duanebester

use .base

-- SQL password message: concat('md5', md5(concat(md5(concat(password, username)), random-salt)))
-- "md58393de45eea6f814e37f41f02540710c"
calculatePassword: Text -> Text -> Bytes -> Text
calculatePassword username password salt = 
    use md5 md5EncodeAscii md5Encode
    userpassMd5 = md5EncodeAscii (password ++ username)
    use Text toUtf8
    userpassMd5Bytes = (toUtf8 userpassMd5)

pchiusano

unique ability Located d where
  location : d a -> Location {} 

unique ability Storage.Distributed d where
  restore : d a -> a
  save : a -> d a
  saveNear : d x -> a -> d a

unique type Kit d m a
  = Empty

lexi-lambda

With scoped effects, handlers must be a part of the program

It is seductive to imagine that effect handlers in an algebraic effect system are not part of the program itself but metalanguage-level folds over the program tree. And in traditional free-like formulations, this is in fact the case. The Eff monad represents the program tree, which has only two cases:

data Eff effs a where
  Pure :: a -> Eff effs a
  Op :: Op effs a -> (a -> Eff effs b) -> Eff effs b

data Op effs a where

emiflake

namespace RFC where
  parseDigit = oneOfChars [?0, ?1, ?2, ?3, ?4, ?5, ?6, ?7, ?8, ?9]
  parseHex = Unipar.satisfy isHexDigit "wasn't a hex digit"
  parseCRLF = (ch ?\r Unipar.>> ch ?\n)

type RawHeaders
  = RawHeaders (Map Text Text)

type Request
  = Request HostName Text RawHeaders

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

milessabin

object Demo {
  // A couple of type classes with type members ...
  trait Foo[T] {
    type A
  }

  object Foo {
    implicit val fooIS = new Foo[Int] { type A = String }
  }

tpolecat

import scalaz.{ Free, Coyoneda, Monad, ~>, State, NonEmptyList }
import scalaz.std.function._
import scalaz.syntax.monad._
import scalaz.effect.IO

import scala.util.Random

object freecoyo extends App {

  // An algebra of primitive operations in the context of a random number generator

djspiewak

package com.rr.experiment

import org.specs2.ScalaCheck
import org.specs2.mutable._

import org.scalacheck._

import scalaz._

import scodec._

david-christiansen

module FizzBuzzC

%default total

-- Dependently typed FizzBuzz, constructively

-- A number is fizzy if it is evenly divisible by 3
data Fizzy : Nat -> Type where
  ZeroFizzy : Fizzy 0
  Fizz : Fizzy n -> Fizzy (3 + n)

piscisaureus

Locate the section for your github remote in the .git/config file. It looks like this:

[remote "origin"]
	fetch = +refs/heads/*:refs/remotes/origin/*
	url = git@github.com:joyent/node.git

Now add the line fetch = +refs/pull/*/head:refs/remotes/origin/pr/* to this section. Obviously, change the github url to match your project's URL. It ends up looking like this: