quelgar

Every Argument for Static Typing Applies to Typed Errors

Think of all the arguments you've heard as to why static typing is desirable — every single one of those arguments applies equally well to using types to represent error conditions.

An odd thing I’ve observed about the Scala community is how many of its members believe that a) a language with a sophisticated static type system is very valuable; and b) that using types for error handling is basically a waste of time. If static types are useful—and if you like Scala, presumably you think they are—then using them to represent error conditions is also useful.

Here's a little secret of functional programming: errors aren't some special thing that operate under a different set of rules to everything else. Yes, there are a set of common patterns we group under the loose heading "error handling", but fundamentally we're just dealing with more values. Values that can have types associated with them. There's absolutely no reason why the benefits of static ty

d1egoaz

If you want to learn Scala, I’d suggest:

• Install IntelliJ + Scala Plugin
• Don’t do the Coursera courses yet.
• Don’t do the “red book” Functional Programming in Scala yet.
• Do: http://underscore.io/books/
  • Essential Scala
  • Essential Play
  • Essential Slick
• Do Scala for the Impatient: https://www.amazon.com/Scala-Impatient-Cay-S-Horstmann/dp/0321774094
• The Neophyte’s Guide to Scala http://danielwestheide.com/scala/neophytes.html

rondy

FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.

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Effective Engineer - Notes

• By Edmond Lau
• Highly Recommended 👍
• http://www.theeffectiveengineer.com/

What's an Effective Engineer?

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

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

cdmckay

package actions

import play.api.Play
import play.api.Play.current
import play.api.mvc._

import scala.concurrent.Future

object HttpsAction extends ActionBuilder[Request] with Results {
    def invokeBlock[A](request: Request[A], block: (Request[A]) => Future[Result]) = {

etorreborre

"U2" has a concert that starts in 17 minutes and they must all
cross a bridge to get there. They stand on the same side of the
bridge. It is night. There is one flashlight. A maximum of two
people can cross at one time, and they must have the flashlight
with them. The flashlight must be walked back and forth. A
pair walk together at the rate of the slower man's pace:

 Bono 1 minute to cross
 Edge 2 minutes to cross
 Adam 5 minutes to cross

hellerbarde

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns             
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs