Book Image

Python Automation Cookbook - Second Edition

By : Jaime Buelta
Book Image

Python Automation Cookbook - Second Edition

By: Jaime Buelta

Overview of this book

In this updated and extended version of Python Automation Cookbook, each chapter now comprises the newest recipes and is revised to align with Python 3.8 and higher. The book includes three new chapters that focus on using Python for test automation, machine learning projects, and for working with messy data. This edition will enable you to develop a sharp understanding of the fundamentals required to automate business processes through real-world tasks, such as developing your first web scraping application, analyzing information to generate spreadsheet reports with graphs, and communicating with automatically generated emails. Once you grasp the basics, you will acquire the practical knowledge to create stunning graphs and charts using Matplotlib, generate rich graphics with relevant information, automate marketing campaigns, build machine learning projects, and execute debugging techniques. By the end of this book, you will be proficient in identifying monotonous tasks and resolving process inefficiencies to produce superior and reliable systems.
Table of Contents (16 chapters)
14
Other Books You May Enjoy
15
Index

Writing a basic Word document

Microsoft (MS) Office is one of the most common pieces of software, and MS Word in particular is almost the de facto standard for editable documents. Generating docx documents is possible with automated scripts, which may help distribute reports in a format that's easily shared in many businesses.

In this recipe, we will learn how to generate a full Word document programmatically.

Getting ready

We'll use the python-docx module to process Word documents:

$ echo "python-docx==0.8.10" >> requirements.txt 
$ pip install -r requirements.txt 

How to do it...

  1. Import python-docx and datetime:
    >>> import docx
    >>> from datetime import datetime
    
  2. Define the context with the data to be stored in the report:
    >>> context = {
    ...     'date': datetime.now(),
    ...     'movies': ['Casablanca', 'The Sound of Music'...