In this post, we'll use two of Elixir's most powerful features - pattern matching and recursion - to sanitize a string by removing invalid Unicode "Specials" characters. Let's dive straight in!
The need to manipulate strings comes up quite often, whether it's to validate user-provided values or transform text into structured data that can be used programmatically. Most often, we'll reach for regular expressions to accomplish this task, but sometimes there's a better solution to the problem: parser combinators. In this two-part article, we'll explore how they work. Before moving on, let's define what 'parsing' is: Source: Wikipedia.
Phoenix LiveView 0.18 just shipped, with lots of new goodies to make developing LiveView an even better experience. In this post, I'll take you through a lesser-known new feature - LiveView's new special HTML attributes - and show you how to write cleaner HTML with :if, :for, and :let. When we're done, you'll have an eloquent, ergonomic, and dynamic function component you can use to render a list anywhere in your LiveView app. Let's dive in!
The XML data format has been around since 1996. It was first envisioned as a lingua franca (bridging language) for data to be serialized and read into completely disparate systems (with different programming languages, operating systems, and even hardware). It has been wildly successful in that goal. In software, though, 26 years is like a lifetime — and in hardware, it's an eternity.
Elixir v1.14 shipped earlier this month with a bunch of new goodies. In this post, we'll explore Elixir's new PartitionSupervisor. We'll take a look at some code that suffers from the exact bottleneck issue that partitions supervisors are designed to solve. Then, we'll fix that bottleneck. Along the way, you'll learn how partition supervisors work under the hood to prevent process bottlenecks. Let's get started!
The latest Elixir release introduces new features to improve your developer and debugging experience. In this post, we'll take a look at the new dbg() functionality, along with some improvements to Inspect and binary evaluation error messaging. All these changes come together to make you an even more productive Elixirist. Let's get started!
At some point, every software engineer will find themselves in a situation where they need to benchmark system performance and test the limits of what a given system can handle. This is a common problem in software engineering, and even more so in the applications that are well suited for Elixir. Finding bottlenecks early on in an application can save a lot of time, money, and effort in the long run, and give developers confidence in the upper limit of a system.
In the first part of this series on maintainable Elixir code, we started by applying rules for code predictability in our code design. We immediately saw an emerging pattern: a series of transformations on state. In this part, we'll explore this pattern further. We'll first learn how to write expressions as reducers. Then we'll use metaprogramming to make use of reducers and enforce code style seamlessly. Finishing up, we'll see an example where all the pieces fit together. Let's get going!
While Elixir is frequently associated with web development, this is not where its capabilities end. As a general-purpose language, it can be used for virtually anything. You don't have to take my word for it — projects such as Nerves, Nx, Scenic, or LiveBook speak for themselves. But today, we will focus on something different: writing a command-line application in Elixir and preparing it for distribution.
There’s a function called Enum.map in Elixir that works on multiple collection types, but it's not without its issues. In this post, I will introduce you to a concept from functional programming called a functor. We’ll make a Functor protocol with a function called fmap that will aspire to be a better version of Enum.map. Note: The article is inspired by the Witchcraft library, which we covered in one of our previous posts. But first: what's the problem with Enum.map exactly?
