Functional go

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.
Functional Go

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".
Functional Go

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.
Functional Go

● Parallelization
○ Functions calls are independent.
○ We can parallelize in different process/CPUs/computers/…
We can execute func1 and func2 in paralell because a won’t be modified.
result = func1(a, b) + func2(a, c)
Functional Go

● Concurrence
a. With no shared data, concurrence gets a lot simpler:
i. No semaphores.
ii. No monitors.
iii. No locks.
iv. No race-conditions.
v. No dead-locks.
Functional Go

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.
Functional Go

Don’t Update, Create - String
name := "Geison"
name := name + " Flores"
const firstname = "Geison"
const lasname = "Flores"
const name = firstname + " " + lastname
Functional Go

Don’t Update, Create - Arrays
years := [4]int{2001, 2002}
years[2] = 2003
years[3] = 2004
years // [2001, 2002, 2003, 2004]
years := [2]{2001, 2001}
allYears := append(years, 2003, [2]int{2004, 2005}
Functional Go

Don’t Update, Create - Maps
ages := map[string]int{"John": 30}
ages["Mary"] = 28
ages // {'John': 30, 'Mary': 28}
Functional Go
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)
Functional Go

Higher Order Functions - Map
// As Golang do not have a builtin Map implementation, it is possible use this one
// https://github.com/yanatan16/itertools/blob/master/itertools.go
mapper := func (i interface{}) interface{} {
return strings.ToUpper(i.(string))
}
Map(mapper, New("milu", "rantanplan"))
//["MILU", "RANTANPLAN"]
Functional Go

Higher Order Functions - Filter
// As Golang do not have a builtin Filter implementation, it is possible use this one
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]
Functional Go

Higher Order Functions - Reduce
// As Golang do not have a builtin Reduce implementation, it is possible use this one
acumullator := func (memo interface{}, el interface{}) interface{} {
return len(memo.(string)) + len(el.(string))
}
Reduce(New("milu", "rantanplan"), acumullator, string).(uint64)
// result 14
Functional Go

Higher Order Functions - 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 15
add_7(10) // result 17
Functional Go

Currying and Partial Functions
Higher-order functions enable Currying, which the ability to take a function that accepts n
parameters and turns it into a composition of n functions each of them take 1 parameter. A direct
use of currying is the Partial Functions where if you have a function that accepts n parameters then
you can generate from it one of more functions with some parameter values already filled in.
Functional Go
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.
Functional Go

Recursion
Looping by calling a function from within itself. When you don’t have access to mutable
data, recursion is used to build up and chain data construction. This is because looping is
not a functional concept, as it requires variables to be passed around to store the state of
the loop at a given time.
● 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.
Functional Go

Solving Golang Lack of TCO(Tail Call Optimization)
// The functional solution have problens with big values
func fibonacciRecursive(n int) int {
if n <= 1 {
return n
}
return n * fibonacciRecursive(n - 1)
}
Functional Go

Solving Golang Lack of TCO(Tail Call Optimization)
// 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
}
Functional Go

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#, ...
Functional Go

A Pratical Example
Exercise: "What's the sum of the first 10 natural number whose square value is
divisible by 5?"
Imperative: Functional:
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 Go
sum := func (memo interface{}, el interface{}) interface{} {
return memo.(float64) + el.(float64)
}
pred := func (i interface{}) bool {
return (i.(uint64) * i.(uint64)) % 5 == 0
}
values := make([]int, 100)
for num := 1; num <= 100; num++ {
values = append(values, num)
}
Reduce(Filter(pred, values), 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
● Closure
● F#
Functional Go

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?
Functional Go

References
● http://en.wikipedia.org/wiki/Functional_programming
● http://www.cse.chalmers.se/~rjmh/Papers/whyfp.pdf
● http://tour.golang.org
● http://www.golangpatterns.info/
● https://github.com/yanatan16/itertools
● http://clojure.org/
● http://www.defmacro.org/ramblings/fp.html
Functional Go

Contact me
● Email:
○ geisonfgf@gmail.com
● Skype
○ geisonfgf
● Facebook
○ http://www.facebook.com/geisonfgf
● Twitter
○ http://www.twitter.com/geisonfgf
Functional Go

Functional go

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Functional go