time.process_time () function in Python

Counters | process_time | Python Methods and Functions

Various timing functions are provided as a time unit . Thus, the time module must be imported, otherwise it will be an error because the definition of time.process_time () is present in the time module .

Example: understand the use of process_time ().

# Python program to display time using process_time ()

from time import process_time

 
# assignment n = 50

n = 50  

 
# Start stopwatch / counter

t1_start = process_time () 

 

for i in range (n):

print (i, end = ' ' )

 

print ( ) 

 
# Stop stopwatch / counter

t1_stop = process_time ()

 

print ( "Elapsed time:" , t1_stop, t1_start) 

  

print ( "Elapsed time during the whole program in seconds:" ,

t1_stop - t1_start) 

Exit:

process_time_ns ():
It always gives an integer time value in nanoseconds. Same as process_time (), but returns time in nanoseconds. This is just the main difference.

Example: understand the use of process_time_ns () .

# Python program for displaying time using process_time_ns ()

from time import process_time_ns

 

n = 50  

 
# Start stopwatch / counter

t1_start = process_time_ns () 

  

for i in range (n):

  print (i, end = ''

 

print () 

 
# Stop stopwatch / counter

t1_stop = process_time_ns ()

 

print ( "Elapsed time:" , t1_stop, t1_start)

 

print ( "Elapsed time durin g the whole program in nanoseconds: " ,

  t1_stop - t1_start) 

Output:

Note: process_time () is very different from pref_counter () because perf_counter ( ) calculates program time with perf_counter () time and if there is any interruption but process_counter only calculates system and CPU time, during process it does not include timeout.

Advantages of process_time ():
1. process_time () provides the system and user CPU time of the current process. 
2. We can calculate both float and integer values ​​of time in seconds and nanoseconds. 
3. Used whenever you need to calculate CPU time for a specific process.





time.process_time () function in Python: StackOverflow Questions

Answer #1

If you just want to measure the elapsed wall-clock time between two points, you could use time.time():

import time

start = time.time()
print("hello")
end = time.time()
print(end - start)

This gives the execution time in seconds.

Another option since 3.3 might be to use perf_counter or process_time, depending on your requirements. Before 3.3 it was recommended to use time.clock (thanks Amber). However, it is currently deprecated:

On Unix, return the current processor time as a floating point number expressed in seconds. The precision, and in fact the very definition of the meaning of “processor time”, depends on that of the C function of the same name.

On Windows, this function returns wall-clock seconds elapsed since the first call to this function, as a floating point number, based on the Win32 function QueryPerformanceCounter(). The resolution is typically better than one microsecond.

Deprecated since version 3.3: The behaviour of this function depends on the platform: use perf_counter() or process_time() instead, depending on your requirements, to have a well defined behaviour.

Answer #2

In Python 3.3+:

from subprocess import STDOUT, check_output

output = check_output(cmd, stderr=STDOUT, timeout=seconds)

output is a byte string that contains command"s merged stdout, stderr data.

check_output raises CalledProcessError on non-zero exit status as specified in the question"s text unlike proc.communicate() method.

I"ve removed shell=True because it is often used unnecessarily. You can always add it back if cmd indeed requires it. If you add shell=True i.e., if the child process spawns its own descendants; check_output() can return much later than the timeout indicates, see Subprocess timeout failure.

The timeout feature is available on Python 2.x via the subprocess32 backport of the 3.2+ subprocess module.

Answer #3

If you want to measure CPU time, can use time.process_time() for Python 3.3 and above:

import time
start = time.process_time()
# your code here    
print(time.process_time() - start)

First call turns the timer on, and second call tells you how many seconds have elapsed.

There is also a function time.clock(), but it is deprecated since Python 3.3 and will be removed in Python 3.8.

There are better profiling tools like timeit and profile, however time.process_time() will measure the CPU time and this is what you"re are asking about.

If you want to measure wall clock time instead, use time.time().

Answer #4

As of 3.3, time.clock() is deprecated, and it"s suggested to use time.process_time() or time.perf_counter() instead.

Previously in 2.7, according to the time module docs:

time.clock()

On Unix, return the current processor time as a floating point number expressed in seconds. The precision, and in fact the very definition of the meaning of “processor time”, depends on that of the C function of the same name, but in any case, this is the function to use for benchmarking Python or timing algorithms.

On Windows, this function returns wall-clock seconds elapsed since the first call to this function, as a floating point number, based on the Win32 function QueryPerformanceCounter(). The resolution is typically better than one microsecond.

Additionally, there is the timeit module for benchmarking code snippets.

Answer #5

Python 3 only:

Since time.clock() is deprecated as of Python 3.3, you will want to use time.perf_counter() for system-wide timing, or time.process_time() for process-wide timing, just the way you used to use time.clock():

import time

t = time.process_time()
#do some stuff
elapsed_time = time.process_time() - t

The new function process_time will not include time elapsed during sleep.

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