huntc

// Re-creates https://doc.akka.io/docs/akka/current/typed/actors.html#first-example

// The messages

struct Greet {
    whom: String,
    reply_to: ActorRef<Greeted>,
}

struct Greeted {

calvinlfer

import akka.stream._
import akka.stream.scaladsl._
/***
  * Example based on numBuckets = 3
  *                                          --- bucket 1 flow --- ~mapAsync(parallelism)~ ---
  *                   |------------------| /                                                  \|---------------|
  * Open inlet[A] --- | Partition Fan Out|  --- bucket 2 flow --- ~mapAsync(parallelism)~ -----| Merge Fan In  | --- Open outlet[B]
  *                   |------------------| \                                                  /|---------------|
  *                                         --- bucket 3 flow --- ~mapAsync(parallelism)~ ---
  *

umidjons

Download Audio from YouTube

-i - ignore errors

-c - continue

-t - use video title as file name

--extract-audio - extract audio track

wsargent

package controllers

import javax.inject._
import play.api.mvc._

@Singleton
class TracerBulletController @Inject() extends Controller {
  private val logger = org.slf4j.LoggerFactory.getLogger("application")

  /*

benjchristensen

Response to https://twitter.com/jeffreymaxwell/status/705760483391963136 requiring more than the 77 characters left on Twitter.

DISCLAIMER: The quality of writing and thinking here is aligned with a Twitter conversation, not a blog post, presentation, or book ;-)

Synchronous RESTful communication between Microservices is an anti-pattern ... you seem to being saying that the Netflix architecture (hystrix, eureka, ribbon, ..) is broken ... hmm what would @benjchristensen say?

viktorklang

alias gbr='git for-each-ref --sort="-authordate:iso8601" --format=" %(color:green)%(authordate:iso8601)%09%(color:white)%(refname:short)" refs/heads'

gregoryyoung

f(events) -> state
    match f(state, event) -> state

f(state, command) -> events

djspiewak

Introduction to scalaz-stream

Every application ever written can be viewed as some sort of transformation on data. Data can come from different sources, such as a network or a file or user input or the Large Hadron Collider. It can come from many sources all at once to be merged and aggregated in interesting ways, and it can be produced into many different output sinks, such as a network or files or graphical user interfaces. You might produce your output all at once, as a big data dump at the end of the world (right before your program shuts down), or you might produce it more incrementally. Every application fits into this model.

The scalaz-stream project is an attempt to make it easy to construct, test and scale programs that fit within this model (which is to say, everything). It does this by providing an abstraction around a "stream" of data, which is really just this notion of some number of data being sequentially pulled out of some unspecified data source. On top of this abstraction, sca

acolyer

Internet Scale Services Checklist

A checklist for designing and developing internet scale services, inspired by James Hamilton's 2007 paper "On Desgining and Deploying Internet-Scale Services."

• http://mvdirona.com/jrh/talksandpapers/jamesrh_lisa.pdf

Basic tenets

• Does the design expect failures to happen regularly and handle them gracefully?
• Have we kept things as simple as possible?

grugq

Operational PGP

This is a guide on how to email securely.

There are many guides on how to install and use PGP to encrypt email. This is not one of them. This is a guide on secure communication using email with PGP encryption. If you are not familiar with PGP, please read another guide first. If you are comfortable using PGP to encrypt and decrypt emails, this guide will raise your security to the next level.