martinheld

JWT Kong Example

• Get and Start Kong and Co

git clone git@github.com:Mashape/docker-kong.git
cd docker-kong/compose
docker-compose up

• Create Kong API Route

onjin

postgres:
  image: postgres:9.4
  volumes:
    - ./init.sql:/docker-entrypoint-initdb.d/init.sql

johanandren

import akka.actor.ActorSystem
import akka.stream._
import akka.stream.scaladsl._

import scala.io.StdIn
import scala.util.Random

object SimplePartitionSample extends App {

  implicit val system = ActorSystem()

eamelink

Recursion and Trampolines in Scala

Recursion is beautiful. As an example, let's consider this perfectly acceptable example of defining the functions even and odd in Scala, whose semantics you can guess:

def even(i: Int): Boolean = i match {
  case 0 => true
  case _ => odd(i - 1)
}

def odd(i: Int): Boolean = i match {

androidfred

Haskell, Stack and Intellij IDEA IDE setup tutorial how to get started

Upon completion you will have a sane, productive Haskell environment adhering to best practices.

Basics

• Haskell is a programming language.
• Stack is tool for Haskell projects. (similar tools for other languages include Maven, Gradle, npm, RubyGems etc)
• Intellij IDEA IDE is a popular IDE.

Install required libraries

sudo apt-get install libtinfo-dev libghc-zlib-dev libghc-zlib-bindings-dev

jpallari

object Main extends App {
  AvoidLosingGenericType.run()
  AvoidMatchingOnGenericTypeParams.run()
  TypeableExample.run()
  TypeTagExample.run()
}

class Funky[A, B](val foo: A, val bar: B) {
  override def toString: String = s"Funky($foo, $bar)"
}

notxcain

trait OrderedAtLeastOnceDelivery extends AtLeastOnceDelivery {
  type DeliveryId = Long

  private case class Delivery(destination: ActorPath, deliveryIdToMessage: (DeliveryId) => Any)

  private val deliveryQueue = scala.collection.mutable.Queue.empty[Delivery]

  override def deliver(destination: ActorPath)(deliveryIdToMessage: (DeliveryId) => Any): Unit = {
    if (super.numberOfUnconfirmed == 0) {
      super.deliver(destination)(deliveryIdToMessage)

dannycoates

Experimenting with AWS Lambda for ETL

A lot of us are interested in doing more analysis with our service logs so I thought I'd share an experiment I'm doing with Sync. The main idea is to transform the raw logs into something that'll be nice to query and generate reports with in Redshift.

The Pipeline

Logs make their way into an S3 bucket (lets call it the 'raw' bucket) where we've got a lambda listening for new data. This lambda reads the raw heka protobuf gzipped data, does some transformation and writes a new file to a different S3 bucket (the 'processed' bucket) in a format that is redshift friendly (like json or csv). There's another lambda listening on the processed bucket that loads this data into Redshift.

DrBoolean

const daggy = require('daggy')
const compose = (f, g) => x => f(g(x))
const id = x => x

//===============Define Coyoneda=========
const Coyoneda = daggy.tagged('x', 'f')

Coyoneda.prototype.map = function(f) {
  return Coyoneda(this.x, compose(f, this.f))
}

fancellu

object MergeSort {

		// recursive merge of 2 sorted lists
	def merge(left: List[Int], right: List[Int]): List[Int] =
        (left, right) match {
	        case(left, Nil) => left
	        case(Nil, right) => right
	        case(leftHead :: leftTail, rightHead :: rightTail) =>
	          if (leftHead < rightHead) leftHead::merge(leftTail, right)
	          else rightHead :: merge(left, rightTail)