How do I get time of a Python program’s execution?

To measure the execution time of a Python program, you can use several methods depending on your needs. Here are the most common approaches:

1. Using time.time() (Simple Wall-Clock Time)

This method measures the total elapsed time (wall-clock time) between two points in your code.

import time

start_time = time.time()

# Your code here
for _ in range(1000000):
    pass

end_time = time.time()
execution_time = end_time - start_time
print(f"Execution time: {execution_time:.4f} seconds")

Pros: Simple and easy to use.
Cons: Includes time from other processes running on the system.

2. Using time.perf_counter() (High Precision)

Provides a higher-resolution timer for benchmarking code performance.

import time

start = time.perf_counter()

# Your code here
result = sum(range(1000000))

end = time.perf_counter()
print(f"Time taken: {end - start:.6f} seconds")

Pros: More precise than time.time().
Cons: Still measures wall-clock time.

3. Using the timeit Module (For Code Snippets)

Ideal for timing small code snippets and averaging multiple runs.

Command Line:

python -m timeit -n 1000 -r 5 "your_code_here"

• -n: Number of loops per run.
• -r: Number of repetitions.

Within Python:

import timeit

code_to_test = """
result = sum(range(1000000))
"""

execution_time = timeit.timeit(code_to_test, number=1000)
print(f"Average time: {execution_time / 1000:.6f} seconds")

Pros: Runs code multiple times for accuracy.
Cons: Requires code to be a string or callable.

4. Using a Context Manager (Reusable)

Create a reusable timer for cleaner code:

import time
from contextlib import contextmanager

@contextmanager
def timer():
    start = time.perf_counter()
    yield
    end = time.perf_counter()
    print(f"Time: {end - start:.4f} sec")

# Usage
with timer():
    # Code to time
    sum(range(1000000))

5. Using datetime (Human-Readable Output)

For a formatted time output (e.g., hours:minutes:seconds):

from datetime import datetime

start = datetime.now()

# Your code here
sum(range(1000000))

end = datetime.now()
print(f"Time: {end - start}")

6. Profiling Entire Scripts with cProfile

For detailed profiling (not just total time):

python -m cProfile your_script.py

Which Method Should You Use?

Use Case	Recommended Method
Simple timing	time.time()
High-precision benchmarks	time.perf_counter()
Small code snippets	timeit module
Reusable timing	Context manager
Detailed performance stats	cProfile

Example: Full Program Timing

import time

def main():
    # Your program logic here
    total = 0
    for i in range(1000000):
        total += i
    print("Sum:", total)

if __name__ == "__main__":
    start = time.perf_counter()
    main()
    end = time.perf_counter()
    print(f"Total execution time: {end - start:.4f} seconds")

Output:

Sum: 499999500000
Total execution time: 0.0453 seconds

Key Notes

• Short-running code: Use timeit for reliable averages.
• Real-world timing: time.perf_counter() minimizes system interference.
• Avoid time.sleep(): It can skew results if used in your code.