book

Modern Python Cookbook - Third Edition

Name: Modern Python Cookbook - Third Edition
Author: Steven F. Lott
ISBN: 9781835466384

by Steven F. Lott

July 2024

Beginner to intermediate

818 pages

17h 32m

English

Packt Publishing

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Modern Python Cookbook
Preface
What you need for this bookWho this book is forWhat this book coversTo get the most out of this book
Chapter 1 Numbers, Strings, and Tuples
1.1 Choosing between float, decimal, and fraction1.2 Choosing between true division and floor division1.3 String parsing with regular expressions1.4 Building complicated strings with f-strings1.5 Building complicated strings from lists of strings1.6 Using the Unicode characters that aren’t on our keyboards1.7 Encoding strings – creating ASCII and UTF-8 bytes1.8 Decoding bytes – how to get proper characters from some bytes1.9 Using tuples of items1.10 Using NamedTuples to simplify item access in tuples
Chapter 2 Statements and Syntax
2.1 Writing Python script and module files – syntax basics2.2 Writing long lines of code2.3 Including descriptions and documentation2.4 Writing better docstrings with RST markup2.5 Designing complex if...elif chains2.6 Saving intermediate results with the := ”walrus” operator2.7 Avoiding a potential problem with break statements2.8 Leveraging exception matching rules2.9 Avoiding a potential problem with an except: clause2.10 Concealing an exception root cause2.11 Managing a context using the with statement
Chapter 3 Function Definitions
3.1 Function parameters and type hints3.2 Designing functions with optional parameters3.3 Using super flexible keyword parameters3.4 Forcing keyword-only arguments with the * separator3.5 Defining position-only parameters with the / separator3.6 Picking an order for parameters based on partial functions3.7 Writing clear documentation strings with RST markup3.8 Designing recursive functions around Python’s stack limits3.9 Writing testable scripts with the script-library switch
Chapter 4 Built-In Data Structures Part 1: Lists and Sets
4.1 Choosing a data structure4.2 Building lists – literals, appending, and comprehensions4.3 Slicing and dicing a list4.4 Shrinking lists – deleting, removing, and popping4.5 Writing list-related type hints4.6 Reversing a copy of a list4.7 Building sets – literals, adding, comprehensions, and operators4.8 Shrinking sets – remove(), pop(), and difference4.9 Writing set-related type hints
Chapter 5 Built-In Data Structures Part 2: Dictionaries
5.1 Creating dictionaries – inserting and updating5.2 Shrinking dictionaries – the pop() method and the del statement5.3 Writing dictionary-related type hints5.4 Understanding variables, references, and assignment5.5 Making shallow and deep copies of objects5.6 Avoiding mutable default values for function parameters
Chapter 6 User Inputs and Outputs
6.1 Using the features of the print() function6.2 Using input() and getpass() for user input6.3 Debugging with f”{value=}” strings6.4 Using argparse to get command-line input6.5 Using invoke to get command-line input6.6 Using cmd to create command-line applications6.7 Using the OS environment settings
Chapter 7 Basics of Classes and Objects
7.1 Using a class to encapsulate data and processing7.2 Essential type hints for class definitions7.3 Designing classes with lots of processing7.4 Using typing.NamedTuple for immutable objects7.5 Using dataclasses for mutable objects7.6 Using frozen dataclasses for immutable objects7.7 Optimizing small objects with __slots__7.8 Using more sophisticated collections7.9 Extending a built-in collection – a list that does statistics7.10 Using properties for lazy attributes7.11 Creating contexts and context managers7.12 Managing multiple contexts with multiple resources
Chapter 8 More Advanced Class Design
8.1 Choosing between inheritance and composition – the ”is-a” question8.2 Separating concerns via multiple inheritance8.3 Leveraging Python’s duck typing8.4 Managing global and singleton objects8.5 Using more complex structures – maps of lists8.6 Creating a class that has orderable objects8.7 Deleting from a list of complicated objects

Chapter 9 Functional Programming Features
9.1 Writing generator functions with the yield statement9.2 Applying transformations to a collection9.3 Using stacked generator expressions9.4 Picking a subset – three ways to filter9.5 Summarizing a collection – how to reduce9.6 Combining the map and reduce transformations9.7 Implementing “there exists” processing9.8 Creating a partial function9.9 Writing recursive generator functions with the yield from statement
Chapter 10 Working with Type Matching and Annotations
10.1 Designing with type hints10.2 Using the built-in type matching functions10.3 Using the match statement10.4 Handling type conversions10.5 Implementing more strict type checks with Pydantic10.6 Including run-time valid value checks
Chapter 11 Input/Output, Physical Format, and Logical Layout
11.1 Using pathlib to work with filenames11.2 Replacing a file while preserving the previous version11.3 Reading delimited files with the CSV module11.4 Using dataclasses to simplify working with CSV files11.5 Reading complex formats using regular expressions11.6 Reading JSON and YAML documents11.7 Reading XML documents11.8 Reading HTML documents
Chapter 12 Graphics and Visualization with Jupyter Lab
12.1 Starting a Notebook and creating cells with Python code12.2 Ingesting data into a notebook12.3 Using pyplot to create a scatter plot12.4 Using axes directly to create a scatter plot12.5 Adding details to markdown cells12.6 Including Unit Test Cases in a Notebook
Chapter 13 Application Integration: Configuration
13.1 Finding configuration files13.2 Using TOML for configuration files13.3 Using Python for configuration files13.4 Using a class as a namespace for configuration13.5 Designing scripts for composition13.6 Using logging for control and audit output
Chapter 14 Application Integration: Combination
14.1 Combining two applications into one14.2 Combining many applications using the Command design pattern14.3 Managing arguments and configuration in composite applications14.4 Wrapping and combining CLI applications14.5 Wrapping a program and checking the output
Chapter 15 Testing
15.1 Using docstrings for testing15.2 Testing functions that raise exceptions15.3 Handling common doctest issues15.4 Unit testing with the unittest module15.5 Combining unittest and doctest tests15.6 Unit testing with the pytest module15.7 Combining pytest and doctest tests15.8 Testing things that involve dates or times15.9 Testing things that involve randomness15.10 Mocking external resources
Chapter 16 Dependencies and Virtual Environments
16.1 Creating environments using the built-in venv16.2 Installing packages with a requirements.txt file16.3 Creating a pyproject.toml file16.4 Using pip-tools to manage the requirements.txt file16.5 Using Anaconda and the conda tool16.6 Using the poetry tool16.7 Coping with changes in dependencies
Chapter 17 Documentation and Style
17.1 The bare minimum: a README.rst file17.2 Installing Sphinx and creating documentation17.3 Using Sphinx autodoc to create the API reference17.4 Identifying other CI/CD tools in pyproject.toml17.5 Using tox to run comprehensive quality checks
Other Books You May Enjoy
Index

Overview

Modern Python Cookbook is your essential resource for mastering Python programming with over 130 expert-crafted recipes tailored to Python 3.12. Whether you're tackling real-world problems or looking to optimize your projects, this guide unfolds in a clear, modular format to help you integrate new techniques, including advanced type matching, dependency management, and data visualization.

What this Book will help me do

Understand and implement core data structures and algorithms in Python for efficient programming.
Apply object-oriented programming and functional programming features to optimize and expand your codebase.
Develop clear and descriptive code using type annotations and matching features present in modern Python versions.
Create compelling data visualizations with tools such as Matplotlib and Pyplot to convey insights effectively.
Manage dependencies and environments efficiently, making your projects adaptable and maintenance-friendly.

Author(s)

Steven F. Lott is a seasoned software developer and prolific author with decades of experience using and teaching Python. He combines his deep technical expertise with a passion for effective coding practices to provide clear and actionable insights in his writing. Steven's approachable style makes complex topics accessible for both new and experienced programmers alike.

Who is it for?

This book is ideal for developers and engineers looking to deepen their Python expertise and stay current with Python 3.12. Beginners will find concise explanations and practical examples to start their programming journey. Experienced developers can explore advanced recipes and best practices to enhance their existing projects. A fundamental understanding of programming concepts and Python basics is recommended to fully utilize this book.

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