14427

use std::rc::Rc;

trait HKT<U> {
    type C; // Current type
    type T; // Type with C swapped with U
}

macro_rules! derive_hkt {
    ($t:ident) => {
        impl<T, U> HKT<U> for $t<T> {

kalefranz

#!/usr/bin/env python
import hashlib
import json
import logging
import logging.handlers
import os
import shutil
import sys
import tempfile
import urllib

ocharles

{-# LANGUAGE GeneralizedNewtypeDeriving #-}

import Control.Monad.IO.Class
import Control.Monad.Trans.Class
import Prelude hiding (log)

--------------------------------------------------------------------------------
-- The API for cloud files.
class Monad m => MonadCloud m where
  saveFile :: Path -> Bytes -> m ()

OlivierBlanvillain

Revisiting Tagless Final Interpreters

Tageless Final interpreters are an alternative to the traditional Algebraic Data Type (and generalized ADT) based implementation of the interpreter pattern. This document presents the Tageless Final approach with Scala, and shows how Dotty with it's recently added implicits functions makes the approach even more appealing. All examples are direct translations of their Haskell version presented in the Typed Tagless Final Interpreters: Lecture Notes (section 2).

The interpreter pattern has recently received a lot of attention in the Scala community. A lot of efforts have been invested in trying to address the biggest shortcomings of ADT/GADT based solutions: extensibility. One can first look at cats' Inject typeclass for an implementation of [Data Type à la Carte](http://www.cs.ru.nl/~W.Swierstra/Publications/DataTypesA

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.

mtesseract

The Problem

Defining records in Haskell causes accessor functions for the record's fields to be defined. There is no seperate namespace for these accessor functions.

The Goal

Be able to

• use records in Haskell, which share field names.
• use lenses for accessing these fields

jFransham

Achieving warp speed with Rust

Contents:

• Number one optimization tip: don't
• Never optimize blindly
• Don't bother optimizing one-time costs
• Improve your algorithms
• CPU architecture primer
• Keep as much as possible in cache
• Keep as much as possible in registers

c0nn3r

import re
import os
import glob
import pandas as pd

import matplotlib.pyplot as plt

from collections import OrderedDict

fig_size = [12, 9]

jdegoes

package fpmax

import scala.util.Try
import scala.io.StdIn.readLine

object App0 {
  def main: Unit = {
    println("What is your name?")

    val name = readLine()

iravid

import akka.actor.ActorSystem
import akka.kafka.ConsumerMessage.CommittableMessage
import akka.kafka.scaladsl.Consumer
import akka.kafka.{ ConsumerSettings, Subscriptions }
import akka.stream.ActorMaterializer
import akka.stream.scaladsl.{ Keep, Sink => AkkaSink }
import org.apache.kafka.common.serialization.StringDeserializer
import scalaz.zio._
import scalaz.zio.stream.Sink
import scalaz.zio.interop.reactiveStreams._