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r/learnprogramming · 2019

Most-mentioned books in r/learnprogramming during 2019

This page ranks books by exact tracked mentions in r/learnprogramming within the published source unit for 2019. Counts come from the reconciled subreddit-by-month matrix; a source unit may be a bounded sample.

41
Books ranked
209
Tracked mentions in 2019
Cover of Clean Code #1

Clean Code

Robert C. Martin

The book 536 Reddit threads cite when arguing about naming variables — revered by beginners, argued over by seniors.

19 in 2019
Cover of Introduction to Algorithms #2

Introduction to Algorithms

Thomas H. Cormen

The textbook four MIT professors wrote to settle every algorithms argument, cited by 254 Reddit commenters across 12 subreddits and still going.

17 in 2019
Cover of Cracking the Coding Interview #3

Cracking the Coding Interview

Gayle Laakmann McDowell

The book that turned software hiring into a sport — written by the ex-Googler who introduced programming challenges to the process in the first place.

14 in 2019
Cover of Structure and Interpretation of Computer Programs #4

Structure and Interpretation of Computer Programs

Harold Abelson

MIT's 1985 Scheme textbook that 319 Reddit commenters have recommended and a noticeably smaller number have finished.

13 in 2019
Cover of The Pragmatic Programmer #5

The Pragmatic Programmer

Andy Hunt

Two veterans hand you a checklist for the craft: don't write code you don't need, own your tools, and fix the broken window before someone else does.

12 in 2019
Cover of Think Like a Programmer #6

Think Like a Programmer

V. Anton Spraul

V. Anton Spraul's guide to breaking down any programming problem before writing a single line of code — written for learners who know syntax but freeze at blank pages.

12 in 2019
Cover of You Don't Know JS #7

You Don't Know JS

Kyle Simpson

Kyle Simpson's free GitHub series that bootcamp grads keep crediting when they finally understand closures, this, and coercion.

9 in 2019
Cover of Code: The Hidden Language of Computer Hardware and Software #8

Code: The Hidden Language of Computer Hardware and Software

Charles Petzold

A retired software engineer builds a computer from telegraph relays and flashlights, one chapter at a time, until you understand what a CPU actually does.

8 in 2019
Cover of Python Crash Course #9

Python Crash Course

Eric Matthes

The author built it for high school students who kept getting lost — 126 Reddit mentions later, it's still the default first Python recommendation.

8 in 2019
Cover of C++ Primer #10

C++ Primer

Stanley B. Lippman

The 1,000-page C++ textbook that r/learnprogramming recommends by name whenever someone asks how to learn the language seriously.

7 in 2019
Cover of Code Complete #11

Code Complete

Steve McConnell

Steve McConnell's 900-page construction manual for software, ranked third on Reddit's canonical reading list and still cited 25 years after publication.

7 in 2019
Cover of Design Patterns #12

Design Patterns

Erich Gamma

The 1994 Gang of Four catalog that named 23 object-oriented patterns, gave developers a shared vocabulary, and taught a generation to over-apply both.

7 in 2019
Cover of Eloquent JavaScript #13

Eloquent JavaScript

Marijn Haverbeke

Marijn Haverbeke's free online JavaScript book — variables to async in one volume — by someone who said he wouldn't wish a game-programming career on anyone.

7 in 2019
Cover of C# in a Nutshell #14

C# in a Nutshell

Joseph Albahari

The O'Reilly reference that r/learnprogramming drops into C#/Unity starter lists alongside free ebooks and YouTube playlists.

6 in 2019
Cover of Clean Architecture #15

Clean Architecture

Robert C. Martin

Uncle Bob's case for building software that survives its own success, bundled with opinions that provoke more argument than the architecture does.

6 in 2019
Cover of The C Programming Language #16

The C Programming Language

Brian W. Kernighan

The 1978 book that defined C's syntax, co-written by its creator, still cited by name 281 times across Reddit in 7 years.

6 in 2019
Cover of Grokking Algorithms #17

Grokking Algorithms

Aditya Y. Bhargava

A Python-illustrated tour of data structures and algorithms that r/learnprogramming treats as the first step before Leetcode, not a replacement for it.

5 in 2019
Cover of Designing Data-Intensive Applications #18

Designing Data-Intensive Applications

Martin Kleppmann

A backend engineer's field guide to the tradeoffs behind every database, queue, and distributed system you will ever touch.

4 in 2019
Cover of Effective Java #19

Effective Java

Joshua Bloch

Joshua Bloch's item-by-item case for writing Java the way the platform was designed to be used, with 90 independent recommendations that aged better than most of the language.

4 in 2019
Cover of The C++ Programming Language #20

The C++ Programming Language

Bjarne Stroustrup

Bjarne Stroustrup's own manual for the language he built — 1,300 pages that explain every design decision, including the ones you're cursing right now.

4 in 2019
Cover of The Mythical Man-Month #21

The Mythical Man-Month

Frederick P. Brooks Jr.

Fred Brooks spent the 1960s building IBM's OS/360 and wrote down everything that went wrong — in 1975, and it still lands.

4 in 2019
Cover of A Mind for Numbers: How to Excel at Math and Science #22

A Mind for Numbers: How to Excel at Math and Science

Barbara Oakley

A failed math student becomes an engineering professor, then writes the manual on how the brain actually acquires hard skills.

3 in 2019
Cover of Fluent Python #23

Fluent Python

Luciano Ramalho

The Python book r/Python recommends when you're done with the tutorials and need to know what the language actually does.

3 in 2019
Cover of The Clean Coder #24

The Clean Coder

Robert C. Martin

Uncle Bob's professionalism manual: say no to bad estimates, refuse death marches, and work the 40 hours then study on your own time.

3 in 2019
Cover of Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow #25

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

Aurélien Géron

Aurélien Géron's end-to-end ML textbook: build a working neural net with Scikit-Learn, Keras, and TensorFlow before you finish the first half.

2 in 2019