How Can I Use Python\'s `timeit` to Compare the Performance of Custom Functions?

Understanding Timeit: Performance Comparison with Custom Functions

Timeit is a powerful module in Python designed to measure the execution time of code snippets. It is an invaluable tool for comparing the performance of different functions, algorithms, or even snippets of the same code.

Comparing Functions with Timeit

To use timeit to compare the performance of two functions, such as insertion_sort and tim_sort, follow these steps:

1. Create a setup statement:

Import the timeit module and define the functions you want to compare. For instance, if your functions are defined in a file named custom_functions.py:

import timeit
from custom_functions import insertion_sort, tim_sort

2. Define the code to time:

Create a string that represents the code you want to time. This code should include the function call and any necessary arguments:

code_to_time = "insertion_sort([10, 5, 2, 4, 7])"

3. Execute the timeit statement:

Use the timeit.timeit() function to measure the execution time of the code:

timeit.timeit(code_to_time, setup="from custom_functions import insertion_sort", number=100)

4. Repeat for other functions:

Repeat steps 2 and 3 for the other functions you want to compare:

code_to_time = "tim_sort([10, 5, 2, 4, 7])"
timeit.timeit(code_to_time, setup="from custom_functions import tim_sort", number=100)

The output from timeit will display the execution time in seconds. By comparing the results, you can determine which function is more efficient for the given task.

Note:

• For more accurate results, it is recommended to run the timeit statement multiple times using the number parameter.
• To compare functions with different arguments, modify the code_to_time variable accordingly.

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