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Cake day: July 8th, 2023

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  • I don’t remember the presentation, but luckily I did remember the concept and here’s an article: https://netflixtechblog.com/reactive-programming-in-the-netflix-api-with-rxjava-7811c3a1496a

    It’s called “reactive” programming and that article goes over some of the basic premises. The context of the presentation was in front-end (web) code where it’s a god awful mess if you try to handle it in an imperative programming style. React = reactive programming. If you’ve ever wondered why React took off like it did, it’s because these concepts transformed the hellish nightmare landscape of jquery and cobbled together websites into something resembling manageable complexity (I’m ignoring a lot of stuff in between, the best parts of Angular were reactive too).

    Reactive programming is really a pipeline of your data. So the concepts are applicable to all sorts of development, from low level packet processing, to web application development on both the front and back end, to data processing, to anything else. You can use these patterns in any software, but unless your data is async it’s just “functional programming”.


  • Yep, that’s how I write my code too. I took a class in college, comparative programming languages, that really changed how I thought about programming. The first section of the class was Ruby, and the code most of us wrote was pretty standard imperative style code. If statements, loops, etc. Then we spent a month or so in Haskell, basically rewriting parts of the standard library by only using more basic functions. I found it insanely difficult to wrap my head around but eventually did it.

    Then we went back and wrote some more Ruby. A program that might have been 20-30 lines of imperative Ruby could often be expressed in 3 or 4 lines of functional style code. For me that was a huge eye opener and I’ve continued to apply functional style patterns regardless of the language I’m using (as long as it’s not out of style for the project, or makes anything less maintainable/reliable).

    Then one day a coworker showed us a presentation from Netflix (presentation was done by Netflix software engineers, not related to the service) and how to think about event handlers differently. Instead of thinking of them as “events”, think about them as async streams of data - basically just a list you’re iterating over (except asynchronously). That blew my mind at the time, because it allows you to unify both synchronous and asynchronous programming paradigms and reuse the same primitives (map/filter/reduce) and patterns in both.

    This is far beyond just eliminating if statements, but it turns out if you can reduce your code to a series of map/filter/reduce, you’re in an insanely good spot for any refactoring, reusing functionality, easily supporting new use cases, flexibility, etc. The downside would be more junior devs almost never think this way (so tough for them to work on), and it can get really messy and too abstract on large projects. You can’t take these things too far and need to stay practical, but those concepts really changed how I looked at programming in a major way.

    It went from “a program is a step by step machine for performing many types of actions” to “a program is a pipeline for processing lists of data”. A step by step machine is complex and can easily break down, esp when you start changing things. Pipelines are simple + reliable, and as long as you connect them up properly the data will flow where it needs to flow. It’s easy to add new parts without impacting and existing code. And any data is a list, even if it’s a list of a single element.


  • Personally I try to keep my code as free of branches as possible for simplicity reasons. Branch-free code is often easier to understand and easier to predict for a human. If your program is a giant block of if statements it’s going to be harder to make changes easily and reliably. And you’re likely leaving useful reusable functionality gunked up and spread out throughout your application.

    Every piece of software actually is a data processing pipeline. You take some input, do some processing of some sort, then output something, usually along with some side effects (network requests, writing files, etc). Thinking about your software in this way can help you design better software. I rarely write code that needs to process large amounts of data, but pretty much any code can benefit from intentional simplicity and design.