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What do you think the benefits of functional programming are? And how do they apply to programmers today?
What are the greatest differences between functional programming and OOP?
The style of functional programming is to describe what you want, rather than how to get it. ie: instead of creating a for-loop with an iterator variable and marching through an array doing something to each cell, you'd say the equivalent of "this label refers to a version of this array where this function has been done on all the elements."
Functional programming moves more basic programming ideas into the compiler, ideas such as list comprehensions and caching.
The biggest benefit of Functional programming is brevity, because code can be more concise. A functional program doesn't create an iterator variable to be the center of a loop, so this and other kinds of overhead are eliminated from your code.
The other major benefit is concurrency, which is easier to do with functional programming because the compiler is taking care of most of the operations which used to require manually setting up state variables (like the iterator in a loop).
Some performance benefits can be seen in the context of a single-processor as well, depending on the way the program is written, because most functional languages and extensions support lazy evaluation. In Haskell you can say "this label represents an array containing all the even numbers". Such an array is infinitely large, but you can ask for the 100,000th element of that array at any moment without having to know--at array initialization time--just what the largest value is you're going to need. The value will be calculated only when you need it, and no further.
The biggest benefit is that it's not what you're used to. Pick a language like Scheme and learn to solve problems with it, and you'll become a better programmer in languages you already know. It's like learning a second human language. You assume that others are basically a variation on your own because you have nothing to compare it with. Exposure to others, particular ones that aren't related to what you already know, is instructive.
Why Functional Programming Matters
http://www.cs.kent.ac.uk/people/staff/dat/miranda/whyfp90.pdf
Abstract
As software becomes more and more complex, it is more and
more important to structure it well. Well-structured software is easy
to write and to debug, and provides a collection of modules that can
be reused to reduce future programming costs.
In this paper we show
that two features of functional languages in particular, higher-order
functions and lazy evaluation, can contribute significantly to
modularity. As examples, we manipulate lists and trees, program
several numerical algorithms, and implement the alpha-beta heuristic
(an algorithm from Artificial Intelligence used in game-playing
programs). We conclude that since modularity is the key to successful
programming, functional programming offers important advantages for
software development.
A good starting point therefore would be to try to understand some things that are not possible in imperative languages but possible in functional languages.
If you're talking about computability, there is of course nothing that is possible in functional but not imperative programming (or vice versa).
The point of different programming paradigms isn't to make things possible that weren't possible before, it's to make things easy that were hard before.
Functional programming aims to let you more easily write programs that are concise, bug-free and parallelizable.
I think the most practical example of the need for functional programming is concurrency - functional programs are naturally thread safe and given the rise of multi core hardware this is of uttermost importance.
Functional programming also increases the modularity - you can often see methods/functions in imperative that are far too long - you'll almost never see a function more than a couple of lines long. And since everything is decoupled - re-usability is much improved and unit testing is very very easy.
It doesn't have to be one or the other: using a language like C#3.0 allows you to mix the best elements of each. OO can be used for the large scale structure at class level and above, Functional style for the small scale structure at method level.
Using the Functional style allows code to be written that declares its intent clearly, without being mixed up with control flow statements, etc. Because of the principles like side-effect free programming, it is much easier to reason about code, and check its correctness.
Once the program grows, the number of commands in our vocabulary becomes too high, making it very difficult to use. This is where object-oriented programming makes our life easier, because it allows us to organize our commands in a better way.
We can associate all commands that involve customer with some customer entity (a class), which makes the description a lot clearer. However, the program is still a sequence of commands specifying how it should proceed.
Functional programming provides a completely different way of extending the vocabulary. Not limited to adding new primitive commands; we can also add new control structures–primitives that specify how we can put commands together to create a program. In imperative languages, we were able to compose commands in a sequence or using a limited number of built in constructs such as loops, but if you look at typical programs, you'll still see many recurring structures; common ways of combining commands
Do not think of functional programming in terms of a "need". Instead, think of it as another programming technique that will open up your mind just as OOP, templates, assembly language, etc may have completely changed your way of thinking when (if) you learned them. Ultimately, learning functional programming will make you a better programmer.
If you don't already know functional programming then learning it gives you more ways to solve problems.
FP is a simple generalization that promotes functions to first class values whereas OOP is for large-scale structuring of code. There is some overlap, however, where OOP design patterns can be represented directly and much more succinctly using first-class functions.
Many languages provide both FP and OOP, including OCaml, C# 3.0 and F#.
Cheers,
Jon Harrop.
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I would like to learn a functional language in order to broaden my horizon. I have knowledge of Python and C/C++ and I want a language to be easy to learn from someone who comes from the imperative domain of languages. I don't care if the language is powerful enough. I just want a language in order to learn the basic of functional programming and then I will try for a more difficult (and powerful language).
Thanks
I recommend pure-lang for these pedagogical ends. It's also plenty powerful. If you want something more popular / with more community support, then I'd recommend Scheme or OCaml, depending on whether you'd rather deal with unfamiliar syntax (go with Scheme) or deal with unfamiliar typing (go with OCaml) first. SML and F# are only slightly different from OCaml. Others have or will mention Clojure, Scala, and Haskell.
Clojure is a variant of Scheme, with its own idiosyncracies (e.g. no tail-call optimization), so using it would be a way of starting with Scheme. I'd expect you'd have an easier time with a less idiosyncratic Scheme implementation though. Racket is what's often used for teaching. Scala looks to be fundamentally similar to OCaml, but this is based on only casual familiarity.
Unlike Haskell, the other languages mentioned all have two advantages: (1) evaluation-order is eager by default, though you can get lazy evaluation by specifically requesting it. In Haskell's the reverse. (2) Mutation is available, though much of the libraries and code you'll see doesn't use it. I actually think it's pedagogically better to learn functional programming while at the same time having an eye on how it interacts with side-effects, and working your way to monadic-style composition somewhat down the road. So I think this is an advantage. Some will tell you that it's better to be thrown into Haskell's more-quarantined handling of mutaton first, though.
Robert Harper at CMU has some nice blog posts on teaching functional programming. As I understand, he also prefers languages like OCaml for teaching.
Among the three classes of languages I recommended (Pure, Scheme and friends, OCaml and friends), the first two have dynamic typing. The first and third have explicit reference cells (as though in Python, you restricted yourself to never reassiging a variable but you could still change what's stored at a list index). Scheme has implicit reference cells: variables themselves look mutable, as in C and Python, and the reference cell handling is done under the covers. In languages like that, you often have some form of explicit reference cell available too (as in the example I just gave in Python, or using mutable pairs/lists in Racket...in other Schemes, including the Scheme standard, those are the default pairs/lists).
One virtue Haskell does have is some textbooks are appearing for it. (I mean this sincerely, not snarkily.) What books/resources to use is another controversial issue with many wars/closed questions. SICP as others have recommended has many fans and also some critics. There seem to me to be many good choices. I won't venture further into those debates.
At first, read Structure and Implementation of Computer Programs. I recommend Lisp (for, example, it's dialect Scheme) as first functional programming language.
Another option is Clojure, which I'm given to understand is more "purely" functional than Scheme/Racket (don't ask me about the details here) and possibly similar enough to let you use it in conjunction with SICP (Structure and Interpretation of Computer Programs, a highly recommended book also suggested by another answer).
I would like to learn a functional language in order to broaden my horizon. I have knowledge of Python and C/C++ and I want a language to be easy to learn from someone who comes from the imperative domain of languages. I don't care if the language is powerful enough. I just want a language in order to learn the basic of functional programming and then I will try for a more difficult (and powerful language).
Great question!
I had done BASIC, Pascal, assembler, C and C++ before I started doing functional programming in the late 1990s. Then I started using two functional languages at about the same time, Mathematica and OCaml, and was using them exclusively within a few years. In particular, OCaml let me write imperative code which looked like the code I had been writing before. I found that valuable as a learner because it let me compare the different approaches which made the advantages of ML obvious.
However, as others have mentioned, the core benefit of Mathematica and OCaml is pattern matching and that is not technically related to functional programming. I have subsequently looked at many other functional languages but I have no desire to go back to a language that lacks pattern matching.
This question is probably off-topic because it is going to result in endless language wars, but here's a general bit of advice:
There are a class of functional programming languages which are sometimes called "mostly functional", in that they permit some imperative features where you want them. Examples include Standard ML, OCaml, F#, and Scala. You might consider one of these if you want to be able to get a grip on the functional idiomatic style while still being able to achieve things in reasonably familiar ways.
I've used Standard ML extensively in the past, but if you're looking for something that has a bit less of a learning curve, I'd personally recommend Scala, which is my second-favourite programming language. The reasons for this include the prevalence of libraries, a healthy-sized community, and the availability of nice books and tutorials to help you getting started (particularly if you have ever had any dealings with Java).
One element that was not discussed is the availability of special pattern-matching syntax for algebraic datatypes, as in Haskell, all flavors of ML, and probably several of the other languages mentioned. Pattern-matching syntax tends to help the programmer see their functions as mathematical functions. Haskell's syntax is sufficiently complex, and its implementations have sufficiently poor parse error messages, that syntax is a decent reason not to choose Haskell. Scheme is probably easier to learn than most other options (and Scheme probably has the king of all macro systems), but the lack of pattern matching syntax would steer me away from it for an intro to functional programming.
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I've noticed that there are certain core concepts that a lot of functional programming fanatics cling to:
Avoiding state
Avoiding mutable data
Minimizing side effects
etc...
I'm not just wondering what other things make functional programming, but why these core ideas are good? Why is it good to avoid state, and the rest?
The simple answer is that if you don't have extra state to worry about, your code is simpler to reason about. Simpler code is easier to maintain. You don't need to worry about things outside a particular piece of code (like a function) to modify it. This has really useful ramifications for things like testing. If your code does not depend on some state, it becomes much easier to create automated tests for that code, since you do not need to worry about initializing some state.
Having stateless code makes it simpler to create threaded programs as well, since you don't need to worry about two threads of execution modifying/reading a shared piece of data at the same time. Your threads can run independent code, and this can save loads of development time.
Essentially, avoiding state creates simpler programs. In a way, there's less "moving parts" (i.e., ways lines of code can interact), so this will generally mean that the code is more reliable and contains less faults. Basically, the simpler the code, the less can go wrong. To me this is the essence of writing state-less code.
There are plenty of other reasons to create stateless, "functional" code, but they all boil down to simplicity for me.
In addition to what #Oleksi said, there is another important thing: referential transparency and transactional data structures. Of course, you do not need a functional programming language to do so, but it's a bit easier with them.
Purely functional data structures are guaranteed to remain the same - if one function returned a tree, it will always be the same tree, and all the further transforms would create new copies of it. It's much easier to backtrack to any previous version of a data structure this way, which is important for many essential algorithms.
Very generally, functional programming means:
encouraging the use of (first-class) functions
discouraging the use of (mutable) state
Why is mutation a problem? Think about it: mutation is to data structures what goto is to control flow. I.e., it allows you to arbitrarily "jump" to something completely different in a rather unstructured manner. Consequently, it is occasionally useful, but most of the time rather harmful to readability, testability, and compositionality.
One typical functional feature is "no subtyping". While it sounds a little bit odd to call this a feature, it is, for two (somehow related) reasons:
Subtyping relationships lead to a bunch of not-so-obvious problems. If you don't limit yourself to single or mixin inheritance, you end up with the diamond problem. More important is that you have to deal with variance (covariance, contravariance, invariance), which quickly becomes a nightmare, especially for type parameters (a.k.a. generics). There are several more reasons, and even in OO languages you hear statements like "prefer composition over inheritance".
On the other hand, if you simply leave out subtyping, you can reason much more detailled about your type system, which leads to the possibility to have (almost) full type inference, usually implemented using extensions of Hindley Milner type inference.
Of course sometimes you'll miss subtyping, but languages like Haskell have found a good answer to that problem: Type classes, which allow to define a kind of common "interface" (or "set of common operations") for several otherwise unrelated types. The difference to OO languages is that type classes can be defined "afterwards", without touching the original type definitions. It turns out that you can do almost everything with type classes that you can do with subtyping, but in a much more flexible way (and without preventing type inference). That's why other languages start to employ similar mechnisms (e.g. implicit conversions in Scala or extension methods in C# and Java 8)
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as an engineering student with a strong mathemathical background, i dealing some problems like this at university:
(numerical) Simulations
AI Problems
Robotics
Control Systems
and some more
as you can see some are just numerical ones, others have to process some kinds of symbols.
currently i'm working with java, but i'm not very pleased with it (can't say exactly why, probably a personal taste) and now i'm searching for a programming language, in which i can easily prototype new algorithms, like for example in python, and don't care about low level stuff, but has the ability to speed things up if neccessary, e.g. with concurrent/parallel programming, etc. (writing it in python and rewrite it in C/C++ isn't really a option i prefer...)
to sum it up:
easy to prototype, but
the ability to speed algorithms up
syntax without boilerplate stuff like in java
syntax which is easy to read (i know this could be achived with the most, but some language encourage you more...)
i've looked around at sites, like http://rosettacode.org/ and picked 2 or 3 favorites: Go, Lisp (and maybe Haskell) but other recommandations are welcome
Common Lisp using SBCL is pretty fast if you take the time to make it fast.
Why does this fit what you want?
symbolic computations
good number handling
compiles to native on demand by default.
I would use python together with cython: http://www.cython.org for speeding up your code. For symbolic computations you have http://code.google.com/p/sympy/
Try Clojure; it fulfills most of your requirements.
Uses Java libraries, compiles to Java bytecode, and has plugins for Java IDEs, so some of your existing knowledge about Java and its ecosystem will come in handy.
Very concise, readable, and ease of prototyping is extremely high.
Great support for different concurrency strategies.
Performance is getting better fast; typical stuff is within a speed factor of 2 of Java, and slow things can typically be made fast with minimally confounding changes (e.g. a few type hints here and there to use Java primitives.)
An alternative to Common Lisp would be a implementation of scheme. My favorite so far is Racket.
http://racket-lang.org/
When I first got into Lisp I started with scheme and ended up being able to learn it within a matter of days. Also Lisp-wise Racket is a pretty complete language and has a decent IDE in DrRacket.
How about F#?
F# is a remarkable language for prototyping for the following reasons:
F# has an interactive mode allowing you to evaluate blocks of code directly, without compiling your entire project.
Type inference helps keep code small, and makes refactoring your type hierarchy relatively painless. This may not be so important in production code, but I found that to be very valuable during prototyping.
F# integration with .NET makes it easy to prototype extensions of your existing products. In the all-too-common case when a prototype becomes a product (due to time constraints), it's also easy to integrate your F# code within your .NET product.
If prototyping makes up a significant part of your overall development process, then F# can really help you speed up your coding.
I don't think F# will produce code that is significantly faster than other .NET languages. The functional style of programming, in particular purity (no side-effects), can be applied to other programming languages, meaning it is just as easy to write concurrent programs in other languages as well. It does however "feel more natural" to do so in F#.
F# has the Option type, which can be used in place of null values. Code reliability with respect to null-pointer exceptions can be guaranteed at compile time, which is a huge benefit.
Finally, be advised that F# is still in development, and suffers issues, some of which may disappear over time, but not all. See for instance what devhawk and Oliver Sturm have to say about it (in particular about linear scoping and interdependent classes, other issues like overloading, better Visual Studio integration have already been addressed).
this is stated in article: https://stackoverflow.com/questions/328329/why-should-i-use-f
by JOH
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Software Engineering as it is taught today is entirely focused on object-oriented programming and the 'natural' object-oriented view of the world. There is a detailed methodology that describes how to transform a domain model into a class model with several steps and a lot of (UML) artifacts like use-case-diagrams or class-diagrams. Many programmers have internalized this approach and have a good idea about how to design an object-oriented application from scratch.
The new hype is functional programming, which is taught in many books and tutorials. But what about functional software engineering?
While reading about Lisp and Clojure, I came about two interesting statements:
Functional programs are often developed bottom up instead of top down ('On Lisp', Paul Graham)
Functional Programmers use Maps where OO-Programmers use objects/classes ('Clojure for Java Programmers', talk by Rich Hickley).
So what is the methodology for a systematic (model-based ?) design of a functional application, i.e. in Lisp or Clojure? What are the common steps, what artifacts do I use, how do I map them from the problem space to the solution space?
Thank God that the software-engineering people have not yet discovered functional programming. Here are some parallels:
Many OO "design patterns" are captured as higher-order functions. For example, the Visitor pattern is known in the functional world as a "fold" (or if you are a pointy-headed theorist, a "catamorphism"). In functional languages, data types are mostly trees or tuples, and every tree type has a natural catamorphism associated with it.
These higher-order functions often come with certain laws of programming, aka "free theorems".
Functional programmers use diagrams much less heavily than OO programmers. Much of what is expressed in OO diagrams is instead expressed in types, or in "signatures", which you should think of as "module types". Haskell also has "type classes", which is a bit like an interface type.
Those functional programmers who use types generally think that "once you get the types right; the code practically writes itself."
Not all functional languages use explicit types, but the How To Design Programs book, an excellent book for learning Scheme/Lisp/Clojure, relies heavily on "data descriptions", which are closely related to types.
So what is the methodology for a systematic (model-based ?) design of a functional application, i.e. in Lisp or Clojure?
Any design method based on data abstraction works well. I happen to think that this is easier when the language has explicit types, but it works even without. A good book about design methods for abstract data types, which is easily adapted to functional programming, is Abstraction and Specification in Program Development by Barbara Liskov and John Guttag, the first edition. Liskov won the Turing award in part for that work.
Another design methodology that is unique to Lisp is to decide what language extensions would be useful in the problem domain in which you are working, and then use hygienic macros to add these constructs to your language. A good place to read about this kind of design is Matthew Flatt's article Creating Languages in Racket. The article may be behind a paywall. You can also find more general material on this kind of design by searching for the term "domain-specific embedded language"; for particular advice and examples beyond what Matthew Flatt covers, I would probably start with Graham's On Lisp or perhaps ANSI Common Lisp.
What are the common steps, what artifacts do I use?
Common steps:
Identify the data in your program and the operations on it, and define an abstract data type representing this data.
Identify common actions or patterns of computation, and express them as higher-order functions or macros. Expect to take this step as part of refactoring.
If you're using a typed functional language, use the type checker early and often. If you're using Lisp or Clojure, the best practice is to write function contracts first including unit tests—it's test-driven development to the max. And you will want to use whatever version of QuickCheck has been ported to your platform, which in your case looks like it's called ClojureCheck. It's an extremely powerful library for constructing random tests of code that uses higher-order functions.
For Clojure, I recommend going back to good old relational modeling. Out of the Tarpit is an inspirational read.
Personally I find that all the usual good practices from OO development apply in functional programming as well - just with a few minor tweaks to take account of the functional worldview. From a methodology perspective, you don't really need to do anything fundamentally different.
My experience comes from having moved from Java to Clojure in recent years.
Some examples:
Understand your business domain / data model - equally important whether you are going to design an object model or create a functional data structure with nested maps. In some ways, FP can be easier because it encourages you to think about data model separately from functions / processes but you still have to do both.
Service orientation in design - actually works very well from a FP perspective, since a typical service is really just a function with some side effects. I think that the "bottom up" view of software development sometimes espoused in the Lisp world is actually just good service-oriented API design principles in another guise.
Test Driven Development - works well in FP languages, in fact sometimes even better because pure functions lend themselves extremely well to writing clear, repeatable tests without any need for setting up a stateful environment. You might also want to build separate tests to check data integrity (e.g. does this map have all the keys in it that I expect, to balance the fact that in an OO language the class definition would enforce this for you at compile time).
Prototying / iteration - works just as well with FP. You might even be able to prototype live with users if you get very extremely good at building tools / DSL and using them at the REPL.
OO programming tightly couples data with behavior. Functional programming separates the two. So you don't have class diagrams, but you do have data structures, and you particularly have algebraic data types. Those types can be written to very tightly match your domain, including eliminating impossible values by construction.
So there aren't books and books on it, but there is a well established approach to, as the saying goes, make impossible values unrepresentable.
In so doing, you can make a range of choices about representing certain types of data as functions instead, and conversely, representing certain functions as a union of data types instead so that you can get, e.g., serialization, tighter specification, optimization, etc.
Then, given that, you write functions over your adts such that you establish some sort of algebra -- i.e. there are fixed laws which hold for these functions. Some are maybe idempotent -- the same after multiple applications. Some are associative. Some are transitive, etc.
Now you have a domain over which you have functions which compose according to well behaved laws. A simple embedded DSL!
Oh, and given properties, you can of course write automated randomized tests of them (ala QuickCheck).. and that's just the beginning.
Object Oriented design isn't the same thing as software engineering. Software engineering has to do with the entire process of how we go from requirements to a working system, on time and with a low defect rate. Functional programming may be different from OO, but it does not do away with requirements, high level and detailed designs, verification and testing, software metrics, estimation, and all that other "software engineering stuff".
Furthermore, functional programs do exhibit modularity and other structure. Your detailed designs have to be expressed in terms of the concepts in that structure.
One approach is to create an internal DSL within the functional programming language of choice. The "model" then is a set of business rules expressed in the DSL.
See my answer to another post:
How does Clojure aproach Separation of Concerns?
I agree more needs to be written on the subject on how to structure large applications that use an FP approach (Plus more needs to be done to document FP-driven UIs)
While this might be considered naive and simplistic, I think "design recipes" (a systematic approach to problem solving applied to programming as advocated by Felleisen et al. in their book HtDP) would be close to what you seem to be looking for.
Here, a few links:
http://www.northeastern.edu/magazine/0301/programming.html
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.86.8371
I've recently found this book:
Functional and Reactive Domain Modeling
I think is perfectly in line with your question.
From the book description:
Functional and Reactive Domain Modeling teaches you how to think of the domain model in terms of pure functions and how to compose them to build larger abstractions. You will start with the basics of functional programming and gradually progress to the advanced concepts and patterns that you need to know to implement complex domain models. The book demonstrates how advanced FP patterns like algebraic data types, typeclass based design, and isolation of side-effects can make your model compose for readability and verifiability.
There is the "program calculation" / "design by calculation" style associated with Prof. Richard Bird and the Algebra of Programming group at Oxford University (UK), I don't think its too far-fetched to consider this a methodology.
Personally while I like the work produced by the AoP group, I don't have the discipline to practice design in this way myself. However that's my shortcoming, and not one of program calculation.
I've found Behavior Driven Development to be a natural fit for rapidly developing code in both Clojure and SBCL. The real upside of leveraging BDD with a functional language is that I tend to write much finer grain unit tests than I usually do when using procedural languages because I do a much better job of decomposing the problem into smaller chunks of functionality.
Honestly if you want design recipes for functional programs, take a look at the standard function libraries such as Haskell's Prelude. In FP, patterns are usually captured by higher order procedures (functions that operate on functions) themselves. So if a pattern is seen, often a higher order function is simply created to capture that pattern.
A good example is fmap. This function takes a function as an argument and applies it to all the "elements" of the second argument. Since it is part of the Functor type class, any instance of a Functor (such as a list, graph, etc...) may be passed as a second argument to this function. It captures the general behavior of applying a function to every element of its second argument.
Well,
Generally many Functional Programming Languages are used at universities for a long time for "small toy problems".
They are getting more popular now since OOP has difficulties with "paralel programming" because of "state".And sometime functional style is better for problem at hand like Google MapReduce.
I am sure that, when functioanl guys hit the wall [ try to implement systems bigger than 1.000.000 lines of code], some of them will come with new software-engineering methodologies with buzz words :-). They should answer the old question: How to divide system into pieces so that we can "bite" each pieces one at a time? [ work iterative, inceremental en evolutionary way] using Functional Style.
It is sure that Functional Style will effect our Object Oriented
Style.We "still" many concepts from Functional Systems and adapted to
our OOP languages.
But will functional programs will be used for such a big systems?Will they become main stream? That is the question.
And Nobody can come with realistic methodology without implementing such a big systems, making his-her hands dirty.
First you should make your hands dirty then suggest solution. Solutions-Suggestions without "real pains and dirt" will be "fantasy".
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Closed 10 years ago.
It seems to me from my experimenting with Haskell, Erlang and Scheme that functional programming languages are a fantastic way to answer scientific questions. For example, taking a small set of data and performing some extensive analysis on it to return a significant answer. It's great for working through some tough Project Euler questions or trying out the Google Code Jam in an original way.
At the same time it seems that by their very nature, they are more suited to finding analytical solutions than actually performing practical tasks. I noticed this most strongly in Haskell, where everything is evaluated lazily and your whole program boils down to one giant analytical solution for some given data that you either hard-code into the program or tack on messily through Haskell's limited IO capabilities.
Basically, the tasks I would call 'practical' such as
Aceept a request, find and process requested data,
and return it formatted as needed
seem to translate much more directly into procedural languages. The most luck I have had finding a functional language that works like this is Factor, which I would liken to a reverse-polish-notation version of Python.
So I am just curious whether I have missed something in these languages or I am just way off the ball in how I ask this question. Does anyone have examples of functional languages that are great at performing practical tasks or practical tasks that are best performed by functional languages?
Regarding languages, I think F# is an example of a languages that's primarily 'functional' but also 'practical'. Scala and Clojure are probably others in this category.
(Going one level deeper, I think the 'formula for success' here is a language that leans strongly towards 'functional', but has access to vast practical libraries (e.g. .Net/JVM/some C FFI) and has good tooling (e.g. IDE support).)
I at least somewhat agree with the implicit premise of the question, namely that there is a tension between 'succinct/beautiful analytical power' and 'pragmatics'.
Does anyone have examples of functional languages that are great at performing practical tasks or practical tasks that are best performed by functional languages?
Our business runs on F# code, for everything from on-line credit card transactions to web analytics. These LOB apps are composed of tiny F# scripts that do everything required quickly and simply using .NET's seamless interop and automation of applications like Outlook and Excel.
Our business makes most of its money selling software written in F# that solves practical problems to customers from many sectors from embedded software for medical equipment to maritime internet service providers.
IMO, Scheme is too minimalistic to be practical- it is used in several courses for teaching (see Structure and Interpretation of Computer Programs). However, modern Lisp languages like Common Lisp, and especially Clojure are gaining importance. Erlang is used by several large industries for high concurrency applications, and I personally haven't seen it being used by end-user programmers. Haskell on the other hand is quite a real-world language, and has been used to write a lot of wonderful software including:
XMonad is an X Window System window manager written purely in Haskell.
Leksah, an IDE for Haskell is written in Haskell itself.
Pugs, one of the leading implementations of Perl 6 is written in Haskell.
Lastly, the Glasgow Haskell Compiler is written in Haskell.
Funny, you and I have very different notions of "practical tasks". You say it's:
Aceept a request, find and process
requested data, and return it
formatted as needed
This is pretty much what a functional language is made for: functions that take data and return new data without preserving any state in-between calls (ie no side effects). This is what you have here and it's also called piping.
Now this isn't what I'd call a practical task. In modern programs you have to deal with GUI's, multithreaded functions and network I/O. All these have state that is required to hold data in-between function calls. Data isn't piped into a function and the result piped out, the functions affect the "global" state too.
And it's this definition of "practical task" where functional programs start to fail. Writing a GUI in a functional program is pretty much impossible if you don't use their imperative extensions for example.
So in conclusion, the answer you're asking for is a heart-felt yes, functional programs are up to the task. The answer you're really looking for however, is that it's a bit more complicated than that.
Have you ever used LINQ?
If so, congratulations. You have used a functional language in a practical context. This is what functional development is about.
And yes, F# is VERY useful.
Erlang is well known for its robustness and features for writing highly-concurrent servers.
It also has a DBMS out-of-box.
Functional Programming in the Real World
Basically, the tasks I would call
'practical' such as
Aceept a request, find and process
requested data, and return it
formatted as needed
You experimented with Erlang and couldn't find a practical task for it under this description of practical?
Accept a request.
You mean like receive. Or just being called straight up as a function.
Find and process requested data.
I'm not entirely sure what you mean here, but for finding data there's file I/O, networking I/O, (distributed) inter-process communication, etc. etc. etc. For finding subsets of that data there's regular expressions, pattern matching, etc.
For processing there's a whole bunch of stuff for strings, lists, mathematics, sets, graphs, etc. Is this not enough for processing? What else are you looking for?
Return it formatted as needed.
I can return the resulting data as atoms, lists, binary blobs, formatted strings, numbers, etc. What was missing from Erlang in this regard? I'm really honestly confused here.
I'm not sure about 'Practical Tasks' definition and what it refers to.
but in other words I think you are talking about solving problems by algorithms that need to be represented by a programming language. if so then the functional language is very useful and practical.Specially when you have limits in time to find the solution and implement it.
for me I still use non-functional languages when participating in solving complex algorithmic contests like Google CodeJam .
I'm planning to learn a functional language that will be better for me for these kind of tasks or problems.