Clojure

Why I tend to avoid core.async?

It’s no surprise that I don’t like core.async very much. For starters, it make my functional composition looks like imperative programming again. There’s also multiple issues that you need to be aware of (like, don’t use async/put! because you will have problems, deadlocks that are difficult to predict, go blocks don’t compose over functions so you loose lots of helper macros like delay).

But the most important reason is that most of the time, I’m working in ClojureScript. And it’s impossible to migrate callback to core.async.

Well, you may be tempted to write something like:

(js/someFunction "i'm async" "lol" #(async/put! some-channel %))

And one day or another you’ll have the dreadful Assert failed: No more than 1024 pending puts are allowed error. There are multiple ways around this problem, but none of then work if you can’t lose messages.
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By Maurício Szabo, ago

Functional SOLID – Open/Closed Principle

Continuing on the series about SOLID principles on functional programming, the next one is the Open/Closed Principle. The definition from the Wikipedia:

The open/closed principle states “software entities (classes, modules, functions, etc.) should be open for extension, but closed for modification”; that is, such an entity can allow its behavior to be extended without modifying its source code.

This is kinda interesting on its own way: what’s an “extension”? Considering the context when it was written, and future interpretations of the principle, the idea is that any program should not be re-compiled (re-written, modified, etc) to be extended. The idea of this principle is that local changes should not propagate to other parts of the program: make entities as self-contained as possible, write then in a way that extensions would not depend on modifications on these entities, then “close” then to modifications. I can see two cases for the “open-closed principle” violation, and the first one is the most common:

(defn as-int [some-str]
  (when (re-matches #"\d+" some-str)
    (Integer/parseInt some-str)))

This code returns an Integer if it can parse a string as a number, and nil if it can’t. Now, suppose we want to “extend” this functionality by accepting other objects like Double (truncates to integer) or nil (returns 0). The only way to do it is to change the when to a case, but that means that for every new implementation I’ll have to change this function. Now, a better way is to use protocols:
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By Maurício Szabo, ago

Functional SOLID – Single Responsibility Principle

I am a firm believer that we have to learn from the past instead of throwing all away for the future. And this is one of these moments: I have seen multiple talks, presentations, slides telling about SOLID and Design Patterns in functional programmings. Some are serious, some are satires, but most only speaks “you just need functions, really!” on their explanation on the principles, effectively diminishing the usefulness of the principles and also by imagining that, somehow, if we only use functions all our problems on developing software would be solved forever.

So, to counter that, I’m going to re-visit SOLID, but this time I’ll not compare with “OO” – instead, I’ll ask for us to try to grasp the meaning behind each principle. I’m going to use the definitions from Wikipedia, because (1) it’s easier to track changes and (2) it’s condensed from multiple sources, so it’ll probably not reflect a single opinion from an author. I also thought about being one single post, but it became quite complicated, so I’m splitting this post in multiple ones (and probably the one about LSP will be the most extensive of all). So, let’s begin by the first: the Single Responsibility Principle:

The single responsibility principle is a computer programming principle that states that every module, class, or function should have responsibility over a single part of the functionality provided by the software, and that responsibility should be entirely encapsulated by the class, module or function
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By Maurício Szabo, ago

My Atom editor configuration for working with Clojure/Script, revisited

Sometime ago, I did a post on how I work with Atom to develop Clojure and ClojureScript projects. It is in Portuguese, so I’m gonna re-visit the subject and also update with my current workflow.

There are two packages that I have to install to work with Clojure: lisp-paredit and chlorine. Without lisp-paredit, when I start a newline, the indentation gets all sorts of problematic. I use it on “strict mode” and use the tools to slurp/barf forward only. As for chlorine, it is needed to have autocomplete, evaluation, show documentation, goto var definition and so on. Last, I use also parinfer so I can remove whole lines of text and parinfer will infer the correct closing of parenthesis for me (most of the time at least).

Now, how exactly do I work with Clojure? When you use lein or boot, you’ll get a nREPL port. This is not the port you use with Chlorine, so I need a bit more of work. I can’t just start a REPL with lein repl or clj, I need to inform the tool to open a socket-repl server. The JVM option needed is: '-Dclojure.server.myrepl={:port,5555,:accept,clojure.core.server/repl}'. So, the commands below are what I use with lein or clj:

JAVA_OPTS='-Dclojure.server.myrepl={:port,5555,:accept,clojure.core.server/repl}' lein repl

or

clj -J'-Dclojure.server.myrepl={:port,5555,:accept,clojure.core.server/repl}'

This will open a REPL at port 5555 (or I can change the port if necessary). Then, it’s time to fire up the Atom’s command palette and select “Connect Clojure Socket REPL”, put 5555 on the port, and connect. Then, I’ll use “Refresh Namespaces” or “Load file” command to load my latest version of code into the REPL, and start working.
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By Maurício Szabo, ago

Heart of Clojure

It all started with the idea to send a talk to Heart of Clojure, based on my work on Chlorine. Now, the talk wasn’t selected, but I decided to go to the conference even then. Being on Brazil, this meant about 19 hours of travel, so without thinking too much I bought the ticket to the conference and decided what do to latter about the travel, where to stay, and how many days I would stay. The first idea was to simply go there to the conference, but I imagined it would be very tiring, so came a strange and incredible idea that I’ll let to another post.

Now, the conference. In fact, it was different from everything I ever saw. First of all, it was amazing – not only because of the technical talks, but the whole experience of being in Leuven, meeting new people, using English as the first language everywhere, trying to understand a little of Dutch (spoiler alert: it didn’t work), and so on…
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By Maurício Szabo, ago

Object-oriented after working with functional programming

Sometimes I need to divide my knowledge in phases: when I started to program, I felt that C/C++ were the best languages to make a software. Then, I’ve began to work with Ruby and learned Test-Driven Development. I divide my knowledge “before TDD” and “after TDD”, because it literally changed the way I could think about software and tests in general. Now, I’ll probably make the same division: “before functional programming” and “after FP”, and I only discovered that things have changed this week: I just discovered I don’t know how to do object oriented programming anymore – and to be honest, it’s not really a bad thing: I also saw in practice how object-oriented programming expects you to write lots of boilerplate in most situations.

This realization came to me when I was working in a peculiar kind of problem – it’s basically a ruby code that needs to connect on messaging system and, when it receives a message, needs to persist it in a relational database. The problem is that this specific system have a strong consistency requirement, so the message could only be updated on DB before a specific event happens: after that, we can’t change it anymore, except for some specific fields. Also, as we’re working with messaging, we can receive the message multiple times, out of order, and all of those strange things that happens on Internet-land. So, to summarize:

  1. The system will receive a message
  2. It’ll UPSERT a record on DB, just with some identification fields (they’ll never change, and if they do, they characterize another message to be persisted – think about an external id)
  3. It’ll BEGIN a transaction and SELECT ... FOR UPDATE my just upserted message
  4. It’ll find, on another table, the rest of the fields on the message
    1. If this record doesn’t exist, we’ll create it (and log)
    2. If it does exist, we’ll check additional info, and decide: or we ignore it (and log), or we upsert (and log), or raise an error

Now, for the implementation. Because consistency is a must have on this system, I don’t want to expose for future programmers (be it myself or some of my friends) some code that’ll induce me to errors: after all, who wants to do with_consistency_check(msg) { Message.upsert!(msg) } when I can just do Message.upsert!(msg), right? So, I don’t want to allow people to be able to modify, find, update, or anything else outside of the with_consistency_check (or whatever name I decide). So, how to do it?
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By Maurício Szabo, ago

Chlorine, Clematis, REPL Tooling

Recently I began to migrate some of the code on Chlorine to REPL Tooling, so things may become more testable. I already found multiple bugs in this approach and began an integration test methodology using Electron (I say that there are three kinds of developers in the field of automated tests – the ones that don’t test, the ones that do, and test freaks. I’m probably the later).

In the beginning, the idea would be to rewrite the renderer of results and exceptions so that I could fix lots of bugs that they have. So far, it’s progressing slowly, but I already can render datomic results in a meaningful way (the last renderer was interpreting as Java objects, which they indeed are) and fix some bugs with tags and other issues.

Now, one of the things that I wanted in the new renderer is the ability to copy/paste results in a meaningful way – as I’m using UNREPL, there are lots of tags that need to be reinterpreted, like #unrepl/browseable for datafy. These need to be “translated” to something useful for rendering on screen, with links to navigate inner details, but for copy-paste they should have a textual representation that makes sense (probably the hard part).

The results of all these experiments are quite interesting – when you evaluate something and th result is a Java object, there’s a link ... that can be used to navigate inside the object: it’ll show getters, the current class, methods that the object supports, so things like “goto definition for Java object” or “Javadocs” aren’t really necessary.

Then, one of my friends asked for a Vim option. Just for fun, I started Clematis, a port of Chlorine to NeoVim. And it seems they things are progressing faster than I thought!
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By Maurício Szabo, ago

Chlorine is thriving!

When I started this project, I was experimenting with shadow-cljs to see if I would be able to make an Atom package that would auto reload, run tests on ClojureScript, and se how far could I push ClojureScript in an Atom package.

Now, some months later, I’m seeing the package being used by a bunch of people, and I even discovered some bugs in UNREPL! Now, on this post, I’ll discuss a little bit more in detail the design decisions and my vision on the future of the project.

Chlorine is a clojure and ClojureScript atom package. It connects to a socket repl (opened via lein, boot, clj, shadow-cljs, lumo, or even REBL) and then upgrades the repl to be programmatically oriented with unrepl. Unrepl only works on Clojure, so for ClojureScript we use other techniques. Also, socket repl is a stream protocol, so to emulate a “request-response”, we need to coordinate things so Atom (and other editors) can react to commands and know exactly what’s the correct response for each command sent.

Design decisions

The choice for UNREPL was mostly because there is almost no documentation about prepl so far. Also, Socket REPL is literally everywhere: on Clojure , on ClojureCLR, on Lumo and Plank. Also, I wanted a better way to use ClojureScript, and I still have nightmares trying to use it over nREPL… and with Socket REPL things work fine.

Also, when I started the project Clojure 1.10 was just alpha software, and UNREPL offers us insanely good support for lazy lists, big strings, and other things that I wanted to use out of the box. One of the problems I’m still facing is coordination of evaluate/response, but this will probably be solved after a bunch of other fixes I’ll try.
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By Maurício Szabo, ago