text: Functional Go
  Functional Programming by Wikipidia:
  “Functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids state and mutable data”. In other words, functional programming promotes code with no side effects, no change of value in variables. It oposes to imperative programming, which enfatizes change of state”.
  What this means?
  - No mutable data (no side effect).
  - No state (no implicit, hidden state).
  Once assigned (value binding), a variable (a symbol) does not change its value.
  All state is bad? No, hidden, implicit state is bad.
  Functional programming do not eliminate state, it just make it visible and explicit (at least when programmers want it to be).
  - Functions are pure functions in the mathematical sense: their output depend only in their inputs, there is not “environment”.
  - Same result returned by functions called with the same inputs.
  What are the advantages?
  - Cleaner code: “variables” are not modified once defined, so we don’t have to follow the change of state to comprehend what a function, a, method, a class, a whole project works.
  - Referential transparency: Expressions can be replaced by its values. If we call a function with the same parameters, we know for sure the output will be the same (there is no state anywhere that would change it).
  There is a reason for which Einstein defined insanity as “doing the same thing over and over again and expecting different results”.
  Advantages enabled by referential transparence
  - Memoization
  - Cache results for previous function calls.
  - Idempotence
  - Same results regardless how many times you call a function.
  - Modularization
  - We have no state that pervades the whole code, so we build our project with small, black boxes that we tie together, so it promotes bottom-up programming.
  - Ease of debugging
  - Functions are isolated, they only depend on their input and their output, so they are very easy to debug.
  - Parallelization
  - Functions calls are independent.
  - We can parallelize in different process/CPUs/computers/…
  result = func1(a, b) + func2(a, c)
  We can execute func1 and func2 in paralell because a won’t be modified.
  - Concurrence
  - With no shared data, concurrence gets a lot simpler:
  - No semaphores.
  - No monitors.
  - No locks.
  - No race-conditions.
  - No dead-locks.
  Golang is a multi paradigm programming language. As a Golang programmer why uses functional programming?
  Golang is not a functional language but have a lot of features that enables us to applies functional principles in the development, turning our code more elegant, concise, maintanable, easier to understand and test.
  Don’t Update, Create — String
  Wrong
  name := “Geison”name := name + “ Flores”
  Right
  const firstname = “Geison”const lasname = “Flores”const name = firstname + “ “ + lastname
  Don’t Update, Create — Arrays
  Wrong
  years := [4]int{2001, 2002}years[2] = 2003years[3] = 2004years // [2001, 2002, 2003, 2004]
  Right
  years := [2]int{2001, 2001}allYears := append(years, 2003, [2]int{2004, 2005}
  Don’t Update, Create — Maps
  Wrong
  ages := map[string]int{“John”: 30}ages[“Mary”] = 28ages // {‘John’: 30, ‘Mary’: 28}
  Right
  ages1 := map[string]int{“John”: 30}ages2 := map[string]int{“Mary”: 28}func mergeMaps(mapA, mapB map[string]int) map[string]int { allAges := make(map[K]V, len(ages1) + len(ages2)) for k, v := range mapA { allAges[k] = v } for k, v := range mapB { allAges[k] = v } return allAges}allAges := mergeMaps(ages1, ages2)
  Higher Order Functions
  Functions and methods are first-class objects in Golang, so if you want to pass a function to another function, you can just treat it as any other object.
  func caller(f func(string) string) { result := f(“David”) fmt.Println(result)}f := func(s name) string { return “Hello “ + name}caller(f)
  As Golang don`t have a builtin Map implementation, it is possible use this one below:
  yanatan16/itertools
  itertools - A golang implementation of the python standard library module.
  github.com
  Map
  mapper := func (i interface{}) interface{} { return strings.ToUpper(i.(string))}Map(mapper, New(“milu”, “rantanplan”))//[“MILU”, “RANTANPLAN”]
  Filter
  pred := func (i interface{}) bool { return i.(uint64) > 5}Filter(pred, Uint64(1,2,3,4,5,6,7,8,9,10))//[6, 7, 8, 9, 10]
  Reduce
  acumullator := func (memo interface{}, el interface{}) interface{} { return len(memo.(string)) + len(el.(string))}Reduce(New(“milu”, “rantanplan”), acumullator, string).(uint64)// result 14
  Closure
  func add_x(x int) func() int { return func(y int) int { // anonymous function return x + y }}add_5 := add_x(5)add_7 := add_x(7)add_5(10) // result 15add_7(10) // result 17.
  func plus(x, y int) int { return x + y}func partialPlus(x int) func(int) int { return func(y int) int { return plus(x, y) }}func main() { plus_one := partialPlus(1) fmt.Println(plus_one(5)) //prints 6}
  Eager vs Lazy Evaluation
  - Eager evaluation: expressions are calculated at the moment that variables is assined, function called…
  - Lazy evaluation: delays the evaluation of the expression until it is needed.
  - Memory efficient: no memory used to store complete structures.
  - CPU efficient: no need to calculate the complete result before returning.
  - Laziness is not a requisite for FP, but it is a strategy that fits nicely on the paradigm(Haskell).
  Golang uses eager evaluation (but short-circuits && or ||).
  Golang channels and goroutines enable the creation of generators that could be a way to have lazy evaluation.
  Golang arrays are not lazy, use channels and goroutines to emulate a generator when necessary..
  - Purely functional languages have no imperative for-loops, so they use recursion a lot.
  - If every recursion created an stack, it would blow up very soon.
  - Tail-call optimization (TCO) avoids creating a new stack when the last call in a recursion is the function itself.
  - TCO is not implemented in Golang.
  - Unfortunarely following recursion style in Golang has it’s own tax: Performance.
  Solving Golang Lack of TCO(Tail Call Optimization)
  The functional solution have problems with big values
  func fibonacciRecursive(n int) int { if n <= 1 { return n } return n * fibonacciRecursive(n — 1)}
  The iterative solution works perfectly with large values
  func fibonacci(n int) int { current, prev := 0, 1 for i := 0; i < n; i++ { current, prev = current + prev, current } return current}
  FP in OOP?
  It is possible do FP in OOP? Yes it is!
  - OOP is orthogonal to FP.
  - Well, at least in theory, because:
  - Typical OOP tends to emphasize change of state in objects.
  - Typical OOP mixes the concepts of identity and state.
  - Mixture of data and code raises both conceptual and practical problems.
  - OOP functional languages: Scala, F#, …
  A Pratical Example
  Exercise: “What’s the sum of the first 10 natural number whose square value is divisible by 5?”
  Imperative
  func main() { n, numElements, s := 1, 0, 0 for numElements < 10 { if n * n % 5 == 0 { s += n numElements++ } n++ } fmt.Println(s) //275}
  Functional
  sum := func (memo interface{}, el interface{}) interface{} { return memo.(float64) + el.(float64)}pred := func (i interface{}) bool { return (i.(uint64) * i.(uint64)) % 5 == 0}createValues := func () []int {
  values := make([]int, 100) for num := 1; num <= 100; num++ { values = append(values, num) }
  return values}Reduce(Filter(pred, createValues), sum, uint64).(uint64)
  The last advice
  Learn at least one functional language, it will open your mind to a new paradigm becoming you a better programmer.
  Some Functional Languages:
  - Haskell
  - ML (Standard ML, Objective Caml, …)
  - Scheme
  - Erlang
  - Scala
  - Clojure
  - F#
  Conclusion
  - As you can tell, Golang helps you write in functional style but it doesn’t force you to it.
  - Writing in functional style enhances your code and makes it more self documented. Actually it will make it more thread-safe also.
  - The main support for FP in Golang comes from the use of closures, iterators and generators.
  - Golang still lack an important aspect of FP: Map, Filter, Reduce, Immutable and Generic types, Pattern Matching and Tails Recursion.
  - There should be more work on tail recursion optimization, to encourage developers to use recursion.
  - Any other thoughts?