Ruby articles

Many of the concepts you're already familiar with as a web developer are applicable in Go. In this article, Ayooluwa Isaiah shows us how middleware, templating, and other aspects of the go language work together to create a coherent web-development experience.

You'll probably never implement sorting from scratch. But sorting algorithms are foundational in computer science and have become a standard feature of the ritual hazing...er...interview process for developers at all levels. In this article, Julie Kent introduces us to the merge sort algorithm. She'll show us how it works, implement it in ruby, and discuss its performance characteristics.

Understanding parsers is like seeing the matrix. You start to understand the tree-like structure of your code. You begin to realize that so many language features are just syntactic sugar concealing a simple core. In this article, Alex Braha Stoll will guide us through the world of parsers. He'll explain basic concepts, then use Ruby to implement a simple parser for his toy language, Stoffle.

If you've ever built a UI in Rails, you've probably noticed that views tend to get slower over time. That's because adding features to a UI often means adding DB queries to the view. They add up. Fortunately, Rails provides us with an easy-to-apply band-aid in the form of view caching. In this article, Jonathan Miles introduces us to view caching, discusses when it's appropriate to use, and covers common pitfalls to watch out for.

You're doing some currency calculations in your app. It seems to be working well. But after a while, strange discrepancies emerge. The books stop balancing. People get mad. All because the code treated currency like any other number. In this article, Julio Sampaio shows us which of Ruby's number classes are unsuitable for currency, and walks us through better options.

Sometimes when your app is slow, it's not your fault. Your code might be optimized to the teeth, but it won't matter if it has to perform intrinsically slow tasks, like fetching data from an external API. In these situations, Rails' low-level caching can be a life-saver. But caching is infamously tricky. It's dangerous to go alone. In this article, Jonathan Miles guides us through the landscape of low-level caching. He covers the basics, but more importantly, digs into essential details of cache invalidation and points out common pitfalls.

If I asked you to sit down right now and sort a list of numbers, there's a good chance that you'd intuitively rediscover the selection sort algorithm. It's a simple approach that can have significant performance implications. That's why it shows up so frequently in technical interviews - even though most developers never implement sorting from scratch. In this article, Julie Kent walks us through the selection sort algorithm, builds a working implementation in Ruby, and discusses its performance characteristics.

Few things are scarier than a database slowly losing integrity over weeks or years. For a while, nobody notices anything. Then users start reporting bugs, yet you can't find any code that's broken. By the time you realize the problem, it may be happening for so long that your backups are unusable. We can avoid problems like these with skillful use of transactions. In this article, Kingsley Silas introduces us to transactions at the database level, discusses when they should be considered, and shows us how to use them in Rails.

Let me know if this feels familiar. Your users want to "login with GitHub," so you install a gem, follow the setup instructions, then pray it never needs maintenance because you have no real idea how OAuth2 works. Let's fix that. In this article, Diogo Souza shows us the fundamental concepts behind OAuth2 and how to implement them using Devise and Doorkeeper.

Few things are more frustrating than slow, flaky test suites. You're ready to deploy, wait 20 minutes for CI to run, only to find that a test failure in code you've never touched is blocking you. You dig into the source and find the problem: an external API call. It works (slowly) most of the time. But sometimes the network glitches and it fails. What do you do? In this article, José Manuel shows us several techniques for removing external API dependencies from our tests.

Lexers are magical. They take your messy, hand-typed, human text, and convert it into a clean data structure that the computer can process. Every time you run a ruby program, use structured search or type in a date by hand, you'll find a lexer hard at work. In this article, Alex Braha Stoll pulls back the curtain to show us how lexers work and how to implement one for a simple programming language.

You'll probably never need to implement bubble sort from scratch. Just call Array#sort! But sorting algorithms are a popular interview topic for a reason. They ask a bigger question: "Sure, you know what your code does, but do you know how it works? Do you understand the subtle ways that choices you make can impact performance?" In this article, Julie Kent will walk us through the famous Bubble Sort algorithm, demonstrating how it works, how to implement it in Ruby, and how to predict its performance.

Text encoding is fundamental to programming. Web sites, user data, and even the code we write are all text. When encoding breaks, it can feel like the floor is falling out from under you. You're cast into a dimension of bitmasks and codepoints. Logs and backtraces are useless. You consider trading your text editor for a hex editor. But there's hope! In this article, Jose Manuél will show us how encoding errors happen, how they're expressed in Ruby, and how to troubleshoot them. So the next time one of these errors lands on your desk, you'll be in a better position to handle it.

Developers make fun of legacy systems because we're scared of them. We're afraid that the tiniest change will cause the app to break in unexpected ways. We're afraid we won't realize it until a customer complains. One way to combat this fear is through testing. In this article, José Manuel shows us how to retrofit legacy systems with acceptance test suites so we can maintain them with less fear and more confidence.

Whoever first said that "the fastest code is no code" must have really liked memoization. After all, memoization speeds up your application by running less code. In this article, Jonathan Miles introduces us to memoization. We'll learn when to use it, how to implement it in Ruby, and how to avoid common pitfalls. Buckle up!

Building a neural network isn't exactly like building a human brain, but it's the closest any of us are going to get. In this article Julie Kent introduces us to neural nets as a concept and shows us how to implement a simple one in Ruby.

Few projects are as enticing or as rewarding as creating your own programming language. It's impractical, sure. But as an exercise, it strengthens muscles that most of us don't get to use very often and makes us better all-around developers. In this article — the first in a series — Alex Braha Stoll shows us how to get started building our own toy language and interpreter from scratch using Ruby.

We've all been there. You're clicking around your Rails application, and it just isn't as snappy as it used to be. You start searching for a quick-fix and find a lot of talk about caching. Take your existing app, add some caching, and voila, a performance boost with minimal code changes. However, it's not this simple. Like most quick fixes, caching can have long-term costs. In this article, Jonathan Miles discusses what caching is and what can go wrong, as well as explains non-caching strategies you can use to speed up your Rails app.

The world is full of linear relationships. When one apple costs $1 and two apples cost $2, it's easy to figure out the price of any number of apples. But what happens when you have 100s of data points? What if your data source is noisy? That's when it's helpful to use a technique called linear regression. In this article Julie Kent shows us how linear regression works, and walks through a practical example in Ruby.

When you deploy a new Rails app, you typically face a double-bind. If you use an easy platform like Heroku, you could create problems for yourself as your application scales. If you use a more fully-featured platform, you risk wasting time on ops that could be spent on your product. What if you could have both: an easy deployment option that is easy to scale? In this article, Amos Omondi argues that AWS Elastic Beanstalk gives us both, then he shows us everything we need to know to get a Rails 6 app up and running on EB.