mkaz

10 Scala One Liners to Impress Your Friends

Here are 10 one-liners which show the power of scala programming, impress your friends and woo women; ok, maybe not. However, these one liners are a good set of examples using functional programming and scala syntax you may not be familiar with. I feel there is no better way to learn than to see real examples.

Updated: June 17, 2011 - I'm amazed at the popularity of this post, glad everyone enjoyed it and to see it duplicated across so many languages. I've included some of the suggestions to shorten up some of my scala examples. Some I intentionally left longer as a way for explaining / understanding what the functions were doing, not necessarily to produce the shortest possible code; so I'll include both.

1. Multiple Each Item in a List by 2

The map function takes each element in the list and applies it to the corresponding function. In this example, we take each element and multiply it by 2. This will return a list of equivalent size, compare to o

OlivierBlanvillain

Revisiting Tagless Final Interpreters

Tageless Final interpreters are an alternative to the traditional Algebraic Data Type (and generalized ADT) based implementation of the interpreter pattern. This document presents the Tageless Final approach with Scala, and shows how Dotty with it's recently added implicits functions makes the approach even more appealing. All examples are direct translations of their Haskell version presented in the Typed Tagless Final Interpreters: Lecture Notes (section 2).

The interpreter pattern has recently received a lot of attention in the Scala community. A lot of efforts have been invested in trying to address the biggest shortcomings of ADT/GADT based solutions: extensibility. One can first look at cats' Inject typeclass for an implementation of [Data Type à la Carte](http://www.cs.ru.nl/~W.Swierstra/Publications/DataTypesA

beala

import Control.Monad.State.Strict
import qualified Data.Map.Strict as Map

-- This is the standard fibonacci implementation with exponential complexity.
naiveFibs :: Int -> Integer
naiveFibs 0 = 0
naiveFibs 1 = 1
naiveFibs n = naiveFibs (n-2) + naiveFibs (n-1)

-- For reference, calculating the 35th fibonacci takes 9.49 sec.

non

import spire.algebra._
import spire.implicits._

object Transducer {
  type RF[R, A] = (R, A) => R

  def apply[A, B](f: A => B) =
    new Transducer[B, A] {
      def apply[R](rf: RF[R, B]): RF[R, A] = (r, a) => rf(r, f(a))
    }

judotens

#!/bin/bash
# scrape all leaked bitcoin private keys into a tab separated text
# <private key>\t<bitcoin_address>
#
# support autoresume. just add these line into your cron : * * * * bash bitcoinkey.sh
# results stored on keys.txt

if [ ! -f last.page ]; then prev=`echo 0`; else prev=`cat last.page`; fi;
if [ -z $1 ]; then akhir=`echo 10`; else akhir=`echo $1`; fi;
abis=$(($prev+$akhir))

djspiewak

Collections Redesign Proposal

I'm going to start off by motivating what I'm doing here. And I want to be clear that I'm not "dissing" the existing collections implementation or anything as unproductively negative as that. It was a really good experiment, it was a huge step forward given what we knew back in 2.8, but now it's time to learn from that experiment and do better. This proposal uses what I believe are the lessons we can learn about what worked, what didn't work, and what is and isn't important about collections in Scala.

This is going to start out sounding really negative and pervasively dismissive, but bear with me! There's a point to all my ranting. I want to be really clear about my motivations for the proposal being the way that it is.

Problems

Generic Interfaces

KodrAus

Profiling performance

Using perf:

$ perf record -g binary
$ perf script | stackcollapse-perf.pl | rust-unmangle | flamegraph.pl > flame.svg

NOTE: See @GabrielMajeri's comments below about the -g option.

RxDx

Create a file:
$ pico /Users/Shared/logoutHook.sh

File content:
#!/bin/bash
say 'Hasta la vista baby!'

Set exuction permission:
$ sudo chmod +x /Users/Shared/logoutHook.sh

jkeefe

BLUETOOTH SNIFFER

Working to sniff Bluetooth Low Energy with the adafruit sniffer

For more information, see this blog post

Going the python route, as described here

before installing pySerial, did ...

viktorklang

import scala.concurrent.duration._
import scala.concurrent.ExecutionContext
import scala.concurrent.Future
import akka.pattern.after
import akka.actor.Scheduler

/**
 * Given an operation that produces a T, returns a Future containing the result of T, unless an exception is thrown,
 * in which case the operation will be retried after _delay_ time, if there are more possible retries, which is configured through
 * the _retries_ parameter. If the operation does not succeed and there is no retries left, the resulting Future will contain the last failure.