mrwhick wrote up a nice solution in to this problem here (look for run_continuously()
)
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.
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(job_func, cancel_on_failure=False):
@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
@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.
def job_that_executes_once():
# Do some work ...
return schedule.CancelJob
schedule.every().day.at('22:30').do(job_that_executes_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.
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)
def my_job():
# This job will execute every 5 to 10 seconds.
print('Foo')
schedule.every(5).to(10).seconds.do(my_job)
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')