Last hours on my country

Right now, as I’m writing this, I have about 6 bags full of (mostly) clothes, a file with different documents, a bunch of fears, and a lot of hope. Tomorrow, if everything goes well, is my last day living in Brazil.

It was a strange adventure, first by making a simple trip (well, as far as “jump on a motorcycle with my wife and travel though the country and beyond, and end up traveling 6,449km” is considered simple), then by staying a whole month on an Airbnb and trying everything, from local meetups to social projects to local culture, restaurants, food, etc, and then finally getting all the documentation to live on the country we chose: Uruguay.
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Implementing shadow.remote API

Since version 0.8.0 of Chlorine, there’s a new way to evaluate ClojureScript code: that’s the Shadow-CLJS Remote API. It is basically a new REPL (not nREPL, no Socket REPL) over WebSockets to try to solve problems when translating other REPLs to ClojureScript. So, to understand why these problems exist, I’ll first introduce the difference between ClojureScript and Clojure.

On Clojure, you’re always inside a JVM. This means that compilation happens on the same JVM that your REPL, and your code is running. If you practice REPL-Driven Development, even your tests are running on the same JVM. In practical terms, it means that when you fire up your REPL, you already have everything ready to run code, compile code, and evaluate forms.

On ClojureScript, the compiler is written in Clojure – that means it’s running on the JVM. So, to produce Javascript code you don’t need a Javascript environment – and that’s when things become confusing, because when exactly will you run the REPL? Let’s try from another angle: if you start the REPL on compilation time, you can’t evaluate code (because there’s no Javascript generated, nor any Javascript engine running). If you start the REPL when you run the compiled code, this REPL can become unusable if you stop the Javascript environment, and also you have to coordinate lots of state and translations between formats.
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Reagent Mastermind

One of these days, a friend of mine posted about his experience writing the “Mastermind” game in React (in portuguese only). The game is quite simple:

  1. You have six possible colors
  2. A combination of 4 colors is chosen randomly (they can be repeated – for example, blue,blue,blue,blue is a valid combination) – you have to guess that number
  3. You have up to 10 guesses of 4 colors. For each color on the right position, you win a “black” point. For each color in the wrong position, you win a “white” point
  4. If you can’t guess on the 10th try, you loose.

So, first, we’ll create a shadow-cljs app – create a package.json file, fill it with {"name": "Mastermind"}, then run npm install shadow-cljs. Traditional stuff.

Then, we’ll create the shadow-cljs.edn file. It’ll only contain a single target (:browser), opening up a dev-http server so we can serve our code, and we’ll add reagent library dependency. I also added the material-ui dependency, but you don’t really need it for the code. Now, running npx shadow-cljs watch browser will start a webserver at port 3000, and we can start to develop things.
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Please, use the right terms for “typing”…

Names matter. That’s one of the things that I learned, working multiple years on programming software. When you have something called “integration”, for example, that means different things for different people, that’s a recipe for disaster.

That’s why I get quite triggered when people use Untyped / Typed, Weak / Strong typed, Uni / Multi typed, to describe programming languages – because it means different things to different people, or are simply wrong. So let’s dive into it:

Untyped languages or languages without types are quite rare: Assembly is the most interesting example (there’s literally no types in Assembly: everything is a memory address, byte, word, etc). Some virtual machines’ bytecodes are also untyped. In this case, most languages are typed. Ruby, for example, have types, and you can dispatch different behavior depending on the type of the caller (because it’s a class-based object-oriented language). Clojure is also typed, because you can do type-based polymorphism with protocols using defprotocol and defrecord for example. You can also use deftype, and if there’s a specific command to define types, how can we call it “untyped”?

Weak / Strong typed is a term that’s hard to define. Some people say that it’s when you have pointers, because you can bypass the typing at all; others, when the compiler erases typing at run-time; some say that’s when the language tries to coerce and implicitly convert from one type to another, to try to figure out what you want…

Now, a language that allows you to bypass typing because you have pointers is called “memory unsafe”; if the compiler erases typing information, is called “type erasure”; coercion of course is called “coercion”, and can be “automatic” or “manual” coercion (for example, most languages try to coerce integers to decimals at some point); even the ability to convert between types is controversial: on Ruby and Scala, operators are also methods of the class (and, on Ruby, you can rewrite methods on classes that already exist, so automatic conversion is a user-defined feature) – so, please use the right term.

Unityped means a language that only have one type. I believe only some markup languages enter on this classification. Calling a language that have multiple types as unityped because someone imagined that all these multiple types can somewhat collapse into a single one is, at minimum, strange; and also, again, we do have a term for languages like Javascript, Ruby, Python, Smalltalk, and Clojure.
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ClojureScript vs clojure.core.async

I’m going to make a somewhat bold statement: core.async does not work with ClojureScript. And, in this post, I’m going to show some examples why this is true, at least for the current versions of core.async.

So let’s start by understanding a little bit about the runtime: Javascript is a single-threaded runtime that implicitly runs an event-loop. So, for example, when you ask to read a file, you can do it synchronously or asynchronously. If you decide to run in that asynchronously, it means that as soon as you issue the fs.readFile command, you need to register a callback and the control is returned to the “main thread”. It’ll keep running until it runs out of commands to execute, then the runtime will wait the result from the callback; when it returns, the function that you registered will be called with the file contents. When the function ends, the JS runtime will await to see if there’s any other pending call, and it’ll exit if there’s nothing else to do.

The same thing happens in browser environment, but in this case the callbacks are events from the DOM: like clicking on buttons or listening for changes in some elements. The same rules apply here: the runtime is single threaded and when something happens it will first execute everything that needs to be executed, then it will be called back with the event that happened.

So maybe we can change these callbacks with core.async channels right? But the answer is no, because core.asyncs go blocks will not run in different threads (because, again, the runtime is single-threaded). Instead, it creates a state machine and it’ll control of when each of these go blocks will be called, at what time, eventually replacing the event-loop that Javascript environment already have.
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What’s happening on Brazil?

I don’t really like to talk about non-technical things here, but… sometimes the circumstances push me to do it.

We are facing strange times: covid-19. We, as people, plural. There’s no individuals in this matter, because if only one person takes action, nothing will change. If only one country, again nothing will change. We need union, more than ever.

Then, comes Brazil. People simply believe that “our climate is warmer”, “the pandemic is nothing to worry about”, and “it’s just a small flu” – I’m not talking only about the bizarre declarations of the president, but from the common person. Our approximate numbers (approximate because we’re not testing all cases: I, personally, know three people that had the exact right symptoms for Covid-19 that didn’t receive any testing, and were asked to just “rest at home, and if it becomes worse search a medic”. One of then, as soon as he felt a little better, was visiting his friends and eating food at restaurants) keep skyrocketing, and fake news are appearing here and there that these numbers were fabricated by the enemies of the current government.

So, there are only guidelines – no official laws, no real restrictions. They all have to be decided by local authorities, and all against the president (that, on this day, made some insinuations that he can start a coup if people don’t obey him!) that I really hope doesn’t have all the power he thinks he have.
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The History of Chlorine

Before I even started with Clojure, I was analyzing LightTable – the idea of that editor was to support better integrations between the code you’re writing and the code that’s running. It was a really good experience, but the main problem I had is that it was in the very beginning, with few plug-ins and bad documentation. I tried to make the parinfer plug-in work in the editor, but it had lots of bugs and then I simply changed back to Atom. At the time, proto-repl was the best package to work with Clojure, and I made some small changes to it (so I could add some callbacks to when a new connection to nREPL was made, and other small issues) to improve my workflow.

Fast forwarding a little bit, I started my first Clojure job at Nubank. Most people were using InteliJ, but I felt that by using Atom I had a different approach on problem solving, specially those hard parts where the fast feedback of “run in the REPL and see the results in your editor, then browse over the keys” could give better insights about what’s happening. I tried to implement some features that proto-repl didn’t have at the time (and Chlorine still does not have some) like “automatically add nREPL port”, and “watch expressions” (almost the same as watch variables in a debugger). These ended up in a package called clojure-plus, that still exist today.

I also began to experiment with ClojureScript (at the time, only Figwheel was available – Figwheel-main didn’t even exist!) and found that existing tools didn’t provide the same power that I had with Clojure. It also didn’t have autocomplete, goto var definition, and so on. To ease a little bit these problems, I ended up adding on clojure-plus some CLJS support – when you tried to evaluate a .cljs file, it would try to connect to ClojureScript, reserve a REPL, then evaluate the code over there.
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Implementing a nREPL Client

Some people asked me on how did I implement the nREPL client on Chlorine. So, I’m writing this post!

nREPL is a simple protocol. It uses “sessions” that are used to isolate evaluation contexts and other things (for example, on Chlorine every connection connect to two REPLs: one “primary” and one “auxiliar” that is used to run commands like autocomplete / goto var definition, and so on). On nREPL, this isn’t necessary: you just connect to a single REPL and use two different sessions. Just for the record, because the way Chlorine works, I didn’t implement it like this (because I would have to rewrite lots of code – maybe in the future).

Now, to explain the protocol, let’s separate things in parts: the first thing I do (and I was already doing in the past) is to connect to a socket. Then, I looked at the documentation for nREPL to understand how to send and receive commands to the REPL. Now, there are some details on the way that every operation is implemented that I simply ignored because it was not necessary to understand then from the perspective of my application…
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nREPL on… Chlorine?

When I started the Chlorine project, I just thought it would be great if I could target all Clojure-like REPLs that already exist but didn’t have tooling support. At the time, this would include Lumo and Plank, mostly. Also, Shadow-CLJS and Figwheel have some “clunky run-some-code-and-transform-in-cljs” way of working that simply didn’t click with me.

Now, almost a year later, Chlorine supports Clojure, ClojureScript (Shadow-CLJS, Lumo, Plank, or even over clj), ClojureCLR, Arcadia, Babashka, Clojerl (Clojure on Erlang) and Joker (Clojure on Go, also a linter). But the reality is that working with a pure Socket REPL is really hard – a socket REPL works exactly like a regular one, printing namespaces after each code, and so on. Also, there are some strange decisions on some REPLs, mostly likely ClojureScript (that is the second most used Clojure flavor), so things are not always easy. To put things in perspective, currently Chlorine uses 3 ways to evaluate code: It uses unrepl, that only works on Clojure, or uses internal APIs of shadow-cljs (that obviously only works for shadow-cljs), and for other implementations it uses a kind of a hack – it evaluates the code, inside a trycatch, and it returns a vector where the first element is a symbol in a specific format that Chlorine will understand and then link that with the response. This “hacky way” is currently being used for every other implementation except Clojure and Shadow-CLJS. Things work (autocomplete works too), but it is not pretty and sometimes have strange results.

As a matter of fact, I was already thinking about removing UNREPL (it’s really hard to implement new features on it, and some good ideas only work in theory – for example, the ability to evaluate long strings / collections and render only a part at a time aren’t that good with lots of edge-cases) and, to do it, I though about a better, non-hacky way to evaluate things on some Socket-REPLs (that, again, would only work on some REPLs – ClojureScript REPLs will probably never support “upgradable REPLs” because of the way they work) – the only thing that I had to understand is how to implement this “upgraded REPL”…

Then, recently, Babashka added an initial support for nREPL, with an insane low amount of lines. So, I’ve tried to implement a way to evaluate code over nREPL… and it was really simple to do it, using a npm library that already did it. But implementing like this meant that the user would need to know if the host/port to connect is a Socket REPL, or a nREPL (and the user does not know – lots of tools like lein and shadow-cljs show an nREPL port to be connected).
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REPL-Tooling Clients

Chlorine, Clover and Clematis are all implementations of the same library: REPL-Tooling. In this post I will show you how to create a new implementation of it in a way that’s completely disconnected from any editors, so you can grasp the general concepts.

Suppose I want to do an implementation for an editor that doesn’t run JavaScript – so it’ll connect by some kind of socket. In this example I’m going to use WebSockets because… why not?

We’re going to create a shadow-cljs node project and add repl-tooling as a dependency. We will also had some more dependencies: mostly ws for websockets and the same react libraries that we use for reagent (react, create-react-class and react-dom) – repl-tooling still needs reagent, and probably in the future I will split it into two different libraries (one for the REPL handling and other for the visual rendering part). This supposedly is not to much of a problem because ClojureScript compiler will probably remove these parts in the dead code elimination process anyway. So, our package.json file will just be like this:

{
  "name": "ws-repl",
  "devDependencies": {
    "shadow-cljs": "^2.8.83"
  },
  "dependencies": {
    "create-react-class": "^15.6.3",
    "install": "^0.13.0",
    "react": "^16.12.0",
    "react-dom": "^16.12.0",
    "ws": "^7.2.1"
  }
}

And our shadow-cljs.edn file:

{:source-paths ["src"]

 :dependencies [[repl-tooling "0.4.0"]]
 :builds {:node {:output-to "index.js"
                 :target :node-script
                 :main ws-repl.core/main}}}

The first step is when someone connects to the WebSocket. Then, we’ll just create a connection to the client, and send a list of supported commands – for now, is just the “connect” command:
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