from apscheduler.schedulers.blocking import BlockingScheduler
scheduler = BlockingScheduler()
def worker():
print("hello scheduler")
scheduler.add_job(worker, 'cron', day_of_week='0-6', hour=00, minute=00, second=00)
scheduler.start()
import time
from apscheduler.schedulers.blocking import BlockingScheduler
def my_job():
print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
scheduler = BlockingScheduler()
scheduler.add_job(my_job, 'cron', second='*/5')
scheduler.add_job(my_job, 'cron', minute='*/5')
scheduler.add_job(my_job, 'cron', hour='*/5')
scheduler.add_job(my_job, 'cron', year=2017, month=3, day=22, hour=17, minute=19, second=7)
scheduler.add_job(my_job, 'cron', month='6-8,11-12', day='3rd fri', hour='0-3')
scheduler.add_job(my_job(), 'cron', day_of_week='mon-fri', hour=5, minute=30, end_date='2020-05-30')
scheduler.start()
1、while循环中使用sleep
缺点:不容易控制,而且是个阻塞函数
def timer(n):
'''''
每n秒执行一次
while True:
print(time.strftime('%Y-%m-%d %X',time.localtime()))
yourTask()
time.sleep(n)
2、schedule模块
优点:可以管理和调度多个任务,可以进行控制
缺点:阻塞式函数
import schedule
import time
import datetime
def job1():
print('Job1:每隔10秒执行一次的任务,每次执行2秒')
print('Job1-startTime:%s' %(datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
time.sleep(2)
print('Job1-endTime:%s' % (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
print('------------------------------------------------------------------------')
def job2():
print('Job2:每隔30秒执行一次,每次执行5秒')
print('Job2-startTime:%s' % (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
time.sleep(5)
print('Job2-endTime:%s' % (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
print('------------------------------------------------------------------------')
def job3():
print('Job3:每隔1分钟执行一次,每次执行10秒')
print('Job3-startTime:%s' % (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
time.sleep(10)
print('Job3-endTime:%s' % (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
print('------------------------------------------------------------------------')
def job4():
print('Job4:每天下午17:49执行一次,每次执行20秒')
print('Job4-startTime:%s' % (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
time.sleep(20)
print('Job4-endTime:%s' % (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
print('------------------------------------------------------------------------')
def job5():
print('Job5:每隔5秒到10秒执行一次,每次执行3秒')
print('Job5-startTime:%s' % (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
time.sleep(3)
print('Job5-endTime:%s' % (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
print('------------------------------------------------------------------------')
if __name__ == '__main__':
schedule.every(10).seconds.do(job1)
schedule.every(30).seconds.do(job2)
schedule.every(1).minutes.do(job3)
schedule.every().day.at('17:49').do(job4)
schedule.every(5).to(10).seconds.do(job5)
while True:
schedule.run_pending()
3、Threading模块中的Timer
优点:非阻塞
缺点:不易管理多个任务
from threading import Timer
import datetime
def printHello():
print('TimeNow:%s' % (datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
t = Timer(2, printHello)
t.start()
if __name__ == "__main__":
printHello()
4、sched模块
sched模块实现了一个时间调度程序,该程序可以通过单线程执行来处理按照时间尺度进行调度的时间。
通过调用
scheduler.enter(delay,priority,func,args)
函数,可以将一个任务添加到任务队列里面,当指定的时间到了,就会执行任务(
func函数
)。
delay
:任务的间隔时间。
priority
:如果几个任务被调度到相同的时间执行,将按照priority的增序执行这几个任务。
func
:要执行的任务函数
args
:func的参数
import time, sched
import datetime
s = sched.scheduler(time.time, time.sleep)
def print_time(a='default'):
print('Now Time:',datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'),a)
def print_some_times():
print(datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
s.enter(10,1,print_time)
s.enter(5,2,print_time,argument=('positional',))
s.run()
print(datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
print_some_times()
执行结果为:
2018-09-20 16:25:03
Now Time: 2018-09-20 16:25:08 positional
Now Time: 2018-09-20 16:25:13 default
2018-09-20 16:25:13
Process finished with exit code 0
按顺序执行任务:
import time, sched
import datetime
s = sched.scheduler(time.time, time.sleep)
def event_fun1():
print("func1 Time:", datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
def perform1(inc):
s.enter(inc, 0, perform1, (inc,))
event_fun1()
def event_fun2():
print("func2 Time:", datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
def perform2(inc):
s.enter(inc, 0, perform2, (inc,))
event_fun2()
def mymain(func, inc=2):
if func == "1":
s.enter(0, 0, perform1, (10,))
if func == "2":
s.enter(0, 0, perform2, (20,))
if __name__ == '__main__':
mymain('1')
mymain('2')
s.run()
执行结果为:
E:\virtualenv\pachong\Scripts\python.exe F:/workspace/project_01/demo_09.py
func1 Time: 2018-09-20 16:30:28
func2 Time: 2018-09-20 16:30:28
func1 Time: 2018-09-20 16:30:38
func2 Time: 2018-09-20 16:30:48
func1 Time: 2018-09-20 16:30:48
func1 Time: 2018-09-20 16:30:58
func2 Time: 2018-09-20 16:31:08
func1 Time: 2018-09-20 16:31:08
func1 Time: 2018-09-20 16:31:18
func2 Time: 2018-09-20 16:31:28
func1 Time: 2018-09-20 16:31:28
func1 Time: 2018-09-20 16:31:38
s.run()会阻塞当前线程的执行
t=threading.Thread(target=s.run)
t.start()
也可以用
s.cancal(action)
来取消sched中的某个action
5、定时框架APScheduler
APSScheduler是python的一个定时任务框架,它提供了基于日期date、固定时间间隔interval、以及linux上的crontab类型的定时任务。该矿机不仅可以添加、删除定时任务,还可以将任务存储到数据库中、实现任务的持久化。
APScheduler有四种组件:
triggers(触发器):触发器包含调度逻辑,每一个作业有它自己的触发器,用于决定接下来哪一个作业会运行,除了他们自己初始化配置外,触发器完全是无状态的。
job stores
(作业存储):用来存储被调度的作业,默认的作业存储器是简单地把作业任务保存在内存中,其它作业存储器可以将任务作业保存到各种数据库中,支持MongoDB、Redis、SQLAlchemy存储方式。当对作业任务进行持久化存储的时候,作业的数据将被序列化,重新读取作业时在反序列化。
executors
(执行器):执行器用来执行定时任务,只是将需要执行的任务放在新的线程或者线程池中运行。当作业任务完成时,执行器将会通知调度器。对于执行器,默认情况下选择ThreadPoolExecutor就可以了,但是如果涉及到一下特殊任务如比较消耗CPU的任务则可以选择ProcessPoolExecutor,当然根据根据实际需求可以同时使用两种执行器。
schedulers
(调度器):调度器是将其它部分联系在一起,一般在应用程序中只有一个调度器,应用开发者不会直接操作触发器、任务存储以及执行器,相反调度器提供了处理的接口。通过调度器完成任务的存储以及执行器的配置操作,如可以添加。修改、移除任务作业。
APScheduler提供了七种调度器:
BlockingScheduler:适合于只在进程中运行单个任务的情况,通常在调度器是你唯一要运行的东西时使用。
BackgroundScheduler: 适合于要求任何在程序后台运行的情况,当希望调度器在应用后台执行时使用。
AsyncIOScheduler:适合于使用asyncio异步框架的情况
GeventScheduler: 适合于使用gevent框架的情况
TornadoScheduler: 适合于使用Tornado框架的应用
TwistedScheduler: 适合使用Twisted框架的应用
QtScheduler: 适合使用QT的情况
APScheduler提供了四种存储方式:
MemoryJobStore
sqlalchemy
mongodb
redis
APScheduler提供了三种任务触发器:
data
:固定日期触发器:任务只运行一次,运行完毕自动清除;若错过指定运行时间,任务不会被创建
interval
:时间间隔触发器
cron
:cron风格的任务触发
import time
from apscheduler.schedulers.blocking import BlockingScheduler
def job():
print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
if __name__ == '__main__':
scheduler = BlockingScheduler()
scheduler.add_job(job, 'interval', seconds=5)
scheduler.start()
import time
from apscheduler.schedulers.blocking import BlockingScheduler
def job():
print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
if __name__ == '__main__':
scheduler = BlockingScheduler()
scheduler.add_job(job, 'date', run_date='2018-09-21 15:30:00')
scheduler.start()
import time
from apscheduler.schedulers.background import BackgroundScheduler
def job():
print('job:', time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
if __name__ == '__main__':
scheduler = BackgroundScheduler()
scheduler.add_job(job, 'interval', seconds=3)
scheduler.start()
while True:
print('main-start:', time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
time.sleep(2)
print('main-end:', time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
运行结果为:
main-start: 2018-09-21 15:54:28
main-end: 2018-09-21 15:54:30
main-start: 2018-09-21 15:54:30
job: 2018-09-21 15:54:31
main-end: 2018-09-21 15:54:32
main-start: 2018-09-21 15:54:32
main-end: 2018-09-21 15:54:34
main-start: 2018-09-21 15:54:34
job: 2018-09-21 15:54:34
main-end: 2018-09-21 15:54:36
main-start: 2018-09-21 15:54:36
import time
from apscheduler.schedulers.background import BackgroundScheduler
def job():
print('job:', time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
if __name__ == '__main__':
scheduler = BackgroundScheduler()
scheduler.add_job(job, 'date', run_date='2018-09-21 15:53:00')
scheduler.start()
while True:
print('main-start:', time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
time.sleep(2)
print('main-end:', time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
运行结果为:
main-start: 2018-09-21 15:52:57
main-end: 2018-09-21 15:52:59
main-start: 2018-09-21 15:52:59
job: 2018-09-21 15:53:00
main-end: 2018-09-21 15:53:01
import time
from apscheduler.schedulers.background import BackgroundScheduler
def job():
print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
if __name__ == '__main__':
scheduler = BackgroundScheduler()
scheduler.add_job(job, 'cron', day_of_week='fri', second='*/5')
year (int|str) – 4-digit year
month (int|str) – month (1-12)
day (int|str) – day of the (1-31)
week (int|str) – ISO week (1-53)
day_of_week (int|str) – number or name of weekday (0-6 or mon,tue,wed,thu,fri,sat,sun)
hour (int|str) – hour (0-23)
minute (int|str) – minute (0-59)
econd (int|str) – second (0-59)
start_date (datetime|str) – earliest possible date/time to trigger on (inclusive)
end_date (datetime|str) – latest possible date/time to trigger on (inclusive)
timezone (datetime.tzinfo|str) – time zone to use for the date/time calculations (defaults to scheduler timezone)
* any Fire on every value
*/a any Fire every a values, starting from the minimum
a-b any Fire on any value within the a-b range (a must be smaller than b)
a-b/c any Fire every c values within the a-b range
xth y day Fire on the x -th occurrence of weekday y within the month
last x day Fire on the last occurrence of weekday x within the month
last day Fire on the last day within the month
x,y,z any Fire on any matching expression; can combine any number of any of the above expressions
scheduler.start()
while True:
print('main-start:', time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
time.sleep(2)
print('main-end:', time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
运行结果:
main-start: 2018-09-21 16:02:55
main-end: 2018-09-21 16:02:57
main-start: 2018-09-21 16:02:57
main-end: 2018-09-21 16:02:59
main-start: 2018-09-21 16:02:59
2018-09-21 16:03:00
main-end: 2018-09-21 16:03:01
main-start: 2018-09-21 16:03:01
main-end: 2018-09-21 16:03:03
main-start: 2018-09-21 16:03:03
2018-09-21 16:03:05
main-end: 2018-09-21 16:03:05
main-start: 2018-09-21 16:03:05
main-end: 2018-09-21 16:03:07
main-start: 2018-09-21 16:03:07
main-end: 2018-09-21 16:03:09
main-start: 2018-09-21 16:03:09
2018-09-21 16:03:10
import time
from apscheduler.schedulers.background import BackgroundScheduler
def job():
print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
if __name__ == '__main__':
scheduler = BackgroundScheduler()
scheduler.add_job(job, 'cron', day_of_week='fri', second='*/5')
year (int|str) – 4-digit year
month (int|str) – month (1-12)
day (int|str) – day of the (1-31)
week (int|str) – ISO week (1-53)
day_of_week (int|str) – number or name of weekday (0-6 or mon,tue,wed,thu,fri,sat,sun)
hour (int|str) – hour (0-23)
minute (int|str) – minute (0-59)
econd (int|str) – second (0-59)
start_date (datetime|str) – earliest possible date/time to trigger on (inclusive)
end_date (datetime|str) – latest possible date/time to trigger on (inclusive)
timezone (datetime.tzinfo|str) – time zone to use for the date/time calculations (defaults to scheduler timezone)
* any Fire on every value
*/a any Fire every a values, starting from the minimum
a-b any Fire on any value within the a-b range (a must be smaller than b)
a-b/c any Fire every c values within the a-b range
xth y day Fire on the x -th occurrence of weekday y within the month
last x day Fire on the last occurrence of weekday x within the month
last day Fire on the last day within the month
x,y,z any Fire on any matching expression; can combine any number of any of the above expressions
scheduler.start()
import time
from pymongo import MongoClient
from apscheduler.schedulers.blocking import BlockingScheduler
from apscheduler.jobstores.mongodb import MongoDBJobStore
def job():
print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())))
if __name__ == '__main__':
scheduler = BlockingScheduler()
client = MongoClient(host='127.0.0.1', port=27017)
store = MongoDBJobStore(collection='job', database='test', client=client)
scheduler.add_jobstore(store)
scheduler.add_job(job, 'interval', second=5)
scheduler.start()
原文链接https://www.jianshu.com/p/b77d934cc252
日拱一卒热爱可抵岁月漫长
不偏安一隅的工程师
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