How Can I Accurately Measure Elapsed Time in Python?

Measuring Elapsed Time in Python

Measuring elapsed time during function execution is crucial for performance analysis and optimization. One common approach is to employ the timeit module. However, as illustrated in the given code snippet, timeit may not always provide the desired results.

Using the time Module

Instead of timeit, a more reliable method for measuring elapsed wall-clock time is to utilize the time module:

import time

start = time.time()
print("hello")
end = time.time()
elapsed_time = end - start

This approach provides the execution time in seconds.

Alternative Options

For Python 3.3 and above, two additional options exist:

• perf_counter: Provides a high-accuracy, monotonic clock that measures the CPU time used by the current process.
• process_time: Measures the total CPU time used by the current process, including both user and system time.

Deprecation of time.clock

Prior to Python 3.3, time.clock was recommended for measuring elapsed time. However, it has since been deprecated in favor of perf_counter and process_time. The behavior of time.clock varies across platforms, leading to potential inaccuracies.

In conclusion, for accurate and reliable measurement of elapsed time in Python, the time module is highly recommended. Additionally, perf_counter or process_time can be utilized as suitable alternatives, depending on the requirements of the specific application.

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