What is the best way to repeatedly execute a funct

Question

I want to repeatedly execute a function in Python every 60 seconds forever (just like an NSTimer in Objective C). This code will run as a daemon and is effectively like calling the python script every minute using a cron, but without requiring that to be set up by the user.

In this question about a cron implemented in Python, the solution appears to effectively just sleep() for x seconds. I don't need such advanced functionality so perhaps something like this would work

while True:
    # Code executed here
    time.sleep(60)

Are there any foreseeable problems with this code?

Answer 1

    ''' 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()

Answer 2

I use this to cause 60 events per hour with most events occurring at the same number of seconds after the whole minute:

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()

Depending upon actual conditions you might get ticks of length:

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

but at the end of 60 minutes you'll have 60 ticks; and most of them will occur at the correct offset to the minute you prefer.

On my system I get typical drift of < 1/20th of a second until need for correction arises.

The advantage of this method is resolution of clock drift; which can cause issues if you're doing things like appending one item per tick and you expect 60 items appended per hour. Failure to account for drift can cause secondary indications like moving averages to consider data too deep into the past resulting in faulty output.

Answer 3

I use Tkinter after() method, which doesn't "steal the game" (like the sched module that was presented earlier), i.e. it allows other things to run in parallel:

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() and do_something2() can run in parallel and in whatever interval speed. Here, the 2nd one will be executed twice as fast.Note also that I have used a simple counter as a condition to terminate either function. You can use whatever other contition you like or none if you what a function to run until the program terminates (e.g. a clock).