Book Image

Modern Python Cookbook

Book Image

Modern Python Cookbook

Overview of this book

Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great scripting language that can power your applications and provide great speed, safety, and scalability. By exposing Python as a series of simple recipes, you can gain insight into specific language features in a particular context. Having a tangible context helps make the language or standard library feature easier to understand. This book comes with over 100 recipes on the latest version of Python. The recipes will benefit everyone ranging from beginner to an expert. The book is broken down into 13 chapters that build from simple language concepts to more complex applications of the language. The recipes will touch upon all the necessary Python concepts related to data structures, OOP, functional programming, as well as statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively use the advantages that it offers. You will end the book equipped with the knowledge of testing, web services, and configuration and application integration tips and tricks. The recipes take a problem-solution approach to resolve issues commonly faced by Python programmers across the globe. You will be armed with the knowledge of creating applications with flexible logging, powerful configuration, and command-line options, automated unit tests, and good documentation.
Table of Contents (18 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Using multiple contexts for reading and writing files


It's common to need to convert data from one format to another. For example, we might have a complex web log that we'd like to convert to a simpler format.

See the Reading complex formats using regular expressions recipe for a complex web log format. We'd like to do this parsing just one time.

After that, we'd like to work with a simpler file format, more like the format shown in the Upgrading CSV from dict reader to namedtuple reader or Upgrading CSV from dict reader to namespace reader recipe. A file that's in CSV notation can be read and parsed with the csv module, simplifying the physical format considerations.

How can we convert from one format to another?

Getting ready

Converting a file of data from one format to another means that the program will need to have two open contexts: one for reading and one for writing. Python makes this easy. The use of with statement contexts assures that the files are properly closed and all of the related...