Book Image

Modern Python Standard Library Cookbook

By : Alessandro Molina
Book Image

Modern Python Standard Library Cookbook

By: Alessandro 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 (21 chapters)
Title Page
Copyright and Credits
Packt Upsell
Contributors
Preface
Index

Logging to file


For long-running programs, logging to the screen is not a very viable option. After running the code for hours, the oldest logged messages will be lost, and even if they were still available, it wouldn't be very easy to read all the logs or search through them.

Saving logs to a file allows for unlimited length (as far as our disk allows it) and enables the usage of tools, such as grep, to search through them.

By default, Python logging is configured to write to screen, but it's easy to provide a way to write to any file when logging is configured.

How to do it...

To test logging to a file, we are going to create a short tool that computes up to the nth Fibonacci number based on the current time. If it's 3:01 P.M., we want to compute only 1 number, while if it's 3:59 P.M., we want to compute 59 numbers.

The software will provide the computed numbers as the output, but we also want to log up to which number it computed and when it was run:

import logging, sys

if __name__ == '__main__...