How to measure elapsed time in python?

To measure time elapsed during program execution, Python provides several methods. The most common approaches are using time.time(), time.perf_counter(), or the timeit module for benchmarking purposes.

Using time.time()

The simplest method uses time.time() to capture timestamps before and after code execution ?

import time

t0 = time.time()
print("Hello")
time.sleep(0.001)  # Simulate some work
t1 = time.time() - t0
print("Time elapsed:", t1, "seconds")

Hello
Time elapsed: 0.0015020370483398438 seconds

Using time.perf_counter() (Recommended)

For more precise measurements, use time.perf_counter() which provides the highest available resolution ?

import time

t0 = time.perf_counter()
# Simulate some computation
result = sum(i**2 for i in range(1000))
t1 = time.perf_counter() - t0
print(f"Computation result: {result}")
print(f"Time elapsed: {t1:.6f} seconds")

Computation result: 332833500
Time elapsed: 0.000123 seconds

Using timeit for Benchmarking

For statistical analysis and benchmarking code snippets, use the timeit module which runs code multiple times ?

import timeit

def square_function(x):
    return x * x

# Time a code snippet multiple times
execution_times = timeit.repeat(
    "for x in range(100): square_function(x)", 
    "from __main__ import square_function", 
    number=10000,
    repeat=3
)

print("Execution times:", execution_times)
print("Best time:", min(execution_times))

Execution times: [0.0234567, 0.0245678, 0.0239876]
Best time: 0.0234567

Comparison of Methods

Conclusion

Use time.perf_counter() for accurate elapsed time measurement and timeit for benchmarking code performance. Avoid the deprecated time.clock() function in modern Python versions.