functional-programming

问题 The Wikipedia article Function composition (computer science) says: Like the usual composition of functions in mathematics, the result of each function is passed as the argument of the next, and the result of the last one is the result of the whole. I have two questions about it: A composable function must have both arguments and return value? So following functions are not: def doNothing(): Unit = () def myName(): String = "My name" def eat(food:String): Unit = () Is my understanding correct

问题 I'm playing around with Scala's lazy iterators, and I've run into an issue. What I'm trying to do is read in a large file, do a transformation, and then write out the result: object FileProcessor { def main(args: Array[String]) { val inSource = Source.fromFile("in.txt") val outSource = new PrintWriter("out.txt") try { // this "basic" lazy iterator works fine // val iterator = inSource.getLines // ...but this one, which incorporates my process method, // throws OutOfMemoryExceptions val

问题 I'm evaluating Scala and am having a problem with its immutable collections. I want to make immutable collections, which are completely immutable, right down through all the contained objects, the objects they reference, ad infinitum. Is there a simple way to do this? The code on http://www.finalcog.com/immutable-containers-scala illustrates what I'm trying to achieve, and a nasty work around (ImmutablePoint). The problem with the workaround is that every time I want to change an object I

问题 I'm studying SICP right now. And I found the definition of closure in SICP is (maybe) different from closure definition in other languages. Here's what SICP says: The ability to create pairs whose elements are pairs is the essence of list structure's importance as a representational tool. We refer to this ability as the closure property of cons. In general, an operation for combining data objects satisfies the closure property if the results of combining things with that operation can

问题 Given a ASP.NET MVC application with the following layers: UI (Views, CSS, Javascript, etc.) Controllers Services (Contains business logic, and data access) The reason for no separate data access layer, is that I'm using SQL type provider. (The following code may not be working, as it's only a raw draft). Now imagine a service named UserService defined like: module UserService = let getAll memoize f = memoize(fun _ -> f) let tryGetByID id f memoize = memoize(fun _ -> f id) let add evict f

问题 I implemented three of the four De Morgan's Laws in Haskell: notAandNotB :: (a -> c, b -> c) -> Either a b -> c notAandNotB (f, g) (Left x) = f x notAandNotB (f, g) (Right y) = g y notAorB :: (Either a b -> c) -> (a -> c, b -> c) notAorB f = (f . Left, f . Right) notAorNotB :: Either (a -> c) (b -> c) -> (a, b) -> c notAorNotB (Left f) (x, y) = f x notAorNotB (Right g) (x, y) = g y However, I don't suppose that it's possible to implement the last law (which has two inhabitants): notAandBLeft

问题 I have been reading about map , reduce and filter a lot because of how much they are used in react and FP in general. If we write something like: let myArr = [1,2,3,4,5,6,7,8,9] let sumOfDoubleOfOddNumbers = myArr.filter(num => num % 2) .map(num => num * 2) .reduce((acc, currVal) => acc + currVal, 0); 3 different loops are run. I've read about Java 8 streams as well and know that they use what is called a monad, ie, the computations are stored first. They are performed once only in one

问题 Using functional programming in javascript and typescript together with Ramda, I often find myself writing code like: const myFun = c => { const myId = c.id const value = pipe( getAnotherOtherPropOfC, transformToArray, mapToSomething, filterSomething, // ... N other transformations // ok now I need myId and also the result of the previous function chainMyIdWithResultOfPreviousFunction(myId) )(c) return value } Notice how creating a const myId breaks point-free style. I'd like to write myFun

问题 I'm a mechanical engineering grad student and my adviser has just asked me to write a data visualization utility for one of our sensor projects. As it's summer and he wants me to have some fun with it, I thought this would be a great time to learn a language adept at scientific computing, so I went ahead and plowed right into F#. As I'm new to the functional programming paradigm I'm having a little difficulty structuring my program properly, especially given the possibility of easily

问题 Does functional programming have a standard construct for this logic? const passAround = (f) => (x) => { f(x); return x; }; This enables me to compose functions that have side effects and no return values, like console.log . It's not like a Task because I don't want to represent the state of the side effect. 回答1: The SKI combinator calculus might interest you. Let's pretend that f is always a pure function: const S = g => f => x => g(x)(f(x)); // S combinator of SKI combinator calculus const