chitchcock

Stevey's Google Platforms Rant

I was at Amazon for about six and a half years, and now I've been at Google for that long. One thing that struck me immediately about the two companies -- an impression that has been reinforced almost daily -- is that Amazon does everything wrong, and Google does everything right. Sure, it's a sweeping generalization, but a surprisingly accurate one. It's pretty crazy. There are probably a hundred or even two hundred different ways you can compare the two companies, and Google is superior in all but three of them, if I recall correctly. I actually did a spreadsheet at one point but Legal wouldn't let me show it to anyone, even though recruiting loved it.

I mean, just to give you a very brief taste: Amazon's recruiting process is fundamentally flawed by having teams hire for themselves, so their hiring bar is incredibly inconsistent across teams, despite various efforts they've made to level it out. And their operations are a mess; they don't real

perival

A Simple Meta-Data Model for a Graph Database

Setting up a Meta-Data Framework

This GraphGist is a quick exploration of a simple meta-data administration which can be used to store the structure of the nodes and relationships in a graph database like neo4j.

The data that is set up here could be used in an application layer to provide tailored

hackwaly

var go;
var callcc;

(function () {
  function noop() {}

  var iteratorConstructor = function* () {}().constructor;
  function isIterator(p) {
    return p != null && p.constructor === iteratorConstructor;
  }

zenparsing

const unwrapSymbol = Symbol();

function unwrap(x) {

    if (this == null)
        return this;
    
    let f = this[unwrapSymbol];
    
    if (typeof f !== "function")

Avaq

const I  = x => x
const K  = x => y => x
const A  = f => x => f (x)
const T  = x => f => f (x)
const W  = f => x => f (x) (x)
const C  = f => y => x => f (x) (y)
const B  = f => g => x => f (g (x))
const S  = f => g => x => f (x) (g (x))
const S_ = f => g => x => f (g (x)) (x)
const S2 = f => g => h => x => f (g (x)) (h (x))

safareli

• Monads are Trees with Grafting
• Understanding F-Algebras
• The Interpreter Pattern Revisited
• Difference between free monads and fixpoints of functors?
• What is the “Free Monad + Interpreter” pattern?
• What are free monads?
• ScalaZ - Getting to grips with the Free Monad
• A Modern Architecture for FP
• Freer Monad, More Extensible Effects
• Dead-Simple Dependency Injection

enghqii

using System;
using System.Collections;
using System.Collections.Generic;

namespace Generator3
{
    class Program
    {
        // classic Generator
        static IEnumerable<string> Script()

jdegoes

Applied Functional Programming with Scala - Notes

Copyright © 2016-2018 Fantasyland Institute of Learning. All rights reserved.

1. Mastering Functions

A function is a mapping from one set, called a domain, to another set, called the codomain. A function associates every element in the domain with exactly one element in the codomain. In Scala, both domain and codomain are types.

val square : Int => Int = x => x * x

eiriktsarpalis

open System
open System.Runtime.CompilerServices

type SymbolicException =
    {
        Source : Exception
        Stacktrace : string list
    }

module SymbolicException =

b-studios

When defining complex functions in pointfree style, I often find myself switching to pointful style. Sometimes, I even convert to ANF and annotate the types to understand the steps.

After completing the function definition, I often convert back to pointfree style for conciseness. End of the story: To understand it again a couple of weeks later, I start expanding to annotated pointful again.

The small 10-lines library at the end of this post allows to define pointfree functions with intermediate type annotations.

Credits: Agda and EqReasoning for syntactical inspiration.