Slide 1

Slide 1 text

Scala <> Haskell Introducing and comparing both languages.

Slide 2

Slide 2 text

• The Basics
 • Type level programming
 • Libraries/Frameworks/ Community

Slide 3

Slide 3 text

The Basics 1. Two FP styles 2. Sum types 3. Pattern matching 4. Functions 5. Imperative constructions 6. Evaluation

Slide 4

Slide 4 text

1. Two FP styles

Slide 5

Slide 5 text

Everything is an object

Slide 6

Slide 6 text

No content

Slide 7

Slide 7 text

There are only functions and constants

Slide 8

Slide 8 text

No content

Slide 9

Slide 9 text

2. Sum/co-product types

Slide 10

Slide 10 text

A product type

Slide 11

Slide 11 text

A sum/co-product type

Slide 12

Slide 12 text

A sum/co-product type This approach introduces two new types: - True.type - False.type

Slide 13

Slide 13 text

A product type

Slide 14

Slide 14 text

A sum/co-product type

Slide 15

Slide 15 text

A sum/co-product type There is only one type: - Boolean and two constants: - True’ - False’

Slide 16

Slide 16 text

3. Pattern matching

Slide 17

Slide 17 text

No content

Slide 18

Slide 18 text

No content

Slide 19

Slide 19 text

Product/Sum types are dual of pattern matching, the first constructs data, the second de- constructs data.

Slide 20

Slide 20 text

4. Functions

Slide 21

Slide 21 text

Lambdas

Slide 22

Slide 22 text

No content

Slide 23

Slide 23 text

No content

Slide 24

Slide 24 text

Functions

Slide 25

Slide 25 text

No content

Slide 26

Slide 26 text

No content

Slide 27

Slide 27 text

Curried functions

Slide 28

Slide 28 text

The type of a function A => B

Slide 29

Slide 29 text

The type of a function A => B B = C => D

Slide 30

Slide 30 text

The type of a curried function A => C => D

Slide 31

Slide 31 text

A curried function

Slide 32

Slide 32 text

A curried function (named syntax)

Slide 33

Slide 33 text

The type of a function a -> b

Slide 34

Slide 34 text

The type of a function a -> b b = c -> d

Slide 35

Slide 35 text

The type of a curried function a -> c -> d

Slide 36

Slide 36 text

A curried function

Slide 37

Slide 37 text

A curried function (named syntax)

Slide 38

Slide 38 text

Multi-argument functions

Slide 39

Slide 39 text

Functions only accept one argument and return one result. Let’s see how can we emulate functions that receive more than one argument.

Slide 40

Slide 40 text

The type of a multi-arg function (A,B,…) => D

Slide 41

Slide 41 text

No content

Slide 42

Slide 42 text

Shorter syntax

Slide 43

Slide 43 text

Even shorter syntax

Slide 44

Slide 44 text

The type of a multi-arg function (a,b,…) -> d

Slide 45

Slide 45 text

No content

Slide 46

Slide 46 text

Even shorter syntax

Slide 47

Slide 47 text

Thanks to pattern matching we can syntactically emulate multi- argument functions

Slide 48

Slide 48 text

Curried functions are more common in Haskell, while multi-argument functions are more common in Scala

Slide 49

Slide 49 text

Curried functions allow partial function application

Slide 50

Slide 50 text

No content

Slide 51

Slide 51 text

No content

Slide 52

Slide 52 text

No content

Slide 53

Slide 53 text

5. Imperative constructions

Slide 54

Slide 54 text

Unrestricted side-effects

Slide 55

Slide 55 text

Side-effects only inside IO type

Slide 56

Slide 56 text

6. Evaluation

Slide 57

Slide 57 text

Strict evaluation by default with lazy evaluation as an option

Slide 58

Slide 58 text

Strict

Slide 59

Slide 59 text

Lazy

Slide 60

Slide 60 text

Lazy evaluation by default with strict evaluation as an option

Slide 61

Slide 61 text

Lazy (non-strict semantics)

Slide 62

Slide 62 text

Strict

Slide 63

Slide 63 text

Evaluation-related keywords particular to Scala

Slide 64

Slide 64 text

Strict evaluation

Slide 65

Slide 65 text

Lazy evaluation

Slide 66

Slide 66 text

Haskell’s lazy-evaluation

Slide 67

Slide 67 text

Non-strict evaluation

Slide 68

Slide 68 text

Type-level programming 1. Type inference 2. Kind inference 3. Type classes 4. Multi-param type classes 5. Monad transformers

Slide 69

Slide 69 text

1. Type inference

Slide 70

Slide 70 text

Local: variables and function return types

Slide 71

Slide 71 text

No content

Slide 72

Slide 72 text

No content

Slide 73

Slide 73 text

No content

Slide 74

Slide 74 text

No content

Slide 75

Slide 75 text

Global: almost all types are calculated

Slide 76

Slide 76 text

No content

Slide 77

Slide 77 text

No content

Slide 78

Slide 78 text

No content

Slide 79

Slide 79 text

Type Inference Less polymorphic More permissive Haskell Scala Hindley-Milner

Slide 80

Slide 80 text

Things that make Scala’s type system more powerful (hence less type inference): - sub typing polymorphism - type lambdas - … Recommended reading (the comments section): 
 http://pchiusano.blogspot.com.es/2011/05/making-most-of- scalas-extremely-limited.html

Slide 81

Slide 81 text

2. Kind inference

Slide 82

Slide 82 text

No content

Slide 83

Slide 83 text

No content

Slide 84

Slide 84 text

No content

Slide 85

Slide 85 text

No content

Slide 86

Slide 86 text

3. Type classes

Slide 87

Slide 87 text

The expression problem Operation\Data Data1 Data2 New data easy in OOP / difficult in FP Operation1 Operation2 Operation3 New operation easy in FP / hard in OOP

Slide 88

Slide 88 text

No content

Slide 89

Slide 89 text

No content

Slide 90

Slide 90 text

Adding a new operation

Slide 91

Slide 91 text

Adding a new data type

Slide 92

Slide 92 text

No content

Slide 93

Slide 93 text

No content

Slide 94

Slide 94 text

No content

Slide 95

Slide 95 text

Adding a new operation

Slide 96

Slide 96 text

Adding a new data type

Slide 97

Slide 97 text

No content

Slide 98

Slide 98 text

4. Multi-param type classes

Slide 99

Slide 99 text

No content

Slide 100

Slide 100 text

How can we constraint the type parameters to allow more polymorphism?

Slide 101

Slide 101 text

The solution is to use functional dependencies (inspired by relational databases)

Slide 102

Slide 102 text

With functional dependencies

Slide 103

Slide 103 text

No content

Slide 104

Slide 104 text

5. Monad transformers

Slide 105

Slide 105 text

No content

Slide 106

Slide 106 text

No content

Slide 107

Slide 107 text

No content

Slide 108

Slide 108 text

Type-level programming 1. Type inference 2. Kind inference 3. Type classes 4. Multi-param type classes 5. Monad transformers

Slide 109

Slide 109 text

Tooling Frameworks Libraries Conferences

Slide 110

Slide 110 text

akka, akka-http, spark, sbt, cats, scalaz, monocle, scalacheck, shapeless, JVM, …

Slide 111

Slide 111 text

scala world, lambda world, scalar, lambda conf, scala days, lx scala, typelevel submit, scala swarm, scala up north, scala exchange, scala io, compose, ICFP , …

Slide 112

Slide 112 text

mtl, lens, quickcheck, speculation, diagrams, criterion, darcs, xmonad, pandoc, yesod, …

Slide 113

Slide 113 text

zurihac, munihac, lambda conf, haskell symposium, lambda world, ICFP, BOB, compose, …

Slide 114

Slide 114 text

My view is that both languages are fantastic, Scala sacrifices type inference and some type safety in exchange of more power. Haskell tries to keep a core with good type inference and type safety even if that incurs in a less powerful type system

Slide 115

Slide 115 text

If you like FP in Scala, give Haskell a try!

Slide 116

Slide 116 text

If you know Haskell, learn you some Scala!

Slide 117

Slide 117 text

Questions?

Slide 118

Slide 118 text

Thank You