How Can Python\'s `timeit` Module Help Compare the Performance of Custom Functions?

Measuring Performance with Timeit: A Guide to Comparing Custom Functions

Are you looking to determine how efficiently your custom functions perform? Timeit, a powerful Python module, provides a straightforward way to compare the execution times of your functions such as "insertion_sort" and "tim_sort."

Interactive Python Session

In an interactive Python session, you have two convenient options for using timeit:

1. IPython Shell: IPython offers the convenient "%timeit" special function, allowing you to compare performance directly within the shell:

def f(x):
    return x*x

%timeit for x in range(100): f(x)  # Performance results for 'f'

2. Standard Python Interpreter: If you're not using the IPython shell, import the functions you need from the main module and use the timeit.repeat() function for performance comparison:

def f(x):
    return x * x

import timeit
timeit.repeat("for x in range(100): f(x)", "from __main__ import f", number=100000)  # Performance results for 'f'

By using timeit, you can quickly and accurately assess the efficiency of your custom functions and make informed decisions about their implementation.

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