New and upcoming Finagle examples

Part of my role as an open source advocate for Scala projects at Twitter involves talking to developers outside of Twitter about how we can make our open source projects more widely useful and accessible, and one of the most common requests for Finagle is for more introductory tutorials and examples.

One of the steps we’re taking in this direction is a major overhaul of finagle-example , which we’ll be moving out of the main Finagle repository and into its own project under the Finagle organization on GitHub. At the same time we’ll be filling out the top-level introduction to the examples (which is currently a little bare), adding more detailed API documentation, providing better example coverage for Finagle subprojects, and creating a larger set of Java examples to show off our new work on improving Java compatibility.

We’re also working on several stand-alone example projects and tutorials, including the Finagle Name Finder, which provides a simple Scala wrapper for a few pieces of OpenNLP, a Java library for natural language processing, and uses that wrapper to define a named entity recognition RPC service built on Finagle and Thrift. You can start up a name finding service in your SBT console with just a few lines of code:

import com.twitter.finagle.Thrift import com.twitter.finagle.examples.names.thriftscala._ val server = SafeNameRecognizerService . create ( langs = Seq ( "en" ), numThreads = 4 , numRecognizers = 4 ) map { service => Thrift . serveIface ( "localhost:9090" , service ) } onSuccess { _ => println ( "Server started successfully" ) } onFailure { ex => println ( "Could not start the server: " + ex ) }

You can then create a client (either locally in the same console, or on another machine):

import com.twitter.finagle.Thrift import com.twitter.finagle.examples.names.thriftscala._ val client = Thrift . newIface [ NameRecognizerService.FutureIface ]( "localhost:9090" )

And feed it a document:

val doc = """ An anomaly which often struck me in the character of my friend Sherlock Holmes was that, although in his methods of thought he was the neatest and most methodical of mankind, and although also he affected a certain quiet primness of dress, he was none the less in his personal habits one of the most untidy men that ever drove a fellow-lodger to distraction. Not that I am in the least conventional in that respect myself. The rough-and-tumble work in Afghanistan, coming on the top of a natural Bohemianism of disposition, has made me rather more lax than befits a medical man. """ client . findNames ( "en" , doc ) onSuccess { response => println ( "People: " + response . persons . mkString ( ", " )) println ( "Places: " + response . locations . mkString ( ", " )) } onFailure { ex => println ( "Something bad happened: " + ex . getMessage ) }

And the service will tokenize the document, identify parts of speech, attempt to find all the names of people, places, and organizations, and promptly return the results:

People: Sherlock Holmes Places: Afghanistan

When you start a service, you can have OpenNLP recognizers loaded into memory for a given set of languages, but the service can also load languages from disk for individual requests—for example, we’ve only loaded the English-language models for the service we started above, but we could also copy a set of Spanish-language models into our models directory, and then our client could ask to use them:

val esDoc = """ Alrededor de 1902 fue el primero en aplicar una descarga eléctrica en un tubo sellado y con gas neón con la idea de crear una lámpara. Inspirado en parte por la invención de Daniel McFarlan Moore, la lámpara de Moore, Claude inventó la lámpara de neón mediante la descarga eléctrica de un gas inerte comprobando que el brillo era considerable. """ val result = client . findNames ( "es" , esDoc )

We’re using the Name Finder project in a new “Finagle Essentials” course at Twitter University, and the slides for that course go into more detail about how the implementation works. The project is currently designed to fit into an overview of the fundamental abstractions behind Finagle, and to demonstrate just how easy it is to get a basic (but useful) Finagle service up and running, but over the next few months we’ll be expanding it to show off more of Finagle’s capabilities.

We’re also working on a tutorial that walks through the implementation of a Finagle protocol for scodec, a Scala binary serialization library that’s part of the Typelevel group of projects. If you’re interested in helping out with this kind of tutorial development, or if you have a Finagle example project, blog post, etc. that you’d like us to feature, or if you just have questions, please get in touch via @finagle or the Finaglers mailing list, and be sure to watch this space for updates as we continue to improve our documentation and examples.