import time, traceback

def every(delay, task):
  next_time = time.time() + delay
  while True:
    time.sleep(max(0, next_time - time.time()))
    try:
      task()
    except Exception:
      traceback.print_exc()
      # in production code you might want to have this instead of course:
      # logger.exception("Problem while executing repetitive task.")
    # skip tasks if we are behind schedule:
    next_time += (time.time() - next_time) // delay * delay + delay

def foo():
  print("foo", time.time())

every(5, foo)

如果你想在不阻塞剩余代码的情况下这样做，你可以使用这个让它在自己的线程中运行:

import threading
threading.Thread(target=lambda: every(5, foo)).start()

该解决方案结合了其他解决方案中很少结合的几个特性:

Exception handling: As far as possible on this level, exceptions are handled properly, i. e. get logged for debugging purposes without aborting our program. No chaining: The common chain-like implementation (for scheduling the next event) you find in many answers is brittle in the aspect that if anything goes wrong within the scheduling mechanism (threading.Timer or whatever), this will terminate the chain. No further executions will happen then, even if the reason of the problem is already fixed. A simple loop and waiting with a simple sleep() is much more robust in comparison. No drift: My solution keeps an exact track of the times it is supposed to run at. There is no drift depending on the execution time (as in many other solutions). Skipping: My solution will skip tasks if one execution took too much time (e. g. do X every five seconds, but X took 6 seconds). This is the standard cron behavior (and for a good reason). Many other solutions then simply execute the task several times in a row without any delay. For most cases (e. g. cleanup tasks) this is not wished. If it is wished, simply use next_time += delay instead.

import time, traceback

def every(delay, task):
  next_time = time.time() + delay
  while True:
    time.sleep(max(0, next_time - time.time()))
    try:
      task()
    except Exception:
      traceback.print_exc()
      # in production code you might want to have this instead of course:
      # logger.exception("Problem while executing repetitive task.")
    # skip tasks if we are behind schedule:
    next_time += (time.time() - next_time) // delay * delay + delay

def foo():
  print("foo", time.time())

every(5, foo)

如果你想在不阻塞剩余代码的情况下这样做，你可以使用这个让它在自己的线程中运行:

import threading
threading.Thread(target=lambda: every(5, foo)).start()

该解决方案结合了其他解决方案中很少结合的几个特性:

Exception handling: As far as possible on this level, exceptions are handled properly, i. e. get logged for debugging purposes without aborting our program. No chaining: The common chain-like implementation (for scheduling the next event) you find in many answers is brittle in the aspect that if anything goes wrong within the scheduling mechanism (threading.Timer or whatever), this will terminate the chain. No further executions will happen then, even if the reason of the problem is already fixed. A simple loop and waiting with a simple sleep() is much more robust in comparison. No drift: My solution keeps an exact track of the times it is supposed to run at. There is no drift depending on the execution time (as in many other solutions). Skipping: My solution will skip tasks if one execution took too much time (e. g. do X every five seconds, but X took 6 seconds). This is the standard cron behavior (and for a good reason). Many other solutions then simply execute the task several times in a row without any delay. For most cases (e. g. cleanup tasks) this is not wished. If it is wished, simply use next_time += delay instead.

我用这个方法使每小时产生60个事件，其中大多数事件在整分钟后的相同秒数内发生:

import math
import time
import random

TICK = 60 # one minute tick size
TICK_TIMING = 59 # execute on 59th second of the tick
TICK_MINIMUM = 30 # minimum catch up tick size when lagging

def set_timing():

    now = time.time()
    elapsed = now - info['begin']
    minutes = math.floor(elapsed/TICK)
    tick_elapsed = now - info['completion_time']
    if (info['tick']+1) > minutes:
        wait = max(0,(TICK_TIMING-(time.time() % TICK)))
        print ('standard wait: %.2f' % wait)
        time.sleep(wait)
    elif tick_elapsed < TICK_MINIMUM:
        wait = TICK_MINIMUM-tick_elapsed
        print ('minimum wait: %.2f' % wait)
        time.sleep(wait)
    else:
        print ('skip set_timing(); no wait')
    drift = ((time.time() - info['begin']) - info['tick']*TICK -
        TICK_TIMING + info['begin']%TICK)
    print ('drift: %.6f' % drift)

info['tick'] = 0
info['begin'] = time.time()
info['completion_time'] = info['begin'] - TICK

while 1:

    set_timing()

    print('hello world')

    #random real world event
    time.sleep(random.random()*TICK_MINIMUM)

    info['tick'] += 1
    info['completion_time'] = time.time()

根据实际情况，你可能会得到长度的刻度:

60,60,62,58,60,60,120,30,30,60,60,60,60,60...etc.

但在60分钟结束时，你会有60个滴答;而且它们中的大多数都将出现在您喜欢的正确偏移时间。

在我的系统中，我得到了< 1/20秒的典型漂移，直到需要纠正。

该方法的优点是具有较好的时钟漂移分辨率;这可能会导致问题，如果你做的事情，比如每tick追加一个项目，你希望每小时追加60个项目。未能考虑漂移可能导致次要指标，如移动平均线，将数据考虑得过于深入过去，从而导致错误的输出。

以下是MestreLion代码的改编版本。 除了原来的函数，这段代码:

1)添加用于在特定时间触发计时器的first_interval(调用者需要计算first_interval并传递进来)

2)在原代码中解决一个竞态条件。在原始代码中，如果控制线程未能取消正在运行的计时器(“停止计时器，并取消计时器动作的执行。这只会在计时器仍处于等待阶段时起作用。”引用自https://docs.python.org/2/library/threading.html)，计时器将无休止地运行。

class RepeatedTimer(object):
def __init__(self, first_interval, interval, func, *args, **kwargs):
    self.timer      = None
    self.first_interval = first_interval
    self.interval   = interval
    self.func   = func
    self.args       = args
    self.kwargs     = kwargs
    self.running = False
    self.is_started = False

def first_start(self):
    try:
        # no race-condition here because only control thread will call this method
        # if already started will not start again
        if not self.is_started:
            self.is_started = True
            self.timer = Timer(self.first_interval, self.run)
            self.running = True
            self.timer.start()
    except Exception as e:
        log_print(syslog.LOG_ERR, "timer first_start failed %s %s"%(e.message, traceback.format_exc()))
        raise

def run(self):
    # if not stopped start again
    if self.running:
        self.timer = Timer(self.interval, self.run)
        self.timer.start()
    self.func(*self.args, **self.kwargs)

def stop(self):
    # cancel current timer in case failed it's still OK
    # if already stopped doesn't matter to stop again
    if self.timer:
        self.timer.cancel()
    self.running = False

如果您的程序还没有事件循环，请使用sched模块，它实现了一个通用的事件调度器。

import sched, time

def do_something(scheduler): 
    # schedule the next call first
    scheduler.enter(60, 1, do_something, (scheduler,))
    print("Doing stuff...")
    # then do your stuff

my_scheduler = sched.scheduler(time.time, time.sleep)
my_scheduler.enter(60, 1, do_something, (my_scheduler,))
my_scheduler.run()

如果您已经在使用事件循环库，如asyncio、trio、tkinter、PyQt5、gobject、kivy等，则只需使用现有事件循环库的方法来调度任务。

我以前也遇到过类似的问题。也许http://cronus.readthedocs.org会有帮助?

对于v0.2，下面的代码片段可以工作

import cronus.beat as beat

beat.set_rate(2) # run twice per second
while beat.true():
    # do some time consuming work here
    beat.sleep() # total loop duration would be 0.5 sec