计时计数可以做到高精度(即< 1毫秒)，因为它与系统时钟同步。它不会随着时间的推移而漂移，也不受代码执行时间长度的影响(当然，前提是它小于间隔时间)。

一个简单的阻塞的例子:

from timed_count import timed_count

for count in timed_count(60):
    # Execute code here exactly every 60 seconds
    ...

你可以通过在线程中运行它来让它变得不阻塞:

from threading import Thread
from timed_count import timed_count

def periodic():
    for count in timed_count(60):
        # Execute code here exactly every 60 seconds
        ...

thread = Thread(target=periodic)
thread.start()

简单地使用

import time

while True:
    print("this will run after every 30 sec")
    #Your code here
    time.sleep(30)

我使用Tkinter after()方法，它不会“窃取游戏”(就像之前提出的sched模块)，即它允许其他东西并行运行:

import Tkinter

def do_something1():
  global n1
  n1 += 1
  if n1 == 6: # (Optional condition)
    print "* do_something1() is done *"; return
  # Do your stuff here
  # ...
  print "do_something1() "+str(n1)
  tk.after(1000, do_something1)

def do_something2(): 
  global n2
  n2 += 1
  if n2 == 6: # (Optional condition)
    print "* do_something2() is done *"; return
  # Do your stuff here
  # ...
  print "do_something2() "+str(n2)
  tk.after(500, do_something2)

tk = Tkinter.Tk(); 
n1 = 0; n2 = 0
do_something1()
do_something2()
tk.mainloop()

Do_something1()和do_something2()可以以任意的间隔速度并行运行。在这里，第2个将以两倍的速度执行。还要注意，我使用了一个简单的计数器作为终止任一函数的条件。你可以使用任何你喜欢的条件，或者不使用，如果你想让一个函数运行到程序终止(例如一个时钟)。

    ''' tracking number of times it prints'''
import threading

global timeInterval
count=0
def printit():
  threading.Timer(timeInterval, printit).start()
  print( "Hello, World!")
  global count
  count=count+1
  print(count)
printit

if __name__ == "__main__":
    timeInterval= int(input('Enter Time in Seconds:'))
    printit()

另一种灵活性解决方案是Apscheduler。

pip install apscheduler

from apscheduler.schedulers.background import BlockingScheduler
def print_t():
  pass

sched = BlockingScheduler()
sched.add_job(print_t, 'interval', seconds =60) #will do the print_t work for every 60 seconds

sched.start()

另外，apscheduler提供了如下所示的许多调度程序。

BlockingScheduler: use when the scheduler is the only thing running in your process BackgroundScheduler: use when you’re not using any of the frameworks below, and want the scheduler to run in the background inside your application AsyncIOScheduler: use if your application uses the asyncio module GeventScheduler: use if your application uses gevent TornadoScheduler: use if you’re building a Tornado application TwistedScheduler: use if you’re building a Twisted application QtScheduler: use if you’re building a Qt application

如果你想要一种非阻塞的方式来周期性地执行你的函数，而不是阻塞无限循环，我会使用线程计时器。这样，您的代码可以继续运行并执行其他任务，并且仍然每n秒调用一次您的函数。我经常使用这种技术打印长时间、CPU/磁盘/网络密集型任务的进度信息。

下面是我在类似问题中发布的代码，带有start()和stop()控件:

from threading import Timer

class RepeatedTimer(object):
    def __init__(self, interval, function, *args, **kwargs):
        self._timer     = None
        self.interval   = interval
        self.function   = function
        self.args       = args
        self.kwargs     = kwargs
        self.is_running = False
        self.start()

    def _run(self):
        self.is_running = False
        self.start()
        self.function(*self.args, **self.kwargs)

    def start(self):
        if not self.is_running:
            self._timer = Timer(self.interval, self._run)
            self._timer.start()
            self.is_running = True

    def stop(self):
        self._timer.cancel()
        self.is_running = False

用法:

from time import sleep

def hello(name):
    print "Hello %s!" % name

print "starting..."
rt = RepeatedTimer(1, hello, "World") # it auto-starts, no need of rt.start()
try:
    sleep(5) # your long-running job goes here...
finally:
    rt.stop() # better in a try/finally block to make sure the program ends!

特点:

只有标准库，没有外部依赖 即使计时器已经启动/停止，也可以安全地多次调用Start()和stop() 要调用的函数可以有位置参数和命名参数 您可以随时更改间隔，它将在下次运行后生效。args、kwargs甚至function也一样!