Performance optimizations WITHOUT Reagent – part 3 (and probably final)

This is probably the last post about these improvements. At the last post, I showed how I threw every performance optimization I tried away (combine-leafs, other stuff, etc) just to throw it all away because React didn’t like what I did.

So, after a lot of time, I decided to do the horrible, insane thing that I did a lot more than I wanted – rewrite the rendering process of Chlorine to not use Reagent. The reason was actually quite simple: I wanted things to be simpler to implement, and honestly, Reagent was getting in my way. Like, A LOT.

Before I continue explaining the performance improvements that I am doing, I have to say something – in the first version of the rendering code (the one that I was trying to optimize at my last posts) I had a huge beginner’s luck – the actual rendering time is amazing for most cases, and while it is slow for some very specific situations, it’s actually not that bad; but there were also some weird trade-offs that I had to do and I cannot use them anymore.

The reason being, Chlorine started to become very strong in the customization code and “interactive renderers”. If you’re not aware, you can configure Chlorine to add custom commands and other amazing stuff, just by opening up a config file, writing some ClojureScript code, and you’re good to go. Unfortunately, also at the first versions of Chlorine, sometimes you would evaluate a code – let’s say a list of a thousand elements – and you get back only 10 or 20 elements. Worse yet, you would not get back a “List”, but an object called an “Incomplete List”. Which was not ideal, and basically made the whole “customize your editor” difficult to say the least.
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Porting Clojure libraries to Ruby – Part 2

Last post I gave an introduction on how I’m working with GraalVM to port Clojure things to Ruby. Now, it’s time to handle the hard parts.

The first thing is – some stuff simply doesn’t work. Pathom3 (the library I wanted to port) depends on Guardrails, which requires core.async, which starts a thread pool, which GraalVM doesn’t like. At all.

And the second things is how to serialize some weird stuff like callbacks. So let’s start with the first part – how to make a “Pathom3 shared library” without GraalVM screaming at us
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Porting Clojure libraries to Ruby

Since I started working with Ruby, in some situations I miss some of the Clojure libraries – especially killer ones like Pathom.

Unfortunately, rewriting the whole library in a different language is completely out of the question, especially because I will reintroduce some of the bugs that are already fixed, and will not have some of the more important features like parallel processing and other stuff.

But it’s not an “end of the world” situation. GraalVM have a very important feature that is to compile Java code to native, using what it’s usually called the “native-image” or, to be more precise, SubtrateVM. I also knew that you could generate shared libraries with this approach, but I never actually did anything and in my last attempts – every time I tried the only result I had was lots of frustrations and weird errors.

So that’s why I’m very proud and very surprised to announce that I have a Pathom working in Ruby right now.

But more on that later – it’s probably not yet ready to be used in production; but what I want to share is how I actually made it work, then challenges I faced (and how to handle them) and how can other people do the same. Finally, I am writing this post to make it easy for other people to do the same – honestly, the whole thing was awfully hard but not because it’s actually hard – but because the documentation is lacking so much that, at some times, I even though things I did were not possible.
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Clojure, and Ruby

I’m gonna make a bold claim here. As a language, Clojure is much better than Ruby. But, as a means of working together with other people, Ruby can be better, and Clojure can be a nightmare.

Here’s the problem with this debate: in Ruby it’s easier to actually bootstrap something because of the Rails framework. Clojure doesn’t have anything like that, but the code tends to get less worse as time goes by – as a functional language where everything is immutable by default, there’s less “surface” that’s touched by a piece of code. For example, suppose you have a function – in Clojure, changing that function only affects callers of that function, whereas in a mutable language, the function can mutate an object/value and now everywhere that uses that same object can be affected.

Another reason, that might be counter-intuitive is because of the real framework itself. When an application grows, you might find that you need less constraints and more freedom to do stuff that was not defined originally. Unfortunately, if you are using Rails (or any other framework), this means that you have to find ways around the framework, because it’s a kind of an “all or nothing” – it’s not that easy to basically do something outside of it and then bring that into your workflow, into your web servers and things like that (for example, I once had to integrate a SQS message queue on Rails, to listen to some message and deliver a notification via websocket. It was such a bad experience that we did a Node.JS app that did just that).
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A new Chlorine is almost done!

For the last few months, I’ve been working on a new version of Chlorine (now that Pulsar is on a good track). Here I want to share what to expect of this new version.

For a quick TL;DR; it’ll have better ClojureScript (shadow-cljs) support, fix some bugs related to evaluating code and the REPL being “locked” without returning the results or evaluating new commands, and have better configurable parameters. Things will probably break a little bit – it’s not a non-breaking-change, unfortunately – but hopefully it’s good enough that people will want to migrate to the new version.
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Clojure does NOT need a “definite web framework”

Few times I feel inclined to answer for a post. There are actually lots of posts that say that Clojure needs “the web framework” like Rails or Django or Phoenix so it’ll be better. Sometimes these ideas have value, sometimes don’t, and sometimes they are simply nonsense at all.

I recently was shown a post that was basically nonsense, and to keep things neutral, I’m not going to link it here. I want to expose why I think these ideas are nonsense, and how a person that’s new to Clojure could think about this lack of frameworks, how to handle this situation, and what to expect from the language.

So, first things first: Clojure is made to be a hosted language. Which means it expects you to use Java libraries, or Javascript ones, if you’re in ClojureScript. Sure, in Javascript things are more difficult mostly because of the weird ecosystem that expects everything to be transpiled first, but most of the time you can use interop just fine.

All this to say: you don’t need to wrap libraries. Most people I know, me included, said sometime that Clojure needs more libraries that wrap over other other things, and while I still would love to just stay on “Clojure-land” most of the time, it’s better to have a stable Java library that we can use over Clojure than an old, unstable, and severely lacking behind features that wrap the Java one to have a “Clojure feel”. Most of the time, you can have a “Clojure feel” with few lines of code anyway.
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ClojureScript vs Core.Async debate – the last updates.

So, my old post made to Reddit, and as I expected, lots of people complained about my conclusion. I still find damaging that Clojure community have this huge energy on defending “core” solutions, even when they are low-level, impractical, or (in this case) does not work well, if it works at all. But, well, I decided to clarify some of the posts, and answer some of the comments that people told me would, supposedly, “solve” the problem. I already answered these questions on other forums, so I’ll try to re-use some of my comments:

Interop with <p!

Some people asked about interop with <p!. Honestly, when I made the article, this option did not exist. Even then, a Promise can be rejected and resolved with arbitrary data, so to translate this code to ClojureScript means capturing the original result of <p!, check if it’s an ExceptionInfo, with the right type, and extract the right part. It’s also harder to compose IMHO (like, with Promises, you can chain actions, then if any of them fail, you can catch the error and the promise is back to the “success” phase). But at least, now it’s less complicated – although I would say, if you’re going to add a library to your project, why not add funcool/promesa instead of core.async? Remembering that promesa is both faster than core.async, and its constructions can work with any arbitrary data, not only promises, so you can treat all code as if it’s async (or sync), without needing to remember which ones are promises, and which ones are not…

Just .pause and .resume constantly

This works, indeed. For example, with sockets:

(.on socket &quot;data&quot; (fn [data]
                     (.pause rs)
                     (async/put! chan data #(.resume socket))))
(.on socket &quot;end&quot; #(async/close! chan))

But not all callback-based async code in ClojureScript allow you to pause events. Node.JS Socket do, WebSocket in browser don’t. Also, NPM package pg, when you query with a cursor, also will not allow it. In this case, there’s nothing you can do, really – you will either drop messages, or an exception will happen.

Use offer!

(go (>! and put! both are fragile with callbacks, because you can’t really “park” or “block” threads in Javascript. Keep put!ing messages in a channel, and you’ll hit an exception “No more than 1024 pending operations” (or something like that). So people asked me to use offer! or make a sliding buffer, etc. This doesn’t really solves the problem if you can’t drop messages – and I do have lots of cases when this happens. There were some people that told me that dropping messages is part of the life, and I wholeheartedly disagree – there are LOTs of situations when you can’t loose anything – bank transactions, socket messages (you can’t reconstruct the payload if you lost part of it), downloads, etc. There are ways to mitigate this, for example:
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Performance optimizations in Reagent – part 2

Have I mentioned that it’s a nightmare to install React Devtools in Electron? Turns out, it’s worth it. But it’s still a pain. If you want to try, you’ll need to first install the extension in a chrome-based browser (like Brave, the one I use) and then install it by code. At Chlorine, what I did was to copy the whole extension folder to a devtools directory and then changed the script to load electron to the script below (see the BrowserWindow.addDevToolsExtension):

const path = require(&#039;path&#039;)
const {app, BrowserWindow} = require(&#039;electron&#039;)

app.on(&#039;ready&#039;, () =&gt; {
  let browser = new BrowserWindow({
    width: 900, height: 600,
    webPreferences: {nodeIntegration: true}})
  browser.loadURL(path.join(&#039;file://&#039;, __dirname, &#039;/index.html&#039;))

  BrowserWindow.addDevToolsExtension(&#039;./devtools&#039;)
})

Originally, the React Devtools was installed at ~/.config/BraveSoftware/Brave-Browser/Default/Extensions/fmkadmapgofadopljbjfkapdkoienihi/4.21.0_0 (tilde is my home folder). If you’re trying to install on Atom editor, you’ll have to open developer tools and issue the following script:

r = require(&#039;remote&#039;)
r.BrowserWindow.addDevToolsExtension(&#039;./devtools&#039;) // or the right directory

This command will fail, but somehow when you reload Atom, the React Devtools will be there. There’s only one feature that I use – highlight which elements were updated. And that’s where our performance tuning starts again.
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The magical wonders of programming with pure data

I’ll start with a disclaimer – if you’re developing in ClojureScript because of performance, you’re doing the wrong thing. Although a Clojure code can be really close to Java performance, ClojureScript simply can’t match JS performance – specially because in Javascript, the fundamental data structures like arrays, sets, and objects are implemented in a faster language, and as of today, no “user space” data structure can get even close the “native” ones. And, let’s not forget that JS is slower than Java.

So, if you want to beat JS performance in ClojureScript, you have to make use of what ClojureScript offers you – the REPL, the fast experimentation, and the wonderful experience of programming with data. So, this is a tale of a huge performance improvement that I’m currently working in Chlorine.

Rendering EDN

In Chlorine and Clover, when you evaluate something, the result will be rendered in a tree-like way at the console. This works quite well for Clojure, because UNREPL makes structures that are too big small, and you can query for more data. So far, so good.

In ClojureScript, Clojerl, Babashka, etc, things are not so good. Big data structures will be rendered fully on the view. They can lock or crash your editor, they can occupy all your memory, etc. The reason for that is that tree structures are hard – when you’re rendering the “parent”, you don’t know what the children will be. Currently, in Chlorine, rendering (range 80000) locks my editor for 4 seconds until it calculates everything, layouts all data, etc… and I wanted to change this.

Reagent vs Helix vs React

I was always intrigued on how much performance hit I get when I use Reagent’s Hiccup data structure instead of React objects – after all, there must be some performance problems, right? After all, that’s the promise of Helix – to not pay this performance hit because you’re closer to what React wants.

So, first things first: profiling Javascript inside Electron IS A NIGHTMARE. I decided to install React Devtools extension on Electron (inside the Atom editor) but that got me into so much trouble, false-positives, wrong profiles that I ended up deciding against it and simply used the “performance” tab to do my profiling. There, I could see batching.cljs hogging my performance, so the next move was easy – move away from Reagent and use Helix.

Except… that Helix uses some macros and I ended up doing the code in React. My testcase was simple: render a vector of 80000 elements and see how it would perform, obviously without all the bells and whistles that Chlorine offers today (otherwise this experiment would be waaay longer). And that’s where things get surprising: with Reagent, I was hitting 1800ms of scripting, and about 120ms of rendering. With React… 1650ms of scripting, and about 200ms of rendering. I decided to do more benchmarks and probably because of OS caching, warm-up, or whatever, the results got even closer, with Reagent sometimes performing better than React – but still too slow.
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