time.process_time() function in Python

time.process_time() function returns the CPU time used by the current process in seconds. It measures only the time during which the CPU executes the program and does not include sleep time or waiting for I/O operations. It is mainly used for benchmarking CPU-intensive tasks.

Example: In this example, CPU time is measured before and after a computation to calculate execution time. (Output may vary depending on system performance.)

import time
s = time.process_time()

t = 0
for i in range(1, 1000000):
    t += i

e = time.process_time()
print(e - s, "seconds")

0.223359418 seconds

Explanation:

• time.process_time() records CPU start time in s.
• Computation runs inside the loop.
• e - s gives CPU time used by the process.

Syntax

time.process_time()

• Parameters: No parameters.
• Return: Returns CPU time used by the current process as a floating-point number (in seconds).

Examples

Example 1: In this example, CPU time is measured for executing a function.

import time

def f():
    return sum(range(1000000))

s = time.process_time()
f()
e = time.process_time()
print(e - s, "seconds")

0.035399988 seconds

Explanation:

• s = time.process_time() records start time.
• f() executes computation.
• e - s gives CPU time taken by the function.

Example 2: Here, CPU time of a built-in function is compared with a manual loop.

import time

s = time.process_time()
sum(range(1000000))
e = time.process_time()
print("Built-in:", e - s)

s = time.process_time()
t = 0
for i in range(1000000):
    t += i
e = time.process_time()
print("Loop:", e - s)

Built-in: 0.02539901
Loop: 0.14826791699999997

Explanation:

• sum(range(...)) executes faster.
• Manual loop takes more CPU time.
• e - s shows performance difference.

Example 3: In this example, CPU time is measured for repeated execution of a task.

import time
s = time.process_time()

for _ in range(5):
    sum(range(1000000))

e = time.process_time()
print("CPU Time:", e - s)

CPU Time: 0.11963688

Explanation:

• Loop runs computation multiple times.
• time.process_time() measures total CPU usage.
• e - s gives total CPU time for all iterations.

time.process_time() vs time.time()

Both functions are used to measure time in Python, but they serve different purposes. One measures CPU execution time, while the other measures real-world elapsed (wall-clock) time.