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

Accumulating and reducing


List comprehensions and map are very convenient tools when you need to apply a function to all elements of an iterable and get back the resulting values. But those are mostly meant to apply unary functions and keep a collection of the transformed values (such as add 1 to all numbers), but if you want to apply functions that should receive more than one element at the time, they don't fit very well.

The reduction and accumulation functions instead are meant to receive multiple values from the iterable and return a single value (in the case of reduction) or multiple values (in the case of accumulation).

How to do it...

The steps for this recipe are as follows:

  1. The most simple example of reduction is summing all items in an iterable:
>>> values = [ 1, 2, 3, 4, 5 ]
  1. This is something that can easily be done by sum, but for the sake of this example, we will use reduce:
>>> import functools, operator
>>> functools.reduce(operator.add, values)
15
  1. If instead...