reactormonk

structure(list(Name = c("AddInteger: 3^10, 3^10", "AddInteger: 3^10, 3^100", 
"AddInteger: 3^10, 3^1000", "AddInteger: 3^10, 3^10000", "AddInteger: 3^10, 3^100000", 
"AddInteger: 3^10, 3^1000000", "AddInteger: 3^10, 3^10000000", 
"AddInteger: 3^10, 3^100000000", "AddInteger: 3^100, 3^10", "AddInteger: 3^100, 3^100", 
"AddInteger: 3^100, 3^1000", "AddInteger: 3^100, 3^10000", "AddInteger: 3^100, 3^100000", 
"AddInteger: 3^100, 3^1000000", "AddInteger: 3^100, 3^10000000", 
"AddInteger: 3^100, 3^100000000", "AddInteger: 3^1000, 3^10", 
"AddInteger: 3^1000, 3^100", "AddInteger: 3^1000, 3^1000", "AddInteger: 3^1000, 3^10000", 
"AddInteger: 3^1000, 3^100000", "AddInteger: 3^1000, 3^1000000", 
"AddInteger: 3^1000, 3^10000000", "AddInteger: 3^1000, 3^100000000", 

reactormonk

import cats._
// import cats._
object f1 {
  trait Fold[I, O] {
    type M
    def tally(i: I): M
    def summarize(m: M): O
    def monoid: Monoid[M]
  }
  object Fold {

reactormonk

library(dplyr)

csv <- read.csv("StockX-Data-Contest-2019-3.csv")

csv$Sneaker.Name.String <- as.character(csv$Sneaker.Name)

csv$Sneaker.Model = as.factor(case_when(
  startsWith(csv$Sneaker.Name.String, "adidas-Yeezy-Boost-350-V2"        ) ~ "Adidas-Yeezy-Boost-350-V2",
  startsWith(csv$Sneaker.Name.String, "Adidas-Yeezy-Boost-350-V2"        ) ~ "Adidas-Yeezy-Boost-350-V2",
  startsWith(csv$Sneaker.Name.String, "Adidas-Yeezy-Boost-350"           ) ~ "Adidas-Yeezy-Boost-350",

reactormonk

library(dplyr)
library(plyr)

models <- c("Adidas-Yeezy-Boost-350", "Nike-Air-Max-90", "Nike-Air-Presto", "Air-Jordan-1-Retro-High", "Nike-Air-Force-1-Low", "Nike-Air-Max-90", "Nike-Air-Max-97", "Nike-Air-Presto", "Nike-Air-VaporMax", "Nike-Blazer-Mid", "Nike-React-Hyperdunk-2017-Flyknit", "Nike-Zoom-Fly", "Nike-Zoom-Fly-Mercurial", "adidas-Yeezy-Boost-350-V2")

csv$Sneaker.Name.String <- as.character(csv$Sneaker.Name)

addModel <- function(model) {
  df <- filter(csv, startsWith(csv$Sneaker.Name.String, model))
  df$Sneaker.Model <- model

reactormonk

library(dplyr)
library(plyr)

models <- c("Adidas-Yeezy-Boost-350", "Nike-Air-Max-90", "Nike-Air-Presto", "Air-Jordan-1-Retro-High", "Nike-Air-Force-1-Low", "Nike-Air-Max-90", "Nike-Air-Max-97", "Nike-Air-Presto", "Nike-Air-VaporMax", "Nike-Blazer-Mid", "Nike-React-Hyperdunk-2017-Flyknit", "Nike-Zoom-Fly", "Nike-Zoom-Fly-Mercurial", "adidas-Yeezy-Boost-350-V2")

csv$Sneaker.Name.String <- as.character(csv$Sneaker.Name)

addModel <- function(model) {
  df <- filter(csv, startsWith(csv$Sneaker.Name.String, model))
  df$Sneaker.Model <- model

reactormonk

class Uncurry fun types r where
  uncurryNP :: fun -> NP I types -> r

instance forall fun r t types.
  ( Uncurry fun types r
  ) => Uncurry (t -> fun) (t ': types) r where
  uncurryNP f ((I a) :* as) = uncurryNP (f a) as

instance (s ~ r) => Uncurry s '[] r where
  uncurryNP z Nil = z

reactormonk

#!/usr/bin/env stack
{- stack --install-ghc
    --resolver lts-10.8
    script
    --compile
    --package monad-logger
    --package katip
    --package universum
    --package lens
-}

reactormonk

#!/usr/bin/env stack
{- stack --install-ghc
    --resolver lts-10.7
    script
    --compile
    --package katip
    --package universum
    --package aeson
-}

reactormonk

#!/usr/bin/env stack
{- stack --install-ghc
    --resolver lts-10.7
    script
    --compile
    --package katip
    --package universum
    --package aeson
-}

reactormonk

#!/usr/bin/env stack
{- stack --resolver lts-9.1
  script
  --compile
  --package recursion-schemes
-}

{-# LANGUAGE DeriveFunctor #-}
{-# LANGUAGE TypeSynonymInstances #-}