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Programming in Javascript\nJavascript approach to functional programming.\nOur book is still in portuguese but we will translate it later 🤷🏻‍️\n\nSummary\nIntroduction\nLambda Calculus\nPure Functions\nCurrying vs Parcial Application\nImmutability\nDeclarative Programming\nHigh Order Functions\nRecursion\nComposition and Pipeline\nModules, Async, contracts, error handling\nNot using classes\nTacit Programming\nCombinators\nCategory Theory\nFunctional Architecture\nFP Languages that compiles to JS\n\nAuthors\n\nAnaBastos\nLukkaslt\nWdiasvargas\nSamverneck\n\nTemplate\nCollaborating\nInstalling\nnpm install -g gitbook-cli\nRunning\ngitbook serve\nBuild to gh-pages\ngitbook install && gitbook build\ncp -R _book/* .\ngit clean -fx _book\n\n"},"00-introduction/00-introduction.html":{"url":"00-introduction/00-introduction.html","title":"Introdução","keywords":"","body":"Introdução\nO que é FP?\n Não é atoa que o nome é \"funcional\". Uma linguagem funcional é qualquer linguagem construida sobre funções logicas, sendo baseadas em funções matematicas no fluxo computacional(Igual na aula da quarta série!).\nA estrutura básica destas linguagens de programação vem da logica combinatória e do calculo lambda, que vamos explicar no proximo capitulo.\nA programação funcional consiste em uma abordagem distinta da convencional programação orientada a objetos para o desenvolvimento de aplicações e software.\nRessaltando que POO é bastante útil ainda hoje e seu ensino e seu uso ainda é  bastante comum atualmente, reafirmamos a sua importância contudo salientando suas limitações. Podemos citar a implantação da computação paralela utilizando POO tende a ser demasiadamente custosa e dificil, por os estados podem ser alterados bem como sofrer efeitos colaterais.\nEm programação funcional não é permitido mutabilidade onde não deveria existir. Funções atuam como blocos de construção.\nProgramar em uma linguagem funcional consiste em construir definições e usar o computador para avaliar expressões sendo o papel do programador construir funções que obedecem princípios matemáticos para resolver um problema. Uma das principais características é que se uma expressão possui valores bem definidos, então a ordem em que o computador realiza essa avaliação não deve afetar o resultado evitando assim um sistema de estados mutáveis\nDesde o seu surgimento, a programação funcional vem sendo a queridinha dos aficionados pela ciência da computação, valorizada pela sua pureza matemática e natureza intrigante, manteve-se escondida em laboratórios de informática, empoeirados... ocupados por cientistas de dados e PhDs esperançosos.\nProgramação funcional não é novidade e sequer modinha. O sistema formal do cálculo lambda foi desenvolvido na década de 30 pelo Allan Church para explorar a computabilidade para com definição e aplicação de funções e recursão. Linguagens como LISP existem há mais de 60 anos.\nMas até poucos anos atrás computadores não eram tão rapidos quanto hoje em dia e tinham bem pouco poder de processamento. Pra isso era importante utilizar linguagens que possibilitassem uma economia na memória e para isso linguagens imperativas que lidavam bem com a memória e faziam tarefas de forma procedural ficaram em alta.\nEm um artigo publicado em 1965 na \"Electronics Maganize\", pergunta-se ao Gordon E. Moore, diretor de pesquisa e desenvolvimento dos semicondutores Fairchild, como ele previa a indústria nos próximos 10 anos e ele observou que o número de componentes em um circuito integrado havia dobrado em aproximadamente um ano, ele assumiu que a próxima geração de chips seria duas vezes mais rápida que a anterior em um período de 18 meses, mas com o mesmo custo que os modelos de anterior, Moore especulou que esse viria a acontecer pelo menos nos próximos anos 10. \nhttps://banner2.kisspng.com/20180806/ku/kisspng-moore-s-law-intel-central-processing-unit-dennard-5b6862deaeace6.8292659815335677107155.jpg\nA parte mais engraçada é que esse padrão se repete até hoje, em o número de transistores aumentou exponencialmente e sua previsão foi popularizada e chamada de Lei de Moore. \nAté que fisicamente um único núcleo não fosse fisicamente capaz de ter mais transistores sem que super-aquecesse. A solução? Começa a era dos multi-nucleos.\nEm contraste, a programação imperativa consiste no uso de comandos que alteram os estados da memória, permite efeitos colaterais que podem alterar a execução do programa e possuem sub rotinas em vez de funções (no sentido matemático). Por conta disso, diz-se que a programação imperativa não tem transparência referencial, ou seja, um mesmo bloco de código pode ter dois resultados completamente diferentes. É conveniente na estruturação do software problemas de múltipla comunicação de threads que ajudam a estruturar o código de forma a modelar a interface de usuário como threads separadas e, assim, lidar da melhor forma com concorrência em tempo real. \nDe qualquer forma, atualmente processamento não é um problema, e faz sentido não se importar tanto com o que acontece por de baixo dos panos e que linguagem estamos usando se queremos garantir uma abstração que faz sentido. E por isso a programação funcional tem sua segunda chance.\nAlém disso, um modelo que faz sentido para concorrência e paralelismo com certeza é a programação funcional principalmente por suas vantagens em processamento.\nDe um tempo para cá a programação funcional vem regenerando-se e se mesclando em linguagens modernas, como Python, Julia, Java, Ruby, Clojure e - por último mas não menos importante - JavaScript.\nEstas linguagens estão adquirindo elementos funcionais como expressões lambdas. E cada vez mais linguagens modernas vão passar a funcionalidades de programação funcional em breve ou já tem em seu core.\n-- Você disse, JavaScript? Aquela linguagem de script usada em programação web?\n-- Sim!\nO JavaScript provou ser uma tecnologia importante, e que veio para ficar - por longo tempo. Basicamente porque é Javascript que roda por trás dos navegadores e devido a isso ela poder ser \"renascida\", extendida, com novas estruturas providas por bibliotecas como o React, o jQuery e tantas mais. Isto está intimamente relacionado com a sua identidade como \"linguagem de programação funcional\". Compreendermos a aplicação de estruturas e algoritmos provenientes da programação funcional nos será útil por longo tempo, independentemente de nível e/ou habilidades de quem a procura.\n-- Por que javascript pode ser funcional?\nO javascript assim como boa parte das linguagens, tem suporte a funções de primeira ordem, ou seja, suas funções podem ser passadas como argumento de outras funções. Além disso essas funções podem ser compostas chamando umas as outras como a(b()). Javascript tem suporte a funções anônimas e com \"Arrow Functions\" introduzidas na sua versão 5, é possivel tornar a linguagem cada vez mais funcional.\nNão se engane no papo de paralelismo e concorrência: Javascript é uma linguagem single thread.\n\nexplicar single thread\nMesmo javascript nao sendo uma linguagem puramente funcional podemos utilizar alguns principios funcionais no nosso codigo\n\n-- Por que devo procurá-la então?\nA programação funcional é muito poderosa, robusta e elegante; extremamente útil para a manipulação de grandes estruturas de dados. Podemos obter diversas vantagens com JavaScript — uma linguagem de script do lado do cliente - se usada como o meio da aplicação do paradigma funcional em tarefas como, respostas ao dom, exibir de forma ordenada a resposta de uma Api e tantas outras das quais precisam os nossos modernos websites.\nEnquanto OOP depente diretamente um estado mutavel, os metodos chamados devem mutar o estado do atual \"self\" ou \"this\". A imutabilidade também pode ser importante para garantir menos bugs.\nPara melhores aplicações precisamos de maneiras simples e possiveis para tal e a programação funcional te ajuda a escrever melhores programas and \"reason\"(n sei como traduzir) sobre os problemas que você quer resolver.\nMuitas pessoas comentam que aparenta dificil de primeira vista, mas é pura questão de adaptação. Quem tem um background de programação procedural pode ter um pouco de dificuldade para se adaptar a um paradigma novo. Mas é similar a aprender OOP de novo ou aprender programação de logo.\nIsso acontece pois você já está familiar com muitos termos e formas de pensar, como por exemplo, utilizar estruturas como \"for\" ou \"while\" para fazer loops ou \"if\" ao invés de pattern matchings. E da mesma forma, é um periodo de tempo até pegar todos os jargões e passar a ler de forma clara até entender seus fundamentos.\nUma das maiores vantagens são a sua mantenabilidade\n\nDeclaratividade são uteis\nFront end e estado imutavel.\n\nNeste livro, aprenderemos grande parte do necessário sobre a programação funcional com JavaScript, a emponderarmos aplicações web mediante o uso de \"JavaScript Funcional\", a desbloquear seus poderes secretos permitindo-nos escrever programas mais curtos e poderosos, mais rápidos, pois num piscar de olhos são transmitidos pela camada TCP devido ao ínfimo tamanho. Veremos a ideia central do paradigma funcional e como aplicá-lo com o auxílio do JavaScript, um passo-a-passo de problemas e precauções que podem surgir, e juntamente, a programação orientada a objetos que será o nosso auxílio - \"auxílio do auxílio\".\nEste exemplo não nos apresentou, mas nem de longe, o que a programação funcional com JavaScript tem a oferecer. Veremos exemplos ainda mais poderosos da abordagem funcional.\n"},"01-λ-calculus/01-λ-calculus.html":{"url":"01-λ-calculus/01-λ-calculus.html","title":"Lambda Calculus","keywords":"","body":"Calculo Lambda\nCalculo lambda é um sistema formal pra representar computações baseado na definicao e aplicacao de funções e nele:\n\nTodas as funcoes sao anonimas\nTodas as funções objetos de ordem elevada(ou high order functions), ou seja, funções podem ser passadas como argumentos de outras funções e também serem retorno de funções.\nPermite a combinação de operadores e funções básiacas na geração de operadores mais complexos;\nPode ser tipada ou não\n\nAlonzo Church inventou o calculo lambda nos anos 30 com o intuito de formalizar a matemática através da noção de funções ao invés da teoria de conjuntos sendo uma representação equivalente á maquina de Turing porém representando computacoes através funções ao inves de maquinas e teve um impacto forte na computação por ser a forma teoria de especificar e implementar linguagens de programação baseadas em funções, aka. linguagens funcionais.\nEm 1937 Alan Turing provou a equivalencia entre uma maquina de turing e o calculo lambda em termos de computabilidade, sendo assim, a ferramenta mais adequada para escrever linguagens de paradigma funcional. Nesse paradigma, a solução de um problema é a feita por meio de funções, usando nessa implementação um conjunto de primitivas e regras para construir essas primitivas.\nDentre seus aspectos interessantes há facilidade sintatica para lidar com computações, e uma facilidade de escrever recursão\nexemplo\nA maioria das linguagens da programação funcional são semelhantes e diferem somente em aspectos sintaticos\nSendo assim modelo matematico para\n\nEspecificacao e implementacao de linguagens funcionais(Haskell, Lisp, Orwell).\nRepresentacao de funções computaveis.\nTeoria da Computabilidade.\nTeoria dos tipos.\nTeoria das provas.\n\nSintaxe\n\nO símbolo λ define uma função.\nO símbolo . separa o a cabeça do corpo, sendo a cabeça uma representação do parâmetro e da expressão.\nPrecedencia e esquerda, ou seja ((MN)L) pode ser escrita MNL.\nLetras diferentes designam variaveis diferentes\n\nTemos então:\n  λx   .   x + 1   (a)\n(head)    (body)  (outra expressao)\n         expressão\nSendo a cabeça λx consistindo no lambda, definindo a função, os seus parametros formais(x) e o corpo a expressão x + y\nTal exeplo pode ser lido como \"Função que recebe x a qual adiciona x a 1\".\nUma expressão lambda representa um programa, um algoritmo, um proedimento para produzir um resultado\nConsidere x + y, ela pode ser formalizada na notação matematica casualmente atravez de funcoes de um unico paramento\nf(x) = x + y ou\ng(y) = x + y\nEm javascript:\nconst f =  x -> x + y\nconst g = y -> x + y\n\nExemplo:\nf(0): 0 + y\nf(1): 1 + y\nRepresentacao dessas funcoes na linguagem lambda:\nf = λx.x + y\ng = λy.x + y\nSendo assim, λx.x + y é equivalenta a função identidade f(x)=x + y\nE sua aplicação:\n(λx.x + y)(0) = 0 + y ou\n(λx.x + y)(1) = 1 + y.\nAplicando λx.x + y no número 0 obtemos (λx.x + y)(0) (também escrito como λx.x 0), que resulta na substituição de x para 0 e assim retornando 0 + y, ou y.  \nFuncoes de multiplos paramentos podem ser representados em linguagem lambda como:\nh(x, y) = x + y ou\nk(y, x) = x + y\nE sua aplicação:\nh = λxy.x + y ou\nk = λyx.x + y.\nPorém essas funcoes podem ser representadas como funções que retornam outras funções como valores, ja que todo \ncalculo lambda recebe apenas um único parametro.\nh = λx.(λy.(x + y))\nEm que ao aplicamos \"a\" temos:\nh(a) = (λx.(λy.(x + y))(a) \n     = λy.(a + y)\nE aplicando o par \"a\" e \"b\" temos:\n(h(a))(b) = ((λx.(λy.(x + y))(a))(b)\n          = (λy.(a + y))(b)\n          = a − b\n Em javascript podemos representar a aplicação parcial de argumentos usando o curry da biblioteca RamdaJS, lembrando que vamos ver mais profundamente sobre currying e ramda com o passar do livro:\nconst h =  curry((x, y) -> x + y)\nh(a)(b) // a + b\n\nExemplo\nPara exemplificar vamos definir duas funções representando True e False, em que a T retorna o seu primeiro valor e F retorna o seu segundo valor\nT ≡ λab.a   F ≡ λab.b\nSendo aplicada parcialmente:\nT ≡ λa.λb.a\nEm javascript:\nconst t = curry((a, b) => a)\nconst f = curry((a, b) => b)\nconst display = (boleano) => boleano(true, false)\n\ndisplay(t) //true\ndisplay(f) //false\n\nJá conseguimos sinalizar se algo é verdadeiro ou falso a partir de calculo lambda apenas aplicando a função display(t) ou display(f).\nNo nosso exemplo, um booleano é uma função, mas como fariamos uma negação?\nNOT ≡ λx.xFT\nNOT é uma função que recebe um booleano e retorna a aplicação do booleano nos parametros F e T.\nconst not = x => x(F, T)\n\ndisplay(not(t))\n\nO AND e OR recebem dois booleanos, o AND aplica o primeiro a em b e F(função false) e o or aplica o primeiro a em t(função true) e b.\nAND ≡ λab.abF\nOR ≡ λab.aTb.\nconst and = curry((a, b) => a(b , f))\nconst or = curry((a, b) => a(t, b))\n\ndisplay(and(t)(f)) //false\ndisplay(and(t)(t)) //true\ndisplay(or(t)(f)) //true\ndisplay(not(or(t)(f))) // false\ndisplay(not(and(t)(or(t)(f)))) //false\n\nE em Scheme, o dialeto LISP criado por Guy Steele ficamos mais próximo ainda da sintaxe do cálculo lambda:\n(define T (lambda (a b) a))\n(define F (lambda (a b) b))\n(define NOT (lambda (x) (x F T)))\n(define AND (lambda (b1 b2) (b1 b2 F)))\n(define OR (lambda (b1 b2) (b1 T b2)))\n\nExemplo sensacional pego (daqui)[http://blog.caelum.com.br/comecando-com-o-calculo-lambda-e-a-programacao-funcional-de-verdade/] e transformado em JS\nFunções Computáveis\nNo Cálulo Lambda, diz-se que uma função F : N → N é computável se e somente se existir uma expressão-lambda f tal que:\n∀x, y ∈ N, F(x) = y ⇔ f x = β y\nβ é chamada igualdade beta, serve para estabelecer a equivalênia entre termos de uma equação envolvendo termos lambda\nλ-termo ou expressão lambda é definida de forma indutiva sobre um conjunto de identificadores {x, y, z, u, v...}, sendo esses identificadores representações de variaveis:\nSendo assim uma variável (também chamada átomo) é um λ-termo.\nA linguagem lambda é composta de todos os λ-termos que podem ser construídos sobre um certo conjunto de identificadores e trata-se de uma linguagem om apenas dois operadores ou comandos: aplicação de função\nà argumentos (chamada de função) e abstração (definição de função).\nAplicação: Função é concebida como abstração\nf(x) = a pode ser escrito como λa\ng(x) = x pode ser escrito como λx\nAbstração: Uma função composta é conhecida como aplicação\nf(3) pode ser escrito como λa(3)\nf(g(x)) pode ser escrito como (λa)(λx)\nO símbolo ≡ é usado para denotar a equivalênia sintátia de λ-termos.\n\nxyz(yx) ≡ (((xy)z)(yx))\nλx.(uxy) ≡ (λx.((ux)y))\nλu.u(λx.y) ≡ (λu.(u(λx.y)))\n(λu.vuu)zy ≡ (((λu.((vu)u))z)y)\nux(yz)(λv.vy) ≡ (((ux)(yz))(λv.(vy)))\n(λxyz.xz(yz))uvw ≡ (λx.(λy.(λz.((xz)(yz)))))u)v)w)\n\nExemplos\nDada uma função λx.x*x*x\ndizemos que λx.x*x*x(2) é uma aplicação dessa função que reduz em 8\nconst cube = x => x * x * x //função\ncube(2) //aplicação da função para 2 a reduzindo em 8\n\nComprimento\nO comprimento de um λ-termo M (lgh(M)) é o número total de ocorrênias de átomos em M, em que, para todo átomo a, lgh(a) = 1;\nSe M ≡ x(λy.yux) então lgh(M) = 5\nlgh(MN) = lgh(M) + lgh(N);\n e lgh(λx.M) = 1 + lgh(M)\nOcorrencia\nSejam P e Q dois λ-termos. A relação P ocorre em Q (ou ainda, P está\ncontido em Q, Q contém P ou P é subtermo de Q) é definida de forma indutiva:\n\nP ocorre em P ;\nSe P oorre em M ou em N , então P ocorre em (MN);\nSe P ocorre em M ou P ≡ x então P oorre em (λx.M).\n\nExemplo\nNo termo ((xy)(λx.(xy))) existem duas ocorrênias de (xy) e três de x.\nAs ocorrênias de xy em λxy.xy são λxy.xy ≡ (λx.(λy.( xy ))).\nPara uma paticular ocorrênia de λx.M em P, a ocorrênia de M é chamada de \u0010escopo\u0011 da ocorrênia de λx à esquerda.\nP ≡ (λy.yx(λx.y(λy.z)x))vw\n\nO escopo do λy mais à esquerda é yx(λx.y(λy.z)x);\nO escopo do λx é y(λy.z)x;\nO escopo do λy mais à direita é z.\n\nVariaveis Livre e Ligadas\nA ocorrênia de uma variável x em um termo P é dita:\n\nLigada se ela está no escopo de um λx em P ;\nLigada e ligadora se e somente se ela é o x em λx;\nLivre caso contrário.\n\nSe x tem pelo menos uma ocorrênia ligadora em P , x é chamada de variável ligada de P ;\n\nSe x tem pelo menos uma ocorrênia livre em P , x é chamada variável livre de P ;\nO conjunto de todas as variáveis livres de P chamado FV (P);\nUm termo que não contém variáveis livres é chamado fechado.\n\nExemplo\nDada a expressão:\n(λx.x + y)(4)\nPara avalia-lá é necessário saber o valor de y, não é necessário se preocupar com o valor de x pois ele é um parametro formal da expressão. x ocorre ligado ao λx, e será substituido assim que o argumento 4 for aplicado ao argumento. Já o y, não é ligado a nada e assim fica livre na expressão.\nλx.(((ly.(λ + z) 7) + x)\nNesse exemplo temos x e y ocorrendo ligados e z sendo livre.\nAgora considere o termo:\nP ≡ (λy.yx(λx.y(λy.z)x))vw\n\nTodos os quatro y são ligados;\nOs y mais à esquerda e mais à direita são ligadores;\nO x mais à esquerda é livre;\nO x central é ligado e ligador;\nO x mais à direita é ligado mas não ligador;\nz, v e w são livres.\nLogo, F V (P) = {x, z, v, w}; x, nesse caso, é uma variável ligada e também livre de P .\n\nUm exemplo de substituição seria: \n[(λy.xy)/x](λy.x(λx.x))\n[(λy.(xy))/x](λy.(x(λx.x))) (Reescrita com todos os parênteses)\nλy.([λy.(xy)/x](x(λx.x))) (Aplicação da regra)\nλy.([λy.(xy)/x]x)([λy.(xy)/x](λx.x)) (Aplicação da regra)\nλy.(λy.(xy))([λy.(xy)/x](λx.x)) (Aplicação da regra)\nλy.((λy.(xy))(λx.x)) (Aplicação da regra)\nλy.(λy.xy)(λx.x) (Remoção dos parênteses desnecessários)\nConversão α (renomeação)\nA conversão-a é o nome dado à operação de mudança de nome (consistente) de um parâmetro formal.\nSeja P um termo que contém uma ocorrênia de λx.M e suponha que y /∈ FV(M).(/∈ = Simbolo de não contem)\nA substituição de: λx.M por λy.[y/x]M é chamada de troca de variável livre, ou conversão alpha em P. Se P pode ser tranformado em Q por meio de uma série finita de conversões alpha, diz-se que P e Q são congruentes e então que P é α-conversível para Q\nP = (λx.x + 1) \nQ = (λx.y + 1)\nAs duas abstrações são equivalentes e a conversão α-conversão nos permite mudar o nome do parâmetro formal de uma abstração lambda.\nsendo denotado como:\nP ≡α Q\nλxy.x(xy) ≡ λx.(λy.x(xy))\n          ≡ α λx.(λv.x(xv))\n          ≡ α λu.(λv.u(uv))\n          ≡ λuv.u(uv))\nPara todos P, Q e R:\n\n(reflexividade) P ≡α P ;\n(transitividade) P ≡α Q, Q ≡α R ⇒ P ≡α R;\n(simetria) P ≡α Q ⇒ Q ≡α P .\n\n[TODO: Deixar legivel]\nRedução β (aplicação)\nRepresenta uma computação, a passagem de um estado de um\nprograma para o estado seguinte, dentro do processo de geração de\num resultado. Podemos interpretar no javascript como a aplicação de um argumento em uma função.\nA aplicação de um argumento à uma abstração lambda implica na substituição das ocorrências das variáveis correspondentes ao argumento. Sendo que funções também podem ser passadas como argumentos. sendo exemplificado como:\nλx.y.((λx.x - 3)(y) + x)(5)(6)\nλy.((λx.x - 3)(y) + 5)(6)\n((λx.x - 3)(6) + 5)\n((6 - 3) + 5)\n8\nObserve que o x mais interno não foi substituido na primeira redução, pois estava protegido pelo seu x ligado, já o primeiro x substituiu por 6 apenas seu x ligado.\nForma Normal\nRepresenta um resultado de uma computação, um valor que não é\npassível de novas simplificações ou elaborações. Um termo Q que não possui nenhuma redução-β é chamado de forma normal-β. Sendo similar ao valor já avaliado de funções.\nSe um termo P reduz-β para um termo Q na forma normal-β, ou avalia os termos até retornarem um valor então diz-se que Q é uma formal normal-β de P.\nFazendo mais churches :)\nconst id = x => x\n\nconst zero = f => x => x\nconst one = f => x => f(x)\nconst two = f => x => f(f(x))\nconst three = f => x => f(f(f(x)))\nconst four = f => x => f(f(f(f(x))))\nconst four2 => f => x => succ(three)\n\n// recursao => explicar bem pq eu apanhei p/ entender\nconst Y = f => (x => x(x))(y => f(x => y(y)(x)));\n\nconst succ = n => f => x => f(n(f)(x))\nconst pred = n => n(p => z => z(succ(p(TRUE)))(p(TRUE)))(z => z(ZERO)(ZERO))(FALSE)\n// const succ_pair = p => pair(SECOND(p))(succ(SECOND(p)))\n// const pred = n => FIRST(n(succ_pair)(pair(ZERO)(ZERO)))\n\nconst add = n => m => m(succ)(n)\nconst sub = n => m => m(pred)(n)\nconst mult = n => m => m(add(n))(ZERO)\nconst exp = n => m => m(n)\nconst FIVE = add(TWO)(THREE)\n\nTODO:\n\n[ ] História\n[ ] Definição\n[ ] Aplicação de função\n[ ] Redução beta\n[ ] Anonymous functions\n[ ] Langs FP\n\n"},"02-pure-functions/02-pure-functions.html":{"url":"02-pure-functions/02-pure-functions.html","title":"Funções puras","keywords":"","body":"O que é pureza?\nComo assim?\nTalvez você não se recorde mas funções matemáticas são um conteúdo passado em escolas na quarta série.\nSe lembra disto?\nEm funções matematicas na escola aprendemos que uma função recebe um argumento(x no caso). No caso da função f(x) = x  x multiplicamos o que recebemos por si mesmo. Então caso x é 1 temos uma imagem y que equivale a 1(1  1 = 1), e assim por diante. \nhttps://speakerdeck.com/anabastos/javascript-funcional-front-end-campinas?slide=8\nCom isso podemos desenhar uma reta num grafico demontrando as possíveis entradas e saidas.\nÉ importante lembrar que cada função tem um dominio e imagem. Em um dominio, ou \"input\" de 1 a 4 temos como \"output\" uma imagem com os valores 2, 4, 9, 16 para suas respectivas contas. Não importa quantas vezes eu faça 1 * 1 pois a resposta SEMPRE será 1. \nhttps://speakerdeck.com/anabastos/javascript-funcional-front-end-campinas?slide=9\nCaso 1 * 1 em algum momento dê 2 NAO TEMOS UMA FUNCAO MATEMATICA.\nhttps://speakerdeck.com/anabastos/javascript-funcional-front-end-campinas?slide=11\nCaso a função seja por exemplo, f(x) = ---- se o input de x for  ou  teremos o mesmo output. Isso é ok pois ainda assim temos uma função matematica.\nhttps://speakerdeck.com/anabastos/javascript-funcional-front-end-campinas?slide=10\nOu seja, uma função pura é exatamente o que se espera de uma função matematica comum:\n\nSempre recebem algo\nSempre retornam algo\nNunca mutam algo fora do escopo da propria função\nPara o mesmo input sempre retornam o mesmo output\n\nlet taxa = 10\n\nfunction valorTotal(valor) {\n  return valor + taxa\n}\n\nvalorTotal(10) // 20\ntaxa += 1;\nvalorTotal(10) // 21 :(\n\nFunções nunca devem depender do contexto em que elas estão\nlet taxa = 10\n\nfunction valorTotal(valor) {\n  return valor + taxa\n}\n\nvalorTotal(10) // 20\ntaxa += 1;\nvalorTotal(10) // 21 :(\n\nUma opção correta seria receber mais argumentos:\nfunction valorTotal(valor, taxa) {\n  return valor + taxa\n}\n\nPoxa mas em função matematica não recebemos apenas uma função como argumento?\nEm matematica vimos que dá para criar funções em termos de outras funções e compor funções(f ∘ g).\nAlgo como:\nf(x) = x + g(y).\nVeremos isso no proximo capitulo de currying.\nHere's a (non-exhaustive) list of FP features:\nFirst-Class Functions\nHigh-Order Functions\nPure Functions\nClosures\nImmutable State\nPure functions\nUma Função Pura retorna o valor computado apenas com argumentos a ela passados. Com ela evitamos o chamado efeito colateral, ou seja, não tocamos em variáeis externas nem no estado global. Em outras palavras, ela deve manter tais argumentos intactos. Podemos concluir que: a função pura apenas retorna valores.\nExemplo disso é uma função matemática. A função Math.sqrt(4) sempre retornará 2, não usará nenhuma informação \"obscura\", como configurações ou estado, e nunca causará efeitos colaterais.\nPodemos dizer que uma função pura corresponde ao termo 'função matemática'; O Amor Uno entre a entrada e a saída. São de fácil interpretação e altamente reutilizáveis. Por terem total independência, são mais suscetíveis a serem reuzadas aqui ou acolá, no projeto x ou y.\nSegue-se abaixo o exemplo de função pura e \"não pura\" - [non-pure].\n// function that prints a message to the center of the screen\nvar printCenter = function( str ) {\n  var elem = document.createElement( \"div\" );\n  elem.textContent = str;\n  elem.style.position = 'absolute';\n  elem.style.top = window.innerHeight / 2 + \"px\";\n  elem.style.left = window.innerWidth / 2 + \"px\";\n  document.body.appendChild( elem );\n};\nprintCenter( 'hello world' );\n\n// pure function that accomplishes the same thing\nvar printSomewhere = function( str, height, width ) {\n  var elem = document.createElement( \"div\" );\n  elem.textContent = str;\n  elem.style.position = 'absolute';\n  elem.style.top = height;\n  elem.style.left = width;\n  return elem;\n};\ndocument.body.appendChild(\n  printSomewhere(\n    'hello world',\n    ( window.innerHeight / 2 ) + 10 + \"px\",\n    ( window.innerWidth / 2 )  + 10 + \"px\"\n  )\n);\n\nA de percebermos que na \"non-pure\" exige-se o estado do objeto window para computar a altura [height] e largura [width], entretanto, a pura exige-nos que passêmo-las - height e width - como argumentos. E tal comportamento - que da pure function provém - permite-nos exibir a mensagem em qualquer posição, tornando-a muito versátil.\nTendemos a pensar que a função non-pure seja melhor devido a ela ter adicionado[appendChild] o elemento [elem] em vez de retorná-lo, entretanto, a função printSomewhere() está mais apta a encaixar-se nas técnias da programação funcional.\nvar messages = [ 'Leibniz', '1646', 'função', 'matemática' ];\nmessages.map( function( s, i ) {\n  return printSomewhere( s, 100 * i * 10, 10 * i * 10 );\n}).forEach( function( element ) {\n  document.body.appendChild( element );\n});\n\nQuando as funções são puras, ou seja, independentes de estado ou do ambiente, não precisamos dar a mínima importância para quando ou onde elas serão computadas. Veremos isso mais adiante com a avaliação preguiçosa.\nFonte\nTransparencia referencial: passando dois como argumento de uma função \"quadrado\" a resposta sempre sera a mesma\nO mesmo não é valido para uma função de geradora de números ou ate mesmo uma que lê arquivos.\nBasically, if a function consistently yields the same result for the same input, it is referentially transparent.\nPure Functions + Immutable Data = Referential Transparency\nCom isso podemos trabalhar com memoization\nWith this concept, a cool thing we can do is to memoize the function. Imagine we have this function: (+ 3 (+ 5 8))\nThe (+ 5 8) equals 13. This function will always result in 13. So we can do this: (+ 3 13)\nWe can replace the entire expression with a numerical constant and memoize it.\nTODO:\n\n[ ] O que é função pura(abordar paralelismo em outras langs)\n[ ] Idepotencia\n[ ] Retornar funções de forma consistente \n[ ] Isolamento de funcionalidade para cada função\n[ ] Use parametros para dados substituiveis ao invés de hardcoding\n[ ] Testing\n\n"},"03-currying-vs-partial-application/03-currying-vs-partial-application.html":{"url":"03-currying-vs-partial-application/03-currying-vs-partial-application.html","title":"Currying & Parcial Application","keywords":"","body":"Currying vs Partial Application\nCurrying\nComo vimos no capitulo 1 a composição de funções recebe apenas um parametro que são aplicados um de cada vez, por isso ao programarmos em linguagens puramente funcional geralmente podemos usar uma função com multiplos parametros pois o proprio compilar reescreve em novas funções de apenas um parametros compostas entre si. Isso é o que chamamos de \"Currying\", palavra que veio do Haskell Curry, um matematico que foi de grande influencia no desenvolvimento de linguagens funcionais.\nVoltando a ponte de funções matematicas, vimos na escola blablabal composição de função.\nPorém, quando usamos multiplos argumentos no js temos algo parecido com isso:\nconst add = (x, y) =>  x + y\nadd(1) //NaN\nadd(1, 1) //2\n\nPara simularmos um currying no javascript podemos fazer algo assim:\nconst h =  x => y => x + y\n}\nadd(a)(b) // a + b\n\nNesse caso estamos retornar uma sub-função dentro de uma função para podermos resolver o x + y passando um parametro por vez.\nTanto que, quanto tentamos aplicar apenas um dos argumentos, não recebemos um NaN mas sim uma função esperando o proximo argumento.\nadd(a) // y => a + y\n\nSupondo que vamos receber vários argumentos na nossa função, nesse caso teremos que retornar funções que retornar funções que retornam funções. \nconst addThree =  x => y => z => x + y + z\n}\naddThree(a)(b)(c) // a + b + c\n\nCompiladores de linguagens funcionais como haskell interpretam apenas um argumento por vez, então por mais que você coloque os argumentos como add(1,2) ele já faz o próprio curry por padrãoe portanto a aplicação parcial de um add(1)(2) da mesma função seria aceita sem problemas.\nUm exemplo disso é assinatura das funções em Haskell, uma função como a função abaixo teria a seguinte assinatura:\naddThree :: Int -> Int -> Int -> Int  \naddThree x y z = x + y + z\n\nEm que representa os argumentos que serão recebidos em ordem e o retorno esperado da função, no caso um inteiro com a soma dos argumentos.\nIsso vem do fato que haskell teve suas bases no calculo lambda em que apenas um argumento é aceito por função, veremos mais sobre isso no capitulo de calculo lambda.\nPara facilitar o processo e simular o que linguagens funcionais fazem, podemos usar o curry da biblioteca RamdaJS também para resolver nosso problema de forma semantica:\nconst add =  curry((x, y) -> x + y)\nadd(a)(b) // a + b\n\nQuando fazemos 1 + 1 no javascript esta operação binaria tem dois parametros, em linguagens funcionais o operador + geralmente funciona como a função que criamos agora. Ou seja, quando voce escreve x + y o compilador reescreve o codigo transforma o calculo em infixo ((+) x y), em que a função + chama dois parametros.\nPartial Application\nNotamos que funções com multiplos parametros podem ser quebrados em funções com parametros menores e é a forma matematica de se fazer isso mas isso nos leva a outra tecnica chamada Aplicação parcial e tem uma diferença tenua do Curry.\nconst add = (a, b) =>\n    (b === undefined) ? (b => add(a, b)) : a + b\n\nAridade\nPodemos também implementar nosso proprio curry no javascript e pra isso chegamos no conceito aridade. Aridade é o numero de argumento que a nossa função espera para sabermos quando devemos parar de retornar funções e retornar um valor. Para implementarmos nosso curry temos de primeiro saber a aridade de nossa função\nconst arity = fn => return fn.length\nconst add => (x, y) => x + y\n\narity(add) //2\n\nNote que a função add que soma dois numeros tem um valor aridade igual a 2.\nconst arity = fn => fn.length\n\nPara implementarmos uma função de curry vamos precisar saber qual a aridade da função e pra isso vamos reutilizar a função arity.\nContinuando a logica, vamos então criar uma função curry e fazer com que ela chame uma uma nova função chamada curried que vai ser nossa função \"\"curriada\"\".\nconst curry = (fn) => {\n    return const curried = () => \"Curry com batata\"\n}\n\nAssim:\nconst add = (x, y) => x + y\ncurry(add) //[Function]\ncurry(add)(1) //\"Curry com batata\" \ncurry(add)(1)(2) //TypeError: curry(...)(...) is not a function\n\nPara considerarmos mais de um argumento podemos então receber os argumentos da primeira função e passar como argumento para nossa curried. Alcançou a aridade a função é chamada caso contrario a função curried é chamada novamente com os argumentos remanescentes.\nconst curry = (fn, ...args) => {\n  return const curried = (...args) => {\n      return args.length >= arity(fn) ?\n        fn.call(this, ...args) :\n        (...rest) =>  curried.call(this, ...args, ...rest);\n  }\n}\n\nTestando temos o esperado:\n\n```javascript\nconst add = (x, y) => x + y\n\nconst curriedAdd = curry(add)\nconst addTwo = add(2)\nadd2(2) //4\n\nTODO:\n\n[ ] Aridade\n[ ] Aplicação parcial e curry\n[ ] Curry do ramda\n[ ] Bons exemplos, reaproveitamento de codigo\n[ ] Citar capitulo de architecture(injeção de dependencia etc)\n\n"},"04-immutability/04-immutability.html":{"url":"04-immutability/04-immutability.html","title":"Imutabilidade","keywords":"","body":"Imutabilidade\nTODO:\n\n[ ] Exemplo do pq pode ser problematico\n[ ] Usar apenas constantes(tricky)\n[ ] Arrays: não usar .push ou .splice.\n[ ] Objects: Object.freeze. destructuring. Object.assign\n[ ] Copiar objetos ao invés mutar\n[ ] Single source of truth e aplicações no Frontend\n\n"},"05-declarative/05-declarative.html":{"url":"05-declarative/05-declarative.html","title":"Programação Declarativa","keywords":"","body":"Programação Declarativa\nTODO:\n\n[ ] Imperativo vs Declarativo\n[ ] Nomear variaveis e funções de forma declarativa\n[ ] Nomes de funções declarativos\n[ ] Evitar imperatividade no código(switch code, too much ifs).\n\nDemonstação\nTalvez seja uma rápida demonstração a melhor maneira de iniciarmos com o paradigma funcional. Realizaremos uma só tarefa de duas maneiras, na primeira utilizaremos os métodos já existentes no 'Core' e noutra o paradigma funcional. Em seguida, compararemos os dois métodos.\nA aplicação – an e-commerce website\nDigamos que estamos a construir uma aplicação do mundo real, um comércio eletrônico para uma empresa de feijão e café que tem como objetivo aceitar pedidos por conrrespondência. Eles vendem café de qualidade e quantidade distintas, acarretando mudanças de preço.\nMetodos imperativos\nPrimeiramente, vamos conferir o estilo imperativo. Para melhor demonstração, temos de criar objetos que mantenham os dados. Neles podemos buscar valores como se estivéssemos operando no banco de dados; e posteriormente, talvez possamos operá-los por lá. Mas, no momento, assumiremos que são definidos de forma estática.\n// create some objects to store the data\nvar columbian = {\n  name: 'columbian',\n  basePrice: 5\n};\nvar frenchRoast = {\n  name: 'french roast',\n  basePrice: 8\n};\nvar decaf = {\n  name: 'decaf',\n  basePrice: 6\n};\n\n// we'll use a helper function to calculate the cost\n// according to the size and print it to an HTML list\nfunction printPrice( coffee, size ) {\n  if( size == 'small' ) {\n    var price = coffee.basePrice + 2;\n  }\n  else if( size == 'medium' ) {\n    var price = coffee.basePrice + 4;\n  }\n  else {\n    var price = coffee.basePrice + 6\n  }\n\n  // create the new html list item\n  var node = document.createElement( 'li' );\n  var label = coffee.name + ' ' + size;\n  var textnode = document.createTextNode( label + ' price: $'+price );\n  node.appendChild( textnode );\n  document.getElementById( 'products1' ).appendChild( node );\n}\n\n// now all we need to do is call the printPrice function\n// for every sigle combination of coffee type and size\nprintPrice( columbian, 'small' );\nprintPrice( columbian, 'medium' );\nprintPrice( decaf, 'medium' );\n\nNotemos a simplicidade do código. E se houvessem mais sabores além dos três? quem sabe 20, ou talvez 40? Imaginemos então que se além do tamanho, existisse as opções orgânico e não orgânico. Haja código!\nUsando este método, estamos dizendo à máquina o que imprimir para cada sabor e tamanho. Isso é o que há de pior em código imperativo - repetição.\nFunctional programming\nEnquanto no paradigma imperativo dizemos para a máquina como ela deve agir para resolver o problema - passo a passo -, no funcional o descrevemos matematicamente para que a máquina aja sob ele.\nTomando o princípio funcional, teremos o mesmo aplicativo com o seguinte código:\n// separate the data and logic from the interface\nvar printPrice = function( price, label ) {\n  var node = document.createElement( 'li' );\n  var textnode = document.createTextNode( label + ' price: $' + price );\n  node.appendChild( textnode );\n  document.getElementById( 'products2' ).appendChild( node );\n};\n\n// create function objects for each type of coffee\nvar columbian = function() {\n  this.name = 'columbian';\n  this.basePrice = 5;\n};\nvar frenchRoast = function() {\n  this.name = 'french roast';\n  this.basePrice = 8;\n};\nvar decaf = function() {\n  this.name = 'decaf';\n  this.basePrice = 6;\n};\n\n//create object literals for te different sizes\nvar small = {\n  getPrice : function() { return this.basePrice + 2 },\n  getLabel : function() { return this.name + ' small' }\n};\nvar medium = {\n  getPrice : function() { return this.basePrice + 4 },\n  getLabel : function() { return this.name + ' medium' }\n};\nvar large = {\n  getPrice : function() { return this.basePrice + 6 },\n  getLabel : function() { return this.name + ' large' }\n};\n\n// put all the coffee types and sizes into arrays\nvar coffeeFlavors = [ columbian, frenchRoast, decaf ];\nvar coffeeSizes = [ small, medium, large ];\n\n// build new objects that are combinations of the above\n// and put them into a new array\nvar coffees = coffeeFlavors.reduce( function( previous, current ) {\n  var newCoffee = coffeeSizes.map( function( mixin ) {\n    // `plusmix` function for functional mixins, see Ch.7\n    var newCoffeeObj = plusMixin( current, mixin );\n    return new newCoffeeObj();\n  });\n  return previous.concat( newCoffee );\n}, [] )\n\n// we've now defined how to get the price and label for each\n// coffee flavor and size combination, now we can just print them\ncoffees.forEach( function( coffee ) {\n  printPrice( coffee.getPrice(), coffee.getLabel() );\n})\n\nNos é evidente que este é enormemente maior em termos de modularidade. Torna-se agora tarefa simples adicionarmos novos tamanhos e sabores, segue-se abaixo um exemplo:\nvar arabica = function() {\n  this.name = 'arabica',\n  this.basePrice = 11;\n};\n\nvar extraLarge = {\n  getPrice : function() { return this.basePrice + 10 },\n  getLabel : function() { return this.name + ' extra large' }\n};\n\ncoffeeFlavors.push( arabica );\ncoffeeSizes.push( extraLarge );\n\nOs arrays de objetos coffee são \"misturados\" com os de objetos size - com o auxílio da função plusMixin (consulte o Cap. 7, Programação funcional e orientada a objetos em javascript). As classes de tipo coffee é quem armazena em variáveis o nome do sabor e o preço padrão, as de tipo size contêm métodos para operarmos com os nomes e preços. A \"mistura\" acontece dentro de uma operação map(), que aplica uma função pura em cada elemento do array e retorna uma nova função dentro da operação reduce() - outra higher order function similar a função map(), exceto pelo fato dele \"reduzir\" todos os elementos de um Array num só elemento. E por conseguinte, o novo array contendo todas as combinações de tipos e tamanhos é iterado com o método forEach(); o forEach() é outra higher order function que aplica um callback em cada objeto do array. Neste exemplo, fornecemos uma função anônima que instancia os objetos e chama a função printPrice() passando os métodos getPrice() e getLabel() como argumentos.\nPoderíamos ainda, deixar nosso exemplo mais funcional removendo a variável coffees e fazendo um encadeamento de funções - este é um poder secreto da programação funcional.\ncoffeeFlavors.reduce( function( previous, current ) {\n  var newCoffee = coffeeSizes.map( function( mixin ) {\n    // `plusMixin` function for functional mixins, see Ch. 7\n    var newCoffeeObj = plusMixin( current, mixin );\n    return new newCoffeeObj();\n  });\n  return previous.concat( newCoffee );\n}, []).forEach(function( coffee ) {\n  printPrice( coffee.getPrice(), coffee.getLabel() );\n})\n\nAlém disso, o fluxo de controle não é \"uma sentada de cima pra baixo\" como aconteceu em nosso código imperativo. Na programação funcional, as higher-order functions tomam o lugar dos laços for e while, e, em consequência quase ou nenhuma importância é dada quanto a ordem de execução. Iniciantes tedem a tremer quando \"batem o olho\" em código quem tem como princípio o paradigma funcional, no começo pode até dar medo, confesso, mas basta um pouco de prática para pegarmos o jeito - não é doloroso -, e logo verá o quão bom é código funcional.\n"},"06-higher-order-functions/06-higher-order-functions.html":{"url":"06-higher-order-functions/06-higher-order-functions.html","title":"Funções de Primeira Classe","keywords":"","body":"Higher Order Functions\n\nNa Computação Funções de Alta Ordem também conhecidas como Funções de Primeira Classe\nsão funções que suportam a passagem de outras funções como argumentos retornando como valor para outras funções.\nEm outras palavras, são funções que operam em outras funções, seja levando-os como argumentos ou devolvendo-os.\nThe idea of functions as first-class entities is that functions are also treated as values and used as data.\nFunctions as first-class entities can:\nRefer to it from constants and variables\nPass it as a parameter to other functions\nReturn it as result from other functions\nThe idea to treat functions as values and pass functions like data. This way we can combine functions with other functions to create new functions with new behavior.\nThese functions have similar logic, but the difference is the operators functions. If we can treat functions as values and pass it as arguments, we can build a function that receives the operator function and use it inside our function. Let's build it!\nExemplos de função sendo passada como argumento ou como retorno\nO que torna javascript uma linguagem de programação que suporta programação funcional é a habilidade de ter HOF. \nDe certa forma podemos dizer que uma Self-invoking function é uma higher-order function. Higher-order functions são funções que recebem ou retornam outras.\nNão é comum vermos Higher-order functions em linguagens tradicionais. O programador imperativo certemante usará um loop para iterar um array, porém, o funcional adotará uma abordagem completamente diferente. Podemos trabalhar o array com uma higher-order function, aplicando-a em cada item prar criar um novo array.\nEssa é a ideia central do paradigma funcional. Uma Higher-order function permite-nos passar sua lógica a outras funções, bem como objetos.\nFunções em JavaScript são tratadas como \"Cidadãs de primeira classe\", tal comportamento pode ser encontrado no Haskell, Scheme ou em linguagens funcionais clássicas. Esse termo pode soar bizarro - Cidadãs de primeira classe -, mas isso simplesmente quer dizer que funções são tratadas da mesma maneira que tipos primitivos: números e objetos. Se números e objetos tem \"passe livre\", funções também têm.\nÉ possivel atribuir essas funções a variaveis var ou letou ainda a constantes const\nvar soma = (x, y) => x + y;\nlet subtracao = (x, y) => x - y;\nconst calcular = (fn, x, y) => fn(x, y);\ncalcular(soma, 1, 2); // 3\ncalcular(subtracao, 1, 2); // -1\n\nPara vermos isto em ação, usaremos uma higher-order com nossa função ValueAccumulator() da seção anterior:\n// using forEach() to iterate through an array and call a\n// callback function, accumulator, for each item\nvar accumulator2 = ValueAccumulator();\nvar objects = [ obj1, obj2, obj3 ]; // could be huge array of objects\nobjects.forEach( accumulator2 );\nconsole.log( accumulator2() );\n\nFonte\nhttps://github.com/LeandroTk/learning-functional-programming/tree/master/javascript\nFunctional Methods with arrays\nArray.prototype.map()\nA função map() é a capitã do time. Ela simplesmente aplica o callback em cada elemento do array.\n\nSintaxe: arr.map( callback [, thisArg] );\n\nParâmetros:\n\ncallback(): esta função produz um elemento para o novo array, recebendo os argumentos:\ncurrentValue: fornece-nos o elemento em processamento.\nindex: fornece-nos a posição do elemento em processamento.\narray: fornece-nos o array em processamento.\n\n\nthisArg(): Esta função é opcional. O valor é usado com this ao executar o callback.\n\nExemplos:\nlet\n  integers = [ 1, -0, 9, -8, 3 ],\n  numbers = [ 1, 2, 3, 4 ],\n  str = \"Santo Tomás de Aquino\";\n\n// map integers to their absolute values\nconsole.log( integers.map( Math.abs ) );\n\n// multiply an array of numbers by their position in the array\nconsole.log( numbers.map( ( x, i ) => x * i ) );\n\n// Capitalize every other word in a string\nstr\n  .split(' ')\n  .map( ( s, i ) => !( i % 2 ) && s.toUpperCase() || s );\n\nEmbora o método Array.prototype.map pertença à o objeto Array, este pode ser facilmente extendido e personalizado a gosto nosso.\nMyObject.prototype.map = function( f ) {\n  return new MyObject( f( this.value ) );\n}\n\nArray.prototype.filter()\nA função filter() é usada para selecionar elementos de um array. O callback deve retornar True (para incluir o elemento no novo array) ou False (para ignorá-lo). Podemos obter um comportamento semelhante mediante o uso da função map() retornando o valor null para os elementos que desejarmos eliminar, mas a função filter() eliminará o elemento do novo array em vez de inserir null em seu lugar.\n\nSintaxe: arr.filter(callback [, thisArg]);\n\nParâmetros:\n\ncallback(): Esta função é usada para testar cada elemento do array. Retorna True para manter o elemento, False caso contrário. Segue-se seus parâmetros:\ncurrentValue: fornece-nos o elemento em processamento.\nindex: fornece-nos a posição do elemento em processamento.\narray: fornece-nos o array em processamento.\n\n\nthisArg(): Esta função é opcional. O valor é usado com this ao executar o callback. \n\nExemplos:\nlet \n  myArray = [ 1, 3, 6, 10, 15 ],\n  words = \"4 é o segundo número quadrado. 2² = 2 x 2 = 2 + 2.\".split(' '),\n  re = /[^x][a-zA-Z]|[éóáúí]/;\n\n// remove all negative numbers\nconsole.log( [ -1, 4, -10, 19 ].filter( x => x > 0 ) );\n\n// remove null values after a map operation\nconsole.log( words.filter( s => s.match( re ) ) );\n\n// remove radom objects from a array\nconsole.log( myArray.filter( () => 0 | Math.random() * 20 ) );\n\nArray.prototype.reduce()\nÀs vezes chamada de fold, a função reduce() é usada para reduzir os elementos do array em um. O callback retorna a lógica responsável por combinar os objetos. Geralmente a usamos com números para obter o produdório ou o somatório destes. E se tratando de um conjunto strings, a usamos para concatená-las formando uma só única.\n\nSintaxe: arr.reduce(callback [, initialValue]);\n\n\ncallback(): esta função retorna a combinação de dois elementos num só. Segue-se seus parâmetros:\npreviousValue: fornece-nos o valor previamente retornado pela última execução do callback, ou o initialValue, se fornecido\ncurrentValue: fornece-nos o elemento em processamento.\nindex: fornece-nos a posição do elemento em processamento.\narray: fornece-nos o array em processamento.\n\n\npreviousValue(): Está função é opcional. É o objeto a ser usado pela primeira execução do callback.\n\nExemplos:\nlet numbers = [ 1, 2, 3, 4 ];\n\n// sum up all the values of an array\nconsole.log( numbers.reduce( ( x, y ) => x + y, 0 ) );\n\n// prod up all the values of an array\nconsole.log( numbers.reduce( ( x, y ) => x * y, 1 ) );\n\n// find the largest number\nconsole.log( numbers.reduce( ( a, b ) => Math.max( a, b ) ) );\n\nHonorable mentions\nA caixa de ferramentas a auxiliar-nos não é composta apenas pelas funções map(), filter() e reduce(). Existem tantas mais, as quais podemos usar em nossos aplicativos funcionais.\nArray.prototype.forEach\nEssencialmente a versão não pura do map(), forEach() também itera e aplica um callback() sobre cada elemento do array, porém, nada retorna. É simplesmente uma alternativa \"clean\" ao laço for.\n\nSintaxe arr.forEach(callback [, thisArg]);\n\nParâmetros: \n\ncallback(): Está função será executada sobre cada elemento do array. Segue-se seus parâmetros:\ncurrentValue: fornece-nos o elemento em processamento.\nindex: fornece-nos a posição do elemento em processamento.\narray: fornece-nos o array em processamento.\n\n\nthisArg(): Esta função é opcional. O valor é usado com this ao executar o callback. \n\nExemplos:\nlet arr = [ 1, 4, 10, 20 ];\n\nlet nodes = arr.map( function( x ) {\n  let elem = document.createElement( \"div\" );\n  elem.textContent = x;\n  return elem;\n});\n\n// log the value of each item\narr.forEach( function( x ) { console.log( x ) } );\n\n// append notes to the DOM\nnodes.forEach( function( x ) { document.body.appendChild( x ) } );\n\nArray.prototype.concat\nAo trabalharmos com diversos arrays e, este trabalho não envolver loops for e while, certamente precisaremos uní-los. Eis a função \"built-in\" concat(). E o legal é que ela retorna os arryas mantendo-os intactos, ou seja, é pura. E tem mais, ela é capaz de unir uma quantidade indefinida de arrays.\n// concatenate two arrays\nconsole.log( [ 2, 4, 6 ].concat( [ 'a', 'b', 'c' ] ) ); // out: [ 2, 4, 6, 'a', 'b', 'c' ]\n\nPodemos perceber que ela uniu-os mantendo o original intacto. Isso quer dizer que podemos fazer o encadeamento sem maiores problemas.\nlet\n  arr1 = [ 2, 6, 12, 20 ],\n  arr2 = [ 1, 4, 9, 16 ],\n  arr3 = [ 1, 5, 13, 25 ];\n\nlet x = arr1.concat( arr2, arr3 );\nlet y = arr1.concat( arr2 ).concat( arr3 );\nlet z = arr1.concat( arr1.concat( arr3 ) );\nconsole.log( x, y, z )\n\nAs variáveis x, y e z todas contêm [ 2, 6, 12, 20, 1, 4, 9, 16, 1, 5, 13, 25 ].\nArray.prototype.reverse\nArray.prototype.sort\nArray.prototype.every and Array.prototype.some\nFonte\n"},"07-recursion/07-recursion.html":{"url":"07-recursion/07-recursion.html","title":"Recursão","keywords":"","body":"Recurção\nTODO\n\n[ ] como funciona\n[ ] resolvendo problemas com recursão\n[ ] continuations\n[ ] TCO\n[ ] trampolines\n[ ] memoization ramda\n\n"},"08-composition-and-pipelines/08-composition-and-pipelines.html":{"url":"08-composition-and-pipelines/08-composition-and-pipelines.html","title":"Composição de pipeline","keywords":"","body":"Composição & Pipeline\nSequential Pattern Strategy\nQuando falamos de paradigmas de programação diferentes também falamos de formar de modelar e pensar em problemas diferentes. \nEm linguagens procedurais nossas computações envolvem nosso código separado em modulos operando em dados. Já em linguagens orientadas a objetos encapsulamos nosso código e dados para que eles interajam entre si por meio de mensagens. Esses modelos são assim pois vem da maquina de turing como já explicado em capitulos anteriores\nVis whose theoretical model of computation is the Turing Machine, LISP's theoretical model of computation is the Lambda calculus \nImg\nPra quem esta habituado com OOP ou programação imperativa, a programação funcional mais pura lida de uma nova perspectiva a forma de modelar o fluxo do seu programa que é o de componentização. Nele os dados fluem por meio de apenas funções completamente independentes entre si visto que o seu modelo teorico de computação vem do lambda calculus lidar apenas com funções.\nEntão na pratica a forma de pensar para resolver um problema no padrão sequencial é, separar o problema em pequenas funções puras de sub-problemas e \"compo-las\" para solucionar.\nPLUS: Também é muito mais facil testar seu código com pequenas funções em que você pode testar cada passo.\nComo composição de funções funciona?\nComposiçao de funções vem também de um conceito matematico, nele trabalhamos com a combination combinação de funções como f ou g em f . g. \nEm Javascript normal fariamos algo assim:\nconst f = x => x + 1;\nconst g = y => y * y;\nconst x = 2;\nconst composed = f(g(x)); // 5\n\nNesse exemplo, temos uma função que adiciona 1 e que dobra o valor. Quando passando x para a função g o seu retorno é passado para função f retornando o valor de 5.\nEntão nossa composição é avaliada de dentro para fora e não segue o fluxo sequencial que queremos então ele aparenta muito mais complexo do que deveria e pra isso precisamos de pipeline.\nPipeline\nPipeline em ciência da computação é todo tipo de processamento de dados conectado em série em que a saída de um elemento é a entrada do proximo similar ao pipe do UNIX.\nO javascript tem uma proposal para a implementação de um pipeline operator inspirado por linguagens funcionais como F#, OCaml, Elixir, Elm. Mas por enquanto é necessario funções como pipe() e compose() do Ramda ou o flow() do Lodash.\nDessa forma nosso código pode aparentar assim:\nconst f = x => x + 1\nconst g = y => y * y\nconst x = 2\nconst composed = x \n  |> f\n  |> g // 5\n\nIsso acaba se tornando muito mais legivel visto que temos uma visão sequencial em que temos controle do fluxo sendo aplicado ao valor x mantendo a declaratividade do código.\nResolvendo problemas\nCurrying\nAsync\nErros\nEither\nSide Effects\n"},"09-modules-and-async/09-modules-and-async.html":{"url":"09-modules-and-async/09-modules-and-async.html","title":"Modulos, Async, contratos, error handling","keywords":"","body":"Modulos, Async e Considerações\nTODO\n\n[ ] Organizar modulos exportanto funções\n[ ] Promises ou futures ao invés de callbacks\n[ ] Predicados\n[ ] Contratos de funções(matematica)\n[ ] Utilizar promises ou monads ao invés de try catchs.\n[ ] Maybe monad para lidar com nulls e undefineds.\n\n"},"10-classes/10-classes.html":{"url":"10-classes/10-classes.html","title":"Não usando classes","keywords":"","body":"Fugindo de classes\nUtilizando objetos literais e funções\nClosure\nClosure é um metodo interessante para manter estado de uma função javascript.\n“Writing in ECMAScript language without understanding closure is like writing Java without understanding classes” — Douglas Crockford.\nJavaScript is a lexical scoping language. This means, inheritance flows inwards. A variable outside a function is available for usage within a function but not the other way around.\nJavascript tem escopo de linguagem lexico. Ou seja, herança flui de dentro pra fora, sendo assim, uma variável fora de função está disponível dentro da função enquanto variáveis dentro da função estão disponíveis apenas dentro da propria função.\nQuando colocamos codigo dentro de funções javascript fechamos o seu escopo e tornamos a variável passada como argumento como independente.\nNo exemplo a seguir temos uma função dentro de uma função closure em que retornamos a função de dentro:\nfunction closure(x) {\n\n    function increase() {\n        return 1 + x;\n    }\n    return increase;\n}\n\nconsole.log(closure(3));\n\nIsso pode ser verificado no próprio navegador:\nhttps://cdn-images-1.medium.com/max/1600/1*QGWZ21n2CUD_DwIWMprYBQ.jpeg\nE ai vem a pergunta, se uma closure é o uso de uma variável fora da própria função, pq este exemplo não é uma closure?\nfunction closure(x) {\n\n    const increased = 1 + x;\n    return increased;\n}\n\nconsole.log(closure(3));\n\nNão é por causa da forma como o Javascript avalia essa expressão. O escopo da função é criado assim que a memória é alocada a ele. Este processo acontece até que a memória alocada para a função ser liberda então qualquer valor criado é perdido.\nfunction closure(x) { // Função é chamda e memória é alocada para ela.\n\n    const increased = 1 + x; // Expressão é executada.\n    return increased; // No fim da função a memória é liberada.\n} \n\nconsole.log(closure(3)); // Processo ocorre sempre que a função é chamada.\n\nO ponto é: quando criamos uma função dentro de outra função criamos um novo escopo que não é desalocado ao fim da execução da função podendo guardar contextos.\nDesta forma podemos criar um número ilimitado de instâncias de função guardando o contexto de seus valores passados.\nfunction closure(x) {\n\n    function increase() {\n        return 1 + x;\n    }\n    return increase;\n}\n\nconst counting = closure(0);\n\nconsole.log(counting.increase()); // return 1\nconsole.log(counting.increase()); // return 2\n\nOu seja, closures são apenas funções com dados preservados. QUando criamos uma closure, estamos falando para o Javascript lembrar o estado de coisas dentro de sua função, e suas unicas variaveis usadas são consideradas 'closures'.\nIsso é particularmente util principalmente porque closures são basicamente funções com estado, similar a classes que teriam variaveis privadas.\nAs variaveis são privadas porque funções externas não podem acessa-las com uma chamadas explicita. Isso permite que uma função inteira tenha conteúdo proprio e se proteja contra mudanças indesejadas.\nClosures portanto são uma forma sucinta de modularizar sem a necessidade de criação de classes. Porém permitindo a replicabilidade do codigo e reduzindo o numero de escopos globais necessarios. \nSendo assim, closures são mais do que criar funções dentro de outras funções. É uma tecnica usada para criar variaveis que são protegidas de mudanças externas, isoladas do resto da aplicação e com estado persistente.\nLenses\n"},"11-tacit/11-tacit.html":{"url":"11-tacit/11-tacit.html","title":"Programação tacita","keywords":"","body":"Tacit Programming\nDefinição e contrução p/ omitir argumentos\nExemplos com ramda\n"},"12-combinators/12-combinators.html":{"url":"12-combinators/12-combinators.html","title":"Combinators","keywords":"","body":"Combinators\nChurch Encoding\nExemplos logicos\nPrincipais Combinators\nY Combinator\nSKI Combinators\n"},"13-category-theory/13-category-theory.html":{"url":"13-category-theory/13-category-theory.html","title":"Teoria das categorias","keywords":"","body":"Teoria das Categorias\nTeoria das categorias é um ramo da matematica abstrata que unifica outros campos da matematica,tal conceito teorico empondera a composição de funções, promove a modularidade, abstração, reusabilidade e componentibilidade de funções por possibilitar dividir problemas grandes em problemas menores.\nUma definição academica de teoria das categorias expressa categorias como uma coleção de dados que satisfazem algumas propriedades particulares:\nUma categoria esta sujeita e satisfaz os seguintes axiomas:\n\nUma coleção de coisas chamadas de objetos por exemplo A,B,C... variando sobre o objeto.\nUma coleção de coisas chamadas morfismos, as vezes chamadas de flechas por padrao f,g,h,... mais tarde α,β,φ,ψ,χ variando sobre o morfismo.\nUma relação sobre morfismos e pares de objetos, comumente chamado de digitacao dos morfismos. A definiçõa padrao expressa como uma relação de f:a → b , para morfismo f e objetos a e b, tambem representado por a → b é o tipo de f, em que f é u morfismo de A para B.\nfonte f = A e o alvo f = B   sempre f: A → B.\nUma operação binaria parcial em morfismos chamada de composição. Onde f:g é a notação de composição dos morfismos  f e g tambem representado por g o f , ou ainda gf , segundo a convenção f=g =g o f= gf.\nPara cada objeto A existe um morfismo distinto chamado de identidade em A. Por padrao idA, ou  id quando A esta limpa a partir do contexto, denota a identidade no objeto A.\nDe uma forma mais suscinta Teoria das categorias é sobre como nosso cerebro trabalha com informações, \"teoria das categorias é sobre conectar pontos\"\n\nTerminologia\nCategorias ainda sao conjuntos com o mesmo tipo. Em javascript eles sao arrays ou objetos que contem variaveis que sao explicitamente declaradas como numbers, strings, booleans, Dates, Nós.\nMorfismos são funções puras, que dada uma entrada sempre retornam a mesma saida.\nOperações Homomorficas podem operar sobre varias categorias.\nTeoria das categorias nos diz que quando temos 2 morfismos onde a categoria da primeira função é a entrada esperada de outra entao elas podem ser compostas. Teoria das categorias possui necessariamente 2 coisas:\n\n1 Objetos(em Javascript sao conhecidos como Tipos)\n2 Morfismos(em Javascript sao funções puras que so trabalham com tipos).\nPorem é necessario uma definicao mais precisa.\nObjetos em teorias das categorias sao mais como variaveis com tipos explicitos de dados e nao como coleções de propriedades como define Javascript\nMorfismos são funções puras que usam esses tipos.\nUsar teoria das categorias em javascript significa trabalhar um certo tipo por categoria. Tipos de dados sao numeros\n\n\nFuntores\nMonadas\n"},"14-architecture/14-architecture.html":{"url":"14-architecture/14-architecture.html","title":"Arquitetura Funcional","keywords":"","body":"Design Patterns\nEvent Sourcing\n"},"15-langs/15-langs.html":{"url":"15-langs/15-langs.html","title":"Linguagens que copilam para JS","keywords":"","body":"Linguagens que compilam JS\nELM\nReason\nClojureScript\nPureScript\nTypeScript\n"}}}