Book Image

Modern Python Standard Library Cookbook

By : Alessandro Molina
Book Image

Modern Python Standard Library Cookbook

By: Alessandro Molina

Overview of this book

The Python 3 Standard Library is a vast array of modules that you can use for developing various kinds of applications. It contains an exhaustive list of libraries, and this book will help you choose the best one to address specific programming problems in Python. The Modern Python Standard Library Cookbook begins with recipes on containers and data structures and guides you in performing effective text management in Python. You will find Python recipes for command-line operations, networking, filesystems and directories, and concurrent execution. You will learn about Python security essentials in Python and get to grips with various development tools for debugging, benchmarking, inspection, error reporting, and tracing. The book includes recipes to help you create graphical user interfaces for your application. You will learn to work with multimedia components and perform mathematical operations on date and time. The recipes will also show you how to deploy different searching and sorting algorithms on your data. By the end of the book, you will have acquired the skills needed to write clean code in Python and develop applications that meet your needs.
Table of Contents (21 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Benchmarking


When writing software, it's frequently important to ensure that some performance constraints are guaranteed. The standard library has most of the tools needed to ensure the timing and resource consumption of the functions we write.

Say we have two functions and we want to know which one is faster:

def function1():
    l = []
    for i in range(100):
        l.append(i)
    return l


def function2():
    return [i for i in range(100)]

How to do it...

The timeit module provides a bunch of utilities to time a function or whole script:

>>> import timeit

>>> print(
...     timeit.timeit(function1)
... )
10.132873182068579

>>> print(
...     timeit.timeit(function2)
... )
5.13165780401323

From the reported timing, we know that function2 is twice as fast as function1.

There's more...

Normally, such a function would run in a few milliseconds, but the reported timings are in the order of seconds.

 

That's because, by default, timeit.timeit will run the benchmarked...