The goal of this page is to make you a more proficient developer. You'll find only resources that I've found truly inspiring, or that have been become timeless classics.
Master](http://www.amazon.com/The-Pragmatic-Programmer-Journeyman-Master/dp/020161622X) 📖: hands-on the most inspiring and useful book I've read about programming.
Construction](http://www.amazon.com/Code-Complete-Practical-Handbook-Construction/dp/0735619670) 📖: a nice addition to The Pragmatic Programmer, gives you the necessary framework to talk about code.
* [Release It!](https://smile.amazon.com/Release-Design-Deploy-Production-Ready-Software/dp/1680502395) 📖: this books goes beyond code and gives you best practices for building production-ready software. It will give you about 3 years worth of real-world experience.
* [The Linux Programming Interface: A Linux and UNIX System Programming Handbook](http://www.amazon.com/The-Linux-Programming-Interface-Handbook/dp/1593272200) 📖: outside of teaching you almost everything you need to know about Linux, this book will give you insights into how software evolves, and the value of having simple & elegant interfaces.
* [Professional software development](http://mixmastamyk.bitbucket.io/pro_soft_dev/) 📖: pretty complete and a good companion to this page. The free chapters are mostly focused on software development processes: design, testing, code writing, etc. - and not so much about tech itself.
* [Practical Advice for New Software Engineers](http://product.hubspot.com/blog/practical-advice-for-new-software-engineers)
* [On Being A Senior Engineer](http://www.kitchensoap.com/2012/10/25/on-being-a-senior-engineer/)
* [Lessons Learned in Software Development](http://henrikwarne.com/2015/04/16/lessons-learned-in-software-development/): one of those articles that give you years of hard-earned lessons, all in one short article. Must read.
* [The Imposter's Handbook](https://bigmachine.io/products/the-imposters-handbook) - $30. From the author: "Don't have a CS Degree? Neither do I - That's why I wrote this book."
* [mr-mig/every-programmer-should-know: a collection of (mostly) technical things every software developer should know](https://github.com/mr-mig/every-programmer-should-know)
* Read the [CLRS](https://mitpress.mit.edu/books/introduction-algorithms). You can watch and download the course on [OCW](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-introduction-to-algorithms-sma-5503-fall-2005/) - there are newer courses as well.
* Or [The Algorithm Design Manual](https://www.amazon.com/Algorithm-Design-Manual-Steven-Skiena/dp/1849967202?ie=UTF8&qid=1297127794&ref_=sr_1_1&sr=8-1)
* Try out some algorithms on [Project Euler](https://projecteuler.net/)
Let's be honest: algo can be a pretty dry topic. [This quora question](https://www.quora.com/Is-there-a-book-that-teaches-algorithms-data-structures-and-other-computer-science-basics-in-a-fun-way) lists some funnier learning alternative, including:
Biases don't only apply to hiring. For instance, the fundamental attribution bias also applies when criticizing somebody's code written a long time ago, in a totally different context.
* [The Conjoined Triangles of Senior-Level Development](http://frontside.io/blog/2016/07/07/the-conjoined-triangles-of-senior-level-development.html) looks into how to define a senior engineer.
* [The Absolute Minimum Every Software Developer Absolutely, Positively Must Know About Unicode and Character Sets (No Excuses!)](http://www.joelonsoftware.com/articles/Unicode.html)
* [Write code that is easy to delete, not easy to extend](http://programmingisterrible.com/post/139222674273/write-code-that-is-easy-to-delete-not-easy-to)
* [Lessons learned writing highly available code](https://medium.com/imgur-engineering/lessons-learned-writing-highly-available-code-7eaf3d7aae00#.u7c4j6hac)
* [The Ten Commandments of Egoless Programming](http://blog.codinghorror.com/the-ten-commandments-of-egoless-programming/)
* [Clean Code: A Handbook of Agile Software Craftsmanship](https://www.goodreads.com/book/show/3735293-clean-code) 📖, Robert C. Martin. Describes numerous useful best practices. A bit long. There's also a [clean code cheatsheet](cheatsheets/Clean-Code-V2.4.pdf).
* [NoSQL Databases: a Survey and Decision Guidance](https://medium.baqend.com/nosql-databases-a-survey-and-decision-guidance-ea7823a822d#.9fe79qr90)
* [Safe Operations For High Volume PostgreSQL](https://www.braintreepayments.com/blog/safe-operations-for-high-volume-postgresql/) (this is for PostgreSQL but works great for other db as well).
* [Zero downtime database migrations](https://blog.rainforestqa.com/2014-06-27-zero-downtime-database-migrations/) (code examples are using Rails but this works great for any programming language)
* [The Infinite Hows](http://www.kitchensoap.com/2014/11/14/the-infinite-hows-or-the-dangers-of-the-five-whys/): this provides a strong criticism of the five whys method.
* [Linux Performance Analysis in 60,000 Milliseconds](http://techblog.netflix.com/2015/11/linux-performance-analysis-in-60s.html)
I highly recommend reading [The Non-Designer's Design Book](http://www.amazon.com/gp/product/0133966151/ref=pd_lpo_sbs_dp_ss_1?pf_rd_p=1944687602&pf_rd_s=lpo-top-stripe-1&pf_rd_t=201&pf_rd_i=0321534042&pf_rd_m=ATVPDKIKX0DER&pf_rd_r=1R7MVQP0BCP7GP9VZGYX). This is a pretty short book that will give you some very actionable design advices.
* If you're working on data, Edward Tufte's [The Visual Display of Quantitative Information](http://www.amazon.com/Visual-Display-Quantitative-Information/dp/0961392142/ref=sr_1_1?ie=UTF8&qid=1458046603&sr=8-1&keywords=tufte) is considered a classic.
* The [Universal Principles of Design](http://www.amazon.com/Universal-Principles-Design-Revised-Updated/dp/1592535879/ref=sr_1_1?ie=UTF8&qid=1458046663&sr=8-1&keywords=universal+principles+of+design) will give you enough vocabulary and concepts to describe design challenges into words.
* [Microsoft's Rest API guidelines](https://github.com/Microsoft/api-guidelines/blob/master/Guidelines.md)
* [Design Patterns: Elements of Reusable Object-Oriented Software](http://www.amazon.com/dp/0201633612/): dubbed "the gang of four", this is almost a required reading for any developer. A lot of those are a bit overkill for Python (because everything is an object, and dynamic typing), but the main idea (composition is better than inheritance) definitely is a good philosophy.
* [Patterns of Enterprise Application Architecture](http://www.amazon.com/dp/0321127420/?tag=stackoverfl08-20): learn about how database are used in real world applications. Mike Bayer's SQLAlchemy has been heavily influenced by this book.
* [Domain-Driven Design: Tackling Complexity in the Heart of Software](https://www.amazon.com/Domain-Driven-Design-Tackling-Complexity-Software/dp/0321125215) 📖, Eric Evans
* [Clean Architecture](https://www.goodreads.com/book/show/18043011-clean-architecture) 📖, Robert C. Martin. Uncle Bob proposes an architecture that leverages the Single Responsibility Principle to its fullest. A great way to start a new codebase. Also checkout the [clean architecture cheatsheet](cheatsheets/Clean-Architecture-V1.0.pdf).
* [Python Design Patterns: For Sleek And Fashionable Code](https://www.toptal.com/python/python-design-patterns): a pretty simple introduction to common design patterns (Facade, Adapter, Decorator). A more complete list of design patterns implementation in Python on [Github](https://github.com/faif/python-patterns). [Also a book here](http://python-3-patterns-idioms-test.readthedocs.io/en/latest/PatternConcept.html).
* SourceMaking's [Design Patterns](https://sourcemaking.com/design_patterns) seems to be a good web resource too.
* O'Reilly's [How to make mistakes in Python](http://www.oreilly.com/programming/free/files/how-to-make-mistakes-in-python.pdf)
* [Education of a Programmer](https://hackernoon.com/education-of-a-programmer-aaecf2d35312): a developer's thoughts after 35 years in the industry. There's a particularly good section about design & complexity (see "the end to end argument", "layering and componentization").
* Google's [API Design Guide](https://cloud.google.com/apis/design/): a general guide to design networked API.
* [Inheritance vs. composition](http://learnpythonthehardway.org/book/ex44.html): a concrete example in Python. [Another slightly longer one here](http://python-textbok.readthedocs.io/en/latest/Object_Oriented_Programming.html). [One last one, in Python 3](http://blog.thedigitalcatonline.com/blog/2014/08/20/python-3-oop-part-3-delegation-composition-and-inheritance/#.V7SZ4tB96Rs).
* [Composition Instead Of Inheritance](http://c2.com/cgi/wiki?CompositionInsteadOfInheritance)
* [Complexity and Strategy](https://hackernoon.com/complexity-and-strategy-325cd7f59a92): interesting perspective on complexity and flexibility with really good examples (e.g. Google Apps Suite vs. Microsoft Office).
* [Simple Made Easy](https://www.infoq.com/presentations/Simple-Made-Easy) 🎞, Rich Hickey. This is an incredibly inspiring talk redefining simplicity, ease and complexity, and showing that solutions that look easy may actually harm your design.
* [Writing automated tests for your documentation](https://krausefx.com/blog/writing-automated-tests-for-your-documentation): this should be required, IMO. Testing code samples in your documentation ensures they never get outdated.
* [Setting Up a Mac Dev Machine From Zero to Hero With Dotfiles](http://code.tutsplus.com/tutorials/setting-up-a-mac-dev-machine-from-zero-to-hero-with-dotfiles--net-35449)
* Bram Moolenaar (Vim author), [Seven habits of effective text editing](http://www.moolenaar.net/habits.html) ([presentation](http://www.moolenaar.net/habits_2007.pdf)). This is about Vim but it contains good lessons about why investing time in learning how to be productive with your text editors pays off.
* [VScode](https://code.visualstudio.com/) is one of the most popular text editors as of writing. [Visual Studio Code Can Do That?](https://www.smashingmagazine.com/2018/01/visual-studio-code/), Smashing Magazine.
* A great example of [notes taken during outage](https://docs.google.com/document/d/1GCK53YDcBWQveod9kfzW-VCxIABGiryG7_z_6jHdVik/pub) and [postmortem from Gitlab (01/31/2017)](https://about.gitlab.com/2017/02/01/gitlab-dot-com-database-incident/). This one's a tricky one because an engineer's action caused the irremediable loss of 6 hours of data.
Note: this is about you as an interviewee, **not** as an interviewer. To check out my list of resources for interviewers, go to my [engineering-management repository](https://github.com/charlax/engineering-management#hiring-interviews).
* [I spent 3 months applying to jobs after a coding bootcamp. Here’s what I learned.](https://medium.freecodecamp.com/5-key-learnings-from-the-post-bootcamp-job-search-9a07468d2331#.uq7vbbjfx)
* [How I Rewired My Brain to Become Fluent in Math](http://nautil.us/issue/40/learning/how-i-rewired-my-brain-to-become-fluent-in-math-rp): subtitled *the building blocks of understanding are memorization and repetition*.
* [One Sure-Fire Way to Improve Your Coding](https://changelog.com/posts/one-sure-fire-way-to-improve-your-coding): reading code!
* [Tips for learning programming](http://blog.hiphipjorge.com/tips-for-learning-programming/)
* [You can increase your intelligence: 5 ways to maximize your cognitive potential](https://blogs.scientificamerican.com/guest-blog/you-can-increase-your-intelligence-5-ways-to-maximize-your-cognitive-potential/): forgive the clickbait title, it’s actually a good article.
* JavaScript and may be one other interpreted language (Python, Ruby, etc.). Interpreted languages are useful for quick one-off automation scripts, and fastest to write for interviews.
* A compiled language (Java, C, C++...).
* A more recent language to see where the industry is going (as of writing, Go, Swift, Rust, Elixir...).
* A language that has first-class support for functional programming (Haskell, Scala, Clojure...).
* [Effective Programs - 10 Years of Clojure](https://www.youtube.com/watch?v=2V1FtfBDsLU) 🎞, Rich Hickey. The author of Clojure reflects on his programming experience and explains the rationale behind some of Clojure's key design decisions.
JavaScript is such a pervasive language that it's almost required learning.
* [mbeaudru/modern-js-cheatsheet](https://github.com/mbeaudru/modern-js-cheatsheet): cheatsheet for the JavaScript knowledge you will frequently encounter in modern projects.
* [10 modern software over-engineering mistakes](https://medium.com/@rdsubhas/10-modern-software-engineering-mistakes-bc67fbef4fc8#.da6dvzyne)
* [A good example of over-engineering: the Juicero press](https://blog.bolt.io/heres-why-juicero-s-press-is-so-expensive-6add74594e50) (April 2017)
> “A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched up to make it work. You have to start over, beginning with a working simple system.”
* [Papers we love](https://github.com/papers-we-love/papers-we-love): papers from the computer science community to read and discuss. Can be a good source of inspiration of solving your design problems.
* [My First 10 Minutes On a Server - Primer for Securing Ubuntu](http://www.codelitt.com/blog/my-first-10-minutes-on-a-server-primer-for-securing-ubuntu/)
* [Reckon you've seen some stupid security things?](https://www.troyhunt.com/reckon-youve-seen-some-stupid-security-things-here-hold-my-beer/): everything *not* to do.
* [High Scalability](http://highscalability.com/): great blog about system architecture, its weekly review article are packed with numerous insights and interesting technology reviews. Checkout the [all-times favorites](http://highscalability.com/all-time-favorites/).
* [Deep Lessons From Google And EBay On Building Ecosystems Of Microservices](http://highscalability.com/blog/2015/12/1/deep-lessons-from-google-and-ebay-on-building-ecosystems-of.html)
* [Service oriented architecture: scaling the Uber engineering codebase as we grow](https://eng.uber.com/soa/)
* [The Log: What every software engineer should know about real-time data's unifying abstraction](https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying): one of those classical articles that everyone should read.
* I already mentioned the book Scalability rules above, but there's also a [presentation](http://www.slideshare.net/cyrilwang/scalability-rules) about it.
#### Stability
* I already mentioned the book Release it! above. There's also a [presentation](http://www.slideshare.net/justindorfman/stability-patterns-presentation) from the author.
* [The Walking Dead - A Survival Guide to Resilient Applications](https://speakerdeck.com/daschl/the-walking-dead-a-survival-guide-to-resilient-applications)
* [Defensive Programming & Resilient systems in Real World (TM)](https://speakerdeck.com/tuenti/defensive-programming-and-resilient-systems-in-real-world-tm)
* [Full Stack Fest: Architectural Patterns of Resilient Distributed Systems](https://speakerdeck.com/randommood/full-stack-fest-architectural-patterns-of-resilient-distributed-systems)
* [Graduating from Bootcamp and interested in becoming a Site Reliability Engineer?](https://medium.com/@tammybutow/graduating-from-bootcamp-and-interested-in-becoming-a-site-reliability-engineer-b69a38ce858b): a great collection of resources to learn about SRE.
* [Site Reliability Engineering](https://landing.google.com/sre/books/): written by members of Google's SRE team, with a comprehensive analysis of the entire software lifecycle - how to build, deploy, monitor, and maintain large scale systems.
* [Testing Strategies in a Microservices Architecture](http://martinfowler.com/articles/microservice-testing/) (Martin Fowler) is an awesome resources explaining how to test a service properly.
* [A Quick Puzzle to Test Your Problem Solving](http://www.nytimes.com/interactive/2015/07/03/upshot/a-quick-puzzle-to-test-your-problem-solving.html?_r=0)... and a great way to learn about confirmation bias and why you're mostly writing positive test cases.
* [The test pyramid](http://martinfowler.com/bliki/TestPyramid.html)
* [Move fast and don't break things](https://docs.google.com/presentation/d/15gNk21rjer3xo-b1ZqyQVGebOp_aPvHU3YH7YnOMxtE/edit#slide=id.g437663ce1_53_591) (presentation)
* [Eradicating Non-Determinism in Tests](http://www.martinfowler.com/articles/nonDeterminism.html), Martin Fowler
* [Your non-linear problem of 90% utilization](https://blog.asmartbear.com/utilization.html), Jason Cohen: why constantly running at 90% utilization is actually counter-productive.
* [Evidence-based advice on how to be successful in any jobs](https://80000hours.org/career-guide/how-to-be-successful/): most self-help advices are not research-based. The ones listed in this article are.
