Other resources for developers

The classic object oriented patterns presented with the problem each one solves, so you apply them where they help rather than everywhere. Pattern vocabulary shows up in design rounds and in every code review you will ever have.

The five principles behind maintainable object oriented code, with examples of what violating each one costs later. Short, and it directly improves the code you write tomorrow.

Thousands of questions and exercises across Linux, networking, Docker, Kubernetes, CI/CD, cloud, SQL and Terraform, with answers. Good for finding the holes in what you think you know, whether or not there is an interview coming.

The index of every curated awesome list, covering nearly every language, framework and topic in software. When you are starting in an unfamiliar area, finding its awesome list first will usually save you a week of searching.

A very large, actively maintained index of free books, courses and cheat sheets, organised by language and subject and available in many languages. Check here before buying anything. A surprising number of standard texts are legally free from their authors.

Hundreds of algorithms implemented and readable, in Python and most other languages. Useful in two ways: as a reference when a description in a textbook has not clicked, and as a first open source contribution, because adding a missing algorithm is a genuinely approachable pull request.

Build something real tutorials sorted by language, from a web server in Go to a text editor in C. If you have finished a course and now feel stuck with nothing to make, start here rather than starting another course.

Step by step tutorials for building your own database, git, shell, compiler, docker or operating system from scratch. This is the best answer to the question of what to build when tutorials stop teaching you anything. Pick the one that scares you slightly and give it a month.

Under 300 pages and it teaches you a language plus what memory actually is. Worth doing even if you will never write C professionally, because pointers, the stack and manual allocation stop being scary words once you have used them. The clearest technical writing on this list.

A book about how to think about computation rather than how to use a language. It will change how you see abstraction, and it will be hard, and those two facts are related. Free online. Best done slowly with the exercises, alongside a real job rather than instead of one.

The reference, not the tutorial. Rigorous, mathematical, and the place to go when you need an algorithm's proof rather than its shape. Own it, look things up in it, and do not try to read it front to back unless you are taking a course alongside.

The book that gave the industry a shared vocabulary for structures we were all inventing separately. Some patterns have aged into language features and some are overused, but knowing the names still makes design conversations shorter. Read it to understand the trade off each pattern is making, not to apply them all.

A thick, thorough handbook on the act of writing code: variables, control flow, defensive programming, how to structure a routine. Not a book to read cover to cover. Keep it nearby and read the chapter that matches whatever you are currently doing badly.

Almost every job you take will hand you a large codebase with no tests and a deadline. This book is about that exact situation: how to get a seam into untested code so you can put a test around it before you change anything. Nothing else covers this ground as well, and you will use it in your first month somewhere new.

Opinionated, sometimes dated, and still the fastest way for a junior engineer to start noticing why some code is painful to change. Take the naming, function size and comment chapters seriously; treat the rest as one experienced person's preferences rather than law. Argued about more than almost any book on this list, which is itself a reason to have read it.

A catalogue of small, safe, named moves for changing code without changing what it does. The value is not the list, it is the habit it builds: you stop rewriting things in one heroic go and start improving them in steps small enough that you never lose a working state. Read the first three chapters even if you never touch the catalogue.

The tooling nobody teaches and everybody is assumed to know: the shell, scripting, editors, version control internals, debugging and profiling. A dozen hours that pay back every week for the rest of your career.

Harvard's introductory course, free, running from C and memory through data structures, algorithms, Python, SQL and web development. Still the best first computer science course available anywhere at any price.

A short, opinionated guide naming the nine subjects that matter and exactly one book and one course for each. Its value is in everything it leaves out.

A complete undergraduate computer science curriculum assembled entirely from free online courses, sequenced with prerequisites and maintained by a community. A degree's worth of material at no cost, minus the accountability.

The official Git book, free in full, covering everyday use and then the internals that explain why Git behaves the way it does. Read chapter ten and Git stops being frightening.

An interactive tutorial that draws the commit graph as you run commands, so you can watch what rebase, merge and cherry pick actually do. The fastest way to build a mental model of Git.

A short page of Git recovery recipes organised by the mistake you just made rather than by the command you need. Bookmark it before you need it, because you will need it.

A book about the craft rather than any language, covering pragmatism about tools, orthogonality, automation, testing and the professional habits that separate a good engineer from a productive one. Updated for its twentieth anniversary and still relevant.