Brave New Geek Introspections of a software engineer

tag

javascript

  1. #19 2 min

    Using Make with React and RequireJS

    RequireJS is a great library for building modular JavaScript clients that conform to the AMD API specification. It gives your JS an import-like mechanism by which you avoid global-namespace issues and makes your code behave more like a server-side language such as Python or Java. It also includes an optimization tool that can concatenate your JavaScript into a single file and minify it, which helps reduce HTTP overhead. I recently wrote about React, which is a library targeted at constructing UIs. React uses a special syntax called JSX for specifying DOM components in XML, and it compiles down to vanilla JavaScript. JSX can either be precompiled or compiled in the browser at runtime. The latter option has obvious performance implications and probably shouldn’t be used in production, but it works great for quickly hacking something together.

  2. #18 3 min

    Building User Interfaces with React

    If you follow me on Twitter, you’ve probably heard me raving about React. React is described as a “JavaScript library for building user interfaces” and was open sourced by Facebook about a year ago. Everybody and their mom has a JavaScript framework, so what makes React so interesting? Why would you use it over mainstays like Backbone or Angular? There are a few things that make React worth looking at. First, React is a library, not a framework. It makes no assumptions about your frontend stack, and it plays nicely with existing codebases, regardless of the tech you’re using. This is great because you can use React incrementally for new or legacy code. Write your whole UI with it or use it for a single feature. All you need is a DOM node to mount.

  3. #17 4 min

    Real-Time Client Notifications Using Redis and Socket.IO

    Backbone.js is great for building structured client-side applications. Its declarative event-handling makes it easy to listen for actions in the UI and keep your data model in sync, but what about changes that occur to your data model on the server? Coordinating user interfaces for data consistency isn’t a trivial problem. Take a simple example: users A and B are viewing the same data at the same time, while user A makes a change to that data. How do we propagate those changes to user B? Now, how do we do it at scale, say, several thousand concurrent users? What about external consumers of that data?