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https://github.com/devtoolsd/DevBooks

A curated, opinionated list of best-in-class books for modern software development, popular programming languages, and AI/ML.
https://github.com/devtoolsd/DevBooks

ai-books books devbook devbooks gobooks java java-books js-books pythonbooks

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A curated, opinionated list of best-in-class books for modern software development, popular programming languages, and AI/ML.

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README 

          
# Awesome DevBooks



A curated, opinionated list of **best-in-class** books for modern software development, popular programming languages, and AI/ML.



---



## Index



- [Software Engineering Essentials](#software-engineering-essentials)

- [Architecture, Data, and Distributed Systems](#architecture-data-and-distributed-systems)

  - [Databases](#databases)

- [Computer Science Foundations (Worth Knowing Forever)](#computer-science-foundations-worth-knowing-forever)

- [Version Control](#version-control)

- [Security](#security)

- [Programming Languages](#programming-languages)

  - [Python](#python)

  - [JavaScript / TypeScript](#javascript--typescript)

  - [Java](#java)

  - [Go](#go)

  - [Rust](#rust)

  - [C / C++](#c--c)

  - [C#](#c)

  - [Kotlin](#kotlin)

- [AI / Machine Learning](#ai--machine-learning)

  - [Big-picture AI + fundamentals](#big-picture-ai--fundamentals)

  - [Deep learning + modern practice](#deep-learning--modern-practice)

  - [ML systems, MLOps, and LLM-era work](#ml-systems-mlops-and-llm-era-work)

- [Contributing](#contributing)



---



## Software Engineering Essentials



- **[The Pragmatic Programmer (20th Anniversary Edition)](https://pragprog.com/titles/tpp20/the-pragmatic-programmer-20th-anniversary-edition/)** - *Andrew Hunt and David Thomas* - Practical habits, thinking tools, and engineering instincts that age incredibly well.

- **[Code Complete (2nd Edition)](https://www.microsoftpressstore.com/store/code-complete-9780735619678)** - *Steve McConnell* - The “how to write good code” encyclopedia: construction, readability, and craft.

- **[Clean Code](https://www.goodreads.com/book/show/3735293-clean-code)** - *Robert C. Martin* - Principles and examples for writing code that stays readable under pressure.

- **[Clean Architecture](https://www.goodreads.com/book/show/18043011-clean-architecture)** - *Robert C. Martin* - Core architectural ideas for keeping systems maintainable as they grow.

- **[Refactoring (2nd Edition)](https://martinfowler.com/books/refactoring.html)** - *Martin Fowler* - The classic playbook for improving design without changing behavior.

- **[Working Effectively with Legacy Code](https://www.amazon.com/Working-Effectively-Legacy-Michael-Feathers/dp/0131177052)** - *Michael Feathers* - How to add tests and make changes safely in scary, untested codebases.

- **[Design Patterns: Elements of Reusable Object-Oriented Software](https://en.wikipedia.org/wiki/Design_Patterns)** - *Erich Gamma, Richard Helm, Ralph Johnson, John Vlissides* - The OG patterns catalog (still useful when you treat it as vocabulary, not dogma).

- **[The Mythical Man-Month](https://en.wikipedia.org/wiki/The_Mythical_Man-Month)** - *Frederick P. Brooks Jr.* - Timeless lessons on why software schedules explode and what to do about it.



---



## Architecture, Data, and Distributed Systems



- **[Designing Data-Intensive Applications](https://dataintensive.net/)** - *Martin Kleppmann* - The go-to guide for storage, streams, consistency, and real-world system tradeoffs.

- **[Domain-Driven Design](https://domainlanguage.com/ddd/)** - *Eric Evans* - Modeling complex domains and aligning code with business reality.

- **[Release It!](https://books.google.com/books/about/Release_It.html?id=UW7jAQAACAAJ)** - *Michael T. Nygard* - Stability patterns and failure-mode thinking for production systems.

- **[Site Reliability Engineering](https://sre.google/books/)** - *Betsy Beyer, Chris Jones, Jennifer Petoff, Niall Murphy (eds.)* - Reliability principles, SLOs, toil reduction, and operating at scale.

- **[Kubernetes: Up & Running](https://www.amazon.com/Kubernetes-Running-Dive-Future-Infrastructure/dp/1491935677)** - *Kelsey Hightower, Brendan Burns, Joe Beda* - A practical mental model for Kubernetes and container orchestration.



### Databases



- **[PostgreSQL Books](https://github.com/sara8086/PostgresBooks)** - A curated list of books and guides for PostgreSQL.



---



## Computer Science Foundations (Worth Knowing Forever)



- **[Structure and Interpretation of Computer Programs (SICP)](https://mitpress.mit.edu/9780262510875/structure-and-interpretation-of-computer-programs/)** - *Harold Abelson, Gerald Jay Sussman, Julie Sussman* - Abstraction, interpreters, and “how to think like a programmer” at a deep level.

- **[Introduction to Algorithms (CLRS)](https://mitpress.mit.edu/9780262046305/introduction-to-algorithms-fourth-edition/)** - *Cormen, Leiserson, Rivest, Stein* - The standard reference for algorithms and data structures.

- **[The Art of Computer Programming](https://www-cs-faculty.stanford.edu/~knuth/taocp.html)** - *Donald E. Knuth* - The deep end of algorithms, analysis, and programming elegance.

- **[Computer Systems: A Programmer’s Perspective](https://csapp.cs.cmu.edu/)** - *Randal E. Bryant and David R. O’Hallaron* - What’s actually happening under your code: memory, caching, linking, concurrency.

- **[Operating Systems: Three Easy Pieces](https://pages.cs.wisc.edu/~remzi/OSTEP/)** - *Remzi H. Arpaci-Dusseau and Andrea C. Arpaci-Dusseau* - OS fundamentals explained clearly (and free online).



---



## Version Control



- **[Pro Git](https://git-scm.com/book/en/v2)** - *Scott Chacon and Ben Straub* - The most readable Git book, from basics to power-user workflows.



---



## Security



- **[Serious Cryptography](https://nostarch.com/seriouscrypto)** - *Jean-Philippe Aumasson* - Cryptography concepts explained for engineers who need to use it correctly.

- **[The Web Application Hacker’s Handbook](https://www.wiley.com/en-us/The+Web+Application+Hacker%27s+Handbook%3A+Finding+and+Exploiting+Security+Flaws%2C+2nd+Edition-p-9781118026472)** - *Dafydd Stuttard and Marcus Pinto* - Practical web security testing and attack/defense thinking.



---



## Programming Languages



### Python



- **[Python by Example](https://github.com/pycollege/python-by-example)** - **Dariush Abbasi** - A practical, example-driven guide to learning Python with clear explanations and real coding tasks.

- **[Fluent Python](https://www.fluentpython.com/about/)** - *Luciano Ramalho* - Idiomatic Python: data model, iterators, concurrency, typing, and best practices.

- **[Effective Python](https://effectivepython.com/)** - *Brett Slatkin* - Sharp, practical items for writing clean, correct, modern Python.

- **[Python Cookbook (3rd Edition)](https://www.amazon.com/Python-Cookbook-Third-David-Beazley/dp/1449340377)** - *David Beazley and Brian K. Jones* - Recipe-driven solutions to real Python problems (from basics to advanced).



#### Related Python Reading



- **[Python Books](https://github.com/lara-west/PythonBooks)** - A comprehensive list of Python books, tutorials, and learning materials.



---



### JavaScript / TypeScript



- **[Eloquent JavaScript](https://eloquentjavascript.net/)** - *Marijn Haverbeke* - Best “learn JS by understanding it” book (and free online).

- **[You Don’t Know JS Yet](https://github.com/getify/You-Dont-Know-JS)** - *Kyle Simpson* - Deep dive into JS mechanics: scope, closures, objects, async, and more.

- **[Programming TypeScript](https://www.amazon.com/Programming-TypeScript-Making-JavaScript-Applications/dp/1492037656)** - *Boris Cherny* - How to scale JS codebases with TypeScript’s type system and patterns.



#### Related JavaScript Reading



- **[JavaScript Books](https://github.com/minouou/jsbooks)** - A collection of books and learning resources for JavaScript.



---



### Java



- **[Effective Java (3rd Edition)](https://www.informit.com/store/effective-java-9780134685991)** - *Joshua Bloch* - The definitive guide to writing robust, idiomatic Java.

- **[Java Concurrency in Practice](https://jcip.net/)** - *Brian Goetz et al.* - The classic on writing safe and scalable concurrent Java code.



---



### Go



- **[Boring Go!](https://golang.college/books/boring-go)** - *Caleb Doxsey* - A hands-on, approachable guide focusing on real-world Go practices and simplicity.

- **[The Go Programming Language](https://www.gopl.io/)** - *Alan A. A. Donovan and Brian W. Kernighan* - Clear, thorough coverage of Go from core language to concurrency.



#### Related Go Reading



- **[GoBooks](https://github.com/dariubs/gobooks)** - A large, curated collection of Go books, tutorials, and learning resources.



---



### Rust



- **[The Rust Programming Language (“the book”)](https://doc.rust-lang.org/book/)** - *Steve Klabnik and Carol Nichols (with contributors)* - The best first principles introduction to Rust (free online).

- **[Programming Rust](https://www.amazon.com/Programming-Rust-Fast-Systems-Development/dp/1491927283)** - *Jim Blandy, Jason Orendorff, Leonora F. S. Tindall* - Practical, detailed Rust for real systems work.



---



### C / C++



- **[The C Programming Language](https://en.wikipedia.org/wiki/The_C_Programming_Language)** - *Brian W. Kernighan and Dennis M. Ritchie* - The classic C text (short, sharp, foundational).

- **[Effective Modern C++](https://www.amazon.com/Effective-Modern-Specific-Ways-Improve/dp/1491903996)** - *Scott Meyers* - Best practices for C++11/14 and “how to stop hurting yourself.”

- **[C++ Primer](https://www.amazon.com/C-Primer-5th-Stanley-Lippman/dp/0321714113)** - *Stanley B. Lippman, Josée Lajoie, Barbara E. Moo* - A thorough, structured path through modern C++.



---



### C#



- **[C# in Depth](https://csharpindepth.com/)** - *Jon Skeet* - The book for understanding the “why” behind C# features (not just syntax).



---



### Kotlin



- **[Kotlin in Action](https://kotlinlang.org/docs/books.html)** - *Dmitry Jemerov and Svetlana Isakova* - Practical Kotlin with the patterns you’ll actually use on real projects.



---



## AI / Machine Learning



### Big-picture AI + fundamentals



- **[Artificial Intelligence: A Modern Approach (AIMA)](https://aima.cs.berkeley.edu/)** - *Stuart Russell and Peter Norvig* - The classic survey of AI concepts, agents, search, logic, probability, and learning.

- **[Pattern Recognition and Machine Learning (PRML)](https://www.microsoft.com/en-us/research/wp-content/uploads/2006/01/Bishop-Pattern-Recognition-and-Machine-Learning-2006.pdf)** - *Christopher M. Bishop* - Core probabilistic ML foundations with a Bayesian viewpoint.

- **[The Elements of Statistical Learning (ESL)](https://hastie.su.domains/ElemStatLearn/)** - *Trevor Hastie, Robert Tibshirani, Jerome Friedman* - Deep statistical learning theory; a reference you’ll keep coming back to.

- **[An Introduction to Statistical Learning (ISLR)](https://www.statlearning.com/)** - *James, Witten, Hastie, Tibshirani, Taylor* - Friendlier, more applied companion to ESL (great first stats-ML book).



### Deep learning + modern practice



- **[Deep Learning](https://www.deeplearningbook.org/)** - *Ian Goodfellow, Yoshua Bengio, Aaron Courville* - The deep learning reference text (also free online).

- **[Hands-On Machine Learning](https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1098125975)** - *Aurélien Géron* - Practical ML with end-to-end projects using modern Python tooling.

- **[Deep Learning with Python](https://deeplearningwithpython.io/)** - *François Chollet* - Intuitive deep learning practice from the creator of Keras (and free to read online).



### ML systems, MLOps, and LLM-era work



- **[Designing Machine Learning Systems](https://books.google.cz/books?id=EzhwEAAAQBAJ)** - *Chip Huyen* - End-to-end ML system design: data, training, deployment, monitoring, iteration.

- **[Natural Language Processing with Transformers](https://transformersbook.com/)** - *Lewis Tunstall, Leandro von Werra, Thomas Wolf* - Modern NLP and transformer workflows with hands-on examples.

- **[Reinforcement Learning: An Introduction](http://incompleteideas.net/book/the-book-2nd.html)** - *Richard S. Sutton and Andrew G. Barto* - The RL classic, from bandits to policy gradients.

- **[Generative Deep Learning](https://www.oreilly.com/library/view/generative-deep-learning/9781098134174/)** - *David Foster* - Practical generative modeling: VAEs, GANs, diffusion, and transformers.



#### Related AI Reading



- **[AI Books](https://github.com/mahseema/aibooks)** - A broad, curated list of books and resources covering AI, ML, and deep learning.

- **[Go Books](https://github.com/dariubs/gobooks)** - List of Golang books

- **[JavaScript Books](https://github.com/minouou/jsbooks)** – A collection of books and learning resources for JavaScript  

- **[PostgreSQL Books](https://github.com/sara8086/PostgresBooks)** – A curated list of books and guides for PostgreSQL  

- **[Python Books](https://github.com/lara-west/PythonBooks)** – A comprehensive list of Python books and tutorials



---



## Contributing



PRs welcome! If you add a book, please:

- keep the exact bullet style,

- prefer official/free links when available,

- add a one-line description that explains *why it’s worth reading*.