Which Python Time Measurement Function is More Accurate: time.clock() vs. time.time()?

Assessing the Accuracy of Python's time.clock() vs. time.time()

In Python, developers commonly rely on time.clock() or time.time() functions to measure execution duration. However, it's crucial to understand their respective accuracy capabilities.

Deprecation of time.clock()

As of Python 3.3, time.clock() has been deprecated. Its usage has been discouraged, with recommendations to use time.process_time() or time.perf_counter() as alternatives.

Accuracy Comparison

Historically, in Python 2.7, time.clock() was considered more suitable for benchmarking and algorithm timing on Unix systems. This was attributed to its reliance on the C function of the same name, which offered a precise representation of processor time.

Time Resolution

On Windows, both time.clock() and time.time() utilized the Win32 function QueryPerformanceCounter() to retrieve wall-clock seconds elapsed since the first call. This typically resulted in a time resolution superior to one microsecond.

Recommendation

Considering the deprecation of time.clock(), it's advisable to utilize either time.process_time() or time.perf_counter() for accurate timing in Python. Additionally, the timeit module provides convenient benchmarking capabilities for code snippets, making it a valuable tool for measuring performance.

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