Whether you want to try using OpenJDK 11-ea, GraalVM, Eclipse OpenJ9, or you are stuck needing to build using OpenJDK 6, jabba has got it all. jabba is a cross-platform Java version manager written by Stanley Shyiko (@shyiko).
AdoptOpenJDK 8 and 11
Here’s how we can use jabba on Travis CI to cross build using AdoptOpenJDK 8 and 11:
Power assert (or power assertion) is a variant of assert(...) function that that prints out detailed error message automatically. It was originally implemented by Peter Niederwieser (@pniederw) for Spock, and in 2009 it was merged into Groovy 1.7. Power assert has spread to Ruby, JavaScript, Rust, etc.
Oracle is moving to ship non-LTS JDK every 6 months, and LTS JDK every 3 years. Also it’s converging to OpenJDK. In this scheme, JDK 9 will be EOL in March 2018; JDK 10 will come out in March 2018, and EOL in September 2018; and LTS JDK 11 that replaces JDK 8 in September 2018 will stay with us until 2021.
As we will see quick succession of JDKs in the upcoming months, here’s a how-to on testing your app on JDK 8, JDK 9, and JDK 10 Early Access using Travis CI.
During the SIP-27 trailing commas discussion, one of the thoughts that came to my mind was unifiying some of the commas with semicolons, and take advantage of the semicolon inference.
This holiday break, I somehow got into binge watching Coursera’s Stanford Machine Learning course taught by Andrew Ng. I remember machine learning to be really math heavy, but I found this one more accessible.
Here are some notes for my own use. (I am removing all the fun examples, and making it dry, so if you’re interested in machine learning, you should check out the course or its official notes.)
Future readers might also want to search for “file URI scheme RFC”, and find the latest version. If you’re a programmer, read the RFC. This post is to raise the awareness of the some of the issues around file to URI encoding, but it’s not a substitution.
On Tech Hub blog I demonstrated how to use sbt server from VS Code to display compiler errors from a running sbt session. In this post, I’ll show how to do that for Sublime Text 3 in this post.
cd ~/Library/Application\ Support/Sublime\ Text\ 3/Packages
git clone https://github.com/tomv564/LSP.git
Run ‘Preferences > Package Control > Satisfy Dependencies’
Next, download sbt-server-stdio.js and save it to ~/bin/ or somewhere you keep scripts. sbt server by default uses Unix domain sockets on POSIX systems and named pipe on Windows, but editors seem to expect stdio. The script is a Node script that’s included as our VS Code extension that discovers the socket, and fronts it with stdio.
It’s been a month since sbt 1.0 shipped, and I can finally sit back and think about sbt server again. Using my weekends time, I started hacking on an implementation of Scala language server on top of sbt server.
what is a language server?
A language server is a program that can provide language service to editors like Visual Studio Code, Eclipse Che, and Sublime Text 3 via Language Server Protocol. A typical operation might be textDocument/didOpen, which tells the server that a source file was opened in the editor.
In this post, I’d like to introduce a version scheme that I call Persistent Versioning. Most of the ideas presented in this post are not new or my own. Let me know if there’s already a name for it.
GitHub Pages is a convenient place to host OSS project docs.
This post explains how to use Travis CI to deploy your docs automatically on a pull request merge.
1. Generate a fresh RSA key in some directory
Make a directory outside of your project first.
Pick a key name deploy_yourproject_rsa, so you can distinguish it from other keys.
$ mkdir keys
$ cd keys
$ ssh-keygen -t rsa -b 4096 -C "yours@example.com"Generating public/private rsa key pair.
Enter file in which to save the key (/Users/xxx/.ssh/id_rsa): deploy_website_rsa
Enter passphrase (empty for no passphrase):
Read More…
In the last post that I wrote about Atreus build, I noted that there’s an issue of keyboard positioning:
Even if I can overcome the layout and memorize the various symbol locations, there’s the issue of the placement. If I place the keyboard in between me and the laptop the screen becomes too far.
I solved this issue by making a tray for Atreus that I can position it on top of the MacBook Pro keyboard.
I’ve been asked by a few people on downloading JARs, and then running them from an sbt plugin.
Most recently, Shane Delmore (@shanedelmore) asked me about this at nescala in Brooklyn.
During an unconference session I hacked together a demo, and I continued some more after I came home.
sbt-sidedish
sbt-sidedish is a toolkit for plugin authors to download and run an app on the side from a plugin.
It on its own does not define any plugins.
Here are a few questions I’ve been thinking about:
How should I express data or API?
How should the data be represented in Java or Scala?
How do I convert the data into wire formats such as JSON?
How do I evolve the data without breaking binary compatibility?
limitation of case class
The sealed trait and case class is the idiomatic way to represent datatypes in Scala, but it’s impossible to add fields in binary compatible way. Take for example a simple case class Greeting, and see how it would expand into a class and a companion object:
Gigahorse 0.2.0 is now released. The new change is that it abstracts over two backends. @alexdupre contributed migration from AHC 1.9 to AHC 2.0, which is based on Netty 4 in #12.
In addition, there’s now an experimental Akka HTTP support that I added. #15
Gigahorse 0.1.0 is now released. It is an HTTP client for Scala with Async Http Client underneath. Please see Gigahorse docs for the details. Here’s an example snippet to get the feel of the library.
scala>import gigahorse._
scala>import scala.concurrent._, duration._scala>Gigahorse.withHttp(Gigahorse.config){ http =>val r =Gigahorse.url("http://api.duckduckgo.com").get. addQueryString("q"->"1 + 1","format"->"json")val f = http.run(r,Gigahorse.asString andThen {_.take(60)})Await.result(f,120.seconds)}
There’s a “pattern” that I’ve been thinking about, which arises in some situation while persisting/serializing objects.
To motivate this, consider the following case class:
scala>caseclassUser(name:String, parents:List[User])defined classUserscala>val alice =User("Alice",Nil)alice:User=User(Alice,List())scala>val bob =User("Bob", alice ::Nil)bob:User=User(Bob,List(User(Alice,List())))scala>val charles =User("Charles", bob ::Nil)charles:User=User(Charles,List(User(Bob,List(User(Alice,List())))))scala>val users =List(alice, bob, charles)users:List[User]=List(User(Alice,List()),User(Bob,List(User(Alice,List()))),User(Charles,List(User(Bob,List(User(Alice,List()))))))Read More…
This is part 3 on the topic of sjson-new. See also part 1 and part 2.
Within the sbt code base there are a few places where the persisted data is in the order of hundreds of megabytes that I suspect it becomes a performance bottleneck, especially on machines without an SSD drive.
Naturally, my first instinct was to start reading up on the encoding of Google Protocol Buffers to implement my own custom binary format.
Two months ago, I wrote about sjson-new. I was working on that again over the weekend, so here’s the update.
In the earlier post, I’ve introduced the family tree of JSON libraries in Scala ecosystem, the notion of backend independent, typeclass based JSON codec library. I concluded that we need some easy way of defining a custom codec for it to be usable.
roll your own shapeless
In between the April post and the last weekend, there were flatMap(Oslo) 2016 and Scala Days New York 2016. Unfortunately I wasn’t able to attend flatMap, but I was able to catch Daniel Spiewak’s “Roll Your Own Shapeless” talk in New York. The full flatMap version is available on vimeo, so I recommend you check it out.
I made a new Github organization called foundweekends for people who like coding in the weekends. If you want to join, or have project ideas ping me on twitter or come talk to us on Gitter.
One of the fun way of thinking about software projects is literary analysis. Instead of the actual source code, think of who wrote it when and why (what problem does it solve), and how it’s written (what influenced it).
Within the Scala ecosystem, not too many genre are as rich as the JSON libraries.
In December 2008, the first edition of Programming in Scala came out, which used JSON as an example in the context of parser combinator, and showed that JSON parser can be written in 10 lines of code:
This is a continuation from the sbt 1.0 roadmap that I wrote recently. In this post, I’m going to introduce a new implementation of sbt server. Please post on sbt-dev mailing list for feedback.
The motivation for sbt server is better IDE integration.
A build is a giant, mutable, shared, state, device. It’s called disk! The build works with disk. You cannot get away from disk.
The disk on your machine is fundamentally a stateful thing, and sbt can execute the tasks in parallel only because it has the full control of the effects. Any time you are running both sbt and an IDE, or you’re running multiple instances of sbt against the same build, sbt cannot guarantee the state of the build.
There’s been some discussions around sbt 1.0 lately, so here is a writeup to discuss it. This document is intended to be a mid-term mission statement. A refocus to get something out. Please post on sbt-dev mailing list for feedback.
For me (and for many of the 27 organizers, I imagine) ScalaMatsuri is a lifestyle. It’s true that there was a successful two-day conference in Tokyo with 550 participants. But for us the organizers, the preparation has been going on since February 28th, for 11 months. Despite the fact that my contribution was small, planning ScalaMatsuri 2016 was by far the most amount of involvement I’ve committed to. Through the course of planning months, there were many discussions over Slack, Hangouts, and occasionally even face-to-face. The fun part was coming up with the ideas together, and seeing them materialize. Sometimes, I was the one coming up with radical ideas that were being executed by someone else, while other times, it was the opposite case and I was getting my hands dirty.
For a flexible language like Scala, it’s useful to think of subset of the programming language, like your own personal Good Parts, and opinionated style guides.
setup
To try -Yno-lub, you can drop in the following sbt plugin to project/ynolub.sbt:
addSbtPlugin("com.eed3si9n"%"sbt-ynolub"%"0.2.0")
lub
When Scala’s type inferencer finds type A and type B to unify, it tries to calculate the lub (least upper bounds) of two types with regards to <:<. This process is sometimes called lubbing. Here are some of the examples:
On my way back from Uppsala, my mind wandered to a conversation I had with a collegue about the intuition of monads, which I pretty much butchered at the time. As I was mulling this over, it dawned on me.
monads are fractals
The above is a fractal called Sierpinski triangle, the only fractal I can remember to draw. Fractals are self-similar structure like the above triangle, in which the parts are similar to the whole (in this case exactly half the scale as parent triangle).
Monads are fractals. Given a monadic data structure, its values can be composed to form another value of the data structure. This is why it’s useful to programming, and this is why it occurrs in many situations.
Two days of #ScalaMatsuri ended as a huge success. But for the next year, I’m leaving ourselves a few homeworks to work on. As the title suggests, the next goal that we should aim for is universal access. In Scala language, universal access principle indicates the fact that both methods and fields can be accessed interchangeably from outside.
For a conference, I mean universal access to mean being more inclusive to various groups of people:
This year was the second Scala conference in Japan. We’ve changed the name to ScalaMatsuri, which means Scala festival in Japanese. 300 tickets sold out. With invited guests and free tickets for sponsors, there may have been even more people. The venue was at CyberAgent, which runs blog service and online ad services.
Day 1 kicked off with Martin’s (@ordersky) ‘Evolution of Scala.’ Many people were looking forward to see Martin, so I think it was full house from the get go. During all sessions that I attended, I was busy typing live text translation using my closed-captioning both from English to Japanese, and from Japanese to English along with other members @cbirchall, @cdepillabout, @okapies, and @oe_uia.
Personally, I don’t mind using SublimeText, which is my editor of choice for a while. But I’m also curious about commandline editors since many people taut their ability to code over the network. You could forward X or remote in using some other way and still use Sublime, but let’s see how if goes.
I started working on this Vim setup when I got a new MBP recently. Figured, I can try something new. So, this post is more of a personal memo written by a total newbie, which is what blogs are all about. caveat emptor. In general though, the configuration is mostly inspired by yuroyoro-san’s blog post from a couple years ago.
The need for regular expressions is real. Whenver I need to transform a set of text files it usually ends up with fumbling through the documentation of find command, zsh, and StackOverflow Perl questions. I would rather use Scala instead of muddling through Perl. It’s really the matter of my familiarity than anything else.
For example, I now have over a hundred reStructuredText files that I want to convert into markdown. I first tried pandoc, and it looked mostly ok. As I was going through the details, however, I noticed that many of the code literals were not converting over as formatted. This is because they were formatted using either single ticks or using Interpreted Text. Preprocessing the text with a series of regex replacements should work.
Woke up early yesterday, so I started skimming @xuwei_k’s override blog post. The topic was so intriguing, I got out of the bed and started translating it as the curious case of putting override modifier when overriding an abstract method in Scala. In there he describes the conundrum of providing the default instances to typeclasses by using Scalaz codebase as an example.
Here’s a simplified representation of the problem:
First, a quote from Programming in Scala, 2nd ed. p. 192:
Scala requires [override] modifier for all members that override a concrete member in a parent class. The modifier is optional if a member implements an abstract member with the same name.
In this post, we’ll discuss this “The modififier is optional.” Since overriding an existing method with implementation requires override modifier, and failure to do so would result to a compiler error, there’s not much to talk about for that case. We’ll focus on whether one should put override modifier or not in the case of overring an abtract method. I don’t think there’s going to be any difference in Scala version, but let’s assume the latest stable 2.10.3.
In this post, I will discuss the execution semantics and task sequencing in sbt 0.13. First we will cover the background, and then I will introduce a new experimental plugin sbt-sequential that adds sequential tasks.
background
Mark said:
The sbt model is to have your side effects be local to your task so that as long as dependencies are satisfied, the task can be executed whenever. The win is parallel by default and enabling faster builds in practice.
