7 Best Python Books Every Developer Should Read

Presenting the most recommended books on Hacker News, Stack Overflow and Reddit

7 Best Python Books Every Developer Should Read

Python is a programming language that lets you work quickly and integrate systems more effectively. It is being used in most of the companies. It’s highly adaptable, easy to maintain, and allows for rapid development.

Based on TopTalkedBooks.com’s data, here are the top python books

1. Head First Python: A Brain-Friendly Guide

Want to learn the Python language without slogging your way through how-to manuals? With Head First Python, you’ll quickly grasp Python’s fundamentals, working with the built-in data structures and functions. Then you’ll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. If you’re intrigued by what you can do with context managers, decorators, comprehensions, and generators, it’s all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time.

Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Pythonuses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works.

2. Automate the Boring Stuff with Python: Practical Programming for Total Beginners

If you’ve ever spent hours renaming files or updating hundreds of spreadsheet cells, you know how tedious tasks like these can be. But what if you could have your computer do them for you?

In Automate the Boring Stuff with Python, you’ll learn how to use Python to write programs that do in minutes what would take you hours to do by hand—no prior programming experience required. Once you’ve mastered the basics of programming, you’ll create Python programs that effortlessly perform useful and impressive feats of automation to:
–Search for text in a file or across multiple files
–Create, update, move, and rename files and folders
–Search the Web and download online content
–Update and format data in Excel spreadsheets of any size
–Split, merge, watermark, and encrypt PDFs
–Send reminder emails and text notifications
–Fill out online forms

Step-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.

3. Fluent Python: Clear, Concise, and Effective Programming

Python’s simplicity lets you become productive quickly, but this often means you aren’t using everything it has to offer. With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best—and possibly most neglected—features. Author Luciano Ramalho takes you through Python’s core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time.

Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.

 

 

This book covers:

  • Python data model: understand how special methods are the key to the consistent behavior of objects
  • Data structures: take full advantage of built-in types, and understand the text vs bytes duality in the Unicode age
  • Functions as objects: view Python functions as first-class objects, and understand how this affects popular design patterns
  • Object-oriented idioms: build classes by learning about references, mutability, interfaces, operator overloading, and multiple inheritance
  • Control flow: leverage context managers, generators, coroutines, and concurrency with the concurrent.futures and asyncio packages
  • Metaprogramming: understand how properties, attribute descriptors, class decorators, and metaclasses work

4. Python Crash Course: A Hands-On, Project-Based Introduction to Programming

Python Crash Course is a fast-paced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time.

In the first half of the book, you’ll learn about basic programming concepts, such as lists, dictionaries, classes, and loops, and practice writing clean and readable code with exercises for each topic. You’ll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you’ll put your new knowledge into practice with three substantial projects: a Space Invaders–inspired arcade game, data visualizations with Python’s super-handy libraries, and a simple web app you can deploy online.

 

As you work through Python Crash Course you’ll learn how to:

*Use powerful Python libraries and tools, including matplotlib, NumPy, and Pygal

*Make 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progresses

*Work with data to generate interactive visualizations

*Create and customize Web apps and deploy them safely online

*Deal with mistakes and errors so you can solve your own programming problems

5. Python Essential Reference (4th Edition)

Python Essential Reference is the definitive reference guide to the Python programming language — the one authoritative handbook that reliably untangles and explains both the core Python language and the most essential parts of the Python library.

Designed for the professional programmer, the book is concise, to the point, and highly accessible. It also includes detailed information on the Python library and many advanced subjects that is not available in either the official Python documentation or any other single reference source.

Thoroughly updated to reflect the significant new programming language features and library modules that have been introduced in Python 2.6 and Python 3, the fourth edition of Python Essential Reference is the definitive guide for programmers who need to modernize existing Python code or who are planning an eventual migration to Python 3. Programmers starting a new Python project will find detailed coverage of contemporary Python programming idioms.

This fourth edition of Python Essential Reference features numerous improvements, additions, and updates:

  • Coverage of new language features, libraries, and modules
  • Practical coverage of Python's more advanced features including generators, coroutines, closures, metaclasses, and decorators
  • Expanded coverage of library modules related to concurrent programming including threads, subprocesses, and the new multiprocessing module
  • Up-to-the-minute coverage of how to use Python 2.6's forward compatibility mode to evaluate code for Python 3 compatibility
  • Improved organization for even faster answers and better usability
  • Updates to reflect modern Python programming style and idioms
  • Updated and improved example code
  • Deep coverage of low-level system and networking library modules — including options not covered in the standard documentation

6. Python Cookbook

Portable, powerful, and a breeze to use, Python is the popular open source object-oriented programming language used for both standalone programs and scripting applications. It is now being used by an increasing number of major organizations, including NASA and Google.Updated for Python 2.4, The Python Cookbook, 2nd Edition offers a wealth of useful code for all Python programmers, not just advanced practitioners. Like its predecessor, the new edition provides solutions to problems that Python programmers face everyday.It now includes over 200 recipes that range from simple tasks, such as working with dictionaries and list comprehensions, to complex tasks, such as monitoring a network and building a templating system. This revised version also includes new chapters on topics such as time, money, and metaprogramming.

 

Here's a list of additional topics covered:

  • Manipulating text
  • Searching and sorting
  • Working with files and the filesystem
  • Object-oriented programming
  • Dealing with threads and processes
  • System administration
  • Interacting with databases
  • Creating user interfaces
  • Network and web programming
  • Processing XML
  • Distributed programming
  • Debugging and testing

Another advantage of The Python Cookbook, 2nd Edition is its trio of authors--three well-known Python programming experts, who are highly visible on email lists and in newsgroups, and speak often at Python conferences.With scores of practical examples and pertinent background information, The Python Cookbook, 2nd Edition is the one source you need if you're looking to build efficient, flexible, scalable, and well-integrated systems.

7. Introduction to Machine Learning with Python: A Guide for Data Scientists

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.

You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.

 

With this book, you’ll learn:

  • Fundamental concepts and applications of machine learning
  • Advantages and shortcomings of widely used machine learning algorithms
  • How to represent data processed by machine learning, including which data aspects to focus on
  • Advanced methods for model evaluation and parameter tuning
  • The concept of pipelines for chaining models and encapsulating your workflow
  • Methods for working with text data, including text-specific processing techniques
  • Suggestions for improving your machine learning and data science skills

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