当前位置: 移动技术网 > IT编程>脚本编程>Python > Python-定时任务APScheduler中两种调度器的区别

Python-定时任务APScheduler中两种调度器的区别

2020年07月30日  | 移动技术网IT编程  | 我要评论

概述

两种调度器BackgroundSchedulerBlockingScheduler的区别

举例说明

APScheduler是python的一个定时任务调度框架,能实现类似linux下crontab类型的任务,使用起来比较方便。它提供基于固定时间间隔、日期以及crontab配置类似的任务调度,并可以持久化任务,或将任务以daemon方式运行。

from apscheduler.schedulers.blocking import BlockingScheduler

def job():
    print('job 3s')

if __name__=='__main__':
    sched = BlockingScheduler(timezone='MST')
    sched.add_job(job, 'interval', id='3_second_job', seconds=3)
    sched.start()

它能实现每隔3s就调度job()运行一次,所以程序每隔3s就输出’job 3s’。通过修改add_job()的参数seconds,就可以改变任务调度的间隔时间。

BlockingSchedulerBackgroundScheduler区别

APScheduler中有很多种不同类型的调度器,BlockingSchedulerBackgroundScheduler是其中最常用的两种调度器。那他们之间有什么区别呢? 简单来说,区别主要在于BlockingScheduler会阻塞主线程的运行,而BackgroundScheduler不会阻塞。所以,我们在不同的情况下,选择不同的调度器:

  • BlockingScheduler: 调用start函数后会阻塞当前线程。当调度器是你应用中唯一要运行的东西时(如上例)使用。
  • BackgroundScheduler: 调用start后主线程不会阻塞。当你不运行任何其他框架时使用,并希望调度器在你应用的后台执行。

下面用两个例子来更直观的说明两者的区别。

  • BlockingScheduler的真实例子
from apscheduler.schedulers.blocking import BlockingScheduler
import time

def job():
    print('job 3s')


if __name__=='__main__':
    sched = BlockingScheduler(timezone='MST')
    sched.add_job(job, 'interval', id='3_second_job', seconds=3)
    sched.start()

    while(True):
        print('main 1s')
        time.sleep(1)

'''
job 3s
job 3s
job 3s
job 3s
'''

 

可见,BlockingScheduler调用start函数后会阻塞当前线程,导致主程序中while循环不会被执行到。

  • BackgroundScheduler的真实例子
from apscheduler.schedulers.background import BackgroundScheduler
import time

def job():
    print('job 3s')


if __name__=='__main__':

    sched = BackgroundScheduler(timezone='MST')
    sched.add_job(job, 'interval', id='3_second_job', seconds=3)
    sched.start()

    while(True):
        print('main 1s')
        time.sleep(1)


'''
main 1s
main 1s
main 1s
job 3s
main 1s
main 1s
main 1s
job 3s
'''

可见,BackgroundScheduler调用start函数后并不会阻塞当前线程,所以可以继续执行主程序中while循环的逻辑。

job执行时间大于定时

from apscheduler.schedulers.background import BackgroundScheduler
import time

def job():
    print('job 3s')
    time.sleep(5)

if __name__=='__main__':

    sched = BackgroundScheduler(timezone='MST')
    sched.add_job(job, 'interval', id='3_second_job', seconds=3)
    sched.start()

    while(True):
        print('main 1s')
        time.sleep(1)

'''
main 1s
main 1s
main 1s
job 3s
main 1s
main 1s
main 1s
Execution of job "job (trigger: interval[0:00:03], next run at: 2018-05-07 02:44:29 MST)" skipped: maximum number of running instances reached (1)
main 1s
main 1s
main 1s
job 3s
main 1s
'''

可见,3s时间到达后,并不会“重新启动一个job线程”,而是会跳过该次调度,等到下一个周期(再等待3s),又重新调度job()。

为了能让多个job()同时运行,我们也可以配置调度器的参数max_instances,如下例,我们允许2个job()同时运行:

from apscheduler.schedulers.background import BackgroundScheduler
import time

def job():
    print('job 3s')
    time.sleep(5)

if __name__=='__main__':
    job_defaults = { 'max_instances': 2 }
    sched = BackgroundScheduler(timezone='MST', job_defaults=job_defaults)
    sched.add_job(job, 'interval', id='3_second_job', seconds=3)
    sched.start()

    while(True):
        print('main 1s')
        time.sleep(1)

'''
main 1s
main 1s
main 1s
job 3s
main 1s
main 1s
main 1s
job 3s
main 1s
main 1s
main 1s
job 3s
'''

每个job是被线程还是进程调度的?

from apscheduler.schedulers.background import BackgroundScheduler
import time,os,threading

def job():
    print('job thread_id-{0}, process_id-{1}'.format(threading.get_ident(), os.getpid()))
    time.sleep(50)

if __name__=='__main__':
    job_defaults = { 'max_instances': 20 }
    sched = BackgroundScheduler(timezone='MST', job_defaults=job_defaults)
    sched.add_job(job, 'interval', id='3_second_job', seconds=3)
    sched.start()

    while(True):
        print('main 1s')
        time.sleep(1)
'''
main 1s
main 1s
main 1s
job thread_id-10644, process_id-8872
main 1s
main 1s
main 1s
job thread_id-3024, process_id-8872
main 1s
main 1s
main 1s
job thread_id-6728, process_id-8872
main 1s
main 1s
main 1s
job thread_id-11716, process_id-8872
'''

可见,每个job()的进程ID都相同,但线程ID不同。所以,job()最终是以线程的方式被调度执行。

参考:https://blog.csdn.net/ybdesire/article/details/82228840

详细:https://www.cnblogs.com/brithToSpring/p/13374911.html

 

本文地址:https://blog.csdn.net/Dorisi_H_n_q/article/details/107658508

如对本文有疑问, 点击进行留言回复!!

相关文章:

验证码:
移动技术网