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  • What is your favourite cleverly written functional code?

    - by sdcvvc
    What are your favourite short, mind-blowing snippets in functional languages? My two favourite ones are (Haskell): powerset = filterM (const [True, False]) foldl f v xs = foldr (\x g a -> g (f a x)) id xs v -- from Hutton's tutorial (I tagged the question as Haskell, but examples in all languages - including non-FP ones - are welcome as long as they are in functional spirit.)

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  • functional test for rails controller private method

    - by mohit
    I have a private method in my controller. which is used for some database update. this method i am calling from another controller method. and it works fine. But when i am trying to write a test case for that method then It is tripping on accessing (session variable and params) in my functional all other methods are working fine the problem is only with private method? In my setup method in functional test, I am setting session also.?

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  • functional test for rails controller privaet method

    - by mohit
    I have a private method in my controller. which is used for some database update. this method i am calling from another controller method. and it works fine. But when i am trying to write a test case for that method then It is tripping on accessing (session variable and params) in my functional all other methods are working fine the problem is only with private method? In my setup method in functional test, I am setting session also.?

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  • Functional Programming Equivalent of Design Patterns Book?

    - by JasonFruit
    Is there a functional-programming equivalent to the Gang of Four Design Patterns book? That is, is there a book that explains and gives examples of how commonly-needed code structures are implemented functionally? I think seeing that would give me a better idea of how to go about using in practice the functional concepts whose theory I understand.

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  • Imperative Programming v/s Declarative Programming v/s Functional Programming

    - by kaleidoscope
    Imperative Programming :: Imperative programming is a programming paradigm that describes computation in terms of statements that change a program state. In much the same way as the imperative mood in natural languages expresses commands to take action, imperative programs define sequences of commands for the computer to perform. The focus is on what steps the computer should take rather than what the computer will do (ex. C, C++, Java). Declarative Programming :: Declarative programming is a programming paradigm that expresses the logic of a computation without describing its control flow. It attempts to minimize or eliminate side effects by describing what the program should accomplish, rather than describing how to go about accomplishing it. The focus is on what the computer should do rather than how it should do it (ex. SQL). A  C# example of declarative v/s. imperative programming is LINQ. With imperative programming, you tell the compiler what you want to happen, step by step. For example, let's start with this collection, and choose the odd numbers: List<int> collection = new List<int> { 1, 2, 3, 4, 5 }; With imperative programming, we'd step through this, and decide what we want: List<int> results = new List<int>(); foreach(var num in collection) {     if (num % 2 != 0)           results.Add(num); } Here’s what we are doing: *Create a result collection *Step through each number in the collection *Check the number, if it's odd, add it to the results With declarative programming, on the other hand, we write the code that describes what you want, but not necessarily how to get it var results = collection.Where( num => num % 2 != 0); Here, we're saying "Give us everything where it's odd", not "Step through the collection. Check this item, if it's odd, add it to a result collection." Functional Programming :: Functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids state and mutable data. It emphasizes the application of functions.Functional programming has its roots in the lambda calculus. It is a subset of declarative languages that has heavy focus on recursion. Functional programming can be a mind-bender, which is one reason why Lisp, Scheme, and Haskell have never really surpassed C, C++, Java and COBOL in commercial popularity. But there are benefits to the functional way. For one, if you can get the logic correct, functional programming requires orders of magnitude less code than imperative programming. That means fewer points of failure, less code to test, and a more productive (and, many would say, happier) programming life. As systems get bigger, this has become more and more important. To know more : http://stackoverflow.com/questions/602444/what-is-functional-declarative-and-imperative-programming http://msdn.microsoft.com/en-us/library/bb669144.aspx http://en.wikipedia.org/wiki/Imperative_programming   Technorati Tags: Ranjit,Imperative Programming,Declarative programming,Functional Programming

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  • System requirement specification vs functional one - separate docs?

    - by user970696
    A lot of sources (e.g. Wikipedia) mentiones System requirement specification and Functional specification as two separate entities. However, Wiegers in his book writes: The software requirements specification is sometimes called a functional specification, a product specification... This is very confusing for me as I thought FS describes just functions while SRS whole system. From this point of view, FS would contain both non functional and functional requirements and everything else.

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  • Is there a name for this functional programming construct/pattern?

    - by dietbuddha
    I wrote a function and I'd like to find out if it is an implementation of some functional programming pattern or construct. I'd like to find out the name of this pattern or construct (if it exists)? I have a function which takes a list of functions and does this to them: wrap(fn1, fn2, fn3, fn4) # returns partial(fn4, partial(fn3, partial(fn2, fn1))) There are strong similarities to compose, reduce, and other fp metaprogramming constructs, since the functions are being arranged together and returned as one function. It also has strong similarities to decorators and Python context managers since it provides a way to encapsulate pre and post execution behaviors in one function. Which was the impetus for writing this function. I wanted the ability that context managers provide, but I wanted to be able to have it defined in one function, and to be able to layer function after function on top.

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  • Why isn't functional language syntax more close to human language?

    - by JohnDoDo
    I'm interested in functional programming and decided to get head to head with Haskell. My head hurts... but I'll eventually get it... I have one curiosity though, why is the syntax so cryptic (in lack of another word)? Is there a reason why it isn't more expressive, more close to human language? I understand that FP is good at modelling mathematical concepts and it borrowed some of it's concise means of expression, but still it's not math... it's a language.

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  • Functional way to get a matrix from text

    - by Elazar Leibovich
    I'm trying to solve some Google Code Jam problems, where an input matrix is typically given in this form: 2 3 #matrix dimensions 1 2 3 4 5 6 7 8 9 # all 3 elements in the first row 2 3 4 5 6 7 8 9 0 # each element is composed of three integers where each element of the matrix is composed of, say, three integers. So this example should be converted to #!scala Array( Array(A(1,2,3),A(4,5,6),A(7,8,9), Array(A(2,3,4),A(5,6,7),A(8,9,0), ) An imperative solution would be of the form #!python input = """2 3 1 2 3 4 5 6 7 8 9 2 3 4 5 6 7 8 9 0 """ lines = input.split('\n') print lines[0] m,n = (int(x) for x in lines[0].split()) array = [] row = [] A = [] for line in lines[1:]: for elt in line.split(): A.append(elt) if len(A)== 3: row.append(A) A = [] array.append(row) row = [] from pprint import pprint pprint(array) A functional solution I've thought of is #!scala def splitList[A](l:List[A],i:Int):List[List[A]] = { if (l.isEmpty) return List[List[A]]() val (head,tail) = l.splitAt(i) return head :: splitList(tail,i) } def readMatrix(src:Iterator[String]):Array[Array[TrafficLight]] = { val Array(x,y) = src.next.split(" +").map(_.trim.toInt) val mat = src.take(x).toList.map(_.split(" "). map(_.trim.toInt)). map(a => splitList(a.toList,3). map(b => TrafficLight(b(0),b(1),b(2)) ).toArray ).toArray return mat } But I really feel it's the wrong way to go because: I'm using the functional List structure for each line, and then convert it to an array. The whole code seems much less efficeint I find it longer less elegant and much less readable than the python solution. It is harder to which of the map functions operates on what, as they all use the same semantics. What is the right functional way to do that?

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  • Is functional GUI programming possible?

    - by eman
    I've recently caught the FP bug (trying to learn Haskell), and I've been really impressed with what I've seen so far (first-class functions, lazy evaluation, and all the other goodies). I'm no expert yet, but I've already begun to find it easier to reason "functionally" than imperatively for basic algorithms (and I'm having trouble going back where I have to). The one area where current FP seems to fall flat, however, is GUI programming. The Haskell approach seems to be to just wrap imperative GUI toolkits (such as GTK+ or wxWidgets) and to use "do" blocks to simulate an imperative style. I haven't used F#, but my understanding is that it does something similar using OOP with .NET classes. Obviously, there's a good reason for this--current GUI programming is all about IO and side effects, so purely functional programming isn't possible with most current frameworks. My question is, is it possible to have a functional approach to GUI programming? I'm having trouble imagining what this would look like in practice. Does anyone know of any frameworks, experimental or otherwise, that try this sort of thing (or even any frameworks that are designed from the ground up for a functional language)? Or is the solution to just use a hybrid approach, with OOP for the GUI parts and FP for the logic? (I'm just asking out of curiosity--I'd love to think that FP is "the future," but GUI programming seems like a pretty large hole to fill.)

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  • Best Functional Approach

    - by dbyrne
    I have some mutable scala code that I am trying to rewrite in a more functional style. It is a fairly intricate piece of code, so I am trying to refactor it in pieces. My first thought was this: def iterate(count:Int,d:MyComplexType) = { //Generate next value n //Process n causing some side effects return iterate(count - 1, n) } This didn't seem functional at all to me, since I still have side effects mixed throughout my code. My second thought was this: def generateStream(d:MyComplexType):Stream[MyComplexType] = { //Generate next value n return Stream.cons(n, generateStream(n)) } for (n <- generateStream(initialValue).take(2000000)) { //process n causing some side effects } This seemed like a better solution to me, because at least I've isolated my functional value-generation code from the mutable value-processing code. However, this is much less memory efficient because I am generating a large list that I don't really need to store. This leaves me with 3 choices: Write a tail-recursive function, bite the bullet and refactor the value-processing code Use a lazy list. This is not a memory sensitive app (although it is performance sensitive) Come up with a new approach. I guess what I really want is a lazily evaluated sequence where I can discard the values after I've processed them. Any suggestions?

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  • Rails Functional test assert_select javascript respond_to

    - by Macint
    Hello, I am currently trying to write functional tests for a charging form which gets loaded on to the page via AJAX(jQuery). It loads the form from the charge_form action which returns the consult_form.js.erb view. This all works, but I am having trouble with my testing. In the functional I can go to the action but I cannot use assert_select to find a an element and verify that the form is in fact there. Error: 1) Failure: test_should_create_new_consult(ConsultsControllerTest) [/test/functional/consults_controller_test.rb:8]: Expected at least 1 element matching "h4", found 0. <false> is not true. This is the view. consult_form.js.erb: <div id="charging_form"> <h4>Charging form</h4> <div class="left" id="charge_selection"> <%= select_tag("select_category", options_from_collection_for_select(@categories, :id, :name)) %><br/> ... consults_controller_test.rb: require 'test_helper' class ConsultsControllerTest < ActionController::TestCase def test_should_create_new_consult get_with_user :charge_form, :animal_id => animals(:one), :id => consults(:one), :format => 'js' assert_response :success assert_select 'h4', "Charging form" #can't find h4 end end Is there a problem with using assert_select with types other than html? Thank you for any help!

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  • Are small amounts of functional programming understandable by non-FP people?

    - by kd35a
    Case: I'm working at a company, writing an application in Python that is handling a lot of data in arrays. I'm the only developer of this program at the moment, but it will probably be used/modified/extended in the future (1-3 years) by some other programmer, at this moment unknown to me. I will probably not be there directly to help then, but maybe give some support via email if I have time for it. So, as a developer who has learned functional programming (Haskell), I tend to solve, for example, filtering like this: filtered = filter(lambda item: included(item.time, dur), measures) The rest of the code is OO, it's just some small cases where I want to solve it like this, because it is much simpler and more beautiful according to me. Question: Is it OK today to write code like this? How does a developer that hasn't written/learned FP react to code like this? Is it readable? Modifiable? Should I write documentation like explaining to a child what the line does? # Filter out the items from measures for which included(item.time, dur) != True I have asked my boss, and he just says "FP is black magic, but if it works and is the most efficient solution, then it's OK to use it." What is your opinion on this? As a non-FP programmer, how do you react to the code? Is the code "googable" so you can understand what it does? I would love feedback on this :) Edit: I marked phant0m's post as answer, because he gives good advice on how to write the code in a more readable way, and still keep the advantages. But I would also like to recommend superM's post because of his viewpoint as a non-FP programmer.

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  • Isn't class scope purely for organization?

    - by Di-0xide
    Isn't scope just a way to organize classes, preventing outside code from accessing certain things you don't want accessed? More specifically, is there any functional gain to having public, protected, or private-scoped methods? Is there any advantage to classifying method/property scope rather than to, say, just public-ize everything? My presumption says no simply because, in binary code, there is no sense of scope (other than r/w/e, which isn't really scope at all, but rather global permissions for a block of memory). Is this correct? What about in languages like Java and C#[.NET]?

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  • Advantages of compilers for functional languages over compilers for imperative languages

    - by Onorio Catenacci
    As a follow up to this question What are the advantages of built-in immutability of F# over C#?--am I correct in assuming that the F# compiler can make certain optimizations knowing that it's dealing with largely immutable code? I mean even if a developer writes "Functional C#" the compiler wouldn't know all of the immutability that the developer had tried to code in so that it couldn't make the same optimizations, right? In general would the compiler of a functional language be able to make optimizations that would not be possible with an imperative language--even one written with as much immutability as possible?

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  • Functional data structures in C++

    - by drg
    Does anyone know of a C++ data structure library providing functional (a.k.a. immutable, or "persistent" in the FP sense) equivalents of the familiar STL structures? By "functional" I mean that the objects themselves are immutable, while modifications to those objects return new objects sharing the same internals as the parent object where appropriate. Ideally, such a library would resemble STL, and would work well with Boost.Phoenix (caveat- I haven't actually used Phoenix, but as far as I can tell it provides many algorithms but no data structures, unless a lazily-computed change to an existing data structure counts - does it?)

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  • Pure functional bottom up tree algorithm

    - by Axel Gneiting
    Say I wanted to write an algorithm working on an immutable tree data structure that has a list of leaves as its input. It needs to return a new tree with changes made to the old tree going upwards from those leaves. My problem is that there seems to be no way to do this purely functional without reconstructing the entire tree checking at leaves if they are in the list, because you always need to return a complete new tree as the result of an operation and you can't mutate the existing tree. Is this a basic problem in functional programming that only can be avoided by using a better suited algorithm or am I missing something?

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  • Is scala functional programming slower than traditional coding?

    - by Fred Haslam
    In one of my first attempts to create functional code, I ran into a performance issue. I started with a common task - multiply the elements of two arrays and sum up the results: var first:Array[Float] ... var second:Array[Float] ... var sum=0f; for(ix<-0 until first.length) sum += first(ix) * second(ix); Here is how I reformed the work: sum = first.zip(second).map{ case (a,b) => a*b }.reduceLeft(_+_) When I benchmarked the two approaches, the second method takes 40 times as long to complete! Why does the second method take so much longer? How can I reform the work to be both speed efficient and use functional programming style?

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  • Functional testing of a 3-rd party java program

    - by Dmitri Nesteruk
    I have a 3-rd party java application (I don't own source code) and I want to perform functional testing on it, similar to the way it's done in watin/watij/selenium/nunitforms etc. Can anyone suggest a library that I can use to do this sort of testing. What I'm interested in is clicking the applet's buttons, reading off text values, and the like. Thanks!

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  • Big datastructures in functional programming

    - by Denis Gorodetskiy
    I'm newbie in Functional Programming. I have a huge neural network with thousands of neurons and every connection between neurons has its weight. I have to update these weights very often, several thousand times per learning session. Is FP still applicable here? I mean in fp we can't modify variables and only able to return new variables not changing previous values. Does this mean I have to recreate whole network on every weight update?

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  • Discovering a functional algorithm from a mutable one

    - by Garrett Rowe
    This isn't necessarily a Scala question, it's a design question that has to do with avoiding mutable state, functional thinking and that sort. It just happens that I'm using Scala. Given this set of requirements: Input comes from an essentially infinite stream of random numbers between 1 and 10 Final output is either SUCCEED or FAIL There can be multiple objects 'listening' to the stream at any particular time, and they can begin listening at different times so they all may have a different concept of the 'first' number; therefore listeners to the stream need to be decoupled from the stream itself. Pseudocode: if (first number == 1) SUCCEED else if (first number >= 9) FAIL else { first = first number rest = rest of stream for each (n in rest) { if (n == 1) FAIL else if (n == first) SUCCEED else continue } } Here is a possible mutable implementation: sealed trait Result case object Fail extends Result case object Succeed extends Result case object NoResult extends Result class StreamListener { private var target: Option[Int] = None def evaluate(n: Int): Result = target match { case None => if (n == 1) Succeed else if (n >= 9) Fail else { target = Some(n) NoResult } case Some(t) => if (n == t) Succeed else if (n == 1) Fail else NoResult } } This will work but smells to me. StreamListener.evaluate is not referentially transparent. And the use of the NoResult token just doesn't feel right. It does have the advantage though of being clear and easy to use/code. Besides there has to be a functional solution to this right? I've come up with 2 other possible options: Having evaluate return a (possibly new) StreamListener, but this means I would have to make Result a subtype of StreamListener which doesn't feel right. Letting evaluate take a Stream[Int] as a parameter and letting the StreamListener be in charge of consuming as much of the Stream as it needs to determine failure or success. The problem I see with this approach is that the class that registers the listeners should query each listener after each number is generated and take appropriate action immediately upon failure or success. With this approach, I don't see how that could happen since each listener is forcing evaluation of the Stream until it completes evaluation. There is no concept here of a single number generation. Is there any standard scala/fp idiom I'm overlooking here?

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