在 python 中安排定期的非阻塞任务而不处理 GIL

Question

I've been using Python's schedule module to schedule overlapping tasks that don't block each other; however, the recommended way to achieve non-blocking behavior is by using python's threading module (which of course, is vulnerable to the GIL ).

Quoting from the schedule module's docs :

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(1).seconds.do(run_threaded, job)
schedule.every(2).seconds.do(run_threaded, job)
schedule.every(3).seconds.do(run_threaded, job)
schedule.every(4).seconds.do(run_threaded, job)
schedule.every(5).seconds.do(run_threaded, job)

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

How do we schedule and execute tasks without worrying about the GIL ?

Answer 1

How do we schedule and execute tasks without worrying about the GIL ?

One relatively simple way to solve this problem is to use the multiprocessing module... this gives us cron-like behavior without worrying about GIL issues...

Avoiding GIL issues with multiprocessing is nothing innovative... I'm just documenting here in hopes of helping future googlers...

from multiprocessing import Process
from datetime import datetime
import time

from schedule import Scheduler

class MPScheduler(Scheduler):
    def __init__(self, args=None, kwargs=None):
        if args is None:
            args = ()
        if kwargs is None:
            kwargs = {}
        super(MPScheduler, self).__init__(*args, **kwargs)
        # Among other things, this object inherits self.jobs (a list of jobs)
        self.args = args
        self.kwargs = kwargs
        self.processes = list()

    def _mp_run_job(self, job_func):
        """Spawn another process to run the job; multiprocessing avoids GIL issues"""
        job_process = Process(target=job_func, args=self.args,
            kwargs=self.kwargs)
        job_process.daemon = True
        job_process.start()
        self.processes.append(job_process)

    def run_pending(self):
        """Run any jobs which are ready"""
        runnable_jobs = (job_obj for job_obj in self.jobs if job_obj.should_run)
        for job_obj in sorted(runnable_jobs):
            job_obj.last_run = datetime.now()   # Housekeeping
            self._mp_run_job(job_obj.job_func)
            job_obj._schedule_next_run()        # Schedule the next execution datetime

        self._retire_finished_processes()

    def _retire_finished_processes(self):
        """Walk the list of processes and retire finished processes"""
        retirement_list = list()   # List of process objects to remove
        for idx, process in enumerate(self.processes):
            if process.is_alive():
                # wait a short time for process to finish
                process.join(0.01)
            else:
                retirement_list.append(idx)

        ## Retire finished processes
        for process_idx in sorted(retirement_list, reverse=True):
            self.processes.pop(process_idx)

def job(id, hungry=True):
    print("{} running {} and hungry={}".format(datetime.now(), id, hungry))
    time.sleep(10)   # This job runs without blocking execution of other jobs

if __name__=='__main__':
    # Build a schedule of overlapping jobs...
    mp_sched = MPScheduler()
    mp_sched.every(1).seconds.do(job, id=1, hungry=False)
    mp_sched.every(2).seconds.do(job, id=2)
    mp_sched.every(3).seconds.do(job, id=3)
    mp_sched.every(4).seconds.do(job, id=4)
    mp_sched.every(5).seconds.do(job, id=5)

    while True:
        mp_sched.run_pending()
        time.sleep(1)