Vavr, Collections, and Java Stream API Collectors

Vavr is now a must-have for every modern Java 8+ project. It encourages writing code in a functional manner by providing a new persistent Collections API along with a set of new Functional Interfaces and monadic tools like Option, Try, Either, etc.

You can read more about it here.

Vavr’s Persistent Collections API

To provide useable immutable data structures, the whole Collections API needed to be redesigned from scratch.

The standard java.util.Collection interface contains methods that discourage immutability such as:

boolean add(E e);
boolean remove(Object o);
boolean addAll(Collection<? extends E> c);
boolean removeAll(Collection<?> c);

One might think that the problem is that those methods allow modifications of the particular collection instance, but this is not entirely true – with immutable data structures, each mutating operation needs to derive a new collection from the existing one. Simply put, each of those methods should be able to return a new instance of the collection.

Here, the whole collections hierarchy is restricted to returning boolean or void from mutating methods – which makes them suitable only for mutable implementations.

Of course, immutable implementations of java.util.Collection exist, but above-mentioned methods are simply forbidden. That’s how it looks like in the com.google.common.collect.ImmutableList:

/**
 * Guaranteed to throw an exception and leave the list unmodified.
 *
 * @throws UnsupportedOperationException always
 * @deprecated Unsupported operation.
 */
@Deprecated
@Override
public final void add(int index, E element) {
  throw new UnsupportedOperationException();
}

And this is far from perfect – even the simplest add() operation becomes a ceremony:

ImmutableList<Integer> original = ImmutableList.of(1);

List<Integer> modified = new ImmutableList.Builder<Integer>()
  .addAll(original)
  .add(2)
  .build();

A major redesign made it possible to interact with immutable collections more naturally and add some new exciting features:

import io.vavr.collection.List;
// ...

List<Integer> original = List.of(1);
List<Integer> modified = original.append(2);

modified.dropWhile(i -> i < 42);
modified.combinations();
modified.foldLeft(0 , Integer::sum)

Collecting Vavr’s Collections

One of the key features of the Java Stream API was the collect() API that made it possible to take elements from Stream and apply the provided strategy to them – in most cases that would be simply placing all elements in some collection.

Vavr’s collections have a method that provides the similar(but limited) functionality but it’s not being used often because almost all operations that were available only using Stream API, are available on the collection level in Vavr.

But… one of the method signatures of Vavr’s collect() is especially intriguing:

<R, A> R collect(java.util.stream.Collector<? super T, A, R> collector)

As you can see, Vavr’s collections are fully compatible with Stream API Collectors and we can use our favourite Collectors easily:

list.collect(Collectors.toList());
list.collect(Collectors.groupingBy(Integer::byteValue));

That might not be super useful for everyday use-cases because the most common operations are accessible without using Collectors but it’s comforting to know that Vavr’s functionality is a superset of Stream API’s (at least in terms of collect() semantics)

Collecting Everything

The interesting realization happens when we decide to investigate the type hierarchy in Vavr:

source: http://www.vavr.io/vavr-docs/

We can notice here that the Value resides on top collections hierarchy and this is where the collect() method mentioned above is defined.

If we look closer, it’s clear that classes like Option, Try, Either, Future, Lazy also implement the Value interface. The reasoning behind this is that they are all essentially containers for values – containers that can hold max up to one element.  

This makes them compatible with Stream API Collectors, as well:

Option.of(42)
  .collect(Collectors.toList());

Try.of(() -> URI.create("4comprehension.com"))
  .collect(Collectors.partitioningBy(URI::isAbsolute));

Summary

The redesign of the Collections API allowed the introduction of cool new methods, as well as achieving full interoperability with Java Stream API Collectors – which can also be applied to Vavr’s functional control structures like Option, Try, Either, Future, or Lazy.

The examples above use:

<dependency>
    <groupId>io.vavr</groupId>
    <artifactId>vavr-test</artifactId>
    <version>0.9.0</version>
</dependency>
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Sample for lift-ng: Micro-burn 1.0.0 released

During a last few evenings in my free time I've worked on mini-application called micro-burn. The idea of it appear from work with Agile Jira in our commercial project. This is a great tool for agile projects management. It has inline tasks edition, drag & drop board, reports and many more, but it also have a few drawbacks that turn down our team motivation.

Motivation

From time to time our sprints scope is changing. It is not a big deal because we are trying to be agile :-) but Jira's burndowchart in this situation draw a peek. Because in fact that chart shows scope changes not a real burndown. It means, that chart cannot break down an x-axis if we really do more than we were planned – it always stop on at most zero.

Also for better progress monitoring we've started to split our user stories to technical tasks and estimating them. Original burndowchart doesn't show points from technical tasks. I can find motivation of this – user story almost finished isn't finished at all until user can use it. But in the other hand, if we know which tasks is problematic we can do some teamwork to move it on.

So I realize that it is a good opportunity to try some new approaches and tools.

Tools

I've started with lift framework. In the World of Single Page Applications, this framework has more than simple interface for serving REST services. It comes with awesome Comet support. Comet is a replacement for WebSockets that run on all browsers. It supports long polling and transparent fallback to short polling if limit of client connections exceed. In backend you can handle pushes in CometActor. For further reading take a look at Roundtrip promises

But lift framework is also a kind of framework of frameworks. You can handle own abstraction of CometActors and push to client javascript that shorten up your way from server to client. So it was the trigger for author of lift-ng to make a lift with Angular integration that is build on top of lift. It provides AngularActors from which you can emit/broadcast events to scope of controller. NgModelBinders that synchronize your backend model with client scope in a few lines! I've used them to send project state (all sprints and thier details) to client and notify him about scrum board changes. My actor doing all of this hard work looks pretty small:

Lift-ng also provides factories for creating of Angular services. Services could respond with futures that are transformed to Angular promises in-fly. This is all what was need to serve sprint history:

And on the client side - use of service:


In my opinion this two frameworks gives a huge boost in developing of web applications. You have the power of strongly typing with Scala, you can design your domain on Actors and all of this with simplicity of node.js – lack of json trasforming boilerplate and dynamic application reload.

DDD + Event Sourcing

I've also tried a few fresh approaches to DDD. I've organize domain objects in actors. There are SprintActors with encapsulate sprint aggregate root. Task changes are stored as events which are computed as a difference between two boards states. When it should be provided a history of sprint, next board states are computed from initial state and sequence of events. So I realize that the best way to keep this kind of event sourcing approach tested is to make random tests. This is a test doing random changes at board, calculating events and checking if initial state + events is equals to previously created state:



First look

Screenshot of first version:


If you want to look at this closer, check the source code or download ready to run fatjar on github.During a last few evenings in my free time I've worked on mini-application called micro-burn. The idea of it appear from work with Agile Jira in our commercial project. This is a great tool for agile projects management. It has inline tasks edition, drag & drop board, reports and many more, but it also have a few drawbacks that turn down our team motivation.

Clojure web development – state of the art

It’s now more than a year that I’m getting familiar with Clojure and the more I dive into it, the more it becomes the language. Once you defeat the “parentheses fear”, everything else just makes the difference: tooling, community, good engineering practices. So it’s now time for me to convince others. In this post I’ll try to walktrough a simple web application from scratch to show key tools and libraries used to develop with Clojure in late 2015.

Note for Clojurians: This material is rather elementary and may be useful for you if you already know Clojure a bit but never did anything bigger than hello world application.

Note for Java developers: This material shows how to replace Spring, Angular, grunt, live-reload with a bunch of Clojure tools and libraries and a bit of code.

The repo with final code and individual steps is here.

Bootstrap

I think all agreed that component is the industry standard for managing lifecycle of Clojure applications. If you are a Java developer you may think of it as a Spring (DI) replacement - you declare dependencies between “components” which are resolved on “system” startup. So you just say “my component needs a repository/database pool” and component library “injects” it for you.

To keep things simple I like to start with duct web app template. It’s a nice starter component application following the 12-factor philosophy. So let’s start with it:

lein new duct clojure-web-app +example

The +example parameter tells duct to create an example endpoint with HTTP routes - this would be helpful. To finish bootstraping run lein setup inside clojure-web-app directory.

Ok, let’s dive into the code. Component and injection related code should be in system.clj file:

(defn new-system [config]
  (let [config (meta-merge base-config config)]
    (-> (component/system-map
         :app  (handler-component (:app config))
         :http (jetty-server (:http config))
         :example (endpoint-component example-endpoint))
        (component/system-using
         {:http [:app]
          :app  [:example]
          :example []}))))

In the first section you instantiate components without dependencies, which are resolved in the second section. So in this example, “http” component (server) requires “app” (application abstraction), which in turn is injected with “example” (actual routes). If your component needs others, you just can get then by names (precisely: by Clojure keywords).

To start the system you must fire a REPL - interactive environment running within context of your application:

lein repl

After seeing prompt type (go). Application should start, you can visit http://localhost:3000 to see some example page.

A huge benefit of using component approach is that you get fully reloadable application. When you change literally anything - configuration, endpoints, implementation, you can just type (reset) in REPL and your application is up-to-date with the code. It’s a feature of the language, no JRebel, Spring-reloaded needed.

Adding REST endpoint

Ok, in the next step let’s add some basic REST endpoint returning JSON. We need to add 2 dependencies in project.clj file:

:dependencies
 ...
  [ring/ring-json "0.3.1"]
  [cheshire "5.1.1"]

Ring-json adds support for JSON for your routes (in ring it’s called middleware) and cheshire is Clojure JSON parser (like Jackson in Java). Modifying project dependencies if one of the few tasks that require restarting the REPL, so hit CTRL-C and type lein repl again.

To configure JSON middleware we have to add wrap-json-body and wrap-json-response just before wrap-defaults in system.clj:

(:require 
 ...
 [ring.middleware.json :refer [wrap-json-body wrap-json-response]])

(def base-config
   {:app {:middleware [[wrap-not-found :not-found]
                      [wrap-json-body {:keywords? true}]
                      [wrap-json-response]
                      [wrap-defaults :defaults]]

And finally, in endpoint/example.clj we must add some route with JSON response:

(:require 
 ...
 [ring.util.response :refer [response]]))

(defn example-endpoint [config]
  (routes
    (GET "/hello" [] (response {:hello "world"}))
    ...

Reload app with (reset) in REPL and test new route with curl:

curl -v http://localhost:3000/hello

< HTTP/1.1 200 OK
< Date: Tue, 15 Sep 2015 21:17:37 GMT
< Content-Type: application/json; charset=utf-8
< Set-Cookie: ring-session=37c337fb-6bbc-4e65-a060-1997718d03e0;Path=/;HttpOnly
< X-XSS-Protection: 1; mode=block
< X-Frame-Options: SAMEORIGIN
< X-Content-Type-Options: nosniff
< Content-Length: 151
* Server Jetty(9.2.10.v20150310) is not blacklisted
< Server: Jetty(9.2.10.v20150310)
<
* Connection #0 to host localhost left intact
{"hello": "world"}

It works! In case of any problems you can find working version in this commit.

Adding frontend with figwheel

Coding backend in Clojure is great, but what about the frontend? As you may already know, Clojure could be compiled not only to JVM bytecode, but also to Javascript. This may sound familiar if you used e.g. Coffescript. But ClojureScript philosophy is not only to provide some syntax sugar, but improve your development cycle with great tooling and fully interactive development. Let’s see how to achieve it.

The best way to introduce ClojureScript to a project is figweel. First let’s add fighweel plugin and configuration to project.clj:

:plugins
   ...
   [lein-figwheel "0.3.9"]

And cljsbuild configuration:

:cljsbuild
    {:builds [{:id "dev"
               :source-paths ["src-cljs"]
               :figwheel true
               :compiler {:main       "clojure-web-app.core"
                          :asset-path "js/out"
                          :output-to  "resources/public/js/clojure-web-app.js"
                          :output-dir "resources/public/js/out"}}]}

In short this tells ClojureScript compiler to take sources from src-cljs with figweel support and but resulting JavaScript into resources/public/js/clojure-web-app.js file. So we need to include this file in a simple HTML page:

<!DOCTYPE html>
<head>
</head>
<body>
  <div id="main">
  </div>
  <script src="js/clojure-web-app.js" type="text/javascript"></script>
</body>
</html>

To serve this static file we need to change some defaults and add corresponding route. In system.clj change api-defaults to site-defaults both in require section and base-config function. In example.clj add following route:

(GET "/" [] (io/resource "public/index.html")

Again (reset) in REPL window should reload everything.

But where is our ClojureScript source file? Let’s create file core.cljs in src-cljs/clojure-web-app directory:

(ns ^:figwheel-always clojure-web-app.core)

(enable-console-print!)

(println "hello from clojurescript")

Open another terminal and run lein fighweel. It should compile ClojureScript and print ‘Prompt will show when figwheel connects to your application’. Open http://localhost:3000. Fighweel window should prompt:

To quit, type: :cljs/quit
cljs.user=>

Type (js/alert "hello"). Boom! If everything worked you should see and alert in your browser. Open developers console in your browser. You should see hello from clojurescript printed on the console. Change it in core.cljs to (println "fighweel rocks") and save the file. Without reloading the page your should see updated message. Figweel rocks! Again, in case of any problems, refer to this commit.

In the next post I’ll show how to fetch data from MongoDB, serve it with REST to the broser and write ReactJs/Om components to render it. Stay tuned!