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

Replacing a file while preserving the previous version


We can leverage the power of pathlib to support a variety of filename manipulations. In the Using pathlib to work with filenames recipe, we looked at a few of the most common techniques of managing directories, filenames, and file suffixes.

One common file processing requirement is to create output files in a fail-safe manner. That is, the application should preserve any previous output file no matter how or where the application fails.

Consider the following scenario:

  1. At time t0 there's a valid output.csv file from yesterday's use of the long_complex.py application.
  2. At time t1 we start running the long_complex.py application. It begins overwriting the output.csv file. It is expected to finish normally at time t3.
  3. At time t2, the application crashes. The partial output.csv file is useless. Worse, the valid file from time t0 is not available either, since it was overwritten.

Clearly, we can make backup copies of files. This introduces an extra...