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Want To Raise Your Python Game? Check Out These Python Books

In this article, we share the 15 best Python books in 2024.

Whether you’re new to Python or an experienced Pythonista looking to boost your skills, we’ve included Python books for beginners and pros.

As the number 3 language among developers, python books can be the ideal way to learn Python for data science, web development, and more. 

And sure, you can find answers to most coding questions online these days, but it’s always a great idea to have at least a few python books on your shelf!

Plus, with the Bureau of Labor and Statistics reporting an average salary of more than $100K for programmers, grabbing a Python book can be the first step to a lucrative career.

So, if you’re ready, let’s dive into the best Python books to boost your skills and get you ready to enter the Python job market .

• Best Python Books for Beginners

1. Python Crash Course (3rd Edition)

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Why we chose this book

Let’s kick off with one of the most popular Python books available, Python Crash Course, by Eric Matthes.

When I was starting out with Python, this was one of the first books I picked up, and it seems I wasn't alone!

With more than 1.5 million copies sold , this book’s clear and concise teaching has made it a firm favorite among aspiring Python developers.

The first thing I have to say is that you won't yawn through endless pages, as this Python book is more of a well-paced sprint through Python essentials .

I also appreciate that it’s split into two halves, with the first solidifying your understanding of basics like loops and classes with clear examples and exercises.

With the fundamentals of Python down, the second half is where you shine by building three Python projects to bolster your portfolio and coding chops.

What about the teaching style? It’s hands-on with a learn-by-doing approach . I love this, as there's no substitute for putting theory into practice. It’s also packed with exercises to test and build your skills.

You can also expect to get to grips with libraries like Pygame for games, Matplotlib and Plotly for data visualization, and Django for web apps.

It’s also really nice to see Matthes using Python 3.11 in the updated edition. He also embraces VS Code as the preferred Python IDE .

In my opinion, this is a no-brainer for beginners but robust enough for pros to brush up their skills.

It’s also clear in the user reviews that readers like the practical approach and clear instructions, making this an ideal Python programming launchpad.

Standout Features :

• Best-seller status with an author who knows how to teach.
• Real-life projects that make your resume pop
• Up-to-date with Python 3.11 and modern tools.

2. Automate the Boring Stuff with Python (2nd Edition)

Time to dive into another popular Python book, Automate the Boring Stuff with Python by Al Sweigart.

I have to admit, this is another one that I picked up when I was starting, as I was drawn to the idea of automating.

After all, who doesn’t want to harness Python to make their life easier?!

One of the best features of this book is Sweigart's approach to teaching, as he makes it easy for beginners and those without prior coding experience. He even has a related Python course on Udemy .

This Python book walks you through each program with detailed instructions, and updated projects at the end of each chapter put your skills to the test.

This is always music to my ears, as there is no substitute for learning Python by doing, and what better way than with real-world tasks that you can relate to.

Plus, you get the fringe benefit of freeing up your time.

In general, the goal of this book is simple: to teach coding in a way that directly impacts your efficiency and productivity .

I also appreciate the fact that the updated edition offers new chapters on input validation, automating Gmail and Google Sheets, and more.

It’s also obvious from the user reviews that aspiring Pythonistas appreciate the emphasis on making coding directly applicable to everyday life.

Whether you're a Python newbie or looking to streamline your workflow , this book's a solid pick.

Standout Features:

• Turns tedious tasks into Python practice.
• New content on input validation and Google automation.
• Step-by-step instructions that build your coding muscles.
• Updated projects that challenge you to apply what you’ve learned.

3. Learning Python (5th Edition)

This is no skimpy pamphlet or Python cheat sheet !

We're talking about a comprehensive deep-dive into Python that’s over 1600 pages long, and it’s another that I added to my bookshelf when starting out. 

Whether you're a newcomer or a seasoned dev looking to expand your Python prowess, this book is a real treasure trove.

And while it may be a few years old, the core material is as relevant today as it was when the book was published.

Not only does it pack a punch with quizzes, exercises, and illustrations , but Lutz's teaching style is interactive and self-paced. 

Given its truly mammoth length, it’s quite a time investment, but one that pays off if you’re serious about Python.

Expect to go deep into general syntax, Python operators , built-in object types, and classes for object-oriented programming.

I really appreciated the strong emphasis on functions to avoid code redundancy, organizing code into modules, and Python’s exception-handling model.

These are essential skills for pro developers , so it makes sense to learn them early. 

You’ll also dive into more advanced features like decorators, descriptors, metaclasses, and Unicode processing. 

The goal of this book isn’t to merely learn Python but to master Python .

That said, I also think it’s an essential reference book to have on hand whenever you need to brush up on a particular topic, whether that's finding a Python substring or creating your own OOP class.

As for user reviews, readers really like the depth of content and the clarity of explanations. 

• Broad and deep exploration of Python.
• Interactive learning with quizzes and exercises rather than passive reading.
• Insights into advanced Python features.

4. Head-First Python (2nd Edition)

This is one of the most unique Python books on our list and another of my favorites.

If you’re unfamiliar with the Head-First series, the idea is to engage your brain visually and practically. 

Yep, forget slogging through dense manuals! This brain-friendly guide is all about taking a hands-on dive into Python .

You'll start with Python's fundamentals, like Python lists and functions, and then apply what you've learned by building a web application, managing databases, and handling exceptions. 

It's also packed with Pythonic tools like context managers, decorators, comprehensions, and generators.

These are some of my favorite aspects of coding in Python, so I really appreciated the fact that they try to encourage learners to use them early.

I also like the fact that it includes exercises and quizzes at the end of each chapter to test your understanding of the material.

If you want a book that makes learning Python enjoyable and less of a chore, this is definitely a solid choice that’s well-liked by existing readers. 

• A visual, engaging approach based on cognitive science and learning theory.
• Practical, hands-on exercises building up to a complete web application.
• Coverage of essential Python features for real-world programming.
• A unique format that makes learning Python intuitive and fun.

5. Introducing Python (2nd Edition)

This is an excellent choice for newcomers to programming who want to start with Python or are taking a Python course .

The main feature that really stands out about this Python book is the author’s methodical yet engaging approach.

Aiming at beginners, you’ll work through the basics and onto more complex subjects with a mix of tutorials and cookbook-style code recipes.

I really like this approach, as it’s ideal for hands-on learning. Which, if you haven’t guessed, is something I’m a big fan of!

I also appreciate the end-of-chapter exercises that allow you to practice what you've learned. 

Overall, this Python book stands out for its ability to teach a robust foundation in Python, including best practices for testing, debugging, and code reuse.

In my opinion, these are all critical skills for real-world programming, so kudos to the author for including them.

To round things out, it also shows you how to apply Python in various fields, such as business, science, and the arts.

This even includes sections on leveraging the vast ecosystem of Python packages. This is a nice touch, as it shows that the author appreciates Python's versatility.

• Blend of foundational tutorials and practical code recipes.
• Engaging writing style that makes learning Python enjoyable.
• Comprehensive coverage of Python with end-of-chapter exercises.
• Covers Python's application in various fields with a variety of tools.

6. Python Basics: A Practical Introduction to Python (1st Edition)

Whether you're completely new to coding or a seasoned dev who wants to learn Python, this is a well-structured and practical introduction.

I also like the sample projects the authors have included, as this ensures you're not just reading about Python but actively learning and applying it.

I’ll say it over and over: this is one of the most important things about learning Python. Code, build, and get practical!

Something that stood out to me about this Python book is the way it’s structured to build your understanding incrementally.

Expect to cover foundational topics like data structures and control flow before venturing into advanced territories like object-oriented programming (OOP).

You’ll also tackle file I/O, working with databases, and even scientific computing and data visualization with NumPy and Matplotlib.

It also covers the basics of creating and modifying PDF files, interacting with the web, and building graphical user interfaces (GUIs). 

Another strong point of this Python book is the interactive quizzes and exercises. These are ideal for reinforcing learning while also making it fun and engaging to measure progress. 

It’s also nice to see the authors include solutions to compare your approach with professional standards.

• Chapters dedicated to fundamental programming concepts.
• Interactive quizzes and practical exercises with solutions.
• Covers a broad range of applications, from web scraping to GUI creation.

7. Learn Python in One Day and Learn It Well (2nd Edition)

I guess the main question is, can you really learn Python in one day with this book?!

In my opinion, maybe! But you should probably be prepared to spend a lot more than one day truly mastering Python, especially if you’re totally new to programming.

That said, I appreciate that this Python book makes the learning process both swift and enjoyable!

One of this book’s main strengths is that the author breaks down complex concepts into digestible steps. This is essential for absolute beginners to grasp the nuances of Python.

Now, bear in mind that at less than 200 pages long, it’s more of a primer than a truly comprehensive guide to learning Python.

Despite the short length, you can expect a hands-on approach to learning basics like variables, data types, user inputs, iteration, errors, functions, modules, and OOP.

I also appreciate the inclusion of step-by-step instructions and practical examples to help you retain the material.

A standout feature for me is the emphasis on real-world applications, as the author has included Python concepts for data, web development, and machine learning.

Overall, if you're looking to dive into Python but are short on time, this book is for you. 

• Concise breakdown of Python for beginners.
• Real-world examples for quick and effective learning.
• Curated selection of topics to cover essential skills
• Hands-on project to encapsulate concepts and reinforce learning.

8. Think Python (2nd Edition)

If you're looking for a Python book that combines practical programming with essential software development principles, Think Python is a fine choice. 

This is also one of my favorite Python books, as it’s short, to the point, and practice-oriented.

I also like the author’s writing style when introducing computer science fundamentals. It really is one of the most thorough options for beginners despite its modest length.

If you want to understand programming beyond syntax and semantics, definitely give this one a try!

It's also a great way to level up your knowledge of Python concepts for interviews.

One of the main strengths of this book is the balance of practical coding exercises with fundamental software development concepts. 

Expect to start with basic programming concepts before taking on Python specifics, like functions, recursion, data structures, and object-oriented design. 

In my opinion, this book is ideal if you want to gain a solid foundation in programming with Python while also learning to think like a computer scientist. 

• A thorough introduction to computer science with Python.
• Programming concepts are clearly defined and logically progressed.
• Practical exercises in every chapter, with case studies for in-depth learning.
• Covers how to think algorithmically and solve programming tasks.

9. Python: For Beginners (1st Edition)

Whether you're just starting out, returning to coding after a break, or a professional who needs a quick primer , this Python book is an excellent choice.

And at only 135 pages, it’s one of the very shortest books on our list.

I also appreciate that the author takes a pragmatic approach to programming, emphasizing the importance of thinking like a programmer . 

For me, this is one of the most important skills for newcomers, so it’s great to see the author baking this in.

And while it’s not promising to teach you Python in a single day, it is designed to let beginners learn basic Python in seven days .

This is something I can believe because even if you’ve never coded in your life, you can definitely learn the core skills in one week.

Interestingly, despite its modest length, this Python book is relatively comprehensive , with chapters on loops, data types, dictionaries, and more.

You’ll also touch on advanced topics like object-oriented programming, file I/O, and regular expressions, not to mention the section on best practices for Python development.

It’s also great to see hands-on coding projects , which I think are essential for bringing new concepts to life. 

• Covers Python essentials such as loops, data types, and object-oriented programming.
• Step-by-step guidance to take a newcomer from installation to coding their own projects.
• Practical exercises cement new Python skills in a fun and engaging way.

10. Learn Python 3 the Hard Way (1st Edition)

The first thing that stood out to me about this book was the title! I mean, who wants to do things the hard way, right?

It’s probably why I picked this book up myself, as I just had to know how hard it would be?

Turns out, it's not that hard!  

If you’re not familiar with the author, Zed Shaw’s method combines discipline and persistence with 52 practical exercises ranging from basic math to web development. 

Expect to cover fundamentals like variables, data types, user input, file I/O, data structures, and advanced topics like object-oriented programming and modules.

You’ll even learn about Python packaging, automated testing, and basic game development.

But what makes this such a good Python book is that it’s designed for those who prefer to learn by doing . 

This means writing out every line of code yourself, avoiding all copy-pasting, and switching off any autocomplete features.

The idea is to truly learn Python by getting the code under your fingers. This is something I wholeheartedly agree with, as it’s all so easy to rely on your IDE to do the coding for you.

And with the growing availability of AI coding assistants , the temptation is even greater for beginners to rely on AI autocompletions when learning Python.

Overall, I'd say it's much easier to avoid common Python mistakes if you make them and then learn from them.

I also like that it goes beyond plain coding , delving into how computers work, program design, and the intricacies of Python.

You can even access more than 5 hours of complementary video content. 

• 52 real-world exercises for hands-on learning.
• Emphasis on manual coding to improve precision and understanding.
• Additional video content for an enriched learning experience.
• Suitable for learners of all levels, from beginners to seasoned professionals.
• Python Books for Improvers & Pros

11. Fluent Python (2nd Edition)

With a focus on idiomatic Python code, this book is ideal if you want to improve your Python skills and learn best practices for writing efficient, elegant, and maintainable code.

Fluent Python really stood out to me for being a deep dive into the Python language for more experienced coders, hence the 1000+ pages!

But rather than being a plain manual, it’s actually a guide to thinking in Python .

I really like this approach, as a Python mindset can be the key to leveraging Python’s full potential in your work or even when prepping for Python certifications .

Expect to take a comprehensive look into Python's data model and built-in data structures while also learning about graph algorithms, caching, and dynamic programming.

You'll also explore advanced topics like treating functions as objects, object-oriented idioms, context managers, generators, and concurrency.

One of my highlights is the emphasis on writing Pythonic code, as you’re often encouraged to put the theory into practice. 

This means that you're not just passively reading but engaging with exercises that reinforce the material.

Even if you’re coming from another language, Ramalho's guidance on metaprogramming with Python is really helpful for reshaping your thinking and approach to coding.

• Deep dive into Python's core language features and libraries for effective coding.
• Practical exploration of advanced topics like metaprogramming, concurrency, and generators.
• Emphasis on idiomatic Python code to make your programs Pythonic.
• Hands-on exercises to solidify concepts and make the learning process active.

12. Python 3: The Comprehensive Guide to Hands-On Python Programming (1st Edition)

If you’re looking for a comprehensive guide to Python, this might be one of your best options.

It's also nice to know that this Python book proudly earned the 2024 IBPA Benjamin Franklin Award in the Professional and Technical Category .

Coming in at a whopping 1000+ pages, it's well suited as a dive deep into Python and a great reference book to have on your shelf.

We’ve all got at least one massive programming book on our shelves, right? 

Aimed at those who want to master Python programming, I think this book stands out for its thorough and hands-on approach, with a large emphasis on writing effective code.

This also makes it a great resource when preparing for Python interviews .

Expect to start with basic Python principles, including detailed explorations of functions, methods, and data types. 

You’ll also be using Python's standard library extensively, which is great to see, as this is one of Python’s greatest strengths.

After which, you’ll gradually ramp up to more complex topics with a deep dive into GUIs (Graphical User Interfaces), network programming, debugging, and optimization. 

I really liked the inclusion of advanced programming techniques , including Django for web development, scientific computing, and interfacing with other programming languages.

These are all excellent skills to add to your toolkit when you’re ready to level up from beginner to expert.

Plus, this Python book is also packed with a wealth of practical code examples , which are also downloadable. 

• Comprehensive and complete handbook on Python 3.
• Detailed exploration of GUIs, network programming, and debugging techniques.
• Advanced topics like Django, scientific computing, and language integration.
• Ample practical code examples for hands-on learning.

13. Effective Python (2nd Edition)

If you’d class yourself as an intermediate-level Python developer, this is a solid choice as it offers a comprehensive guide to the nuances of Pythonic code.

No matter how experienced you are, this book is full of valuable insights.

Expect to go deep into Python's built-in data structures, concurrency and parallelism, robustness, and performance optimization in Python. 

For me, the stand-out feature of this Python book is the clear focus on real-world applications,  not to mention the 90 practical examples to enhance your coding skills.

As I’m sure you know all too well by now, I’m always in favor of practical examples!

It’s also really nice to see that each chapter is broken down into digestible sections, with each centering around a practical, actionable recommendation.

I like this style: learn the concept, then put it into practice.

• In-depth coverage of Pythonic coding practices with 90 practical examples.
• Focus on real-world application, perfect for intermediate to advanced programmers.
• Clear, concise explanations coupled with illustrative code examples.

14. Python Distilled (1st Edition)

As the updated version of the highly popular Python Cookbook , Python Distilled is an essential resource for experienced Python developers. 

The clue is in the title, I guess, but I really like that this Python book conveys the core concepts of Python in a distilled and clear manner.

This is ideal to deepen your Python knowledge without being bogged down in unnecessary details.

I also like the pragmatic structure that dives into the core of the Python language, including topics like data abstraction, control flow, program structure, functions, objects, and modules. 

By focussing on foundational elements, Python Distilled is also a great choice for developers who are making the transition to Python.

For instance, it also covers Python's object-oriented programming model and techniques for proper input/output handling to help programmers relate these concepts to other languages.

Bear in mind this is not a step-by-step tutorial but more of a reference guide that summarizes the most important language features in an easily digestible way.

This makes it a great choice if you’re a seasoned programmer who’s after a quick reference. After all, it’s only 350 pages long.

• Concise yet comprehensive overview of modern Python, focusing on its core elements.
• Clear and simple presentation of complex concepts for experienced programmers.
• Covers fundamental topics like data abstraction, control flow, program structure, and more.
• Practical advice on structuring programs for clarity, reliability, and maintainability.

15. High Performance Python (2nd Edition)

As the final entry on our list, High Performance Python is a standout choice if you want to push the boundaries of efficiency and performance in your Python code.

I really like this book’s style, as it’s not just about writing code that runs; it's about writing Python code that runs fast!

Sure, we all have powerful computers these days, but I think it’s a sign of a real professional when your code is not only Pythonic but optimized for speed .

You’ll also gain insight into how to optimize CPU time, memory usage, and how to use the right data structures.

It even delves into advanced topics like matrix computations and multicore architectures.

Given how popular Python is for data science and data-driven roles, expect to dive deep into the art of performance optimization for high-data-volume programs.

This is ideal if you want to level up your knowledge of Python concepts for data science.

I also appreciate that the book helps you understand the theory behind design choices and practical Python implementations.

This leads me naturally to a standout feature of this book, which is the focus on practical solutions for common performance bottlenecks.

They even include real-world stories from industries like social media analytics and machine learning.

I like this approach, as it adds more depth to performance challenges and how they can impact actual companies and real industries.

• Strategies for writing efficient programs tailored for high performance.
• Techniques for managing I/O and computational operations concurrently.
• In-depth understanding of NumPy, Cython, and Python profilers.
• Guidance on deploying code using modern tools like Docker.
• Why Learn Python In 2024?

If you're brand new to programming, let's start with the basics.

Python is a high-level, general-purpose programming language with a simple and intuitive syntax.

This makes it easy to learn and understand, meaning it’s an excellent language for beginners.

So, if you're completely new to coding, Python is always a great place to start your journey.

Python is also renowned for its versatility and varied applications , meaning you can use it for data science, machine learning, web development, scientific computing, and more.

One of my favorite things about Python is the vast and supportive community of Python developers.

Not only are they always there to help you learn, but they're also constantly creating useful libraries, modules, and Python frameworks .

• How To Choose The Best Python Book

Choosing the best books to learn Python can be tricky, especially if you’re a beginner.

That's exactly why I created this article!

But if you want some tips for finding the best Python books, here are the criteria I used when creating this list:

• Determine your skill level: If you are a beginner, look for Python textbooks that cover the basics. If you’re an experienced programmer, look for advanced books on specific features.
• Check the author's credentials: Focus on Python books written by authors with experience in programming and teaching Python.
• Read reviews: Check out the Python book's reviews online to understand what other readers think. This is often a goldmine of information!
• Consider your learning style: If you prefer a hands-on approach, focus on Python books that include exercises and projects.
• Wrapping Up

And there you go, the 15 best Python books in 2024, including Python books for beginners and experienced coders.

Whether you’re just starting out in Python or you want to level up your skills, we’ve included Python books to help you achieve your goals in your programming career.

Happy reading!

Are you brand new to programming, and you're ready to learn Python? Check out:

Our very own Python Masterclass - Python with Dr. Johns

• Frequently Asked Questions

1. Which Is the Best Book for Python Beginners?

It’s hard to pick the best Python book for beginners, depending on your previous programming experience, preferred learning style, expectations, and more.

If you’re unsure where to start, we’d recommend Head-First Python for its unique teaching approach or the Python Crash Course . But overall, we’d recommend any from our list of the best books for Python beginners.

2. Which One Is the Best Book for Python?

Selecting the best book for learning Python is hard, as it depends on your skill level, interests, and preferred learning style.

If you’re unsure where to start, check out any of the books on our list, as there are options for beginners and experienced developers. If you’re a beginner who wants a comprehensive read, check out Learning Python , or if you’re an advanced developer, consider Python Distilled . 

3. Can You Learn Python From a Book?

Yes, you can learn Python from a book. It’s also important to include hands-on coding practice and maybe work on some of the best Python projects to reinforce your learning. You could also consider backing your book learning with one of the best Python courses.

People are also reading:

• Best Python Compilers
• Best Python Interpreters
• Best way to learn python
• Python Programming languages
• How to Run a Python Script?

1. Stack Overflow. Stack Overflow Developer Survey 2023: Most Popular Technologies - Programming, Scripting, and Markup Languages [Internet]. Stack Overflow; [date unknown; cited 2024 Jan 15]. Available from: https://survey.stackoverflow.co/2023/#section-most-popular-technologies-programming-scripting-and-markup-languages

2. Bureau of Labor Statistics, U.S. Department of Labor. Occupational Employment and Wages, May 2022, 15-1251 Computer Programmers [Internet]. [updated 2021 Mar 31; cited 2024 Jan 15]. Available from: https://www.bls.gov/oes/current/oes151251.htm

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In this article

• 10 Vital Python Concepts for Data Science
• 10 Common Python Mistakes in 2024 | Are You Making Them? Python Data Science Programming Skills
• 10 Python Concepts I Wish I Knew Earlier For Interviews [2024] Python Career Development Interview Questions

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Best Python Books in 2023 (Beginner & Advanced)

• January 9, 2023 January 9, 2023

In this post, we’re going to explore the best books to learn Python in 2023, whether you’re a beginner or an advanced user . Finding the right book to learn can make or break your learning journey. Python is an incredibly in-demand skill for professional software developers, data analysts, and anyone looking to advance their career.

This post will cover the best books to help get you started or advance your career even further! While we generally focus on data science here on datagy, this post will cover the best general Python programming books as well as machine learning-specific books. Want to learn Python for free? Check out my 30 day course here .

Updated for 2023

This post has been updated for 2023! While many of the recommendations are still the same, I have added a handful of new books that I really enjoyed personally. I’ll keep updating the list as I find new interesting books.

As an Amazon Associate I earn from qualifying purchases.

Table of Contents

Best Python Book for Beginners: Python Crash Course, 2nd Edition

The best Python book for beginners in 2023 is Python Crash Course (2nd Edition) . The book is the best-selling Python book , providing a hands-on approach to teaching you. The first half of the book is dedicated to teaching you the fundamentals of Python programming, such as lists, variables, and loops.

It doesn’t stop there, though. The book quickly takes you to interactive programming, giving you hands-on opportunities to use what you’re learning. The book takes you much beyond a beginner programmer, giving you three hands-on projects with very different applications . The book will teach you to:

• Build a Space Invaders-inspired arcade game,
• Create a set of data visualizations with Python’s handy libraries, and
• Build a simple web app you can deploy online.

What I Liked Most about Python Crash Course, 2nd Edition

There’s a lot to like about this book! The book assumes no previous programming knowledge, but it also doesn’t feel overly simplified . The book empowers you to understand programming, giving you enough information to let you make your own decisions based on what you’ve learned.

The hands-on projects give you a wide range of different experiences that cover off many different domains of programming. Being able to build a video game that you’ll actually be able to play beats a lot of the theoretical projects that other books focus on.

Python plays a huge role in modern data science and machine learning. Being able to learn how to build visualizations and web apps (using Django) provides you with actionable portfolio projects to help show off what you’ve learned.

Best Applied Python Book for Beginners: Automate the Boring Stuff with Python, 2nd Edition

Automate the Boring Stuff with Python book is one of the best-selling books in Python, and deservedly so! The book promises to, well, help you automate the boring things in your life. And it manages to do exactly that! The book is beginner-friendly but also provides enough motivation for experienced programmers to think outside their area of expertise.

You’ll learn many exciting things to make your day-to-day life (both at work and at home) easier. This includes scraping web data, automating clicking tasks, and working with Gmail and Google Sheets. Some of the other things you’ll learn include:

• Renaming files and folders in a matter of seconds
• Finding text in different files without needing to open them
• Update and format Excel spreadsheets easily and efficiently

What I liked Most About Automate the Boring Stuff with Python, 2nd Edition

The book makes it incredibly easy to feel like an experienced programmer. And it doesn’t just make you feel like one – it actually can make you an apt programmer. The book provides a huge assortment of hands-on projects , which are undoubtedly the best way to learn.

What I really loved about this book is that it demonstrates how easy it is to automate mundane and time-consuming tasks. The book really empowers you to see your everyday challenges as something that’s quite solvable.

Best Visual Python Book for Beginners: Head-First Python, 2nd Edition

Head First Python is part of a larger “Head-First” series that has been used to teach a variety of programming languages. It’s a tried and tested formula for teaching programming by letting you dive headfirst into Python programming.

The book is a bit shorter than others on the list. However, this doesn’t mean it’s sparse in teaching ability. The book provides the ability to learn in discrete chunks. It also provides a large amount of illustrations, which can be incredibly valuable for more complex concepts like object-oriented programming.

The book covers off:

• The basics of Python and how best to store data
• How to build a web-app using Flask and how to store data in a database
• How to work with objects and decorators to modify your functions’ behaviors

What I liked Most About Head-First Python, 2nd Edition

The book provides a ton of helpful visuals to guide you through learning Python. The illustrations are often helpful and provide a good amount of comedic relief. It’s certainly not a dry programming book and provides enough distraction to keep you engaged in the content!

The book also follows along with a single project and goes so far as to let you build a web app using the micro-framework, Flask. This is definitely a great project to show off on your resume and portfolio. That said, it’s not as immediately actionable as Automate the Boring Stuff with Python. However, it covers a lot more depth than other beginner books.

Best Intermediate Python Book: Fluent Python – Clear, Concise, and Effective Programming

Fluent Python teaches you how to think in a Pythonic way . Because this book is aimed at intermediate programmers it seeks to address two main situations:

• It aims to change experienced programmers coming from other languages to think more Pythonically
• It encorages those moving from beginner to intermediate Python programmers to discover more useful elements of the language

Because Python is a simple language it encourages you to get up and running quickly. But this approach can often mask the complexity of codebases you can develop.

Among other concepts, you’ll learn about:

• Data structures and data models
• Metaprogramming concepts and using functions as objects
• Generators and concurrency

What I liked Most About Fluent Python

I loved how Fluent Python guides you through everything you’d learn in a beginner book, but takes you to the next level . The book takes Python programming concepts like tuples and dictionaries and explains how they can be turned into more advanced data structures.

Because of this, it assumes you have a good handle on the basics of these structure. However, it encourages you to think about how much more these structures and concepts have to offer. The book takes your foundational knowledge of Python and extends it by encouraging you to understand why improving your code is important. The chapter on generators, for example, teaches you the importance of thinking about memory management.

Best Advanced Python Book: Python Cookbook, 3rd Edition

The Python Cookbook provides to advanced programmer tools to discover modern tools and idioms . The book assumes you already know Python and are looking for ways in which to make your code better and more Pythonic.

This book isn’t an introductory book. It assumes you already have a good handle on the topics covered and that you want to improve your understanding . The Python Cookbook will teach you more about how Python works , not just that it works. It will also help you write more elegant, readable, and Pythonic code.

Some of the pieces you’ll learn about include flattening lists, improving data structures with other libraries, and safely handling file operations.

Among other topics, you’ll learn about:

• Data strctures and algorithms
• Iterators and generators
• Files and I/O
• Network and Web Programming

What I liked Most About Python Cookbook

I loved how specific this book was . It was not a general programming book, but rather a very specific book that can teach very widely applicable things. For example, you’ll learn how to turn common data structures, such as tuples into namedtuples to make your code cleaner, safer, and better.

As with any programming cookbook, you’ll be given a ton of different recipes for something very specific. A normal cookbook doesn’t teach you to cook in general, but how to cook a specific meal. Similarly, this book will teach you very specific (though very useful) things to improve your code.

Best Machine Learning Python Book: Introduction to Machine Learning with Python – A Guide for Data Scientists

Introduction to Machine Learning with Python teaches you how to dive into the exciting world of machine learning with Python. It assumes that you know a bit about Python programming, but assumes that you’re not an expert in statistics. The book will teach you how to write good, clean machine learning-oriented code. Of course, a book in itself isn’t enough to make you master machine learning, but it sets a good foundation for putting what you learned into practice.

Throughout the book, you’ll learn how to become an apt user of Scikit-Learn and take on supervised and unsupervised machine learning models. You’ll learn how to:

• Build classifiers and regressors using Scikit-Learn
• Build unsupervised machine learning models
• Understand how to make use of one of the most widely used machine-learning packages, Scikit Learn

What I liked Most About Introduction to Machine Learning with Python

I loved the hands-on approach to not only understanding how to write the code of Scikit-Learn, but understanding why the code is written in the way it is. There is an abundance of machine learning tutorials online, but many skip over the why of the code.

This may be fine for people that already understand machine learning programming, but it’s not for the majority of people. This book doesn’t shy away from that and lets you become a better data scientist by understanding these elements!

Best Deep Learning Python Book: Machine Learning with PyTorch and Scikit-Learn

Machine Learning with PyTouch and Scikit-Learn allows the reader to understand the traditional Scikit-Learn but also move into using PyToch for building and understanding neural networks. It’s an incredibly recent book that covers code in the most recent versions of their respective libraries.

The book guides you through the learning process. Much like other books aimed at beginner programmers, this book builds on top of one another. It provides a great mix of concepts, theory, and practice.

Throughout the book, you’ll learn:

• How to build neural networks from scratch and how PyTorch makes its easier
• How to use neural networks for natural language processing and image generation

What I liked Most About Machine Learning with PyTorch and Scikit-Learn

I loved the mix between concepts, theory, and practice . Neural networks are incredibly difficult concepts – by understanding the pieces that make up a neural network, your confidence can easily grow in the topic.

Because each chapter builds on top of one another, you’re guided through complicated concepts in a way that feels empowering. By learning, for example, how to build a neural network from scratch, you can understand the design patterns of PyTorch.

What do I love the most about this book? It makes difficult concepts approachable and manageable !

Best Python Book for Kids: Python for Kids – A Playful Introduction to Programming

Python for Kids helps make coding in Python interesting, both visually and through word, for kids. The book users color and illustrations to keep the content engaging. Similarly, it teaches kids to program in a way that keeps them interested. Examples use monsters and secret agents.

The book, however, also teaches many different important concepts – though in a fun, engaging way. Kids will learn:

• Data structures and functions
• Conditional flow
• How to draw shape, patterns, and user interfaces

What I liked Most About Python for Kids

I loved that the book teaches programming in a way that’s usable for kids. Kids aren’t worried about building the next machine learning model to change the world. Rather, the book focuses on building games and showing kids how to build engaging and fun programs!

Best Book for Learning Data Structures and Algorithms: A Common-Sense Guide to Data Structures and Algorithms

A Common-Sense Guide to Data Structures and Algorithms is an approachable way to learn data structures and algorithms. With many people jumping into programming and data science without a formal computer science degree (myself included!), data structures and algorithms can be an often-overlooked topic.

Thankfully, this book makes the topic incredibly approachable. While the examples are written in Python, JavaScript, and Rust, they should be easy enough to follow.

What you’ll get out of this book:

• How to approach data structures and algorithms in a hands-on, practical way
• How to understand Big O notation in the context of everyday programming
• How to understand data structures and algorithms using helpful visuals

What I Liked Best About A Common-Sense Guide to Data Structures and Algorithms

I loved that this book was incredibly approachable while being quite serious about getting you up and running with data structures and algorithms. The progression of the book follows a good rhythm and makes sure you understand all of the examples. Moreso, it drills in why different elements are important.

Alternative for Learning Data Structures and Algorithms: Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People

If you’d prefer a much more visual approach to learning data structures and algorithms, Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People is a great alternative. The book provides incredible visuals for each data structure and algorithm, allowing you to dive deep into how they work and why it matters.

What you’ll learn in this book:

What I Liked Best About Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People

The visual approach can be a good foray into understanding complex data structures and algorithms. I liked reading this book in tandem with A Common-Sense Guide to Data Structures and Algorithms. While I’m not typically a visual learner, some of the topics covered really benefited from the approach.

In this post, I explored the best books to learn Python in 2023. Each section covered off a different area that you may want to learn about, from total beginners to those wanting to break into deep learning. Each of these books will teach you different critical pieces to understand in your Python journey. If you’ve read any of them, let me know in the comments what you think!

Nik Piepenbreier

Nik is the author of datagy.io and has over a decade of experience working with data analytics, data science, and Python. He specializes in teaching developers how to use Python for data science using hands-on tutorials. View Author posts

1 thought on “Best Python Books in 2023 (Beginner & Advanced)”

I have written a book on Python which discusses the language in a novel way. The book has just been published by Apress under the title Pragmatic Python Programming. It has received very positive reviews from the first readers and its Hungarian language predecessor is one of the best selling IT books in the Hungarian market. If you are interested in considering adding to your list, the publisher can send you an electronic copy for review. (Naturally, no pressure and just include “Pragmatic Python Programming” on your list if you really think it deserves its place.)

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Top 22 Python Books for Beginners and Advanced Coders

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What Is Python?

How to choose the best python books, best python books for beginners, best python books for learning computer science, best specialized python books, best python books for hackers, one-size-fits-all python books, final thoughts, frequently asked questions (faqs) about python books.

In this article, we’ll look at the best books for learning Python — catering for the absolute beginner level right through to the highest level of proficiency, as well different fields and learning angles.

Get ready, as this will be a deep dive! 🤿

We’ve also recently reviewed the best books for learning HTML , CSS , JavaScript , PHP , Node.js and SQL .

Python Programming: A Beginner’s Guide to Learn Python in 7 Days

Learn python in one day and learn it well: python for beginners with hands-on project, python pocket reference: python in your pocket, learning python: powerful object-oriented programming, fluent python: clear, concise, and effective programming, python for beginners: a crash course guide to learn python in 1 week, python crash course: a hands-on, project-based introduction to programming, automate the boring stuff with python: practical programming for total beginners, learn python 3 the hard way: a very simple introduction to the terrifyingly beautiful world of computers and code, coding for kids: python: learn to code with 50 awesome games and activities, python programming: an introduction to computer science, think python: how to think like a computer scientist, python for everybody: exploring data in python 3, python for data analysis: data wrangling with pandas, numpy, and ipython, invent your own computer games with python, introduction to machine learning with python: a guide for data scientists, python for excel: a modern environment for automation and data analysis, python for finance: mastering data-driven finance, effective python: 90 specific ways to write better python, python tricks: a buffet of awesome python features, black hat python: python programming for hackers and pentesters, python: the bible, extra: cheat sheets, extra: the sitepoint library.

Python is a programming language that you can use for pretty much anything. It’s fun , well thought out , elegant by design , widely adopted , and comparatively easy to learn.

And seriously, none of that is an understatement. Python really goes all the way when it comes to general-purpose programming :

• web development
• machine learning and artificial intelligence
• data science and data analysis
• software testing
• (to some degree) game development and microcontrollers

If you want to know more about Python, check out What Is Python and What Is It Used For?

While Python itself is easy to learn, there is a lot of ground to cover. That’s because there’s a lot you can do with it! Not surprisingly, there are many great books.

Here are some things to consider when picking a Python book:

• your current programming skills
• the field you’re interested in
• your learning approach (is it academic, rather practical, or “hacker” style?)

With that in mind, let’s get acquainted with some titles!

Please note that as an Amazon Associate, SitePoint will earn commisions from qualifying purchases made through links in this article.

The logical place to start is with books for absolute beginners, so here are some of our favorites.

• Author : Ramsey Hamilton
• Publishing : independent (June 14, 2016)
• Paperback : 90 pages
• Ranking on Amazon : 4.4/5 (5,822 ratings)

Python Programming is a very straightforward and concise book, being only 90 pages long! It’s written in simple language, and is a great choice for the absolute beginner. It covers the basics of Python and its data structures, and also touches on topics such as functions, classes, modules, and exceptions.

There are a few quality issues reported in the eBook, such as typos and poor formatting, which can be a bit annoying for the reader. That said, it still has nearly 6,000 ratings on Amazon, so if you’re after a quick, short guide, and a fairly inexpensive book, it may well be worth checking out.

• Author : Jamie Chan
• Publishing : second edition (May 4, 2017)
• Paperback : 174 pages
• Ranking on Amazon : 4.5/5 (1,547 ratings)

If you prefer to learn with hands-on projects, prolific author Jamie Chan’s Learn Python in One Day and Learn It Well is probably a good fit for you.

It’s a fairly compact book that covers the foundations of the language in the first part and then moves on to more advanced topics and a complete project.

The book is part of the series Learn Coding Fast with Hands-On Project (7 books), which also includes books for C++, Java, JavaScript and other languages, in case you want to expand your coding skills.

• Author : Mark Lutz
• Publishing : fifth edition (March 11, 2014)
• Paperback : 262 pages
• Ranking on Amazon : 4.5/5 (848 ratings)

Mark Lutz ( blog ) is one of the earliest Python authors, and Python Pocket Reference is a key item in his prolific lists of works and is in its fifth edition and counting .

Aimed mainly at reference rather than learning , this book covers Python 3.4 and 2.7, and even nearly ten years after first being published it’s still an invaluable reference for all Python programmers. It’s part of O’Reilly’s Pocket Reference series, composed of 34 books on a variety of topics.

It covers the language syntax and standard libraries, including:

• built-in functions and exceptions
• data types and structures
• statements and syntax
• functions and arguments
• classes and objects
• modules and packages

• Publishing : fifth edition (July 30, 2013)
• Paperback : 1,643 pages
• Ranking on Amazon : 4.5/5 (1,729 ratings)

With Learning Python , Mark Lutz has achieved another fifth-edition book. But unlike Python Pocket Reference , Learning Python is a full on deep dive.

This book is part of the Learning Python series (7 books). In over 1,600 pages, it covers:

• types and operations
• functions and generators
• classes and OOP
• exceptions and tools
• other advanced topics

• Author : Luciano Ramalho
• Publishing : first edition (September 15, 2015)
• Paperback : 790 pages
• Ranking on Amazon : 4.7/5 (684 ratings)

Among the best-ranked Python books, Fluent Python ( repo ) is also part of the Learning Python series.

However, in Fluent Python , author Luciano Ramalho ( GitHub ) gets into the so-called “Pythonic way”, illustrating efficient and elegant code that exploits Python’s unique capabilities and style.

If you’re looking for a beginner book that goes the extra mile and pushes you a bit further forward, this might be what you’re looking for.

• Author : Timothy C. Needham
• Publishing : independent (September 21, 2017)
• Paperback : 135 pages
• Ranking on Amazon : 4.3/5 (3,152 ratings)

Python for Beginners is pretty straightforward and it covers all the basics in a “crash course” format.

And while it might not be the most comprehensive book on Python, with over 3,000 ratings on Amazon you can’t deny it’s quite a popular one.

• Author : Eric Matthes
• Publishing : second edition (May 3, 2019)
• Paperback : 544 pages
• Ranking on Amazon : 4.7/5 (7,807 ratings)

This is the most popular book of our selection, the one with the highest ratings — and boy, you’ve got to love that cover!

Written by Eric Matthes ( GitHub , old blog ), author of several Python books , Python Crash Course ( repo ) is still today the #1 best seller in Python programming on Amazon. With over 1,000,000 copies sold, this is arguably the most popular Python book of all time .

Python Crash Course teaches programming through three projects that really show how multi-purpose Python can be:

• a 2D Space Invaders-style arcade game
• responsive data visualizations
• a customized web app

• Author : Al Sweigart
• Publishing : second edition (November 12, 2019)
• Paperback : 592 pages
• Ranking on Amazon : 4.7/5 (2,689 ratings)

With 10 books published and hundreds of repos on GitHub, Al Sweigart ( blog , GitHub ) is a prolific Pythonist author and coder — which, believe it or not, is not that usual, as many authors don’t code all that much!

Automate the Boring Stuff with Python is among the best-ranked Python books, and it has a companion website and a full course on Udemy , both maintained by the author.

Check out the 15-video series below, in which Al covers the entire book . It’s fantastic!

Let’s now focus in on Python books that teach you how to use Python in the field of computer science.

• Author : Zed Shaw
• Publishing : first edition (June 27, 2017)
• Paperback : 320 pages
• Ranking on Amazon : 4.4/5 (936 ratings)

We’re entering more experienced territory now. If you already know some Python and want to go deeper, Zed Shaw ‘s ( GitHub ) Learn Python the Hard Way ( repo ) will take you further through a series of 52 programming exercises.

And if you like the author’s approach, this is part of the five-book series Zed Shaw’s Hard Way , which also includes the followup Learn More Python 3 the Hard Way: The Next Step for New Python Programmers .

• Author : Adrienne Tacke
• Publishing : first edition (March 19, 2019)
• Paperback : 232 pages
• Ranking on Amazon : 4.6/5 (1,517 ratings)

Now for something fun! Python is an excellent language for kids , as it’s relatively simple and easy to learn, yet powerful enough to allow them to create projects and games. Coding for Kids Python will help your kid get started.

Written by Las Vegas–based, Filipina software engineer Adrienne Tacke ( blog , GitHub ), Coding for Kids also helpfully comes in a spiral-bound edition. 😀

• Author : John Zelle
• Publishing : third edition (August 8, 2016)
• Paperback : 552 pages
• Ranking on Amazon : 4.6/5 (387 ratings)

For a more formal approach to the subject, John Zelle, Ph.D has published a book that’s used in many universities as the main textbook for a Computer Science course based on Python.

Python Programming is a fairly complete book, and is a fine starting point for those who are new to the world of programming and computer science.

• Author : Allen Downey
• Publishing : second edition (January 26, 2016)
• Paperback : 289 pages
• Ranking on Amazon : 4.7/5 (515 ratings)

Written by Allen Downey ( GitHub ), professor of Computer Science at Olin College of Engineering, Think Python ( repo ) is one of the best-rated books for those starting with Python.

It covers the basics of the language, including data structures and algorithms, with a focus on the programming mindset, teaching the reader how to think like a computer scientist.

It’s also part of the seven-book Learning Python series.

We’ll now turn our attention to Python books with a more specialized focus.

• Author : Dr. Charles Russell Severance
• Publishing : independent (April 9, 2016)
• Paperback : 247 pages
• Ranking on Amazon : 4.6/5 (2,575 ratings)

Charles Russell Severance ( GitHub ) (or Dr. Chuck, as many know him) is a professor at the University of Michigan, and this book is part of the Python for Everybody Specialization offered at Coursera (to which he’s a major contributor).

Python for Everybody ( site , repo ) has been dubbed “ the most popular programming course in the world “. Not surprisingly, then, this is a great book for getting up to speed quickly on the fundamentals of data analysis, with a concise introduction to the data analysis and visualization tools you need to be a competent Python programmer.

Do you think you could handle a nearly 14-hour course based on this book? With over five million views, it may very well be worth giving it a try!

• Author : William McKinney
• Publishing : second edition (November 14, 2017)
• Paperback : 547 pages
• Ranking on Amazon : 4.6/5 (1,688 ratings)

Python for Data Analysis ( repo ) by William McKinney ( blog , GitHub ) is another great and quite popular data science book.

Aside from print, it’s also available for reading online .

• Publishing : fourth edition (December 16, 2016)
• Paperback : 376 pages
• Ranking on Amazon : 4.7/5 (445 ratings)

Python is not only for data science, but also for game development. And Al Sweigart (also the author of Automate the Boring Stuff with Python ) has written Invent Your Own Computer Games with Python ( repo ) to show readers how to do this.

This book is perfect for kids and adults alike. It starts by explaining the basics of Python programming, and then guides the reader through making games like Tic Tac Toe , Hangman , and Guess the Number .

Also among the best ranked Python books, it’s on its fourth edition, which is quite something for a book on games development with Python!

A quick review and an interview with the author:

• Authors : Andreas Müller and Sarah Guido
• Publishing : first edition (November 15, 2016)
• Paperback : 398 pages
• Ranking on Amazon : 4.5/5 (398 ratings)

Andreas Müller and Sarah Guido ( GitHub ) are both well-known Pythonists, and their book Introduction to Machine Learning with Python ( repo , slide deck ) is considered by some as the best book on machine learning . And it surely is no coincidence, as Andreas is core developer and co-maintainer of the popular machine learning library scikit-learn .

Material covered:

• supervised learning
• unsupervised learning and preprocessing
• representing data and engineering features
• model evaluation and improvement
• algorithm chains and pipelines
• working with text data

Introduction to Machine Learning with Python also part of the seven-book Learning Python series.

• Author : Felix Zumstein
• Publishing : first edition (April 13, 2021)
• Paperback : 335 pages
• Ranking on Amazon : 4.5/5 (208 ratings)

If you are an Excel power user, you should definitely check out Python for Excel ( GitHub ), by Felix Zumstein ( GitHub ).

Felix is a Python consultant and data analyst, and has a deep understanding of Excel. He’s also the core developer of xlwings , the open-source library for automating Excel and Google Sheets with Python.

This book is a practical guide to using Python to automate, clean up, and analyze data stored in Excel spreadsheets, and to create advanced Excel reports.

• Author : Yves Hilpisch
• Publishing : second edition (January 8, 2019)
• Paperback : 720 pages
• Ranking on Amazon : 4.6/5 (268 ratings)

Yet another topic in which Python rules is computational finance, and if you ever need to delve into this field from an algorithmic or data-driven angle, you’ll surely end up using Python.

Author Yves Hilpisch ( GitHub ) has published a number of books on the topic, and Python for Finance ( repo ) is his most popular one to date.

With over 700 pages, it’s a lengthy book. But it does have a fairly comprehensive content:

• mastering the basics : data types and structures, numerical computing with NumPy, data analysis with pandas, and object-oriented programming
• financial data science : data visualization, financial time series, input/output operations, performance Python, mathematical tools, stochastic, statistics
• algorithmic trading : the FXCM trading platform, trading strategies, automated trading
• derivatives analytics : valuation framework, simulation of financial models, derivatives valuation, portfolio valuation, market-based valuation

Next, we’ll survey Python books that are particularly suited to those looking to use Python for hacking .

• Author : Brett Slatkin
• Publishing : second edition (November 15, 2019)
• Paperback : 480 pages
• Ranking on Amazon : 4.7/5 (366 ratings)

We’re now entering expert territory, and the Effective Software Development series is a compilation of books about software development written by a number of authors. Effective Python ( repo ) is written and maintained by Brett Slatkin ( blog , GitHub ).

The second edition is ranked among the best Python books. Among other things, it covers the following advanced topics:

• Pythonic thinking
• metaclasses and attributes
• concurrency and parallelism
• robustness and performance
• testing and debugging

• Author : Dan Bader
• Publishing : first edition (October 25, 2017)
• Paperback : 301 pages
• Ranking on Amazon : 4.7/5 (1,332 ratings)

Author Dan Bader ( blog , GitHub ) is a Python coach, trainer, speaker, and published author. His Python Tricks covers many topics — from the basics to the more advanced topics.

It’s the most rated advanced Python book. If you’re wondering who should read this book, the back cover of the book explains why it might be relevant to you:

if you’re wondering which lesser known parts of Python you should know about if you’ve got experience with legacy versions of Python if you’ve worked with other programming languages and you want to get up to speed with Python if you want to make Python your own and learn how to write clean and Pythonic code

• Authors : Justin Seitz and Tim Arnold
• Publishing : second edition (April 14, 2021)
• Paperback : 216 pages
• Ranking on Amazon : 4.7/5 (413 ratings)

Black Hat Python ( unofficial repo ) is a book about using Python for security research.

It’s not a book for beginners, as it requires some programming and network know-how, but it is ranked among the best books in the cyber security niche, and it’s a must-have for anyone interested in the field.

It covers topics such as:

• creating a trojan command-and-control server using GitHub
• detecting sandboxing and automating common malware tasks like keylogging and screenshotting
• extending the Burp Suite web-hacking tool
• escalating Windows privileges with creative process control
• using offensive memory forensics tricks to retrieve password hashes and find vulnerabilities on a virtual machine
• abusing the Windows COM automation
• exfiltrating data from a network undetected

Let’s finally look at Python books that attempt to cater for everyone — from beginners to advanced users.

• Author : Maurice J. Thompson
• Publishing : independent (April 28, 2018)
• Paperback : 375 pages
• Ranking on Amazon : 4.3/5 (4,243 ratings)

If you want to learn Python all the way , from the very basics to well into advanced topics, then Python: The Bible might be your silver bullet.

The book is part of the four-book Your Place to Learn Python with Ease series, written by Maurice J. Thompson . It’s the only book in this list aimed at beginners, intermediate and advanced learners, and with over 4,000 ratings on Amazon, it’s quite a popular one, too!

Cheat sheets can be extremely handy when all you need is to quickly eyeball a reference.

Not surprisingly, the Python Programming Language cheat sheet, by Berajah Jayne, is a 4.8/5 stars (1,524 ratings) bestseller on Amazon! 👏

SitePoint Premium gives you access the SitePoint Library, with a whole section dedicated to Python books and courses , including the book series by Austin Bingham and Robert Smallshire:

• The Python Apprentice
• The Python Journeyman
• The Python Master

Python is one of the most popular programming languages of all time, and its popularity keeps growing, as it’s quite versatile and can be used for a wide variety of tasks.

Extensive as our list of books and resources is, we have, of course, left out many other options for learning Python. We wish you the best of luck in finding your way to Python expertise — whether via these books or others. 🥇🐍

What are the key factors to consider when choosing a Python book?

When choosing a Python book, consider your current level of understanding and your learning goals. If you’re a beginner, look for books that start with the basics and gradually introduce more complex concepts. For intermediate or advanced learners, books that delve into specific areas of Python, such as data analysis or machine learning, may be more beneficial. Also, consider the teaching style of the book. Some books are more theoretical, while others are more practical and hands-on. Reviews and recommendations can also be helpful in making a decision.

Are Python books suitable for absolute beginners?

Yes, there are many Python books specifically designed for beginners. These books typically start with the basics of programming and Python syntax, then gradually introduce more complex concepts. They often include exercises and projects to help reinforce learning. Some popular beginner-friendly Python books include “Python Crash Course” and “Learn Python the Hard Way”.

Can I learn Python from a book alone?

While a book can be a great resource for learning Python, it’s often beneficial to supplement book learning with other resources. This could include online tutorials, coding exercises, and projects. Practicing coding regularly and working on real-world projects can help reinforce the concepts learned from the book and develop practical programming skills.

What are some good Python books for data analysis?

There are several Python books that focus on data analysis. “Python for Data Analysis” by Wes McKinney is a popular choice. It provides a comprehensive introduction to data analysis using Python and pandas. Another good option is “Data Science for Business” which covers the fundamental principles of data science and how to apply them using Python.

Are there Python books that focus on machine learning?

Yes, there are several Python books that focus on machine learning. “Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow” is a highly recommended book. It provides a practical approach to machine learning with Python and includes many examples and exercises.

How often are Python books updated?

The frequency of updates for Python books varies. Some books are updated regularly to keep up with changes in the Python language and its libraries, while others may not be updated as frequently. It’s always a good idea to check the publication date and any available information about updates when choosing a Python book.

Can Python books help with job preparation?

Yes, Python books can be very helpful for job preparation. They can provide a solid foundation of Python knowledge, which is valuable for many tech jobs. Some books also cover specific areas relevant to certain job roles, such as data analysis or machine learning.

Are there Python books available for kids?

Yes, there are Python books designed specifically for kids. These books typically present Python in a fun, engaging way, often using games or animations. “Python for Kids” and “Coding for Kids: Python” are two popular choices.

What are some good Python books for web development?

For web development with Python, “Flask Web Development: Developing Web Applications with Python” and “Django for Beginners” are highly recommended. These books cover the popular Python web frameworks Flask and Django, respectively.

Are there Python books that cover specific libraries or frameworks?

Yes, there are many Python books that focus on specific libraries or frameworks. For example, “Python for Data Analysis” covers the pandas library, while “Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow” focuses on these specific libraries for machine learning.

Lucero is a programmer and entrepreneur with a feel for Python, data science and DevOps. Raised in Buenos Aires, Argentina, he's a musician who loves languages (those you use to talk to people) and dancing.

10 Best Python Books for Beginners and Skilled Programmers

Join over 2 million students who advanced their careers with 365 Data Science. Learn from instructors who have worked at Meta, Spotify, Google, IKEA, Netflix, and Coca-Cola and master Python, SQL, Excel, machine learning, data analysis, AI fundamentals, and more.

Before you embark on a data science career path , you first need to know at least one programming language as it is an essential skill to break into the industry. So, why learn Python ? For starters, it has risen in popularity in recent years and continues to be highly in demand – currently holding the number 1 spot in the TIOBE Index . And with an accessible syntax and multitude of libraries , it is the top choice for data scientists across the board. Further, employers are increasingly seeking Python experts, as evidenced by Coding Nomads ’ deep dive into the requirements for data science jobs.

While there is countless online learning material at your disposal, sometimes cooking by the book is the way to go. For this reason, we’ve compiled a list of the 10 best Python books in varying degrees of difficulty, from titles for complete beginners to more advanced programmers who are looking to take their skills to the next level:

Python Books for Beginners

Advanced python books.

As with all new challenges, you won’t necessarily have the knowledge to tackle them head-on. But that’s not a bad thing. We all have to start somewhere, right? With these beginner-friendly books, you’ll have more than enough to get you off the ground.

Python Crash Course

Python Crash Course: A Hands-on, Project-Based Introduction to Programming by Eric Matthes is your one-stop shop for all your beginner Python needs. Separated into 2 parts, the book teaches you the basic concepts behind the programming like the if statement , lists , dictionaries , among many others. In the second half, you’ll have the chance to implement your newfound knowledge with practical projects such as:

• An arcade-style game
• Data visualization exercises
• A web application

Written in a straightforward, well-organized style, Python Crash Course breaks down the information into easily digestible chunks. And to supplement that, the author has supplied some free and easily downloadable online resources .

Learning Python

Another great title for beginners is Learning Python: A Powerful Object-Oriented Programming by Mark Lutz. It offers in-depth context to Python’s fundamentals, introducing you to everything you need to know and actually explaining the meaning behind each feature.

The structure is divided into 9 parts, each focusing on a different area, e.g., data types , syntax, modules , decorators, etc. To make things even easier, each topic has its own chapter. In fact, the book is so pack-full of information that it makes for an excellent reference guide as well.

The current (fifth) edition supports both Python 2 and 3.

Learn Python the Hard Way

Don’t let the title fool you –Zed Shaw’s Learn Python the Hard Way is as its subtitle states: “a very simple introduction to the terrifyingly beautiful world of computers and code”. Inside this book, you will find 52 carefully crafted exercises that aim to develop your coding and problem-solving skills, as well as teach you about:

• Data structures
• Object-oriented programming
• Development basics

One downside is that this edition is all about the outdated Python 2. Fortunately, there’s an update – Learn Python 3 the Hard Way .

Automate the Boring Stuff with Python

Have you ever had to work with big spreadsheets or something equally tedious? It can get quite, well, boring . Many of us have undoubtedly sat there, wishing the task could complete itself. Automate the Boring Stuff with Python: Practical Programming for Beginners by Al Sweigart shows us how to do just that.

Even if you have no prior experience, this beloved bestseller will take you through the process step by step, turning you from an inexperienced Python newbie into a budding programmer. By the time you’ve finished, you’ll know how to write simple automated programs for web scraping , sending emails, PDF and Word file management, etc. – saving yourself some time while you’re at it.

Python for Everybody

Python for Everybody: Exploring Data in Python 3 by Charles R. Severance is a comprehensive Python guide for students who want to learn programming and experiment with big data . Much like picking up a dictionary, you’ll study the easy-to-read Python syntax while also:

• Importing information
• Labeling data
• Using variables and functions

The author has also included handy charts and pieces of code so you can follow along every step of the way. But that’s not all – you’ll be able to find supplementary free resources on his website, PY4E .

Bonus: A Byte of Python

As a student or even a working professional in a field other than data science or programming, the prices of these books can make quite a dent in your wallet. Thus, we wanted to introduce you to a great alternative – the open-source book by C. H. Swaroop, A Byte of Python .

This title is perfect for beginners as it’ll give you an overview of Python and its history, then move on to introduce the basic principles without overwhelming you. Of course, you still get in-depth explanations and examples and, at the end, the author presents you with a problem to solve on your own, using your newfound knowledge.

What is even more special about this book is that the Python community has translated it into 26 other languages, making it accessible for an even wider audience.

Already have some knowledge of Python? Then, these books will help you sharpen the tools you have and gain a competitive advantage amongst your peers.

Keep in mind, however, that they are not light reads – you need some previous experience to understand and successfully navigate through the contents of these books.

Python Tricks

With Python Tricks: A Buffet of Awesome Python Features , author Dan Bader shares surprising tricks and best practices in a few concise lines, supplying extremely clear descriptions of why code behaves as it does.

It’s important to note that this book is geared towards intermediate learners rather than advanced programmers; it does not go into the full depths of the language. However, it will teach you how to:

• Clean up your code
• Become more efficient
• Catch up to the latest versions of Python

With chapters like Covering Your A** with Assertions or A Shocking Truth about String Formatting , you get a roadmap into the lesser-known parts of Python, written in an uncomplicated, friendly tone.

Python for Data Analysis

Perhaps you’re familiar with the name Wes McKinney, the creator of the pandas library, or perhaps you’re just interested in data science. In both cases, Wes’s book, Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython , is perfect for you.

In this hands-on guide, you will get thorough instructions on how to:

• Work with the essential Python libraries
• Perform data wrangling
• Implement linear algebra and time series data into your analysis
• Solve real-world problems through practical examples

Drawing from his years of experience, Wes McKinney aims to teach you how to take advantage of all Python functionalities for your data science exploration. Moreover, there is a third, updated edition coming out soon, but you can get early access to the raw, unedited text on the author’s website.

Learn More Python the Hard Way

This title sounds familiar, doesn’t it? Learn More Python 3 the Hard Way is a follow-up to Zed Shaw’s beginner-friendly book we mentioned previously. Similar to its predecessor, it features another 52 exercises, designed to test and build upon your core Python knowledge.

The book is divided into 5 sections:

• Working with commands
• Organizing data
• Applying algorithms
• Processing text
• Implementing simple networking protocols

Don’t expect it to go easy on you – from the first page, you’re plunged into a series of challenging exercises that will ultimately help you achieve a higher level of proficiency.

Effective Python

Effective Python: 90 Specific Ways to Write Better Python by Brett Slatkin is a fountain of programming knowledge. Covering topics like metaclasses and concurrency, as well as essentials like robustness, testing, and collaboration, the book gathers everything you need to advance in your specialization, all under one roof.

It can be difficult to find resources that are solely focused on the language we’re currently learning. Effective Python is one such resource that concentrates entirely on what makes Python so… Pythonic . Instead of teaching you the basis of syntax , the author directly goes into the nitty-gritty to explain the language’s specific “quicks” so that you extract the most gain.

Fluent Python

Finally, we’re going to introduce you to one of the most popular books to learn Python for advanced specialization – Fluent Python: Clear, Concise, and Effective Programming by Luciano Ramalho. At almost 800 pages, this beast concerns itself with all the often-overlooked features that Python has to offer, as well as introducing you to concepts such as metaprogramming. It will draw you out of your programming conventions and allow you to consider a new way of coding that is much cleaner and more efficient.

Having said that, it is not an easy read and if you don’t already have a certain level of proficiency, then you might find it difficult to follow along with the jargon and concepts covered. Essentially, Fluent Python aims for exactly what it says on the tin – to make you truly fluent .

You can soon expect a second edition that builds upon everything in the original while leveraging all the best practices in Python 3.

Best Python Books: Next Steps

Now that you have all the resources available, it’s time to get down to business. Learning any language is a journey that never actually stops – the same applies to Python as it constantly evolves over time. Once you’re confident in your abilities, however, you’re ready to start on your own projects (browse our recommendations for free resources if you’re stuck), then apply for Python jobs .

And if books aren’t your thing, then feel free to check out our Introduction to Python course, which lays the foundations of the programming language. After, if you’re feeling up for the challenge, you can try our intensive Python Programmer Bootcamp course that will truly take you to the next level.

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📚 Best-Books.dev

The 25 best python books of all time, a data-backed answer, methodology.

There are countless lists on the internet claiming to be the list of must-read python books and it seemed that all those lists always recommended that same books minus two or three odd choices.

Finding good ressources for learning programming is always tricky. Every-one has its own opinion about what book is the best to learn, and as we say in french, “Color and tastes should not be argued about”.

However I though it would be interesting to trust the wisdom of the crown and to find the books that appeared the most in those “Best Python Book” lists.

If you want to jump right on the results go take a look below at the full results . If you want to learn about the methodology, bear with me.

I’ve simply asked Google for a few queries like “Best Python Books” and its variations of. I have then scrapped all those pages (using ScrapingBee, a web scraping API I’m working on).

I’ve deduplicated the links and ended up with nearly 170 links. Using the title of the pages I was also able to quickly discards:

• list focused on one particular technology or platform
• list focused on one particular year
• list focused on free books
• Quora and Reddit threads

I ended up with almost 130 HTML files. I went on opening all the files on my browser, open my chrome inspector, found and wrote the CSS selector matching book titles in the article. This took me around 1hours, almost 30 seconds per page.

This also allowed me to discard even more nonrelevant pages, and I discarded a lot. In the end I compiled around 70 lists into this one.

Book titles were then extracted with manuel extraction and some web scraping.

I ended up with a huge list of books, not usable without some post-processing.

To find the most quoted python books I needed to normalize my results.

I had to play with all the different variation like “{title} by {author}” or “{title} - {author}”.

Or “{title}:{subtitle}” and “{title}”, or even all the one containing edition number.

And afterquite a bit of manual cleaning.

My list now looked like this:

From there it was easy to compute the most recommended books. You can find all the data used to process this list on this repo . Now let’s take a look at the list:

Python Data Science Handbook

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.

Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.

Deep Learning with Python

This book was written for anyone who wishes to explore deep learning from scratch or broaden their understanding of deep learning. Whether you’re a practicing machine-learning engineer, a software developer, or a college student, you’ll find value in these pages. This book offers a practical, hands-on exploration of deep learning. It avoids mathematical notation, preferring instead to explain quantitative concepts via code snippets and to build practical intuition about the core ideas of machine learning and deep learning.

You’ll learn from more than 30 code examples that include detailed commentary, practical recommendations, and simple high-level explanations of everything you need to know to start using deep learning to solve concrete problems. The code examples use the Python deep-learning framework Keras, with Tensor- Flow as a back-end engine. Keras, one of the most popular and fastest-growing deeplearning frameworks, is widely recommended as the best tool to get started with deep learning.

Python: Learn Python in One Day and Learn It Well

Have you always wanted to learn computer programming but are afraid it'll be too difficult for you? Or perhaps you know other programming languages but are interested in learning the Python language fast?

This book is for you. You no longer have to waste your time and money learning Python from lengthy books, expensive online courses or complicated Python tutorials.

Violent Python

Violent Python shows you how to move from a theoretical understanding of offensive computing concepts to a practical implementation. Instead of relying on another attacker’s tools, this book will teach you to forge your own weapons using the Python programming language. This book demonstrates how to write Python scripts to automate large-scale network attacks, extract metadata, and investigate forensic artifacts.

It also shows how to write code to intercept and analyze network traffic using Python, craft and spoof wireless frames to attack wireless and Bluetooth devices, and how to data-mine popular social media websites and evade modern anti-virus.

The Hitchhiker's Guide to Python

The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old, Python has become the primary or secondary language (after SQL) for many business users. With popularity comes diversity—and possibly dilution.

This guide, collaboratively written by over a hundred members of the Python community, describes best practices currently used by package and application developers. Unlike other books for this audience, The Hitchhiker’s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.

Natural Language Processing with Python

This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication.

Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify 'named entities' Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (Nltk) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages - or if you're simply curious to have a programmer's perspective on how human language works - you'll find Natural Language Processing with Python both fascinating and immensely useful.

Invent Your Own Computer Games with Python

Begin by building classic games like Hangman, Guess the Number, and Tic-Tac-Toe, and then work your way up to more advanced games, like a text-based treasure hunting game and an animated collision-dodging game with sound effects. Along the way, you’ll learn key programming and math concepts that will help you take your game programming to the next level.

Python Pocket Reference

This convenient pocket guide is the perfect on-the-job quick reference. You’ll find concise, need-to-know information on Python types and statements, special method names, built-in functions and exceptions, commonly used standard library modules, and other prominent Python tools. The handy index lets you pinpoint exactly what you need.

Written by Mark Lutz—widely recognized as the world’s leading Python trainer—Python Pocket Reference is an ideal companion to O’Reilly’s classic Python tutorials, Learning Python and Programming Python, also written by Mark.

Python in a Nutshell

Useful in many roles, from design and prototyping to testing, deployment, and maintenance, Python is consistently ranked among today’s most popular programming languages. The third edition of this practical book provides a quick reference to the language—including Python 3.5, 2.7, and highlights of 3.6—commonly used areas of its vast standard library, and some of the most useful third-party modules and packages.

Ideal for programmers with some Python experience, and those coming to Python from other programming languages, this book covers a wide range of application areas, including web and network programming, XML handling, database interactions, and high-speed numeric computing. Discover how Python provides a unique mix of elegance, simplicity, practicality, and sheer power.

Programming Python

If you've mastered Python's fundamentals, you're ready to start using it to get real work done. Programming Python will show you how, with in depth tutorials on the language's primary application domains: system administration, GUIs, and the Web. You'll also explore how Python is used in databases, networking, front end scripting layers, text processing, and more. This book focuses on commonly used tools and libraries to give you a comprehensive understanding of Python’s many roles in practical, real world programming.\n You'll learn language syntax and programming techniques in a clear and concise manner, with lots of examples that illustrate both correct usage and common idioms. Completely updated for version 3.x, Programming Python also delves into the language as a software development tool, with many code examples scaled specifically for that purpose.

Introduction to Machine Learning with Python

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.

Dive into Python 3

There are a huge number of python developers who will need to learn to port their code to python 3, and Dive Into Python 3 is the ideal hands-on introduction to the latest version of python for them. Its unique style of giving a chunk of code first and then picking it apart is ideally suited to existing developers who want to understand the new version of the language quickly.

Python Essential Reference

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.\n 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.

Python Tricks

With Python Tricks: The Book you’ll discover Python’s best practices and the power of beautiful & Pythonic code with simple examples and a step-by-step narrative.

You'll get one step closer to mastering Python, so you can write beautiful and idiomatic code that comes to you naturally. \n Learning the ins and outs of Python is difficult—and with this book you'll be able to focus on the practical skills that really matter. Discover the “hidden gold” in Python’s standard library and start writing clean and Pythonic code today.

Python Machine Learning

This book is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you’ll keep coming back to as you build your machine learning systems.

Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself.

Effective Python

It’s easy to start developing programs with Python, which is why the language is so popular. However, Python’s unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up.

Think Python: How to Think Like a Computer Scientist

If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3.

Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser.

Python for Data Analysis

This book is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. My goal is to offer a guide to the parts of the Python programming language and its data-oriented library ecosystem and tools that will equip you to become an effective data analyst. While 'data analysis' is in the title of the book, the focus is specifically on Python programming, libraries, and tools as opposed to data analysis methodology. This is the Python programming you need for data analysis.

Learn Python the Hard Way

Zed Shaw has perfected the world’s best system for learning Python 3. Follow it and you will succeed—just like the millions of beginners Zed has taught to date! You bring the discipline, commitment, and persistence; the author supplies everything else.

Automate the Boring Stuff with Python

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? \n In this fully revised second edition of the best-selling classic 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. You'll learn the basics Python and explore Python's rich library of modules for performing specific tasks, like scraping data off websites, reading PDF and Word documents, and automating clicking and typing tasks.

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.

Python Crash Course

is a straightforward introduction to the core of Python programming. Author Eric Matthes dispenses with the sort of tedious, unnecessary information that can get in the way of learning how to program, choosing instead to provide a foundation in general programming concepts, Python fundamentals, and problem solving. Three real world projects in the second part of the book allow readers to apply their knowledge in useful ways.

Readers will learn how to create a simple video game, use data visualization techniques to make graphs and charts, and build and deploy an interactive web application. Python Crash Course, 2nd Edition teaches beginners the essentials of Python quickly so that they can build practical programs and develop powerful programming techniques.

Fluent Python

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.

Learning Python

Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages.

Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3— the latest releases in the 3.X and 2.X lines—plus all other releases in common use today. You’ll also learn some advanced language features that recently have become more common in Python code.

Python Cookbook

If you need help writing programs in Python 3, or want to update older Python 2 code, this book is just the ticket. Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms.

Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works.

Although the order might surprise some, by definition, most of you must have heard of these books already.

A few additional things I learned making this list:

• O’Reilly is the big winner of this list with 12 books in the top 25
• I’m happy to see one of my favorite editor, No Starch Press with 4 books in the list
• Mark Lutz is the author of 3 books

I hope you enjoyed this article.

Keep me updated!

Receive weekly update about best programming books! Just that, no spam, no bs.

//Go With Code/

Helping people learn coding and tech

11 best python books for beginners and all skill levels (2021).

Python is a very powerful programming language yet also one of the easiest to learn thanks to its simple, English-like syntax (the actual Python code).

Still, the kind of resource you use for learning python can be the difference between frustration and having the concepts clicking fast. Especially for beginners new to programming. And why it’s important to choose a really good python book.

The best python book for you will depend on your programming skill level and your motivation for learning python.

In this article, you’ll discover the overall best python books for beginners, kids, intermediate and advanced python programmers.

And if you want to use python for data analysis or machine learning, there’s something for you too.

Disclosure: This article includes affiliate links that may provide a commission to me at no cost to you if you make a purchase through them.

Table of Contents

Which are the Best Python Books for Beginners?

Best python books for kids, best python books for intermediate python coders, best python books for advanced pythonistas, best book for learning python for machine learning, best book for learning python for data analysis, python crash course, 2nd edition: a hands-on, project-based introduction to programming.

By Eric Matthe  

Python Crash Course is the best-selling python book for beginners for good reason. A quick glimpse from Amazon shows almost 5,000 ratings, the most we’ve seen of any Python book.

It will ease you into each topic, explain it in a crystal-clear way, and demonstrate coding with follow along exercises. A very positive experience when learning your first coding language!

At the end of the book, you will develop three different programs that will help solidify what you’ve learned.

Who’s It For

Hands down, Python Crash Course is the best python book for beginners. No prior coding knowledge or a background in tech required to learn from the book.

What’s Covered

The basic topics including variables, lists, classes, loop, python libraries and tools, writing python code, testing it and making it interactive, 2D games, data visualization, and web apps.

The practical projects include a game, a web app, and data visualization. 

• Instills a solid foundation in coding
• Presented in a logical way
• Easy to understand writing style
• In-depth explanation of code snippets
• Revised and up to date 
• Three practical projects
• Intermediate developers might find the explanations tedious

Where to Buy

Automate the boring stuff with python, 2nd edition: practical programming for total beginners  .

By Al Sweigart  

The practical approach makes Automate the Boring Stuff with Python one of the best books for learning python for those new to programming.

It’s the second best book to pick once you’re done with the Python Crash Course.

It’s also the best first book if your goal for learning python is to automate tedious tasks.

Automate the Boring Stuff with Python is geared towards those learning python for the first time. No prior programming experience is required.

It’s especially perfect for administrators, academicians, or anyone who wishes to automate certain tasks to boost productivity.

What’s Covered 

The basics of Python and the modules needed to develop programs that perform tasks like data scraping, reading documents, automating typing, sending emails, updating files, searching the web and more.

• The practical approach makes python less daunting
• Step by step instruction and practical projects
• Breaks down sections into bite-sized chunks
• Accompanied by great online resources 
• It’s not very well organized for a total newbie

Learn Python 3 the Hard Way

By Zed Shaw 

Zed’s book Learn Python 3 the Hard Way is actually a simple intro to programming despite the “hard” part in the book name. The “hard way” is really just another name for “instruction”. Meaning the book has the reader go through exercises, typing in each Python example file exactly, then making that file run.

At first this may seem difficult but you’ll get used to it. And then things get a lot easier once you’re used to learning this way (learning by doing).

The total beginner who isn’t familiar with programming. Expect to learn the basics all the way to advanced stuff.

Setting up your Python environment, writing your first program, work with numbers, math and strings, printing to the screen, reading from and writing to files. functions and variables, conditionals (if/else), dictionaries, modules, classes, an intro to object oriented programming, debugging, making a game, making a website and finally a command line crash course near the end of the book.

• The book is structured as one exercise after another. It’s filled with practical examples and forces you to learn by doing. Some folks like this approach (I do) so I’ve listed as a pro.
• The content is very comprehensive and a beginner will keep themselves busy learning basic to advanced concepts.
• Not colorful and isn’t as non-intimidating to look at but for those serious about learning this shouldn’t be a problem
• This isn’t actually a con but the book title seems to imply learning the “hard” way when actually that’s not the case and the author’s approach by example is fantastic 😉
• The book claims to offer online videos however I couldn’t find them when I typed in the URL listed within the book, just went straight to a place to purchase the book. The book is great, just that if you are planning to list online videos would be great if they actually work

Python for Kids: A Playful Introduction to Programming 

By Jason R. Briggs  

Python for Kids, a Playful Introduction to Programming is by far the best python book for kids to learn how Python works and how to use it.

Fun activities and colorful illustrations bring coding to life. Explanations are easy enough for kids to follow on their own and puzzles help solidify their knowledge.

What’s more! Kids get to code up two games at the end of the book.  

The book is designed for 10 year old kids and older. However, it’s an excellent book for anyone getting started in python, no matter the age.

Classes and objects, data structures, functions and modules, control structures, drawing shapes and patterns, and creating animations and games.

• Well-written and organized
• Uses 4th – 5th grade vocabulary
• Full-color illustrations 
• Detailed without being overwhelming
• Puzzles strengthen learning
• Kids get to code up two games
• Some topics are way beyond a child’s level

Coding for Kids: Python: Learn to Code with 50 Awesome Games and Activities 

By Adrienne Tacke  

Coding for kids: Python uses silly games and fun activities to make learning python easy and fun for children starting from age 10.

Blended into the fun are sample lines of code, clear instruction, and explanations of terms. 

Although the book is designed with children ( 10+ year olds) in mind, even adults find it a simple and fun way to learn and apply python.

Kids learn the basics of python, writing code, debugging, drawing pictures, and even developing games.

• Uses innovative games and exercises
• Simplifies python and makes it fun
• Has easy to follow instructions
• Activities to solidify what they learn
• Difficult challenges to tackle 
• Colorful illustrations and screenshots 
• Teaches problem solving skills
• Requires some guidance from an adult

Python Tricks: A Buffet of Awesome Python Features

By Dan Bader

Python Tricks is a brilliant book for intermediate level python developers. 

Dan Bader has a knack for presenting ideas in a way that makes even hard to understand concepts make sense and sink in at first read. 

As you step up into the next level in your python learning journey, Python Tricks will make you a more efficient python developer and help you write beautiful idiomatic code.

Python Tricks is a fantastic book for intermediate python developers. It’s also a great resource for seasoned programmers looking to add python to their resume.

Python Tricks starts with the basic concepts such as functions and moves to more advanced python topics. It explains the best practices and offers valuable tips and tricks.

• A quick but very helpful read
• Written in an engaging style
• Clear phrasing and presentation
• Simple and practical examples
• Not a comprehensive book if you want to become an expert

Effective Python: 90 Specific Ways to Write Better Python, 2nd Edition

By Brett Slatkin  

Effective Python is a treasure trove of python specific tips and techniques that will make your code easier to understand, more secure, and faster.

It does a very good job of explaining python best practices and quirks.

Who’s It For?

Effective Python is great for intermediate python programmers looking to get to know python better as well as programmers already proficient in other programming languages but new to python.

Classes, interfaces,  concurrency and parallelism, metaclasses, robustness, testing, debugging, collaboration…

• Covers python specific features
• Well thought out examples
• Thorough but concise explanations
• Easy to read and understand
• Not comprehensive as it only delves into specific topics

Fluent Python: Clear, Concise, and Effective Programming, 1st Edition

By Luciano Ramalho

Fluent Python is the best book to take your python skills to a whole new level. Even the most advanced python programmers admit to learning new things or gaining a different perspective with this book.

Being the best book for understanding pythonic tricks, it will teach you how to use the best but lesser known features of the language to write shorter, faster, and more readable code.

Who’s It For

If you’re already an advanced python programmer and want to dive deep under the covers or become fluent in Python 3, there’s no better book to take you there than Fluent Python

If you’re an advanced programmer in other languages, Fluent Python will show all the features that make Python unique so you can make the most of it.

Python data model, data structures, functions as objects, object-oriented idioms, control flow, duck typing, generators, decorators,  abstract base classes, multiple inheritance, and meta programming.

• A very large and in-depth resource
• Structured approach to mastering python fast
• Simple and easy to understand examples
• Teaches the what, the how, and the rationale 
• Easy and even entertaining to read
• Helpful in the transition to Python 3
• Rarely goes beyond the standard libraries

Python Cookbook, Third Edition

By David Beazley

Packed with practical recipes written and tested with Python 3.3, Python Cookbook is the best book for getting up to speed with Python 3.

The book is packed with high-quality examples of code you can use as well as explanations of when and why to use the code.

It will give you great insight into the workings of Python under the hood and have you producing elegant code with minimal lines.

Python Cookbook is for the advanced programmers looking to understand the nuances of python 3 as well as adopt a modern style of coding with python.

Python Cookbook is a very comprehensive python book.

It covers the core of the Python language, addresses a wide range of application domains, and goes over new Python 3 features. 

It starts with the basics and gradually moves to advanced topics such as metaprogramming and concurrency.

• Covers a wide range of topics
• Easy to advanced recipes
• Teaches modern tools and idioms
• Makes a great python resource
• Great reference book for python 3
• Uses bite-sized portions 
• Explains the how and the why
• Too advanced for beginners with only a knowledge of the basics

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

By Andreas C. Müller and Sarah Guido  

Introduction to Machine Learning with Python is a fantastic introduction to machine learning in Python and the best book for getting started in machine learning. 

It will teach you how to build machine learning applications without overwhelming you with the theory and math behind the algorithms.

It is well written, well organized, and has very good examples and intuitive explanations of concepts.

Although the book is beginner friendly, you will get the most out of it if you’re at least familiar with NumPy, Scikit-learn or any other data science or machine learning library. 

Fundamental concepts, machine learning algorithms, data presentation, model evaluation, parameter tuning, pipelines, processing techniques, supervised learning, feature engineering…

• Makes machine learning easy to learn for beginners
• Intuitive explanations of models
• Easy for a beginner to grasp
• Uses hands on examples
• Explanations for complex topics leave a lot to be desired
• Experienced programmers might find it too basic

Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

By: Wes McKinney

Python for Data Analysis uses easy to follow and practical case studies to teach python programming in data analysis.

It will show you how to organize, manipulate, process, clean, and crunch data using python tools and libraries.

Anyone who wants to learn Python programming for data analysis will benefit from this book.

It’s great for data scientists who want to add python skills to their arsenal as well as python programmers looking to get into data science.

The book is all about pandas, NumPy, IPython, Jupyter, matplotlib, and Seaborn for data analysis. It also teaches how to use scikitlearn for machine learning.

• Equips readers with practical tools
• Updated for Python 3.6
• Practical and modern approach
• Numerous, detailed code examples
• Well structured into small chunks
• Use of random numbers makes examples too abstract 
• Requires at least basic knowledge of python or programming in general

Wrapping Up

Python books are written with different students in mind. The best book for learning python will depend on whether you’re just getting into code and have decided to get started with Python.

Or perhaps you’re well versed in other programming languages but new to python, or already an intermediate or advanced programmer looking to take your python skills to the next level.

Written by expert pythonistas and top rated by learners, the books featured here are currently the best resources for learning python.

Pick the right book for your skill level and goals and you will be on your way to becoming a great pythonista.

Mike is the creator of Go With Code and a coder at heart 🙂

11 Best Python Books for Beginners (2024 Update)

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Python is the de facto language for data scientists, statisticians, machine learning experts, and web enthusiasts. There is a plethora of learning material available for Python and selection once could be difficult.

Are you interested in learning the Python language and looking for some excellent book that will help you skyrocket your Python expertise? Then you have come to the right place. Here is a curated list of the best books to learn Python for beginners. These books are highly recommended by Python experts and are helpful for students to grasp the programming fundamentals. These resources will guide you to build your career in this promising field and make you a better Python developer. Read more…

Best Python Programming Books for Beginner & Advanced Coders

1) python crash course, 2nd edition: a hands-on, project-based introduction to programming.

Author Name: Eric Matthes

Publisher: No Starch Press

Latest Edition: 2nd edition 

No of Pages: 544 pages

Python Crash Course teaches you basics python fundamental. The book is divided into two parts. The first half of this book, you’ll introduce to fundamental of python programming. Like lists, dictionaries, classes, and loops, and practice.

In the second half, you’ll assign three projects: arcade game, Space Invaders, data visualizations. This book ends by providing some basic information about how to develop simple web apps.

2) Python Pocket Reference: Python in Your Pocket

Author Name: Mark Lutz

Publisher: O′Reilly

Latest Edition: 5th edition 

No of Pages: 266 pages

It is an ideal pocket guide for quick on job reference for Python developers. You’ll find concise, need to know information on Python types and statements, names of a special method, inbuilt functions, exceptions, and other frequently used standard library modules.

The book also covers Built-in object types, syntax, statements for creating as well as processing objects, functions, modules for structuring and reusing code. It also includes special operator overloading methods, standard library modules, and extensions important Python idioms and hints, etc.

3) Python Programming: An Introduction to Computer Science

Author Name: John M Zelle

Publisher: Ingram short title

Latest Edition: 3rd edition

No of Pages: 552 pages

This e-book is designed to be used as a primary textbook for python course. This third edition of Python Programming keeps up the tradition of updating content with the latest in the market. It provides details about new technologies and while maintaining a time-tested approach to teach the basic concept of computer science.

It also provides easy to understand graphical examples, spanned across 4 to the 12 th chapter.

4) Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

Author Name: Wes Mckinney

No of Pages: 522 pages

This e-book offers complete instruction for manipulating, processing, cleaning, and crunching datasets in Python. You will also find many practical case studies that show you how to solve a broad set of data analysis problems.

It is ideal to learn python program, and data analysts as the book have a practical, modern introduction to data science tools using Python. In this Python book, you will also learn the latest version of NumPy, Pandas, IPython, and Jupyter.

5) Python Cookbook: Recipes for Mastering Python 3

Author Name: David Beazley

Publisher: O'Reilly

Latest Edition: 3rd edition 

No of Pages: 708 pages

Python Cookbook is an ideal book if you need help writing programs in Python 3. It also helps you to update the Python 2 code. The book is recommended for experienced Python program who wants to learn modern tools use for Python development.

Inside, this book you will find topics related to core Python language and tasks common to a wide range of application domains. It offers many code samples you can use in your along with discussion about how and why the solution works.

6) Python Data Science Handbook: Essential Tools for Working with Data

Author Name: Jake Vanderplas

Latest Edition: 1st edition 

No of Pages: 548 pages

A python is a popular programming language because of its libraries for storing, manipulating, and gathering insight from data. There are many resources available to learn data science. However, with the help of this book, you will get in-depth information about Pandas, IPython, NumPy, Matplotlib, and other related tools.

It is a perfect reference book for Data scientists and crunchers familiar with reading and writing Python code. This helps you to tackle day-to-day coding issues occurs in python development.

7) Learn Python the Hard Way

Author Name: Shaw Zed A.

Publisher: Addison-Wesley Professional

No of Pages: 308 pages

In this book, you’ll able to learn Python by working through 52 well-developed exercises. Corrects your coding mistakes, learn what good programs look like and how to plan them.

You will learn how to install a complete Python environment, organizing & writing code, basic mathematics, variables, looping and logic, Python packaging, automated testing. Finally, you will learn the basic game & web development using Python programming language .

8) Python Programming for Beginners

Author Name: Philip Robbins

Publisher: Independently published

No of Pages: 122 pages

Complete Python Guide with example is a book for those people who are scared of Python’s long and complicated code. This popular book covers complex concepts of Python and examines it in simple steps.

This e-book teaches you basic Python coding fundamentals like classes, objects, tuples, strings, etc. Moreover, the examples given in this book helps you to understand all the Python concepts in easy to understand manner.

9) Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow

Author Name: Sebastian Raschka Vahid Mirjalili

Latest Edition: 2nd edition

No of Pages: 622 pages

Python Machine Learning offers practical techniques to develop machine learning, deep learning, and data analysis algorithms. The book updated using the latest python libraries.

This book includes TensorFlow deep learning library. The scikit-learn code given in this book is also fully updated. You will get the knowledge about the best practices that help you to improve and optimize your machine learning algorithms. At the end of the book, you’ll be able to explore new data analysis opportunities available in today’s world.

10) Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit

Author Name: Steven Bird

Publisher:  O′Reilly

No of Pages: 502 pages

In this book, you will learn the concept of natural language processing. You will also learn how to write Python programs. This also works with large collections of unstructured text. This book teaches you how to write Python programs that work with large collections of unstructured text.

This book is helpful to enhance practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) which is open source library.

11) Django for Beginners: Build websites with Python and Django

Author Name: William S. Vincent

Publisher:  WelcomeToCode

No of Pages: 343 pages

The book is a step-by-step guide for developing web applications with Python and Django 2.1. You will learn how to build, test, and deploy five most comprehensive websites. This includes a blog app with user accounts, Message Board app, and a Newspaper app along with reader comments.

Apart from this, this book also teaches you various features of Django and best practices around models, views, templates, user registration, testing, and deployment.

🏅Why Learn Python Programming?

Python programming is widely used in Artificial Intelligence, Natural Language Generation, Neural Networks, and other advanced fields of Computer Science. Moreover, Python is one of the most demanded programming languages in the market, so there are huge job opportunities for candidates having knowledge of Python programming.

📚 Which book is best for learning Python?

Following are some of the best Python Books for Beginners & Advanced Programmers:

• Python Crash Course, 2nd Edition: A Hands-On, Project-Based Introduction to Programming
• Python Pocket Reference: Python in Your Pocket
• Python Programming: An Introduction to Computer Science
• Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
• Python Cookbook: Recipes for Mastering Python 3

🚀Who can learn Python?

Anyone who have basic knowledge of any programming language concepts like loops , functions, etc., it will help you learn Python online easily.

• Online Python Compiler (Editor / Interpreter / IDE) to Run Code
• PyUnit Tutorial: Python Unit Testing Framework (with Example)
• How to Install Python on Windows [Pycharm IDE]
• Hello World: Create your First Python Program
• Python Variables: How to Define/Declare String Variable Types
• Python Strings: Replace, Join, Split, Reverse, Uppercase & Lowercase
• Python TUPLE – Pack, Unpack, Compare, Slicing, Delete, Key
• Dictionary in Python with Syntax & Example

Best Python Books

Advance your python programming skills with these top-rated guides, chosen for their consistent appearance across authoritative tech and coding sources..

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Discover the essential resources to master Python with our curated list of the Best Books for Learning Python. Whether you're a beginner or an experienced programmer, these books cover the entire spectrum of Python, from basics to advanced topics.

ltcbuzy/The-Best-Python-Books

Folders and files, repository files navigation, the best python books, best books for learning python, 1.effective python: 59 ways to write better python.

Brett Slatkin (Addison-Wesley, 2015)

This compilation comprises 59 standalone articles aimed at enhancing your Python proficiency. From Pythonic best practices and lesser-known functionalities to built-in tools, the content spans a spectrum of complexity. It commences with fundamental concepts like understanding your Python version and progresses to more intricate, often overlooked areas such as identifying and addressing memory leaks.

2. Head-First Python, 2nd edition

Paul Barry (O’Reilly, 2016)

I have a strong preference for the Head-First series of books, even though they might be considered lighter in overall content compared to other recommendations in this section. However, the benefit of this approach is that it enhances the book's user-friendliness.

3. Python Cookbook

David Beazley & Brian K. Jones (O’Reilly, 3rd edition, 2013)

This book distinguishes itself with its exceptional level of detail. While code cookbooks generally serve as concise guides showcasing efficient methods for common tasks, Python Cookbook takes a unique approach. Each recipe not only provides a comprehensive code solution but also includes an in-depth discussion by the author, offering insights into specific elements of the solution.

4. Python Crash Course

Eric Matthes (No Starch Press, 2016)

This book serves as an outstanding resource for both novice and seasoned Python enthusiasts, providing a comprehensive journey through the language's fundamentals and advanced applications. Beginning with a thorough exploration of basic elements and data structures such as variables, strings, numbers, lists, and tuples, the book gradually immerses readers in more complex concepts.

The coverage extends to if statements, logical tests, and an in-depth examination of dictionaries. It then progresses seamlessly to encompass user input, while loops, functions, classes, and file handling, offering valuable insights into code testing and debugging along the way.

What sets this book apart is its practical approach in the latter half, featuring three major projects that elevate the learning experience. The first project involves creating an engaging Alien Invasion game using the pygame package, introducing ship design, alien fleet movements, and a scoreboard.

The second project delves into data visualization using matplotlib, exploring concepts like random walks, dice rolling, and statistical analysis. Readers also learn to interact with web APIs, retrieving and visualizing data from platforms like GitHub and HackerNews.

The final project unfolds as a comprehensive guide to building a web application using Django. From project setup to user account management and deployment on Heroku, this project provides a real-world application development experience.

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

Luciano Ramalho (O’Reilly, 2014)

Designed for seasoned Python 2 programmers aiming to transition to Python 3 proficiency, this book serves as an ideal resource. It caters to individuals with a strong grasp of Python basics, whether in version 2 or 3, seeking to elevate their skill set. Furthermore, it doubles as a valuable reference for experienced programmers from other languages, offering quick insights into executing specific tasks in Python.

6.Learn Python 3 the Hard Way

Zed A. Shaw (Addison-Wesley, 2016)

Considered a classic, 'Learn Python the Hard Way' has a distinctive approach that I highly appreciate. Embracing the 'hard way' method requires users to type in all the code, complete exercises diligently, and independently find solutions to encountered problems. What sets this book apart is its well-structured content—each chapter is meticulously presented, ensuring clarity and ease of understanding.

7.Effective Computation in Physics: Field Guide to Research with Python

Anthony Scopatz, Kathryn D. Huff (O’Reilly, 2015)

If only I had this book during my initial journey with Python. Contrary to its name, it proves to be an outstanding resource for those without a background in physics, research, or computational issues. It truly serves as a comprehensive field guide for Python usage. Beyond imparting Python knowledge, it delves into associated subjects such as command-line usage, version control, and the intricacies of testing and deploying software.

8. Think Python: How to Think Like a Computer Scientist, 2nd edition

Allen B. Downey (O’Reilly, 2015)

If the idea of learning Python through video game creation seems too lighthearted, Allen Downey's book 'Think Python' offers a more serious perspective.

True to its title, the book aims to instill the thought processes of coding, and it accomplishes this goal effectively. In contrast to other resources, it adopts a more structured and linear organization. 'Think Python' concentrates on imparting fundamental Python programming knowledge in a straightforward, clear, and comprehensive manner.

Intermediate

• Python 3 Object-Oriented Programming by Dusty Phillips English 2nd Edition
• The Hacker's Guide to Python by Julien Danjou English Edition
• Python in Practice: Create Better Programs Using Concurrency, Libraries, and Patterns by Mark Summerfield English Edition
• Expert Python Programming: Best practices for designing, coding, and distributing your Python software by Tarek Ziadé English Edition
• Core Python Applications Programming by Wesley Chun English 3rd Edition
• Intermediate Python Online
• Effective Python: 59 Specific Ways to Write Better Python English Edition
• Fluent Python by Luciano Ramalho English Edition
• Learning Python Design Patterns by Chetan Giridhar English 2nd Edition
• Mastering Python Design Patterns by Sakis Kasampalis English Edition
• The Well-Grounded Python Developer by Doug Farrell English Edition
• Violent Python: A Cookbook for Hackers, Forensic Analysts, Penetration Testers and Security Engineers by TJ O'Connor English Edition
• Black Hat Python: Python Programming for Hackers and Pentesters by Justin Seitz English Edition
• Gray Hat Python: Python Programming for Hackers and Reverse Engineers by Justin Seitz English Edition

Here's a list of 50 highly recommended books for learning Python:

• Python Crash Course" by Eric Matthes
• Automate the Boring Stuff with Python" by Al Sweigart
• Fluent Python" by Luciano Ramalho
• Effective Python: 90 Specific Ways to Write Better Python" by Brett Slatkin
• Learning Python" by Mark Lutz
• Python Pocket Reference" by Mark Lutz
• Python Cookbook" by David Beazley and Brian K. Jones
• Head-First Python" by Paul Barry
• Think Python" by Allen B. Downey
• Programming Python" by Mark Lutz
• Dive into Python 3" by Mark Pilgrim
• Python for Data Analysis" by Wes McKinney
• Introduction to Machine Learning with Python" by Andreas C. Müller and Sarah Guido
• Python Tricks: A Buffet of Awesome Python Features" by Dan Bader
• Test-Driven Development with Python" by Harry J.W. Percival
• Python in a Nutshell" by Alex Martelli
• Python Programming: An Introduction to Computer Science" by John Zelle
• Data Science from Scratch" by Joel Grus
• Flask Web Development" by Miguel Grinberg
• Web Scraping with Python: A Comprehensive Guide" by Ryan Mitchell
• Python Web Scraping Cookbook" by Michael Heydt
• Building Machine Learning Powered Applications" by Emmanuel Ameisen
• Mastering Python Networking" by Eric Chou
• Effective Computation in Physics" by Anthony Scopatz and Kathryn D. Huff
• Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron
• Introduction to Deep Learning with Python" by François Chollet
• Python Machine Learning" by Sebastian Raschka and Vahid Mirjalili
• Python for Finance" by Yves Hilpisch
• Python Geospatial Analysis Cookbook" by Michael Diener
• Clean Code in Python" by Mariano Anaya
• Natural Language Processing in Action" by Lane, Howard, and Hapke
• Python Crash Course" by Matthes and Matthes
• Mastering Regular Expressions" by Jeffrey E.F. Friedl
• Learning Python Design Patterns" by Gahlot, Chetan
• Data Science for Business" by Provost and Fawcett
• Hitchhiker’s Guide to Python" by Kenneth Reitz and Tanya Schlusser
• Python Machine Learning" by Raschka and Mirjalili
• The Pragmatic Programmer: Your Journey to Mastery" by Andrew Hunt and David Thomas
• Data Science for Dummies" by Pierson
• Flask By Example" by Sayal and Nagaraja
• Python GUI Programming with Tkinter" by Moore, Chadwick, and Haas
• Introduction to Computer Science and Programming Using Python" by John V. Guttag
• Python Machine Learning Blueprints" by Alexander T. Combs
• Hands-On Reinforcement Learning with Python" by Sudharsan Ravichandiran
• Real Python" by Fletcher Heisler
• Web Scraping with Python" by Richard Lawson
• Automate This: How Algorithms Came to Rule Our World" by Christopher Steiner

Certainly! If you're looking to purchase any of the mentioned Python books or explore a wide range of other titles, please visit our home page . We're here to assist you in finding the right resources to enhance your Python learning journey. Whether you're a beginner or an experienced programmer, our curated selection of books covers various aspects of Python programming. Feel free to explore and reach out if you need any assistance or recommendations. Happy learning!

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Python is a very powerful and high-level object-oriented programming language and due to its versatile nature, it is the most popular one. Python’s dynamic typing and elegant syntax , together with its interpreted nature, make it a perfect language for scripting and application development in many areas. It has powerful libraries to work with. Also, you can see a fantastic career opportunity in Python. The major areas of its application include Web Development. Data Science — including machine learning, artificial intelligence, data analysis, data visualization , and Game Development.

When it comes to learning a particular language like Python , books can be the best way to let you grasp even a single concept. Books build the foundations and reading gives more objective and descriptive information. When you spend time reading something, it makes you more clear and concise. You pay a lot of attention while reading and thus it lets you know everything in detail. 

Learning Python is at the top of my recommendation list for anyone wanting to start programming with Python. – Doug Hellman

So, Moving from basics to advanced level here are some of the Top 10 Python Books

1.   Python Crash Course – A Hands-on, Project-Based Introduction to Programming (2nd Edition)

This could provide you with a good start, to begin with, Python if you’re a beginner. This book has been the world’s best-selling book for the Python programming language. It has been divided into two sections: 

• The first section gives you the basics of Python dealing with data types, operators, functions, loops, and much more. 
• The second section focuses solely on programming and projects related to web development, data visualization, game development, and so on. 
• It also has wonderful libraries such as NumPy , Matplotlib , etc which could provide in-depth knowledge about Data Science and Visualization.

The book focuses on the practical part It will surely give you the best learning experience. If you’re the one who wanted to dig deep into programming, this book will get you writing real programs. This is the one that keeps you interested in learning more and more. 

Author: Eric Mathews

2. A Byte of Python

This book mainly targets newbies who are all new to the world of programming. Its basic concepts revolve around how to play with files. The topics covered in this book are: 

• Focuses on concepts like – Operators and Functions, Control Flow .
• Provides examples of Data Structures and OOPS (Object Oriented Programming Language).
• The concept of Exceptional Handling (try-and-catch method) is clearly explained

Initially, this book works on seeking the reader’s attention and then moves to every concept in detail, along with examples. Indeed, this is one of the best books to learn Python as a Beginner. The best thing is that it is also available in 26 languages . 

Author: C.H. Swaroop

3. Head First Python – A Brain-Friendly Guide (2nd Edition)

A book is a quick and easier fix for you that aims to be easy and friendly (as the name suggests) to the reader’s mind. It has visual formats rather than a text-based approach helping you to visualize and learn in a better, more efficient, and faster way. It focuses on concepts like:

• It provides a quick grasp of Python fundamentals.
• It helps in building web applications, data wrangling, exception handling , and other major concepts. It goes beyond the syntax to make you learn how to create applications for Android phones, Google’s App Engine, and more. 
• If you’re the one who’s fascinated with concepts like context managers, decorators, comprehensions, and generators , all you want to work with is here.  

It gives the best learning experience which helps in becoming a Certified Python Programmer.

“This book’s admirable clarity, humor, and substantial doses of clever make it the sort of book that helps even non-programmers think well about problem-solving.”                                                                                                                                                                                                                                                      — Cory Doctorow

Author: Paul Harry

4. Python Programming – An Introduction to Computer Science (3rd Edition)

Python Programming targets the university-level students who are being introduced to the world of Computer Science. It helps you break down the complexity of tools and programming concepts in a simple yet efficient way. It works on topics like:

• Basic programming deals with graphics.
• Write simple programs, computing with numbers.
• Works with Strings, Lists, and Files
• Loop, Structures, and Boolean
• Data Collections, Algorithm Design and Recursion.

It provides details about new technologies while maintaining a time-tested approach to teaching the basic concept of computer science. There are various examples to practice with and gain hands-on practice.

Author: John M Zelle 

5. Python in a Nutshell – A Desktop Quick Reference  (3rd Edition)

A book that covers the basics of Python and is also a wonderful resource when it comes to libraries and language references. If you’re fundamentally more strong with Python, go ahead and learn some of the more complicated concepts this book deals with. The major points covered in this book are:

• An explanation of object-oriented programming in Python, which covers both the classic and new-style object models .
• Covers other core topics, including exceptions, modules, strings, and regular expressions , and also has Python’s cross-platform capabilities.
• A quick and easy reference for Python’s built-in types and functions, as well as the key modules in the Python standard library, including time,  thread,  os, sys, math, and socket, among many others.
• Its application areas include GUIs, web and network programming, database interactions, and XML handling .

It’s a complete guide to improving your programming skills in Python. Python, in a Nutshell, provides a solid and quick reference to information that programmers rely mostly upon. This latest addition to the best-selling “In a Nutshell” series will very soon earn its place in any Python programmer’s library.

Author: Alex Martelli

6. Fluent Python – Clear, Concise, and Effective Programming  (2nd Edition)

This book is a hands-on guide that helps you to write efficient Python code by using the best features of the language. A book is something that tells you how to make the best use of language’s in-built features. It covers various concepts like:

• Data Structures, OOPs concepts, Python Data Model.
• Functions as Objects, Control Flow and Meta-Programming.
• Decorators, classes, inheritance.

This book is recommended for those who are already familiar with the basics of Python. It gives a complete tour of Python’s key features and libraries, to let you learn how to write code that is shorter, faster, and more readable. You’ll also learn to develop effective yet idiomatic Python code by exploring Python’s best guide. 

Author: Luciano Ramalho 

7. Python Cookbook

Python Cookbook helps you master your programming skills in Python 3. It is a ticket for experienced Python programmers who have sample codes through which readers can take help in building their projects. It covers a variety of topics covering application domains such as:

• Data encoding, data structures, algorithms, metaprogramming .
• Concurrency, network, web programming, testing, and exceptions.
• It also has discussions about the working of the sample code.

The book also has complete recipes for various topics, covering Python and its uses, along with tasks similar to a large number of application domains. To get more information about data structures and algorithms in Python, go through the tutorial Python Data Strictures and Algorithms .

Author: David Beazley and Brian K Jones

8. Programming Python – Powerful Object-Oriented Programming 

This book is basically for intermediate Python developers. The book explains the commonly used tools, language syntax, and programming techniques through a brief yet precise approach. You’ll explore on following areas:

• Databases, networking, text processing.
• GUIs, the Web, and system administration. 
• How do the databases use the language, text processing, front-end scripting layers, and networking? 

It has many examples that show common idioms and correct usage. The book also digs into the language as a software development tool, along with multiple examples given solely for that purpose. It explains language syntax and programming techniques and several other concepts to make you very clear about the topics. 

Author: Mark Lutz

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

This book teaches you how to use Python for Machine Learning applications. It deals with data and a lot more. Also, the steps required to create a rich machine learning are clearly explained here. It also covers algorithms used for machine learning along with their implementation in Python. It focuses on concepts like: 

• Genuinely understand what Computer Science, Algorithms, Programming, Data, Big Data, Artificial Intelligence, Machine Learning, and Data Science is.
• Advanced methods for model evaluation.
• Familiarity with the NumPy and Matplotlib libraries .
• Concept of pipelines used to encapsulate your workflow and chaining models.

It lets you know what problems Machine Learning can solve, and how the process behind it. Also, you’ll get to know how to avoid issues with Machine Learning, to successfully implement it without losing your mind!

Author: Sarah Guido and Andreas C. Muller

10. Python for Data Analysis

This is the perfect guide to help you become a data analyst, also provides case studies that help you gain more knowledge and practicality of Python. Also, lets you know when and where to use specific tools. It has numerous features such as :

• Use the IPython shell and Jupyter notebook for exploratory computing.
• Use flexible tools to load, clean, merge, transform, and reshape data.
• Apply the pandas group-by-facility to slice, dice, and summarize datasets.
• Analyze and manipulate regular and irregular time series data.
• Plotting and Visualization.
• Learn to solve real-world data analysis problems with thorough, detailed examples.

Books like Python For Data Analysis are indeed a gem and must-read for any Data Scientist who uses Python and want to learn more to become proficient in this technology. 

Author: Wes McKinney

Also, there are some Python books that you can read to gain some more insights and get perfect in Python.

• Python Machine Learning by Sebastian Raschka and Vahid Mirjalili offers the practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis. 
• Django for beginners by William S. Vincent is a project-based introduction to Django, the popular Python-based web framework. Suitable for total beginners who have never built a website before as well as professional programmers looking for a fast-paced guide to modern web development and Django fundamentals.

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7 Best Python Books for Beginners in 2023

Did you know? Python’s name originated from Monty Python.

If you are thinking of picking a language as a beginner, Python is not just a fine language to choose. It’s practically undeniable.

Why? Python’s popularity has absolutely exploded in recent years. A 2019 InfoWorld article says, “At the current pace of growth, Tiobe estimates Python could surpass Java and C in popularity in three to four years. ”

To put this in perspective, Java and C has dominated our world for decades. The languages have, until recently, been widespread in computer science classrooms and software companies.

But we are in a new age. Unlike a more complex language like Go , Python is now often taught at top universities of computer science instead of the more traditional languages.

One top computer science university, Rice University, teaches a full computer science curriculum through Coursera with Python . According to their course description, this is the reasoning they give:

Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera.

Python offers a ease-of-use and modern comfort that other languages can’t compete with. Python is also the choice for learning tools like Raspberry Pi and to teach kids programming.

Python is everywhere.

And it gets better. Due to Python’s popularity and accessibility, Python has an abundance of learning resources that is unparalleled in charm and style.

The book publisher No Starch Press (which will appear many times in this article) pioneers engaging and creative books on Python.

The best books on Python provide you the ability to learn at your own time even if you are on the go. In order to attain better employment opportunities in the software industry, you can learn to master Python programming skills through books, courses, and projects.

The best books about Python will help you craft interesting projects with new, innovative ideas. Fortunately, there are many books I would deem the best Python books for beginners. Unlike other categories of books, it’s hard to narrow them down.

In this article, we have put the spotlight on the best books for learning Python through a collection of book reviews.

Each book review will highlight the taste of the book, contents covered, and how it can benefit you. Depending upon your background and book’s style and content, different books may resonate with you.

An Overview of Python

Did I already mention that Python is a popular programming language?

Created by Guido van Rossum and released in 1991, this general-purpose language can be used for a variety of applications. Python includes capabilities such as web development, software development, artificial intelligence (AI), OS, prototyping, GUI-apps, image processing, and scientific computing. It's also a popular language for machine learning, data analysis, and visualization.

Many tech giants like Google, Microsoft, Netflix, and Mozilla are using Python. Even many financial firms also recruit Python developers. This is also the primary language used for the massive cloud computing project OpenStack.

Best Books on Python for Beginners

Although there are many online courses and resources, learning from books is still the best way to improve Python programming. Not all Python programming books are made equal. Best Python books must meet the following criteria:

Use clear, precise, and easy-to-understand language

Thoroughly teach and explain the most important Python concepts

Contain practice problems and questions for you to work on your own

Engaging able to hold the attention of readers

Structured and friendly toward self-taught programmers

Here are the best Python books for beginners:

Book 1: Learn Python 3 the Hard Way

Learn Python 3 the Hard Way by Zed A. Shaw helps the reader learn the basics of programming with Python 3. Readers will learn Python through 52 outstandingly crafted exercises. Each exercise is building on the previous, and each one teaches the reader about some new features of the language. You just have to do all these exercises and find your own solutions to problems you run into.

The book starts with Exercise 0 which is about getting Python set up on your computer. As you go through the book, you will learn about the following:

Install a complete Python environment

Organize and write code

Fix and break code

Basic mathematics

Strings and text

Interact with users

Work with files

Looping and logic

Data structures using lists and dictionaries

Program design

Object-oriented programming

Inheritance and composition

Modules, classes, and objects

Python packaging

Automated testing

Basic game development

Basic web development

The contents of this book are concise and well-constructed. It is suitable for both beginners and professionals. This classic book will help you to learn how the software works; what good programs look like; how to read, write, and think about Python code; and how to find and fix your mistakes. The ‘hard way’ from the title turns out to be the easy way to learn and master Python!

You can access  Learn Python 3 the Hard Way  free for 10 days with O’Reilly Learning. 

Book 2: Head First Python, 2nd Edition

Head First Python by Paul Barry is a brain-friendly guide for Python programming. It is not as comprehensive as some of the other books, it still covers a wide range of Python tasks in a user-friendly way. This book is designed to guide you through Python programming challenges in a fun way. It has a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. 

There are 12 chapters in this book and the contents covered in the book are:

Chapter 1 covers the basics

Chapter 2 covers List Data

Chapter 3 covers Structured Data

Chapter 4 covers Code Reuse

Chapter 5 covers Building a Webapp

Chapter 6 covers Storing and Manipulating Data

Chapter 8 covers a little bit of class

Chapter 7 gives the concept of using a Database

Chapter 9 covers the context management protocol

Chapter 10 covers function decorators

Chapter 11 covers exception handling and a little bit about threading

Chapter 12 covers advanced iteration

Each chapter is organized around a unifying project “building a dynamic website for a school athletic coach using Python through a Common Gateway Interface (CGI)”. If you are looking for a fun and approachable book for Python, then this one is for you. The contents will make you stay focused and you will not be bored!

You can access  Head First Python free for 10 days with O’Reilly Learning. 

Book 3: Python Crash Course, 2nd Edition

Python Crash Course by Eric Matthews is one of the bestselling Python books in the world. This book is well written and nicely organized. This is a fast-paced and comprehensive introduction to Python language for beginners who wish to learn Python programming. This book has a patient and experienced pedagogical style, along with a combination of thorough language instruction and a lot of illustrative sample codes. 

The contents of the book are divided into two parts. The first part of the book discusses the basics of Python programming. It has the following chapters:

Chapter 1 covers the basics on how to get started

Chapter 2 covers the variables and Simple Data Types

Chapter 3 introduces Lists

Chapter 4 covers the contents on how to work with Lists

Chapter 5 covers the basics of ‘if Statements’

Chapter 6 covers the basics of Dictionaries

Chapter 7  covers the user input and while loops

Chapter 8 introduces Functions

Chapter 9 introduces Classes

Chapter 10 introduces Files and Exceptions

Chapter 11 covers the topic of how to test your code before you add it to a project

The second part of this book follows a practical approach and includes three challenging and entertaining projects. This helps you test your knowledge by presenting three different projects, an arcade game ‘Alien Invasion’, data visualizations, a web application using Python’s libraries.

As you go through the book, you will learn how to:

  •  Use powerful Python libraries and tools, including Pygame, Matplotlib, Plotly, and Django

  •  Make 2D games that respond to keypresses and mouse clicks, and that increase in difficulty

  •  Use 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

The book is recommended not just for beginners but for anyone who has a vague understanding of the language and wants to polish his/her Python programming. As you go through the book, you learn the use of libraries, tools. and amazing visualizations. I love this book!

You can access this book free for 10 days with O’Reilly Learning.

Book 4: Serious Python

Serious Python by Julien Danjou is an outstanding book for those who already have gone through beginner’s guides and tutorials or already have experience of other programming languages. This book teaches you how to write Python code in an expert way. The chapters are not just covering the mere syntax but take your Python skills to a new level. 

This book is will let you learn how to make and use effective decorators and methods. The wonderful book will help you to employ Python for functional programming using generators, pure functions, and functional functions. It also helps you to extend flake8 to work with the AST to introduce more sophisticated automatic checks into your programs. The book aids you to apply dynamic performance analysis and managing relational databases and stream data with PostgreSQL.

The book is divided into thirteen of the following chapters:

Chapter 1 covers laying out the files and folders for your Python project. 

Chapter 2 covers modules, libraries, frameworks, and importing. This is especially helpful from other languages that have similar, but distinct, ways of importing code.

Chapter 3 covers Python-specific documentation and Good API Practice

Chapter 4 covers the handling of timestamps and time zones as it is important programming information. This chapter brings to light easy-to-miss Python modules that make working with dates and timezones manageable.

Chapter 5 covers packaging and distributing Python code Distributing Your Software

Chapter 6 covers unit testing, fixtures, and mocks. It also covers code coverage.py tool for measuring the effectiveness of your unit tests.

Chapter 7 covers decorators and static/class/abstract methods. 

Chapter 8 covers functional programming concepts. This chapter is a must-read for anyone who does not know about functional programming. 

Chapter 9 covers the abstract syntax tree, Hy, and lisp-like attributes.

Chapter 10 covers performance and optimization, explaining not just the cProfile module but also the dis module for disassembling Python bytecode for analysis.

Chapter 11 covers scaling and architecture and provides a good introduction to several concepts that many programmers are unaware of.

Chapter 12 covers concepts of managing relational databases

Chapter 13 covers a few miscellaneous topics that don't quite fit in any other chapter. 

This book is filled with practical information and compiled the contents in a well-organized way. Serious Python will simply polish your Python skills from good to outstanding!\

Book 5: Real-World Python

Real-World Python by Lee Vaughan is a project-based approach to learning Python programming. This is my favorite book for advanced Python programmers as you will explore some of Python’s more powerful tools and learn how to tackle challenging problems with code.

Real-World Python is a collection of worked projects for those who already readers who know some basic Python and want to do something with their knowledge. The book will teach you how to investigate and solve real-world problems using sophisticated computer vision, machine learning, data analysis, and language processing tools. The book's projects teach thought processes, problem-solving, and coding syntax. 

This book lets you learn and think through challenges like saving shipwrecked sailors, detecting asteroids, discovering planets, selecting landing sites for Mars, and many more. The book's practical projects introduce important Python modules, like NLTK and OpenCV, which are used extensively in data analysis and machine learning. Some of the projects of this book are:

Saving Shipwrecked Sailors with an algorithm ‘Bayes’ Rule’

Sending super-secret messages based on a book code

Finding Pluto

Winning the moon race with Apollo 8

Selecting landing sites for a Mars probe using real NASA maps

Detecting distant exoplanets and alien megastructures orbiting distant stars

Identifying friend or foe

Restricting access with face recognition

Surviving a zombie outbreak with data science

Test the hypothesis that we’re all living in a computer simulation

Overall, this book best suits those who are familiar with Python programming concepts and libraries. By the end of the book, readers will be able to create complete working programs by thinking through intriguing Python projects. If you’re someone who likes to learn by doing, then this book is for you!

Book 6: Python One-Liners

Python One-Liners by Christian Mayer will show you how to perform useful tasks with a concise one line of Python code.  You will learn how to systematically unpack and understand any line of Python code, and write concise and eloquent Python like a professional!

Through this book, you will learn how to…

Leverage data structures to solve real-world problems

Use NumPy basics

Calculate basic statistics of multidimensional data arrays and the K-Means algorithms for unsupervised learning

Create more advanced regular expressions 

Understand a wide range of computer science topics, including anagrams, palindromes, supersets, permutations, factorials, algorithmic sorting and many more

The book covers essential advanced topics like slicing, regular expressions, list comprehension, broadcasting, lambda functions, algorithms, logistic regression, and more. Each chapter introduces a problem to solve, walks the reader through the skills necessary to solve that problem, then provides a concise one-liner Python solution with a detailed explanation. The chapters in the book cover the following:

Chapter 1 is a brief Python refresher

Chapter 2 covers the Python Tricks

Chapter 3 covers concepts of data science

Chapter 4 covers the concepts of machine learning (ML)

Chapter 5 covers regular expressions 

Chapter 6 covers useful algorithms

By the end of the book, you will know how to write refined and concise Python in merely a single line. The unique style of the book not only encourages you to read for a long time without getting bored but also makes you do stuff along the way.

Book 7: Automate the Boring Stuff with Python, 2nd Edition

Automate the Boring Stuff with Python by Al Sweigart is one of the best books for beginning programmers. To read this book, you do not need any prior Python programming experience. In this book, you will learn how to use Python to write programs that do in minutes what would take you hours to do. 

This book will help you to create programs that perform useful feats of automation to send e-mail responses, fill out online forms, search for text in one or multiple files, search the Web and download online content, update and format excel data, and edit PDFs. 

The book is well designed and clearly written. It has twenty chapters and is divided into two parts. The first part of the book covers the Python programming basics:

Chapter 1 covers the Python basics

Chapter 2 covers the flow control

Chapter 3 covers the functions

Chapter 4 covers the lists

Chapter 5 covers the dictionaries and structuring data

Chapter 6 covers the manipulating strings

The second part of the book covers automating tasks and introduces the use of python libraries for some common and useful tasks. This section includes a variety of projects including:

Pattern Matching with Regular Expressions

Input Validation

Reading and Writing Files

Organizing Files

Web Scraping

Working with Excel Spreadsheets

Working with Google Sheets

Working with PDF and Word Documents

Working with CSV Files and JSON Data

Keeping Time, Scheduling Tasks, and Launching Programs

Sending Email and Text Messages

Manipulating Images

Controlling the Keyboard and Mouse with GUI Automation

This book walks you through each program with step-by-step instructions. At the end of each chapter, there are practice projects that challenge your newly gained skills and hands-on knowledge. Python is often said to be a fun language to learn. If you have given up learning Python half-way through a boring and tough book, try this one. This book is a fun read and valuable to have on your shelf!

Final Thoughts

That wraps our article about some of the best books to learn Python. It is hard to say which is the best book as it depends upon your background and choice.

In this series, you may have noticed: you can access every single one of these books for free digitally with O’Reilly Media’s astoundingly massive library . This is my secret to being able to read and access so many books. O’Reilly is partnered with literally all of the major players. If you own any technical books at all, they are probably digitized on O’Reilly Learning.

With the great selection of the best books on Python covering almost all topics one can imagine, the learning opportunities are endless!

Have you read some of the books already? Which book did you find the most helpful?

If you find this article on the best books about Python valuable, please share it with your friends, and if you want to continue learning and growing through books, you can always sign up for the Books on Code free email course, Get the Most from Technical Books (for Programmers) .

If you’re interested in more learning resource recommendations, check out these 72 free coding resources . I will see you there. 👋😁

Miranda is the founder of Books on Code , with a mission to bring book-lover culture to programmers. Learn more by checking out Miranda on LinkedIn .

Learning Code for Free: The Ultimate Guide for 2023

Clean code review: top 7 principles you must know.

The 5 Best Books for Python Developers

Are you a beginning Python developer who’s looking to deepen your knowledge? We’ve got 5 books that will take your Python coding skills to the next level!

The breadth and depth of software products and applications that use Python have been increasing tremendously. You can observe Python’s dominance across many domains such as artificial intelligence, data science, machine learning, web development, and mobile game development.

As a natural result of this dominance, the demand for Python developers skyrocketed. In simple terms, a Python developer is a person who creates, develops, and maintains software tools and products using Python. Once you are skilled in Python, there is a promising career awaiting you; check out what Python jobs you can get in 2023 .

So You Want to Really Learn Python …

To learn a programming language or any other software tool, you need resources. Python is an open-source programming language with a huge and active community that helps you get the support you need when you need it. Hence, there is no shortage of resources to learn Python .

However, if not approached wisely, this rich selection of resources might turn into a disadvantage. Randomly selecting and consuming resources is not an effective way to learn Python; you’re more likely to get discouraged and give up rather than pick up a useful skill.

The best Python learning resources are structured around a carefully designed curriculum. Interactive online courses created by professionals are very helpful in this regard. They help you practice while learning, which is essential to mastering any programming language.

If you are a newcomer to coding, the Python Basics track is an ideal place to start your learning journey. It consists of 3 interactive courses and a total of 229 coding challenges. At the time of writing this article, Python Basics: Part 1 is totally free.

Books on programming languages are generally also very good learning resources. They’re written by subject matter experts who have used the language for many years. Hence, you have the chance to learn not only the terms and concepts but also the experience of using the language in real-life projects.

However, books should not be the only resource you use while learning Python; they usually lack interactivity. Once you learn about a subject, the best way to have a comprehensive understanding of it is to solve examples or coding challenges. Such an experience is best offered by interactive online courses.

A big advantage of using books is that they cover some terms and concepts in more depth than online courses. You might say books are better at teaching theory, while online courses are better at teaching you how to code. Therefore, think of books as a supplementary learning material for online courses.

So far, three articles about the best Python books have been published on the LearnPython.com blog:

• The Best Python Books
• The Best Python Books, Part 2
• The Best Python Books for Data Science

In this article, we will review the 5 best books for Python developers with some experience. I’ve made my selections based on my own experience and what I have learned from the Python community.

The Best Books for Advancing Python Developers

Each book title is linked to its Amazon page so that you can find it easily. It is important to note that Amazon has had no impact on the selection, nor do we receive any compensation from linking to the Amazon listings.

1.   Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin

Whatever programming language you use, writing clean code is crucially important. As a Python developer, most of your time will be spent reading other people’s code. Your code will be read by your colleagues and other developers as well. If code is messy, reading and understanding it could become a nuisance.

The book mentions that every year, countless hours and significant resources are lost because of poorly written code – definitely a serious issue. This book will teach you Agile methodology as well as the principles, patterns, and practices of writing clean code.

You will learn how to apply these principles in the following areas:

• Meaningful names
• Objects and data structures

Error handling

2.   Python Cookbook by David Beazley and Brian Jones

This book is packed with practical recipes for solving various Python-related problems. It contains more than a dozen recipes that cover core elements of Python as well as domain-specific topics. Each recipe comes with code samples, so you will have the chance to test it for yourself.

Each recipe can be considered as a practical solution to a common problem. Code samples along with their explanations help you implement real-life projects. Besides, you can always build on these code samples.

The recipes are organized into chapters on data structures and algorithms; iterators and generators; functions; classes and objects; modules and packages; concurrency, and several other areas.

This book is not an introduction to Python; it’s for people who already have some Python experience. It will help you in your journey to become a proficient Python developer.

3.   Python Testing with pytest by Brian Okken

Testing is an essential part of any software product. Whether you create a simple script or a large program with several modules, you need a testing process to write robust and maintainable code. One of the most commonly used tools for testing Python code is pytest, a testing framework that helps you write tests quickly and efficiently.

This book will teach you how to best use the pytest framework with easy-to-understand and simple instructions. It will guide you in writing, organizing, and executing tests. It starts with simple tests and gradually increases the complexity to cover the more advanced features of the pytest framework.

By completing this book and going through the code samples it contains, you will learn how to leverage pytest to test your code, detect issues, and fix bugs quickly. The end result will be higher-quality, deployment-ready code.

4.  

As its name suggests, this book is for increasing the performance of your Python code. Performance may not be an issue when you are writing short scripts for completing simple tasks. However, for programs with high volumes of data, performance can quickly become an issue. In such cases, you need to focus on not only completing the task but also doing it as efficiently as possible.

The book teaches intermediate and advanced Python developers how to optimize their code for performance. It starts with identifying and explaining issues in the code that cause poor performance. Then it introduces different ways and techniques to increase performance, such as the efficient use of built-in data structures, vectorized computations, parallel and concurrent programming, and memory usage.

4.   Python Algorithms: Mastering Basic Algorithms in the Python Language by Magnus Lie Hetland

A computer program is simply a set of instructions organized in a certain way to complete a task. Hence, a computer program is essentially an algorithm. The way you write and organize instructions is fundamental to writing efficient programs.

Data structures and algorithms are a highly challenging part of computer science and programming. This book focuses on algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. You will learn about well-known algorithms and data structures and how to implement them with Python.

Python Books + Python Practice = Your Path to Mastery

The 5 books we covered in this article are definitely great learning material. However, they should not be your only learning resource. Adding the in-depth theory from books to practice and hands-on experience is the best learning path.

LearnPython.com provides several tracks and courses to help you with hands-on learning. Learn Programming with Python is a good way to start. With 5 interactive courses and a total of 414 coding challenges, you will learn the basics and have the chance to practice and absorb the material.

As a Python developer, you are expected to combine theory and practice and do it effectively. Read this article if you want to learn more about how to think like a Python developer.

Happy learning!

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Top 7 Python Libraries for Data Science Workflows

Python’s rising use in data science projects isn’t just hype: It’s a testament to its incredible power and versatility. Unlike specialized statistical software, Python’s flexible syntax and extensive library ecosystem make it the Swiss Army knife of data analysis. This is due in part to the plethora of Python libraries for data science that can help you deal with messy data, build intricate machine learning models, and craft stunning visualizations—all within a single, cohesive environment.

Python’s libraries are each designed to tackle specific aspects of the data science workflow. Think of them as specialized tools in a carpenter’s workshop, each with its own unique purpose. And just as the right tool can make or break a carpentry project, choosing the right libraries can significantly impact the efficiency and success of your data science endeavors. In this article, we cover the top seven Python libraries for data science and explore their benefits.

The Library Selection Dilemma

The sheer abundance of Python libraries for data science, while a blessing, can also be a curse. It’s like walking into a store with a thousand different products—great, but also a tad overwhelming. With so many options, it can be challenging to determine which libraries are truly essential, decide which ones best suit your specific needs, and figure out how to integrate them seamlessly into your workflow.

Let’s take a look at the best Python libraries for data science and how they can help build a better data science project.

1. Pandas: Your Data Wrangler

Pandas is the undisputed workhorse of data analysis in Python. It’s like a trusty spreadsheet on steroids, providing you with powerful tools to manipulate, clean, and transform your data. Need to filter outliers, merge datasets, or aggregate information? Pandas has you covered.

Think of Pandas as your data’s personal trainer—it helps you whip your data into shape, making it ready for analysis. With its intuitive DataFrame and Series objects, you can easily load data from various sources, perform complex calculations, and even visualize your results.

2. NumPy: The Engine for Numerical Power

While Pandas might be the wrangler, NumPy is the raw horsepower that drives many data science operations. At its core, NumPy provides the high-performance multidimensional array object known as the ndarray, a seemingly simple structure that is the bedrock upon which much of Python’s scientific computing capabilities are built.

NumPy provides the computational power to perform mathematical operations on arrays and matrices with native code speed. From basic arithmetic to linear algebra and Fourier transforms, NumPy’s optimized C and Fortran code (which it uses under the hood) allows you to work with numerical data in Python yet get the performance benefits (e.g. vectorization) of C, at least for the operations that NumPy supports.

Why is this essential for data science? In many cases, data is represented as arrays or matrices—think images, time series, or tabular data. NumPy’s efficient operations on these structures make it an indispensable tool for tasks like data cleaning, feature engineering, and statistical analysis, especially when combined with other Python libraries for data science.

3. Scikit-learn: Your Machine Learning Arsenal

Scikit-learn is the go-to machine learning toolbox for Python. It’s well-stocked with numerous algorithms for common ML tasks like classification, regression, clustering, and dimensionality reduction. Whether you’re predicting customer churn, classifying images, or finding hidden patterns in your data, scikit-learn provides the building blocks to perform the task.

One of scikit-learn’s greatest strengths is its consistent and intuitive interface, particularly when working with other Python libraries for data science. Whichever algorithm you choose, the steps for training, evaluating, and deploying models follow a similar pattern. This makes it easy to experiment with different approaches and find the one that best suits your problem.

In addition, scikit-learn seamlessly integrates with other data science libraries in Python, like NumPy and Pandas, allowing you to easily move from data preparation to model building and evaluation. It also provides robust tools for model selection, hyperparameter tuning, and performance assessment, ensuring that you can build models that generalize well to new data.

To illustrate the seamless integration of scikit-learn with other Python data science libraries like NumPy and Pandas, let’s walk through a practical example where we prepare data, build a model, tune its parameters, and evaluate its performance.

The Exaloop Advantage: While scikit-learn is remarkably powerful and user-friendly, training and evaluating large models on extensive datasets can be time-consuming. This is where Exaloop can lend a helping hand. By leveraging parallel processing and hardware acceleration, Exaloop can expedite the preprocessing, training and prediction phases of your machine learning pipelines, allowing you to experiment with more complex models and larger datasets without sacrificing speed.

4. Matplotlib and Seaborn: Your Data Visualization Dream Team

In the world of data science, insights are only as valuable as your ability to communicate them effectively. That’s where Matplotlib and Seaborn come in—together they’re a power combination that empowers you to create appealing, informative visualizations to bring your data to life.

Matplotlib, the grandfather of Python visualization libraries, is like a blank canvas. It provides you with the building blocks to create a wide variety of charts, from simple line plots and scatter plots to complex heatmaps and 3D visualizations. With Matplotlib, you have complete control over every aspect of your plots, including colors, fonts, axes, and legends.

To demonstrate Matplotlib’s versatility, consider the following Python code snippet, which creates four different types of plots:

This code produces four distinct visualizations:

Line Plot: A simple graph representing a sine wave, showcasing trends over a continuous variable.

Scatter Plot: A diagram using red points to depict the relationship between two variables, ideal for spotting patterns and outliers.

Heatmap: A graphical representation of data where values are depicted by color, useful for highlighting variances across a dataset.

3D Line Plot: A three-dimensional plot that adds depth to the visual representation, enhancing the analysis of complex datasets.

However, this level of customization can sometimes come at the cost of convenience. This is where Seaborn shines. Built on top of Matplotlib, Seaborn offers a higher-level interface that streamlines the creation of nice-looking plots. Its default styles are elegant and modern, and its specialized functions make it easy to create complex visualizations like pair plots, violin plots, and heatmaps with just a few lines of code.

To illustrate this, compare the following code examples that create violin plots and heatmaps using Matplotlib and Seaborn:

Matplotlib Code for Violin Plot and Heatmap

Seaborn Code for Violin Plot and Heatmap

• Matplotlib requires setting up more details manually to create a violin plot and a heatmap. While it offers extensive customization, it can be cumbersome for rapid, elegant plotting.
• Seaborn , built on top of Matplotlib, simplifies these tasks significantly. It provides a more modern and elegant default style and specialized functions that reduce the complexity and code needed to produce similar visualizations.

The demonstration of these two libraries shows Seaborn’s strength in creating complex visualizations effortlessly, validating the statement about its elegance and functionality.

Together, Matplotlib and Seaborn provide a comprehensive toolkit for data visualization in the realm of Python libraries for data science. Matplotlib gives you the flexibility to create any type of plot imaginable, while Seaborn simplifies the process and ensures that your visualizations look polished and professional.

5. Statsmodels: Unleashing the Power of Statistical Analysis

Data science isn’t just about fancy machine learning algorithms: It’s also about understanding the underlying relationships and patterns in your data through rigorous statistical analysis. This is where Statsmodels enters the scene, offering a comprehensive suite of tools for exploring, analyzing, and interpreting your data from a statistical perspective.

Using Statsmodels is like having a seasoned statistician by your side, guiding you through the intricacies of hypothesis testing, regression analysis, time series modeling, and more. It provides a rich collection of statistical models, estimation techniques, and diagnostic tools, so you can gain deep insights into your data and make informed decisions.

Whether you’re testing the effectiveness of a new drug, forecasting sales trends, or seeking to understand the factors influencing customer behavior, Statsmodels empowers you to apply statistical rigor to your data science projects. Its comprehensive documentation and examples make it easy to get started (even if you’re not a statistics expert) and to incorporate it with other data science libraries in Python.

6. SciPy: The Scientific Computing Powerhouse

Building upon the foundation laid by NumPy, SciPy is a comprehensive library that extends Python’s scientific computing capabilities to new heights. If NumPy is the engine, SciPy is the full-fledged toolbox, equipped with a wide range of modules for tasks like optimization, integration, interpolation, signal and image processing, and more.

Think of SciPy as a multi-tool for scientists and engineers. It provides you with the specialized instruments to tackle a diverse range of scientific and technical problems. Need to find the minimum of a complex function? SciPy’s optimization module can do that. Want to smooth out noisy data? Its signal processing tools are at your disposal.

SciPy’s versatility makes it an indispensable asset for data scientists working in fields like physics, engineering, biology, and finance, especially when used with other data science Python libraries. It allows you to perform complex calculations, analyze experimental data, and build sophisticated models with ease. Its seamless integration with NumPy and other Python libraries for data science ensures a smooth and efficient workflow for your scientific computing tasks.

The Exaloop Advantage: While SciPy offers a wealth of functionality, some of its modules—particularly those involving intensive numerical computations—can benefit from Exaloop’s performance optimizations. Exaloop can help you accelerate tasks such as solving differential equations, performing spectral analysis, or optimizing complex systems, allowing you to explore a wider range of possibilities and gain deeper insights into your scientific data.

7. Dask: Scaling Python for Big Data

As datasets grow in size and complexity, traditional Python libraries like Pandas and NumPy can start to show their limitations. Dask , a powerful library designed to parallelize and distribute computations across multiple cores or even clusters of machines, can solve this problem. Dask acts as a supercharged version of your favorite tools, able to handle datasets that would otherwise bring your computer to a crawl.

Dask provides familiar APIs that mirror those of Pandas and NumPy, making it easy to scale up your existing workflows with other Python libraries for data science—all without a steep learning curve. Need to analyze terabytes of data on your laptop? Dask can distribute the workload across multiple cores, significantly speeding up your analysis. Working with a cluster of machines? Dask can leverage their combined power to tackle even more massive datasets.

The Exaloop Advantage: While Dask seeks to scale Python through distributed computing, it doesn’t enhance Python’s notoriously poor performance itself. That’s where Exaloop comes in: Exaloop accelerates Python to native code speed and can even be used within other distributed computing frameworks like Dask.

Expanding Your Toolkit with Exaloop

While the Python libraries for data science discussed so far provide a solid foundation for data science workflows, Exaloop offers a unique opportunity to elevate your capabilities even further. By seamlessly integrating with your favorite Python libraries, Exaloop turbocharges their performance, enabling you to tackle larger datasets, more complex models, and more demanding analyses with remarkable speed and efficiency.

Exaloop’s high-performance Python execution engine is to leverage the power of parallel processing and hardware acceleration. It automatically distributes computations across multiple cores or GPUs, allowing you to harness the full potential of your hardware without having to write specialized code.

For data scientists, this translates to several key benefits:

• Eliminating Engineering Roadblocks: You can focus on the data science problem at hand, not on optimizing code for performance. Exaloop handles the heavy lifting, so you don’t need specialized software engineering skills to achieve significant speedups.
• Faster Time to Insight: Exaloop accelerates your workflows, such as training a machine learning model, running a complex simulation, or analyzing a massive dataset, enabling you to iterate more quickly and arrive at insights faster.
• Cost Savings: By maximizing the utilization of your existing hardware, Exaloop can help you reduce the infrastructure costs associated with cloud computing or high-performance computing clusters.

Exaloop truly shines in scenarios where performance is critical. For example, if you’re working with large-scale datasets that don’t fit comfortably in memory, Exaloop can seamlessly distribute the workload across multiple machines, enabling you to analyze the data efficiently. Similarly, if you’re training computationally intensive models, Exaloop can leverage GPUs to significantly speed up the training process.

In essence, Exaloop empowers you to think bigger and bolder with your data science projects. It removes the performance limitations that often hold back Python users, allowing you to focus on what you do best: extracting valuable insights from your data.

Conclusion: Streamline and Supercharge Your Data Science Journey

The world of data science is vast and ever-evolving. The Python libraries we’ve explored in this article represent just a fraction of the tools available to you, each offering unique capabilities to help you tackle specific challenges and unlock valuable insights from your data.

But remember: The power of these libraries is magnified when they’re combined with the right tools. With its ability to accelerate computations and eliminate performance bottlenecks, Exaloop empowers you to get the most out of your Python workflows. Whether you’re working with massive datasets, training complex models, or simply seeking to streamline your analysis, Exaloop can be your secret weapon for achieving faster, more efficient, and more impactful results.

If you’re ready to take your data science endeavors to the next level, join the Exaloop waitlist to discover how it can transform your workflows. Don’t let slow tools hold you back.

Can I use Exaloop with my existing Python libraries for data science?

Absolutely. Exaloop can use standard Python packages out-of-the-box, but also offers new, optimized implementations of several key libraries, including ones discussed in this article. This means you can continue using your familiar tools and workflows while benefiting from Exaloop’s speed and efficiency.

Which Python data science libraries benefit the most from Exaloop?

Exaloop’s optimized implementations of libraries like NumPy and Pandas include a number of new library-specific optimizations and are able to leverage its parallel processing and GPU capabilities, which can yield order-of-magnitude performance gains.

Is Exaloop only for large-scale data science projects?

While Exaloop excels at handling large datasets and complex models, particularly in terms of increasing throughput for data processing and analysis, it can also be used for applications that rely on smaller datasets or are latency-bound instead of throughput-bound.

• Date updated: 2024-06-05
• Date Published: 2024-06-05

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