what is the difference between time.perf_counter() and time.process_time()?

Question

I am using Jupyter notebook. I'm trying to measure how long will it take to count the Avogadro's number with python. I found that time.perf_counter() and time.process_time() modules will be useful for this kind of work. So I tried both of them, but the result was totally different. What makes this kind of difference? Here are my codes.

import time  a = 10 ** 5  def AvogadroCounting():     i = 0     while i <= a:         i += 1  AvogadroCounting()  t_fract = time.perf_counter()  #time to count fraction of avogadro's number in Seconds   print(t_fract, 'secs') 

and my notebook gives 693920.393636181 secs.

import time  a = 10 ** 5  def AvogadroCounting():     i = 0     while i <= a:         i += 1  AvogadroCounting()  t_fract =  time.process_time()  #time to count fraction of avogadro's number in Seconds   print(t_fract, 'secs') 

and this gives 2048.768273 secs.

Answer 1

time.perf_counter() keeps going during sleep, time.process_time() does not.

time.perf_counter() → float

Return the value (in fractional seconds) of a performance counter, i.e. a clock with the highest available resolution to measure a short duration. It does include time elapsed during sleep and is system-wide. The reference point of the returned value is undefined, so that only the difference between the results of consecutive calls is valid.

time.process_time() → float

Return the value (in fractional seconds) of the sum of the system and user CPU time of the current process. It does not include time elapsed during sleep. It is process-wide by definition. The reference point of the returned value is undefined, so that only the difference between the results of consecutive calls is valid.

See the official documentation

import time  def pc():     start = time.perf_counter()     time.sleep(1)     print(time.perf_counter()-start)  def pt():     start = time.process_time()     time.sleep(1)     print(time.process_time()-start)  pc()  # 0.99872320449432 pt()  # 0.0