Book Image

Modern Python Standard Library Cookbook

By : Molina
Book Image

Modern Python Standard Library Cookbook

By: 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 (16 chapters)

Getting the nth element of any iterable


Randomly accessing to containers is something we are used to doing frequently and without too many issues. For most container types, it's even a very cheap operation. When working with generic iterables and generators on the other side, it's not as easy as we would expect and it often ends up with us converting them to lists or ugly for loops.

The Python standard library actually has ways to make this very straightforward.

How to do it...

The itertools module is a treasure of valuable functions when working with iterables, and with minor effort it's possible to get the nth item of any iterable:

import itertools

def iter_nth(iterable, nth):
    return next(itertools.islice(iterable, nth, nth+1))

Given a random iterable, we can use it to grab the element we want:

>>> values = (x for x in range(10))
>>> iter_nth(values, 4)
4

How it works...

The itertools.islice function is able to take a slice of any iterable. In our specific case, we want...