Python Automation Cookbook - Second Edition

By : Jaime Buelta

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.

Preface

Who this book is for

What this book covers

To get the most out of this book

Get in touch

Let's Begin Our Automation Journey

Activating a virtual environment

Installing third-party packages

Creating strings with formatted values

Manipulating strings

Extracting data from structured strings

Using a third-party tool—parse

Introducing regular expressions

Going deeper into regular expressions

Adding command-line arguments

Free Chapter

Automating Tasks Made Easy

Preparing a task

Setting up a cron job

Capturing errors and problems

Sending email notifications

Building Your First Web Scraping Application

Downloading web pages

Interacting with forms

Using Selenium for advanced interaction

Accessing password-protected pages

Speeding up web scraping

Searching and Reading Local Files

Crawling and searching directories

Reading text files

Dealing with encodings

Reading CSV files

Reading log files

Reading file metadata

Reading images

Reading PDF files

Reading Word documents

Scanning documents for a keyword

Generating Fantastic Reports

Creating a simple report in plain text

Using templates for reports

Formatting text in Markdown

Writing a basic Word document

Styling a Word document

Generating structure in Word documents

Adding pictures to Word documents

Writing a simple PDF document

Structuring a PDF

Aggregating PDF reports

Watermarking and encrypting a PDF

Fun with Spreadsheets

Writing a CSV spreadsheet

Updating CSV files

Reading an Excel spreadsheet

Updating an Excel spreadsheet

Creating new sheets in an Excel spreadsheet

Creating charts in Excel

Working with cell formats in Excel

Creating a macro in LibreOffice

Cleaning and Processing Data

Preparing a CSV spreadsheet

Appending currency based on location

Standardizing the date format

Aggregating results

Process data in parallel

Process data with Pandas

Developing Stunning Graphs

Plotting a simple sales graph

Drawing stacked bars

Plotting pie charts

Displaying multiple lines

Drawing a scatter plot

Visualizing maps

Adding legends and annotations

Combining graphs

Saving charts

Dealing with Communication Channels

Working with email templates

Sending an individual email

Reading an email

Adding subscribers to an email newsletter

Sending notifications via email

Producing SMS messages

Receiving SMS

Creating a Telegram bot

Why Not Automate Your Marketing Campaign?

Introduction

Detecting opportunities

Creating personalized coupon codes

Sending a notification to a customer on their preferred channel

Preparing sales information

Generating a sales report

Machine Learning for Automation

Introduction

Analyzing images with Google Cloud Vision AI

Extracting text from images with Google Cloud Vision AI

Analyzing text with Google Cloud Natural Language

Creating your own custom machine learning model to classify text

Automatic Testing Routines

Introduction

Writing and executing test cases

Testing external code

Testing using dependency mocking

Testing using HTTP call mocking

Preparing testing scenarios

Running tests selectively

Debugging Techniques

Introduction

Learning Python interpreter basics

Debugging through logging

Debugging with breakpoints

Improving your debugging skills

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Index

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Reading text files

After searching for a particular file, the next typical action is to open it and read its content. Text files are very simple yet very powerful files. They store data in plain text, without complicated binary formats.

Text file support is provided natively in Python, and it's easy to consider it a collection of lines that can be represented as Python strings.

Getting ready

We'll read the zen_of_python.txt file, containing The Zen of Python by Tim Peters, which is a collection of aphorisms that very well describe the design principles behind Python.

It is available in the GitHub repository here: https://github.com/PacktPublishing/Python-Automation-Cookbook-Second-Edition/blob/master/Chapter04/documents/zen_of_python.txt:

Beautiful is better than ugly.
Explicit is better than implicit.
Simple is better than complex.
Complex is better than complicated.
Flat is better than nested.
Sparse is better than dense.
Readability counts.
Special...

Python Automation Cookbook - Second Edition

By : Jaime Buelta

Python Automation Cookbook - Second Edition

By: Jaime Buelta

Overview of this book

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Current Title:

Python Automation Cookbook - Second Edition

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Reading text files

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