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)
16
Other Books You May Enjoy
17
Index

Writing generator functions with the yield statement

A generator function is designed to apply some kind of transformation to each item of a collection. The generator is called "lazy" because of the way values must be consumed from the generator by a client. Client functions like the list() function or implicit iter() function used by a for statement are common examples of consumers. Each time a function like list() consumes a value, the generator function must consume values from its source and use the yield statement to yield one result back to the list() consumer.

In contrast, an ordinary function can be called "eager." Without the yield statement, a function will compute the entire result and return it via the return statement.

A consumer-driven approach is very helpful in cases where we can't fit an entire collection in memory. For example, analyzing gigantic web log files is best done in small doses rather than by creating a vast in...