time.process_time () function in Python



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.