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Learning Functional Programming through Multimedia
As the title implies, The Haskell School of Expression introduces functional programming through the Haskell programming language and through the use of graphics and music. It serves as an effective introduction to both the language and the concepts behind functional programming. This text was published in 2000, but since Haskell 98 is the current standard, this is still a very relevant book.
Haskell's standardization process gives us a window into two different facets of the community: Haskell is designed to be both a stable, standardized language (called Haskell 98), and a platform for experimentation in cutting-edge programming language research. So though we have a standard from 1998, the implementations (both compilers and interpreters) are continually evolving to implement new, experimental features which may or may not make it into the next standard.
For instance, the Glasgow Haskell Compiler has implemented a meta-programming environment called Template Haskell. Haskell is also easy to extend in directions that don't change the language itself, through the use of Embedded Domain-Specific Languages (EDSLs) such as WASH for web authoring, Parsec for parsing, and Dance (more of Paul Hudak's work) for controlling humanoid robots.
Before we get too far, I should offer a disclaimer: The Haskell community is rather small, and if you scour the net, you may find conversations between myself and Paul Hudak or folks in his research group, since I use some of their software. That said, I don't work directly with Hudak or his research group.
In fact, the small size of the Haskell community is a useful feature. It is very easy to get involved, and folks are always willing to help newbies learn, since we love sharing what we know. You may even find that if you post a question about an exercise in The Haskell School of Expression , you'll get a reply from the author himself.
I consider this book to be written in a "tutorial" style. It walks the reader through the building of applications, but doesn't skimp on the concepts (indeed, the chapters are meant to alternate between "concepts" and "applications"). In some ways, the code examples make it a little difficult to jump around, since you are expected to build upon previous code. The web site provides code, however, so you can always grab that and use it to fill in the missing pieces.
For readers who wish to use this book as a tutorial, and to implement all of the examples (which is highly recommended), I suggest that you grab the Hugs interpreter and read the User's Guide while you're reading the first few chapters of The Haskell School of Expression. Hugs is very portable, free, and easy to use. It also has an interface with Emacs. Unfortunately, some of the example code has suffered from bit-rot, and certain things don't work out-of-the-box for X11-based systems. The bit-rot can be solved by using the "November 2002" version of Hugs. This is all explained on SOE's web page.
The Haskell School of Expression should be very effective for programmers who have experience in more traditional languages, and programmers with a Lisp background can probably move quickly through some of the early material. If you've never learned a functional language, I highly recommend Haskell: Since Haskell is purely functional (unlike Lisp), it will more or less prevent you from "cheating" by reverting to a non-functional style. In fact, if you've never really looked at functional programming languages, it may surprise you to learn that Haskell has no looping constructs or destructive assignment (that is, no x = x + 1). All of the tasks that you would accomplish through the use of loops are accomplished instead through recursion, or through higher-level abstractions upon recursion.
Since I was already comfortable with recursion when I started this book, it is hard for me to gauge how a reader who has never encountered recursion would find this book's explanation of the concept. The Haskell School of Expression introduces recursion early on, in section 1.4. It is used in examples throughout the book, and if you follow along with these examples, you will most certainly be using it a lot. The introduction seems natural enough to me, but I note that Hudak does not give the reader any extra insight or tricks to help them along. Not to worry, though; recursion is very natural in Haskell and the reader may not even notice that they are doing something a little tricky.
The use of multimedia was a lot of fun for me, and should quickly dispel the myth that IO is difficult in Haskell. For instance, Hudak has the reader drawing fractals by page 44, and throughout the book, the reader will be drawing shapes, playing music, and controlling animated robots.
Any book on Haskell must be appraised for its explanation of monads in general and IO specifically. Monads are a purely functional way to elegantly carry state across several computations (rather than passing state explicitly as a parameter to each function). They are a common stumbling block in learning Haskell, though in my opinion, their difficulty is over-hyped.
Since input and output cause side-effects, they are not purely functional, and don't fit nicely into a function-call and recursion structure. Haskell has therefore evolved a way to deal safely and logically with IO through the use of monads, which encapsulate mutable state. In order to perform IO in Haskell, one must use monads, but not necessarily understand them.
Some people find monads confusing; I've even heard a joke that you need a Ph.D. in computer science in order to perform IO in Haskell. This is clearly not true, and this book takes an approach which I whole-heartedly agree with. It gets the reader using monads and IO in chapter 3 without explaining them deeply until chapters 16 (IO) and 18 (monads). By the time you get there, if you have heard that monads are confusing, you might be inclined to say "how is this different from what we've been doing all along?" Over all, I was pleased with the explanation of monads, especially state monads in chapter 18, but I felt that the reader is not given enough exercises where they implement their own monads.
If you're worried that drawing shapes and playing music will not appeal to your mathematic side, you will be pleased by the focus on algebraic reasoning for shapes (section 8.3) and music (section 21.2), and a chapter on proof by induction (chapter 11).
After reading this book you will be prepared to take either of the two paths that Haskell is designed for: You can start writing useful and elegant tools, or you can dig into the fascinating programming language research going on. You will be prepared to approach arrows, a newer addition to Haskell which, like monads, have a deep relationship to category theory. Arrows are used extensively in some of the Yale Haskell group's recent work. You will see a lot of shared concepts between the animation in The Haskell School of Expression and Yale's "Functional Reactive Programming" framework, Yampa. If you like little languages, you'll appreciate how useful Haskell is for embedded domain-specific languages. It may be even more useful now that Template Haskell is in the works. Andrew Cooke described Purely Functional Data Structures as a great second book on functional programming. In my opinion, The Haskell School of Expression is the great first book you're looking for.
You can purchase Learning Functional Programming through Multimedia from bn.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.
Today, if you don't have enough flashy multimedia to attract the user to stay and look at what you have to say, you never even get your foot in the door. Chances are that someone who has taken the time to learn to both use the technology and apply it in a meaningful way probably has something to say.
With a generation of multimedia oriented programmers available I expect to see a much higher degree of interactivity in many different areas, from thing like mouse gestures to multi-dimensional navigation metaphores where we can simultaniously demonstrate our interests and our abilities so that we can arrive at the appropriate 'step' in whatever process we are trying to achieve.
"Can there be a Klein bottle that is an efficient and effective beer pitcher?"
Since I was already comfortable with recursion when I started this book, it is hard for me to gauge how a reader who has never encountered recursion would find this book's explanation of the concept.
Who is the target audience for this book? I would assume programmers, of at least moderate experience. It's not like there are thousands of script/VB kiddies jumping over themselves to learn functional languages. Makes me wonder, how many semi-experienced programmers are there out there who aren't comfortable with using/understanding recursive functions?
Meh. A decent computing science course will have an extensive class in data structures, usually implemented in C, in which you'll likely cover at least linked lists and trees, followed by a second, more extensive course on general algorithms, in which you'll cover heaps and other more advanced data structures. If it doesn't, it ain't worth enrolling in. *shrug*
Of course, after you've learned *how* a linked list is implemented, you should never have to roll your own. And if you do find yourself rolling your own, you should seriously question *why* before continuing, as there are many high quality, well tested implementations already floating around (for example, glib).
Do you also discourage the use of Perl, or shell scripts, or Tcl, or Java? Or is it just functional languages that you don't like because they do not map to existing processors?
-- Ed Avis ed@membled.com
Ah, I would say that "writing a program" by putting together other people's building blocks is not programming but code assembly. I would actually say that most "programmers" out there really don't know how to program, and that's why we have lots of the issues present today.
Um, no. Writing a program is always assembling building blocks unless you always start by writing an assembler for your target hardware.
The good programmers are the ones who assemble the correct building blocks the right way. The people who reinvent the linked list for every project are the ones who cause us the most problems (and yes, I've reinvented many linked lists in the past).
Once you break free from the mentality that you must always make your own malloc(), printf(), hashtables, trees, linked lists, etc... you can move on to higher level issues like the actual application you're working on.
-- The world is watching America, and America is watching TV.
"My fingers Emit sparks of fire in Expectation of my future labours." William Blake
Do people think it's a good thing for a C++/Java/.NET programmer to go back to the drawing board for a few months and learn stuff like functional programming?
Absolutely. It's a tragedy to go through life as a programmer without knowing FP. The more you learn about programming in general, the better you will be a programming.
I thought about coming up with a syllabus for myself of C, Haskell, LISP and Perl
I always recommend against perl. Very few people understand perl (no matter what they tell you), and I've yet to see a significant perl program without several significant bugs because of lack of proper exception handling or ambiguity (stuff like if($var) where $var can be false on what would otherwise be considered valid input).
I'd definitely recommend python instead if you want to learn some scripting (maybe ruby if you like stuff that looks like perl, but has a more reasonable philosophy).
C, like any other assembler, is OK to learn, but shouldn't be used for much of anything except to write extentions in high level languages.
Haskell is good. OCaml is good. Scheme is a good lisp derivative that's small enough to learn pretty easily.
You might want to add smalltalk and/or objective C in there. Smalltalk is pure OO (the OO version of Haskell, if you will). Objective C is C with smalltalk-style OO. When combined with the NeXTSTEP frameworks, you can learn a lot of very useful patterns.
A big part of functional programming is programming without side effects. Learning to program without side effects can greatly help you create more stable applications.
-- The world is watching America, and America is watching TV.
Optimizing Haskell by choice unboxings and strictness annotations is against the whole point of the language (*). More imporatantly, it is close to impossible for anyone but the compiler-writer to get right.
Predicting how a lazy program will perform is hard, and figuring out where it hurts is even harder. This is in part due to the massive restructurings the compiler does. One small annotation may be sufficient for the compiler to infer a function's strictness. Knowing where to put the annontation, tho, is nigh guesswork. Then I refactor the function, and there goes my strictness again.
But, this _is_ preferable to writing in C, I'll agree with you there.
(*) However, I think the worker-wrapper transformation may be the most beautiful optimization I've ever seen.
Another thing to remember is that while processor speeds double fairly often, programmer speeds are a constant given a distinct set of tools. If picking a language that executes slower allows a programmer to write more software in a given period of time, then that language is superior choice for all but the most time sensitive applications.
In other words, I don't want to waste time fucking around with pointers when I could be working on something more pertinant to the task at hand. I don't care HOW my matrix gets sorted. I just care that it does. If I waste some cycles, so what? This computer performs 53 MILLION in between each monitor refresh. If writing in a more abstract language permits me to get twice as much done per day of programming (and in my experience, it's more like 5-10 times), I'm willing wait.
Besides, while computers may no be able to "think," code optimization is not reasoning as much as it is pattern based. In fact, modern refactoring tools are better optimizers than most programmers, because they know more of these patterns. And unlike human programmers, refactoring tools aren't tempted to glaze over modern day essentials like bounds or type checking, resulting in fewer bugs and better security.
Hey freaks: now you're ju