Book Image

Modern Python Cookbook - Second Edition

By : Steven F. Lott
Book Image

Modern Python Cookbook - Second Edition

By: Steven F. Lott

Overview of this book

Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great language that can power your applications and provide great speed, safety, and scalability. It can be used for simple scripting or sophisticated web applications. By exposing Python as a series of simple recipes, this book gives you insight into specific language features in a particular context. Having a tangible context helps make the language or a given standard library feature easier to understand. This book comes with 133 recipes on the latest version of Python 3.8. The recipes will benefit everyone, from beginners just starting out with Python to experts. You'll not only learn Python programming concepts but also how to build complex applications. The recipes will touch upon all necessary Python concepts related to data structures, object oriented programming, functional programming, and statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively take advantage of it. By the end of this Python book, you will be equipped with knowledge of testing, web services, configuration, and application integration tips and tricks. You will be armed with the knowledge of how to create applications with flexible logging, powerful configuration, command-line options, automated unit tests, and good documentation.
Table of Contents (18 chapters)
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Summarizing a collection – how to reduce

A reduction is the generalized concept behind computing a sum or a product of a collection of numbers. Computing statistical measures like mean or variance are also reductions. In this recipe, we'll look at several summary techniques.

In the introduction to this chapter, we noted that there are three processing patterns that Python supports elegantly: map, filter, and reduce. We saw examples of mapping in the Applying transformations to a collection recipe and examples of filtering in the Picking a subset – three ways to filter recipe. It's relatively easy to see how these higher-level functions define generic operations.

The third common pattern is reduction. In the Designing classes with lots of processing and Extending a collection: a list that does statistics recipes, we looked at class definitions that computed a number of statistical values. These definitions relied—almost exclusively—on the...