time.process_time() function in Python

The time.process_time() function in Python returns the sum of system and user CPU time consumed by the current process. Unlike time.time(), it excludes time spent sleeping and focuses only on actual processing time.

Syntax

time.process_time()

This function returns a float value representing the CPU time in seconds.

Basic Example

Here's how to get the current process time ?

import time

# Get current process time
current_time = time.process_time()
print(f"Current process time: {current_time} seconds")

Current process time: 0.015625 seconds

Measuring Execution Time

The most common use case is measuring how long a process takes to execute ?

import time

def print_numbers(limit):
    for i in range(limit):
        print(i, end=' ')

# Measure execution time
start_time = time.process_time()
print_numbers(100)
end_time = time.process_time()

print()  # New line after numbers
print(f"Process time: {end_time - start_time:.6f} seconds")

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 
Process time: 0.015625 seconds

Practical Example: CPU-Intensive Task

Let's measure the CPU time for a computation-heavy task ?

import time

def calculate_factorial(n):
    result = 1
    for i in range(1, n + 1):
        result *= i
    return result

# Measure CPU time for factorial calculation
start_time = time.process_time()
factorial_result = calculate_factorial(10000)
end_time = time.process_time()

print(f"Factorial calculated successfully!")
print(f"CPU time used: {end_time - start_time:.6f} seconds")

Factorial calculated successfully!
CPU time used: 0.031250 seconds

Key Points

Understanding process_time() characteristics:

• CPU time only: Excludes time spent waiting or sleeping
• Process-specific: Measures only the current process
• Monotonic: Values always increase, never go backward
• System + User time: Includes both kernel and user space execution

Comparison with Other Time Functions

import time

# Compare different time functions
start_process = time.process_time()
start_perf = time.perf_counter()

# Simulate work with a small delay
for i in range(1000000):
    pass

end_process = time.process_time()
end_perf = time.perf_counter()

print(f"process_time(): {end_process - start_process:.6f} seconds")
print(f"perf_counter(): {end_perf - start_perf:.6f} seconds")

process_time(): 0.078125 seconds
perf_counter(): 0.082156 seconds

Conclusion

Use time.process_time() when you need to measure actual CPU processing time, excluding sleep and I/O wait times. It's ideal for benchmarking CPU-intensive algorithms and measuring computational performance.