We have a very nice GoF book (Design Patterns: Elements of Reusable Object-Oriented Software) about patterns in Object Oriented Programming, and plenty of articles and resources in the web on this subject.
Are there any books (articles, resources) on patterns(best practices) for functional programming?
For dynamic programming in languages like Python and Ruby?
For AOP?
A related question was asked before: "Does functional programming replace GoF design patterns", with great responses.
The equivalent of "design patterns" is very vague in FP. In general, every time you see a "pattern" in your code you should create something to cover all of its uses in a uniform way. Often it will be a higher-order function.
For example, the following C code
for (int i = 0; i < n; i++)
if (a[i] == 42)
return true;
return false;
can be thought of some basic "design pattern" - checking if there's some special element on the list. This snippet could appear many times in code with different conditions. In FP, you simply use a higher order function several times. It's not a "pattern" anymore.
Functional programming has its own practices, but they are much different from "design patterns" in OOP. They include use of polymorphism, lists, higher-order functions, immutability/purity, laziness [not all are essential or specific to FP]... See also "what are core concepts of FP". Also, type classes (Haskell), modules and functors (OCaml), continuations, monads, zippers, finger trees, monoids, arrows, applicative functors, monad transformers, many purely functional data structures (book) etc. Functional pearls, already mentioned by Randall Schulz, form a very rich resource of FP at its best.
To learn how to write idiomatic code, any book/resource on a functional programming language will suffice IMHO (for example, RWH and LYAH); differences between thinking imperatively and functionally are always explained there.
In dynamic languages, Jeff Foster's link is a good collection; here is a very clever use of memoization in JavaScript that could be considered a "design pattern".
The list of design patterns described in GoF is written for languages like C++ and Java. It is sometimes considered a list of workarounds to make inflexible languages more dynamic. For example the Visitor pattern is not really needed in Ruby because you can simply change add member functions to your class at runtime. The Decorator pattern is obsolete if you can use mixins.
It's my experience that when I'm implementing a solution in C++ I tend to spend most of my time writing scaffolding code. I begin with creating a platform that allows me to think in my application's program domain. Design patterns probably were developed as a way to categorize different kinds of scaffolding.
I should mention that when I am programming in Ruby I don't have much supporting code. There just doesn't seem to be a need for it.
My theory is that other languages don't emphasize the concept of design patterns simply because their basic language constructs are sufficient. In defense of Java and C++: maybe this is because functional and AOP languages are often used in more specific problem domains or niches, while Java and C++ are used for everything.
And now for something different. If you are getting a bit bored with OO design and you want to learn something new then you might be interested in the the book Elements of Programming written by Stepanov. In this book he explains how programming can be approached from a mathematical point of view. For a preview, check out his Class notes for Adobe (found among others on this page). You may also be interested in Adobe's Collected Papers.
Here's a link to Design Patterns in Dynamic Programming
Aren't the Functional Pearls (one of) the canonical set(s) of design patterns for functional programming?
There is a Design patten in Ruby.
Beside the design patterns mentioned in GOF, it also list some others pattern like Convention over Configuration .
Personally my most important pattern for dynamic languages - write tests. It's even more important than in statically-typed languages.
Related
I recently started programming in Julia for research purposes. Going through it I started loving the syntax, I positively experienced the community here in SO and now I am thinking about porting some code from other programming languages.
Working with highly computational expensive forecasting models, it would be nice to have them all in a powerful modern language as Julia.
I would like to create a project and I am wondering how I should design it. I am concerned both from a performance and a language perspective (i.e.: Would it be better to create modules – submodules – functions or something else would be preferred? Is it better off to use dictionaries or custom types?).
I have looked at different GitHub projects in my field, but I haven't really found a common standard. Therefore I am wondering: what is more in the spirit of the Julia language and philosophy?
EDIT:
It has been pointed out that this question might be too generic. Therefore, I would like to focus it on how it would be better structuring modules (i.e. separate modules for main functions and subroutines versus modules and submodules, etc.). I believe this would be enough for me to have a feel about what might be considered in the spirit of the Julia language and philosophy. Of course, additional examples and references are more than welcome.
The most you'll find is that there is an "official" style-guide. The rest of the "Julian" style is ill-defined, but there are some ways to heuristically define it.
First of all, it means designing the software around multiple dispatch and the type system. A software which follows a Julian design philosophy usually won't be defining a bunch of functions like test_pumpkin and test_pineapple, instead it will use dispatches on test for types Pumpkin and Pineapple. This allows for clean/understandable code. It will break tasks up into small type-stable functions which will allow for good performance. It likely will also be written very generically, allowing the user to use items that are subtypes of AbstractArray or Number, and using the power of dispatch to allow their software to work on numbers they've never even heard of. (In this respect, custom types are recommended over dictionaries when you need performance. However, for a type you have to know all of the fields at the beginning, which means some things require dictionaries.)
A software which follows a Julian design philosophy may also implement a DSL (Domain-Specific Language) to allow a simpler interface to the user. Instead of requiring the user to conform to archaic standards derived from C/Fortran, or write large repetitive items and inputs, the package may provide macros to allow the user to more heuristically define the problem for the software to solve.
Other items which are part of the Julian design philosophy are up for much debate. Is proper Julia code devectorized? I would say no, and the loop fusing broadcast . is a powerful way to write MATLAB-style "vectorized" code and have it be perform like a devectorized loop. However, I have seen others prefer devectorized styles.
Also note that Julia is very different from something like Python where in Julia, you can essentially "build your own standard way of doing something". Since there's no performance penalty for functions/types declared in packages rather than Base, you can build your own Julia world if you want, using macros to define your own "function-like" objects, etc. I mean, you can re-create Java styles in Julia if you wanted.
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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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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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Why would one use a functional language in an otherwise Imperative project?
Many tasks are inherently addressed by functional concepts, such as composable calculations. It is feasible that you will encounter these kinds of problems in projects which have otherwise been developed in an object-oriented fashion.
The best tool for a job is independent of that tool's dominant paradigm.
If your project is truly imperative, you probably don't want a purely functional language. But you probably still want a language with functional features; functional style addresses low-level code structure in the same way that object-oriented style addresses high-level structure. Both allow you to package certain common patterns in a language-supported way.
In a primarily imperative project, functional style is useful at the expression and statement level, allowing you to abstract common loops and sequences:
For example, take this common pattern:
newlist = []
for x in oldlist:
y = dosomething(x)
newlist.append(y)
That's map:
newlist = map(dosomething, oldlist)
Or this:
total = 1
for n in numbers:
total = total * n
Becomes fold (also known as reduce):
total = fold(*, 1, numbers)
Imperative style does not address this low-level duplication all that well--hence the "I wish I had a nickel for every time I typed for(int i = 0; ...)". Even in OO languages without functional features, code inside methods doesn't differ much from similar non-OO languages.
Some IDEs for address this by providing code snippets. This addresses the lack of abstraction power in the wrong way. The way to handle a repeated pattern is not to encourage cut-and-paste with little holes for variable names, but to abstract the pattern into a reusable unit.
Note: I addressed embedding functional code in an imperative project. A top-to-bottom project in functional style will look different. Here are some links taken from similar Stack Overflow questions:
http://www.25hoursaday.com/weblog/2008/06/16/FunctionalProgrammingInC30HowMapReduceFilterCanRockYourWorld.aspx
http://www.joelonsoftware.com/items/2006/08/01.html
Many methods in languages like Java and C++ could be written in a more readable and dense form using FP concepts such as higher-order functions, currying, closures, etc.
See Scala for many interesting examples.
Probably, the most common reason - is to localise and restrict the imperative part (i.e., potentially dangerous and harder to debug, analyse and maintain).
A common problem faced by application developers is building queries: "I want all customers over the age of 18 who have spent $10K in the past year." The process of defining a query that returns all customers, then filtering it by one criterion, then another, and finally a third, is called composing the query. Composition is a strong suit of a functional approach, meaning the query definition problem and a functional solution are well-matched. To see this in action in a popular object-oriented language, see C# and LINQ
Why would one use a functional language in an otherwise Imperative project?
Some examples:
The Mathematica kernel is written in a proprietary dialect of C. Mathematica is a functional language so it makes it much easier to implement many mathematical algorithms and, consequently, it became the language of choice for implementing large parts of Mathematica itself. Retrospectively, this was a huge success as it made it possible to implement many more algorithms quickly and cheaply using a more expressive language.
Joule is a front-end GUI app for traders from the market leader of European energy trading. Although most of the lines of code in Joule are C# they chose to implement some parts of it in F#. In particular, the implied prices engine that combines real bids and asks across related contracts to create implicit bids and asks was written entirely in F#. Retrospectively, this was a huge success as it replaced a substantial (~50kLOC) C++ code base with a comparatively tiny (~1kLOC) F# code base that does the same thing more quickly. The author of Joule's implied prices engine wrote a related article here.
Microsoft's Halo 3 computer game and Bing search engine both have some of their dense mathematical code written in Microsoft's own functional language F#.
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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.