Maurício Szabo

Introduction to Kafka with Clojure

Recently I was trying to study Kafka, but I didn’t find a single resource that would give me a quick introduction and hands-on experience with it and Clojure. So, I’m making my own here! Don’t expect a “too deep introduction” – this is just the quick-and-dirty introduction about the concepts, and then I’ll show some code examples in Clojure

Kafka is a messaging system similar to RabbitMQ and SQS. The great differential is that it’s faster than both solutions, and works very well in cluster mode. Installing Kafka locally is quite complicated so you probably will wants to use the docker-compose.yaml file below:

version: '2'
services:
  zookeeper:
    image: confluentinc/cp-zookeeper:5.3.1
    hostname: zookeeper
    container_name: zookeeper
    ports:
      - "2181:2181"
    environment:
      ZOOKEEPER_CLIENT_PORT: 2181
      ZOOKEEPER_TICK_TIME: 2000
  kafka:
    image: confluentinc/cp-enterprise-kafka:5.3.1
    hostname: broker
    container_name: broker
    depends_on:
      - zookeeper
    ports:
      - "9092:9092"
    environment:
      KAFKA_BROKER_ID: 1
      KAFKA_ZOOKEEPER_CONNECT: 'zookeeper:2181'
      KAFKA_LISTENER_SECURITY_PROTOCOL_MAP: PLAINTEXT:PLAINTEXT,PLAINTEXT_HOST:PLAINTEXT
      KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://broker:29092,PLAINTEXT_HOST://localhost:9092
      KAFKA_METRIC_REPORTERS: io.confluent.metrics.reporter.ConfluentMetricsReporter
      KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR: 1
      KAFKA_GROUP_INITIAL_REBALANCE_DELAY_MS: 0
      CONFLUENT_METRICS_REPORTER_BOOTSTRAP_SERVERS: broker:29092
      CONFLUENT_METRICS_REPORTER_ZOOKEEPER_CONNECT: zookeeper:2181
      CONFLUENT_METRICS_REPORTER_TOPIC_REPLICAS: 1
      CONFLUENT_METRICS_ENABLE: 'true'
      CONFLUENT_SUPPORT_CUSTOMER_ID: 'anonymous'

This file will create the Kafka broker (like a single node of the messaging) and will add Zookeeper (that will allow you to coordinate between different Kafkas, decide which node is the leader, and also participate on the node election when the leader goes down, and other things). You will connect into 9092 port, and then listen and send messages from there.
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By Maurício Szabo, ago

Subtyping on functional languages

This is almost a new post on the Function SOLID series. It should be about the Liskov Substitution Princible, but before we talk about it it’s important to understand the concept of subtyping.

Subtyping in Dynamic languages like Clojure or in languages that do not have hierarchical typing like Haskell seems strange. But subtyping is not only a concept about object-oriented programming languages – it’s about restrictions, and the concept of variance. I’m going to try to explain both in this post

To begin with, we can say that a supertype is more generic than a subtype, but that’s not all. In truth, is all about properties that you can prove about a specific data. For example, if we use Clojure as a starting language you could say that the coll? is a property of maps and vectors, but vector? is a property that only applies to vectors. In practice, this means that coll? is a superclass of vector?.

(coll? []) ; => true
(coll? {}) ; => true

(vector? []) ; => true
(vector? {}) ; => false

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By Maurício Szabo, ago

My last experience with Ruby

On my last job I tried to go back to Ruby programming language. Not really by choice – but just because it was a language and was familiar with, and my last two jobs in Clojure didn’t really work out for me (not because of the language, really). I even imagined that some things would be easier in Ruby, specially while working with relational databases (something I really did miss while I was working in the Clojure language).

At the time, in my opinion, Rails was still a great framework – maybe a little too complex. And I imagined that somehow there could be better ways of doing Ruby code that could use the best parts of Rails and avoid the worst (like ActiveRecord, for example, maybe even substitute it with Sequel or ROM).

No a year and a half later I’m back to Clojure – and I will probably never go back to Ruby. And the reason is quite simple: I was working with Ruby doing exactly the same code that I did about three years ago. Rails didn’t change that much, but still was a huge mess when you had to upgrade from one version to another. The same problems I had in the past kept happening again and again, and it felt like a huge step backwards for me.
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By Maurício Szabo, ago

(check (my-code) => (needs :tests))

So, yesterday I made a talk (in Portuguese only, unfortunately) about the difficulties of testing Clojure and ClojureScript code. Specifically, I think the most problematic issue is the lack of “custom matcher libraries”, and how the default error messages are kinda bad and don’t help you identify the problems.

Then, on Clojurians’ #announcements Slack channel, I found that clojure.test Expectations library have a new version. So, why not integrate it on my Check library, and maybe continue developing it?

What is check?

Midje is too magic. Clojure.test is too little. Thinking about findind a “middle ground” I’ve started the “check” project, and I’m using it to test my personal projects like Chlorine, Clover, REPL-Tooling and Paprika. The problem is that, while the API is stable, but it still doesn’t do all the things I want.
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By Maurício Szabo, ago

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

Quick Post – native apps with ClojureScript

React apps now run on the desktop with Electron. They also run on the desktop with react-native-desktop, or proton-native. In this simple post, I’ll share my (very small!) experience with proton-native:

First, you need Shadow-CLJS. Because of the npm integration, you can literally just:

npm install proton-native react react-dom create-react-class

And then add [reagent "0.8.1"] to dependencies on shadow-cljs.edn file. Then, configure a :node-script target and start to build things. This means that your shadow-cljs.edn file will be:

{:source-paths ["src" "test"]
 :dependencies [[reagent "0.8.1"]]
 :builds {:desktop {:target :node-script
                    :main demo.app/init
                    :output-to "target/index.js"}}}

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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