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Home > Programming > Reactive Programming > Clojure Reactive Programming
Clojure Reactive Programming
Clojure Reactive Programming

Clojure Reactive Programming: Design and implement highly reusable reactive applications by integrating different frameworks with Clojure

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Clojure Reactive Programming

Chapter 2. A Look at Reactive Extensions

Reactive Extensions—or Rx—is a Reactive Programming library from Microsoft to build complex asynchronous programs. It models time-varying values and events as observable sequences and is implemented by extending the Observer design pattern.

Its first target platform was .NET, but Netflix has ported Rx to the JVM under the name RxJava. Microsoft also develops and maintains a port of Rx to JavaScript called RxJS, which is the tool we used to build the sine-wave application. The two ports work a treat for us since Clojure runs on the JVM and ClojureScript in JavaScript environments.

As we saw in Chapter 1, What is Reactive Programming?, Rx is inspired by Functional Reactive Programming but uses different terminology. In FRP, the two main abstractions are behaviors and events. Although the implementation details are different, observable sequences represent events. Rx also provides a behavior-like abstraction through another data...

The Observer pattern revisited

In Chapter 1, What is Reactive Programming?, we saw a brief overview of the Observer design pattern and a simple implementation of it in Clojure using watches. Here's how we did it:

(def numbers (atom []))

(defn adder [key ref old-state new-state]
  (print "Current sum is " (reduce + new-state)))

(add-watch numbers :adder adder)

In the preceding example, our observable subject is the var, numbers. The observer is the adder watch. When the observable changes, it pushes its changes to the observer synchronously.

Now, contrast this to working with sequences:

(->> [1 2 3 4 5 6]
     (map inc)
     (filter even?)
     (reduce +))

This time around, the vector is the subject being observed and the functions processing it can be thought of as the observers. However, this works in a pull-based model. The vector doesn't push any elements down the sequence. Instead, map and friends ask the sequence for more elements. This is a synchronous operation...

Creating Observables

This chapter is all about Reactive Extensions, so let's go ahead and create a project called rx-playground that we will be using in our exploratory tour. We will use RxClojure (see https://github.com/ReactiveX/RxClojure), a library that provides Clojure bindings for RxJava() (see https://github.com/ReactiveX/RxJava):

$ lein new rx-playground

Open the project file and add a dependency on RxJava's Clojure bindings:

(defproject rx-playground "0.1.0-SNAPSHOT"
  :description "FIXME: write description"
  :url "http://example.com/FIXME"
  :license {:name "Eclipse Public License"
            :url "http://www.eclipse.org/legal/epl-v10.html"}
  :dependencies [[org.clojure/clojure "1.5.1"]
                 [io.reactivex/rxclojure "1.0.0"]])"]])

Now, fire up a REPL in the project's root directory so that we can start creating some observables:

$ lein repl

The first thing we need to do is import...

Manipulating Observables

Now that we know how to create observables, we should look at what kinds of interesting things we can do with them. In this section, we will see what it means to treat Observables as sequences.

We'll start with something simple. Let's print the sum of the first five positive even integers from an observable of all integers:

(rx/subscribe (->> (Observable/interval 1 TimeUnit/MICROSECONDS)
                   (rx/filter even?)
                   (rx/take 5)
                   (rx/reduce +))
                   prn-to-repl)

This is starting to look awfully familiar to us. We create an interval that will emit all positive integers starting at zero every 1 microsecond. Then, we filter all even numbers in this observable. Obviously, this is too big a list to handle, so we simply take the first five elements from it. Finally, we reduce the value using +. The result is 20.

To drive home the point that programming with observables really is just like operating...

Flatmap and friends

In the previous section, we learned how to transform and combine observables with operations such as map, reduce, and zip. However, the two observables above—musicians and bands—were perfectly capable of producing values on their own. They did not need any extra input.

In this section, we examine a different scenario: we'll learn how we can combine observables, where the output of one is the input of another. We encountered flatmap before in Chapter 1, What is Reactive Programming? If you have been wondering what its role is, this section addresses exactly that.

Here's what we are going to do: given an observable representing a list of all positive integers, we'll calculate the factorial for all even numbers in that list. Since the list is too big, we'll take five items from it. The end result should be the factorials of 0, 2, 4, 6, and 8, respectively.

The first thing we need is a function to calculate the factorial of a number n, as well...

Error handling

A very important aspect of building reliable applications is knowing what to do when things go wrong. It is naive to assume that the network is reliable, that hardware won't fail, or that we, as developers, won't make mistakes.

RxJava embraces this fact and provides a rich set of combinators to deal with failure, a few of which we examine here.

OnError

Let's get started by creating a badly behaved observable that always throws an exception:

(defn exceptional-obs []
  (rx/observable*
   (fn [observer]
     (rx/on-next observer (throw (Exception. "Oops. Something went wrong")))
     (rx/on-completed observer))))

Now let's watch what happens if we subscribe to it:

(rx/subscribe (->> (exceptional-obs)
                   (rx/map inc))
              (fn [v] (prn-to-repl "result is " v)))

;; Exception Oops. Something went wrong  rx-playground.core/exceptional-obs/fn--1505

The exception thrown by exceptional-obs isn't caught anywhere so...

The Observer pattern revisited

In Chapter 1, What is Reactive Programming?, we saw a brief overview of the Observer design pattern and a simple implementation of it in Clojure using watches. Here's how we did it:

(def numbers (atom []))

(defn adder [key ref old-state new-state]
  (print "Current sum is " (reduce + new-state)))

(add-watch numbers :adder adder)

In the preceding example, our observable subject is the var, numbers. The observer is the adder watch. When the observable changes, it pushes its changes to the observer synchronously.

Now, contrast this to working with sequences:

(->> [1 2 3 4 5 6]
     (map inc)
     (filter even?)
     (reduce +))

This time around, the vector is the subject being observed and the functions processing it can be thought of as the observers. However, this works in a pull-based model. The vector doesn't push any elements down the sequence. Instead, map and friends ask the sequence for more elements. This is a synchronous operation.

Rx makes sequences...

Creating Observables

This chapter is all about Reactive Extensions, so let's go ahead and create a project called rx-playground that we will be using in our exploratory tour. We will use RxClojure (see https://github.com/ReactiveX/RxClojure), a library that provides Clojure bindings for RxJava() (see https://github.com/ReactiveX/RxJava):

$ lein new rx-playground

Open the project file and add a dependency on RxJava's Clojure bindings:

(defproject rx-playground "0.1.0-SNAPSHOT"
  :description "FIXME: write description"
  :url "http://example.com/FIXME"
  :license {:name "Eclipse Public License"
            :url "http://www.eclipse.org/legal/epl-v10.html"}
  :dependencies [[org.clojure/clojure "1.5.1"]
                 [io.reactivex/rxclojure "1.0.0"]])"]])

Now, fire up a REPL in the project's root directory so that we can start creating some observables:

$ lein repl

The first thing we need to do is import RxClojure, so let's get this out of the way by typing the following in the REPL:

(require...
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Description

If you are a Clojure developer who is interested in using Reactive Programming to build asynchronous and concurrent applications, this book is for you. Knowledge of Clojure and Leiningen is required. Basic understanding of ClojureScript will be helpful for the web chapters, although it is not strictly necessary.

What you will learn

  • Understand the key abstractions of Functional Reactive Programming (FRP) and Compositional Event Systems (CES)
  • Discover how to think in terms of timevarying values and event streams
  • Create, compose, and transform Observable sequences with Reactive Extensions
  • Create a CES framework from scratch using core.async as its foundation
  • Build a simple ClojureScript game using Reagi
  • Integrate Om and RxJS in a web application
  • Implement a reactive API to Amazon Web Services
  • Discover approaches to backpressure and error handling
  • Get to grips with futures and learn where they fit in

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Mar 23, 2015
Length: 232 pages
Edition : 1st
Language : English
ISBN-13 : 9781783986675
Vendor :
Eclipse Foundation
Category :
Programming
Languages :
Clojure
Concepts :
Reactive Programming

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Product Details

Publication date : Mar 23, 2015
Length: 232 pages
Edition : 1st
Language : English
ISBN-13 : 9781783986675
Vendor :
Eclipse Foundation
Category :
Programming
Languages :
Clojure
Concepts :
Reactive Programming

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Table of Contents

12 Chapters
1. What is Reactive Programming? Chevron down icon Chevron up icon
1. What is Reactive Programming?
A taste of Reactive Programming
A bit of history
Signals and events
Implementation challenges
Applications of FRP
Summary
2. A Look at Reactive Extensions Chevron down icon Chevron up icon
2. A Look at Reactive Extensions
The Observer pattern revisited
Creating Observables
Manipulating Observables
Flatmap and friends
Error handling
Backpressure
Summary
3. Asynchronous Programming and Networking Chevron down icon Chevron up icon
3. Asynchronous Programming and Networking
Building a stock market monitoring application
Rolling averages
Identifying problems with our current approach
Removing incidental complexity with RxClojure
Summary
4. Introduction to core.async Chevron down icon Chevron up icon
4. Introduction to core.async
Asynchronous programming and concurrency
core.async
Rewriting the stock market application with core.async
Error handling
Backpressure
Transducers
Summary
5. Creating Your Own CES Framework with core.async Chevron down icon Chevron up icon
5. Creating Your Own CES Framework with core.async
A minimal CES framework
Exercises
A respondent application
CES versus core.async
Summary
6. Building a Simple ClojureScript Game with Reagi Chevron down icon Chevron up icon
6. Building a Simple ClojureScript Game with Reagi
Setting up the project
Reagi and other CES frameworks
Summary
7. The UI as a Function Chevron down icon Chevron up icon
7. The UI as a Function
The problem with complex web UIs
Enter React.js
ClojureScript and Om
Building a simple Contacts application with Om
Intercomponent communication
Exercises
Summary
8. Futures Chevron down icon Chevron up icon
8. Futures
Clojure futures
Fetching data in parallel
Imminent – a composable futures library for Clojure
The movies example revisited
Futures and blocking IO
Summary
9. A Reactive API to Amazon Web Services Chevron down icon Chevron up icon
9. A Reactive API to Amazon Web Services
The problem
Infrastructure automation
AWS resources dashboard
CloudFormation
EC2
RDS
Designing the solution
Exercises
Summary
A. The Algebra of Library Design Chevron down icon Chevron up icon
A. The Algebra of Library Design
The semantics of map
Finding the average of ages
Applicative Functors
Gathering stats about ages
Monads
Summary
B. Bibliography Chevron down icon Chevron up icon
B. Bibliography
Index Chevron down icon Chevron up icon
Index

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Lucas Medeiros Reis Aug 31, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is an intermediate to advanced book on Clojure and Clojurescript programming. It's a selection of techniques for concurrency, asynchronous and reactive programming, with a perfect balance of practice and theory.Chapter 4, on core async, is a good example is chapter 4. Borges outlines the issues with using callbacks to deal with concurrency, and he also discusses Communicating Sequential Processes as a solution. That's the theory. Then, he shows an implementation of this solution using Futures, and also explains the core async library. The rest of the chapter is an implementation of a toy stock market app. This to be the best material on learning core async that I've found.The other chapters are just as good. Don't miss it if you are interested in taking your Clojure skills to the next level.
Amazon Verified review Amazon
Claudio Natoli Jul 08, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I was fortunate to have seen a small part of this title ahead of print; consequently, I had high hopes for the full published work, and was not disappointed.This title is a solid compendium of FRP in Clojure. After a brief introduction to the history, terms and patterns of FRP, you'll find yourself reading about such topics as Rx, asynchronous networking, core.async, Om, futures and more, with numerous examples covering at times both Clojure and ClojureScript.On the topic of examples, one highlight of this book is the frequent revisiting of a particular problem or snippet, with alternative approaches, as motivating examples for how Reactive Programming and/or different libraries and patterns can be leveraged. For instance, the Futures chapter develops an example using clojure.core futures, and then illustrates some of the difficulties in their application by constrasting with an alternative library developed by the author.While a broad range of concepts are covered, the material should be accessible even to those relatively new to Clojure (if you know what "lein" is, you're good to go!)
Amazon Verified review Amazon
neuronsong Nov 19, 2015
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I would gladly buy from this seller again.
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Amazon Customer May 31, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This short, focused book nicely covers both the concepts and clojure/clojurescript applications of Reactive programming (FRP). Reading it will give you a nice, efficient push up the learning curve. There's no better praise for a technical book, in my view.
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Amazing book, I highly recommend it!
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About the author

Profile icon Leonardo Borges
Leonardo Borges
LinkedIn icon Github icon
Leonardo Borges is a programming languages enthusiast who loves writing code, contributing to open source software, and speaking on subjects he feels strongly about. He has used Clojure professionally, both as a lead consultant at ThoughtWorks and as a development team lead at Atlassian, where he helped build real-time collaborative editing technology. Leonardo is currently the CTO for MODRON. Apart from this book, he contributed a couple of chapters to Clojure Cookbook, O'Reilly. Leonardo founded and currently runs the Sydney Clojure User Group in Australia. He also writes posts about software, with a focus on functional programming, on his website. When he isn't writing code, he enjoys riding motorcycles, weightlifting, and playing the guitar.
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  • They are lower price than print
  • They save resources and space
What is an eBook? Chevron down icon Chevron up icon

Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

When you have purchased an eBook, simply login to your account and click on the link in Your Download Area. We recommend you saving the file to your hard drive before opening it.

For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.