Related
I'm having problem understanding the usefulness of Rust enums after reading The Rust Programming Language.
In section 17.3, Implementing an Object-Oriented Design Pattern, we have this paragraph:
If we were to create an alternative implementation that didn’t use the state pattern, we might instead use match expressions in the methods on Post or even in the main code that checks the state of the post and changes behavior in those places. That would mean we would have to look in several places to understand all the implications of a post being in the published state! This would only increase the more states we added: each of those match expressions would need another arm.
I agree completely. It would be very bad to use enums in this case because of the reasons outlined. Yet, using enums was my first thought of a more idiomatic implementation. Later in the same section, the book introduces the concept of encoding the state of the objects using types, via variable shadowing.
It's my understanding that Rust enums can contain complex data structures, and different variants of the same enum can contain different types.
What is a real life example of a design in which enums are the better option? I can only find fake or very simple examples in other sources.
I understand that Rust uses enums for things like Result and Option, but those are very simple uses. I was thinking of some functionality with a more complex behavior.
This turned out to be a somewhat open ended question, but I could not find a useful response after searching Google. I'm free to change this question to a more closed version if someone could be so kind as to help me rephrase it.
A fundamental trade-off between these choices in a broad sense has a name: "the expression problem". You should find plenty on Google under that name, both in general and in the context of Rust.
In the context of the question, the "problem" is to write the code in such a way that both adding a new state and adding a new operation on states does not involve modifying existing implementations.
When using a trait object, it is easy to add a state, but not an operation. To add a state, one defines a new type and implements the trait. To add an operation, naively, one adds a method to the trait but has to intrusively update the trait implementations for all states.
When using an enum for state, it is easy to add a new operation, but not a new state. To add an operation, one defines a new function. To add a new state, naively, one must intrusively modify all the existing operations to handle the new state.
If I explained this well enough, hopefully it should be clear that both will have a place. They are in a way dual to one another.
With this lens, an enum would be a better fit when the operations on the enum are expected to change more than the alternatives. For example, suppose you were trying to represent an abstract syntax tree for C++, which changes every three years. The set of types of AST nodes may not change frequently relative to the set of operations you may want to perform on AST nodes.
With that said, there are solutions to the more difficult options in both cases, but they remain somewhat more difficult. And what code must be modified may not be the primary concern.
On slide 30/78 of this presentation, Simon suggests that implementation of type classes was a "despair" at the beginning. Is anybody aware why that was?
I guess I'm one of the few people who have first hand experience of why it was hard, since I implemented it in hbc when there was no prior art.
So what was clear from the Wadler&Blott paper was that type checking was an extension of Hindley-Milner type checking and that at runtime you should be passing dictionaries around. From that to an actual implementation is a rather big step. A good way to understand the difficulty is to actually implement it starting from just the Wadler-Blott paper.
First, you need to come up with the idea of a type checker that not only checks types but also transforms the program; inserting evidence (dictionaries) while type checking. You also need to figure out how to construct new dictionaries from old ones using the instance declarations as an inference system.
It might all seem obvious in retrospect, but remember that since that time a lot of papers with explanations have been written. Understanding how to do something from a paper is very different from coming up with it in the first place.
Furthermore, you want type classes to be reasonably efficient which leads to its own set of problems.
It seems that Template Haskell is often viewed by the Haskell community as an unfortunate convenience. It's hard to put into words exactly what I have observed in this regard, but consider these few examples
Template Haskell listed under "The Ugly (but necessary)" in response to the question Which Haskell (GHC) extensions should users use/avoid?
Template Haskell considered a temporary/inferior solution in Unboxed Vectors of newtype'd values thread (libraries mailing list)
Yesod is often criticized for relying too much on Template Haskell (see the blog post in response to this sentiment)
I've seen various blog posts where people do pretty neat stuff with Template Haskell, enabling prettier syntax that simply wouldn't be possible in regular Haskell, as well as tremendous boilerplate reduction. So why is it that Template Haskell is looked down upon in this way? What makes it undesirable? Under what circumstances should Template Haskell be avoided, and why?
One reason for avoiding Template Haskell is that it as a whole isn't type-safe, at all, thus going against much of "the spirit of Haskell." Here are some examples of this:
You have no control over what kind of Haskell AST a piece of TH code will generate, beyond where it will appear; you can have a value of type Exp, but you don't know if it is an expression that represents a [Char] or a (a -> (forall b . b -> c)) or whatever. TH would be more reliable if one could express that a function may only generate expressions of a certain type, or only function declarations, or only data-constructor-matching patterns, etc.
You can generate expressions that don't compile. You generated an expression that references a free variable foo that doesn't exist? Tough luck, you'll only see that when actually using your code generator, and only under the circumstances that trigger the generation of that particular code. It is very difficult to unit test, too.
TH is also outright dangerous:
Code that runs at compile-time can do arbitrary IO, including launching missiles or stealing your credit card. You don't want to have to look through every cabal package you ever download in search for TH exploits.
TH can access "module-private" functions and definitions, completely breaking encapsulation in some cases.
Then there are some problems that make TH functions less fun to use as a library developer:
TH code isn't always composable. Let's say someone makes a generator for lenses, and more often than not, that generator will be structured in such a way that it can only be called directly by the "end-user," and not by other TH code, by for example taking a list of type constructors to generate lenses for as the parameter. It is tricky to generate that list in code, while the user only has to write generateLenses [''Foo, ''Bar].
Developers don't even know that TH code can be composed. Did you know that you can write forM_ [''Foo, ''Bar] generateLens? Q is just a monad, so you can use all of the usual functions on it. Some people don't know this, and because of that, they create multiple overloaded versions of essentially the same functions with the same functionality, and these functions lead to a certain bloat effect. Also, most people write their generators in the Q monad even when they don't have to, which is like writing bla :: IO Int; bla = return 3; you are giving a function more "environment" than it needs, and clients of the function are required to provide that environment as an effect of that.
Finally, there are some things that make TH functions less fun to use as an end-user:
Opacity. When a TH function has type Q Dec, it can generate absolutely anything at the top-level of a module, and you have absolutely no control over what will be generated.
Monolithism. You can't control how much a TH function generates unless the developer allows it; if you find a function that generates a database interface and a JSON serialization interface, you can't say "No, I only want the database interface, thanks; I'll roll my own JSON interface"
Run time. TH code takes a relatively long time to run. The code is interpreted anew every time a file is compiled, and often, a ton of packages are required by the running TH code, that have to be loaded. This slows down compile time considerably.
This is solely my own opinion.
It's ugly to use. $(fooBar ''Asdf) just does not look nice. Superficial, sure, but it contributes.
It's even uglier to write. Quoting works sometimes, but a lot of the time you have to do manual AST grafting and plumbing. The API is big and unwieldy, there's always a lot of cases you don't care about but still need to dispatch, and the cases you do care about tend to be present in multiple similar but not identical forms (data vs. newtype, record-style vs. normal constructors, and so on). It's boring and repetitive to write and complicated enough to not be mechanical. The reform proposal addresses some of this (making quotes more widely applicable).
The stage restriction is hell. Not being able to splice functions defined in the same module is the smaller part of it: the other consequence is that if you have a top-level splice, everything after it in the module will be out of scope to anything before it. Other languages with this property (C, C++) make it workable by allowing you to forward declare things, but Haskell doesn't. If you need cyclic references between spliced declarations or their dependencies and dependents, you're usually just screwed.
It's undisciplined. What I mean by this is that most of the time when you express an abstraction, there is some kind of principle or concept behind that abstraction. For many abstractions, the principle behind them can be expressed in their types. For type classes, you can often formulate laws which instances should obey and clients can assume. If you use GHC's new generics feature to abstract the form of an instance declaration over any datatype (within bounds), you get to say "for sum types, it works like this, for product types, it works like that". Template Haskell, on the other hand, is just macros. It's not abstraction at the level of ideas, but abstraction at the level of ASTs, which is better, but only modestly, than abstraction at the level of plain text.*
It ties you to GHC. In theory another compiler could implement it, but in practice I doubt this will ever happen. (This is in contrast to various type system extensions which, though they might only be implemented by GHC at the moment, I could easily imagine being adopted by other compilers down the road and eventually standardized.)
The API isn't stable. When new language features are added to GHC and the template-haskell package is updated to support them, this often involves backwards-incompatible changes to the TH datatypes. If you want your TH code to be compatible with more than just one version of GHC you need to be very careful and possibly use CPP.
There's a general principle that you should use the right tool for the job and the smallest one that will suffice, and in that analogy Template Haskell is something like this. If there's a way to do it that's not Template Haskell, it's generally preferable.
The advantage of Template Haskell is that you can do things with it that you couldn't do any other way, and it's a big one. Most of the time the things TH is used for could otherwise only be done if they were implemented directly as compiler features. TH is extremely beneficial to have both because it lets you do these things, and because it lets you prototype potential compiler extensions in a much more lightweight and reusable way (see the various lens packages, for example).
To summarize why I think there are negative feelings towards Template Haskell: It solves a lot of problems, but for any given problem that it solves, it feels like there should be a better, more elegant, disciplined solution better suited to solving that problem, one which doesn't solve the problem by automatically generating the boilerplate, but by removing the need to have the boilerplate.
* Though I often feel that CPP has a better power-to-weight ratio for those problems that it can solve.
EDIT 23-04-14: What I was frequently trying to get at in the above, and have only recently gotten at exactly, is that there's an important distinction between abstraction and deduplication. Proper abstraction often results in deduplication as a side effect, and duplication is often a telltale sign of inadequate abstraction, but that's not why it's valuable. Proper abstraction is what makes code correct, comprehensible, and maintainable. Deduplication only makes it shorter. Template Haskell, like macros in general, is a tool for deduplication.
I'd like to address a few of the points dflemstr brings up.
I don't find the fact that you can't typecheck TH to be that worrying. Why? Because even if there is an error, it will still be compile time. I'm not sure if this strengthens my argument, but this is similar in spirit to the errors that you receive when using templates in C++. I think these errors are more understandable than C++'s errors though, as you'll get a pretty printed version of the generated code.
If a TH expression / quasi-quoter does something that's so advanced that tricky corners can hide, then perhaps it's ill-advised?
I break this rule quite a bit with quasi-quoters I've been working on lately (using haskell-src-exts / meta) - https://github.com/mgsloan/quasi-extras/tree/master/examples . I know this introduces some bugs such as not being able to splice in the generalized list comprehensions. However, I think that there's a good chance that some of the ideas in http://hackage.haskell.org/trac/ghc/blog/Template%20Haskell%20Proposal will end up in the compiler. Until then, the libraries for parsing Haskell to TH trees are a nearly perfect approximation.
Regarding compilation speed / dependencies, we can use the "zeroth" package to inline the generated code. This is at least nice for the users of a given library, but we can't do much better for the case of editing the library. Can TH dependencies bloat generated binaries? I thought it left out everything that's not referenced by the compiled code.
The staging restriction / splitting of compilation steps of the Haskell module does suck.
RE Opacity: This is the same for any library function you call. You have no control over what Data.List.groupBy will do. You just have a reasonable "guarantee" / convention that the version numbers tell you something about the compatibility. It is somewhat of a different matter of change when.
This is where using zeroth pays off - you're already versioning the generated files - so you'll always know when the form of the generated code has changed. Looking at the diffs might be a bit gnarly, though, for large amounts of generated code, so that's one place where a better developer interface would be handy.
RE Monolithism: You can certainly post-process the results of a TH expression, using your own compile-time code. It wouldn't be very much code to filter on top-level declaration type / name. Heck, you could imagine writing a function that does this generically. For modifying / de-monolithisizing quasiquoters, you can pattern match on "QuasiQuoter" and extract out the transformations used, or make a new one in terms of the old.
This answer is in response to the issues brought up by illissius, point by point:
It's ugly to use. $(fooBar ''Asdf) just does not look nice. Superficial, sure, but it contributes.
I agree. I feel like $( ) was chosen to look like it was part of the language - using the familiar symbol pallet of Haskell. However, that's exactly what you /don't/ want in the symbols used for your macro splicing. They definitely blend in too much, and this cosmetic aspect is quite important. I like the look of {{ }} for splices, because they are quite visually distinct.
It's even uglier to write. Quoting works sometimes, but a lot of the time you have to do manual AST grafting and plumbing. The [API][1] is big and unwieldy, there's always a lot of cases you don't care about but still need to dispatch, and the cases you do care about tend to be present in multiple similar but not identical forms (data vs. newtype, record-style vs. normal constructors, and so on). It's boring and repetitive to write and complicated enough to not be mechanical. The [reform proposal][2] addresses some of this (making quotes more widely applicable).
I also agree with this, however, as some of the comments in "New Directions for TH" observe, the lack of good out-of-the-box AST quoting is not a critical flaw. In this WIP package, I seek to address these problems in library form: https://github.com/mgsloan/quasi-extras . So far I allow splicing in a few more places than usual and can pattern match on ASTs.
The stage restriction is hell. Not being able to splice functions defined in the same module is the smaller part of it: the other consequence is that if you have a top-level splice, everything after it in the module will be out of scope to anything before it. Other languages with this property (C, C++) make it workable by allowing you to forward declare things, but Haskell doesn't. If you need cyclic references between spliced declarations or their dependencies and dependents, you're usually just screwed.
I've run into the issue of cyclic TH definitions being impossible before... It's quite annoying. There is a solution, but it's ugly - wrap the things involved in the cyclic dependency in a TH expression that combines all of the generated declarations. One of these declarations generators could just be a quasi-quoter that accepts Haskell code.
It's unprincipled. What I mean by this is that most of the time when you express an abstraction, there is some kind of principle or concept behind that abstraction. For many abstractions, the principle behind them can be expressed in their types. When you define a type class, you can often formulate laws which instances should obey and clients can assume. If you use GHC's [new generics feature][3] to abstract the form of an instance declaration over any datatype (within bounds), you get to say "for sum types, it works like this, for product types, it works like that". But Template Haskell is just dumb macros. It's not abstraction at the level of ideas, but abstraction at the level of ASTs, which is better, but only modestly, than abstraction at the level of plain text.
It's only unprincipled if you do unprincipled things with it. The only difference is that with the compiler implemented mechanisms for abstraction, you have more confidence that the abstraction isn't leaky. Perhaps democratizing language design does sound a bit scary! Creators of TH libraries need to document well and clearly define the meaning and results of the tools they provide. A good example of principled TH is the derive package: http://hackage.haskell.org/package/derive - it uses a DSL such that the example of many of the derivations /specifies/ the actual derivation.
It ties you to GHC. In theory another compiler could implement it, but in practice I doubt this will ever happen. (This is in contrast to various type system extensions which, though they might only be implemented by GHC at the moment, I could easily imagine being adopted by other compilers down the road and eventually standardized.)
That's a pretty good point - the TH API is pretty big and clunky. Re-implementing it seems like it could be tough. However, there are only really only a few ways to slice the problem of representing Haskell ASTs. I imagine that copying the TH ADTs, and writing a converter to the internal AST representation would get you a good deal of the way there. This would be equivalent to the (not insignificant) effort of creating haskell-src-meta. It could also be simply re-implemented by pretty printing the TH AST and using the compiler's internal parser.
While I could be wrong, I don't see TH as being that complicated of a compiler extension, from an implementation perspective. This is actually one of the benefits of "keeping it simple" and not having the fundamental layer be some theoretically appealing, statically verifiable templating system.
The API isn't stable. When new language features are added to GHC and the template-haskell package is updated to support them, this often involves backwards-incompatible changes to the TH datatypes. If you want your TH code to be compatible with more than just one version of GHC you need to be very careful and possibly use CPP.
This is also a good point, but somewhat dramaticized. While there have been API additions lately, they haven't been extensively breakage inducing. Also, I think that with the superior AST quoting I mentioned earlier, the API that actually needs to be used can be very substantially reduced. If no construction / matching needs distinct functions, and are instead expressed as literals, then most of the API disappears. Moreover, the code you write would port more easily to AST representations for languages similar to Haskell.
In summary, I think that TH is a powerful, semi-neglected tool. Less hate could lead to a more lively eco-system of libraries, encouraging the implementation of more language feature prototypes. It's been observed that TH is an overpowered tool, that can let you /do/ almost anything. Anarchy! Well, it's my opinion that this power can allow you to overcome most of its limitations, and construct systems capable of quite principled meta-programming approaches. It's worth the usage of ugly hacks to simulate the "proper" implementation, as this way the design of the "proper" implementation will gradually become clear.
In my personal ideal version of nirvana, much of the language would actually move out of the compiler, into libraries of these variety. The fact that the features are implemented as libraries does not heavily influence their ability to faithfully abstract.
What's the typical Haskell answer to boilerplate code? Abstraction. What're our favorite abstractions? Functions and typeclasses!
Typeclasses let us define a set of methods, that can then be used in all manner of functions generic on that class. However, other than this, the only way classes help avoid boilerplate is by offering "default definitions". Now here is an example of an unprincipled feature!
Minimal binding sets are not declarable / compiler checkable. This could lead to inadvertent definitions that yield bottom due to mutual recursion.
Despite the great convenience and power this would yield, you cannot specify superclass defaults, due to orphan instances http://lukepalmer.wordpress.com/2009/01/25/a-world-without-orphans/ These would let us fix the numeric hierarchy gracefully!
Going after TH-like capabilities for method defaults led to http://www.haskell.org/haskellwiki/GHC.Generics . While this is cool stuff, my only experience debugging code using these generics was nigh-impossible, due to the size of the type induced for and ADT as complicated as an AST. https://github.com/mgsloan/th-extra/commit/d7784d95d396eb3abdb409a24360beb03731c88c
In other words, this went after the features provided by TH, but it had to lift an entire domain of the language, the construction language, into a type system representation. While I can see it working well for your common problem, for complex ones, it seems prone to yielding a pile of symbols far more terrifying than TH hackery.
TH gives you value-level compile-time computation of the output code, whereas generics forces you to lift the pattern matching / recursion part of the code into the type system. While this does restrict the user in a few fairly useful ways, I don't think the complexity is worth it.
I think that the rejection of TH and lisp-like metaprogramming led to the preference towards things like method-defaults instead of more flexible, macro-expansion like declarations of instances. The discipline of avoiding things that could lead to unforseen results is wise, however, we should not ignore that Haskell's capable type system allows for more reliable metaprogramming than in many other environments (by checking the generated code).
One rather pragmatic problem with Template Haskell is that it only works when GHC's bytecode interpreter is available, which is not the case on all architectures. So if your program uses Template Haskell or relies on libraries that use it, it will not run on machines with an ARM, MIPS, S390 or PowerPC CPU.
This is relevant in practice: git-annex is a tool written in Haskell that makes sense to run on machines worrying about storage, such machines often have non-i386-CPUs. Personally, I run git-annex on a NSLU 2 (32 MB of RAM, 266MHz CPU; did you know Haskell works fine on such hardware?) If it would use Template Haskell, this is not possible.
(The situation about GHC on ARM is improving these days a lot and I think 7.4.2 even works, but the point still stands).
Why is TH bad? For me, it comes down to this:
If you need to produce so much repetitive code that you find yourself trying to use TH to auto-generate it, you're doing it wrong!
Think about it. Half the appeal of Haskell is that its high-level design allows you to avoid huge amounts of useless boilerplate code that you have to write in other languages. If you need compile-time code generation, you're basically saying that either your language or your application design has failed you. And we programmers don't like to fail.
Sometimes, of course, it's necessary. But sometimes you can avoid needing TH by just being a bit more clever with your designs.
(The other thing is that TH is quite low-level. There's no grand high-level design; a lot of GHC's internal implementation details are exposed. And that makes the API prone to change...)
In every project I've started in languages without type systems, I eventually begin to invent a runtime type system. Maybe the term "type system" is too strong; at the very least, I create a set of type/value-range validators when I'm working with complex data types, and then I feel the need to be paranoid about where data types can be created and modified.
I hadn't thought twice about it until now. As an independent developer, my methods have been working in practice on a number of small projects, and there's no reason they'd stop working now.
Nonetheless, this must be wrong. I feel as if I'm not using dynamically-typed languages "correctly". If I must invent a type system and enforce it myself, I may as well use a language that has types to begin with.
So, my questions are:
Are there existing programming paradigms (for languages without types) that avoid the necessity of using or inventing type systems?
Are there otherwise common recommendations on how to solve the problems that static typing solves in dynamically-typed languages (without sheepishly reinventing types)?
Here is a concrete example for you to consider. I'm working with datetimes and timezones in erlang (a dynamic, strongly typed language). This is a common datatype I work with:
{{Y,M,D},{tztime, {time, HH,MM,SS}, Flag}}
... where {Y,M,D} is a tuple representing a valid date (all entries are integers), tztime and time are atoms, HH,MM,SS are integers representing a sane 24-hr time, and Flag is one of the atoms u,d,z,s,w.
This datatype is commonly parsed from input, so to ensure valid input and a correct parser, the values need to be checked for type correctness, and for valid ranges. Later on, instances of this datatype are compared to each other, making the type of their values all the more important, since all terms compare. From the erlang reference manual
number < atom < reference < fun < port < pid < tuple < list < bit string
Aside from the confsion of static vs. dynamic and strong vs. weak typing:
What you want to implement in your example isn't really solved by most existing static typing systems. Range checks and complications like February 31th and especially parsed input are usually checked during runtime no matter what type system you have.
Your example being in Erlang I have a few recommendations:
Use records. Besides being usefull and helpfull for a whole bunch of reasons, the give you easy runtime type checking without a lot of effort e.g.:
is_same_day(#datetime{year=Y1, month=M1, day=D1},
#datetime{year=Y2, month=M2, day=D2}) -> ...
Effortless only matches for two datetime records. You could even add guards to check for ranges if the source is untrusted. And it conforms to erlangs let it crash method of error handling: if no match is found you get a badmatch, and can handle this on the level where it is apropriate (usually the supervisor level).
Generally write your code that it crashes when the assumptions are not valid
If this doesn't feel static checked enough: use typer and dialyzer to find the kind of errors that can be found statically, whatever remains will be checkd at runtime.
Don't be too restrictive in your functions what "types" you accept, sometimes the added functionality of just doing someting useful even for different inputs is worth more than checking the types and ranges on every function. If you do it where it matters usually you will catch the error early enough for it to be easy fixable. This is especially true for a functionaly language where you allways know where every value comes from.
A lot of good answers, let me add:
Are there existing programming paradigms (for languages without types) that avoid the necessity of using or inventing type systems?
The most important paradigm, especially in Erlang, is this: Assume the type is right, otherwise let it crash. Don't write excessively checking paranoid code, but assume that the input you get is of the right type or the right pattern. Don't write (there are exceptions to this rule, but in general)
foo({tag, ...}) -> do_something(..);
foo({tag2, ...}) -> do_something_else(..);
foo(Otherwise) ->
report_error(Otherwise),
try to fix problem here...
Kill the last clause and have it crash right away. Let a supervisor and other processes do the cleanup (you can use monitors() for janitorial processes to know when a crash has occurred).
Do be precise however. Write
bar(N) when is_integer(N) -> ...
baz([]) -> ...
baz(L) when is_list(L) -> ...
if the function is known only to work with integers or lists respectively. Yes, it is a runtime check but the goal is to convey information to the programmer. Also, HiPE tend to utilize the hint for optimization and eliminate the type check if possible. Hence, the price may be less than what you think it is.
You choose an untyped/dynamically-typed language so the price you have to pay is that type checking and errors from clashes will happen at runtime. As other posts hint, a statically typed language is not exempt from doing some checks as well - the type system is (usually) an approximation of a proof of correctness. In most static languages you often get input which you can't trust. This input is transformed at the "border" of the application and then converted to an internal format. The conversion serves to mark trust: From now on, the thing has been validated and we can assume certain things about it. The power and correctness of this assumption is directly tied to its type signature and how good the programmer is with juggling the static types of the language.
Are there otherwise common recommendations on how to solve the problems that static typing solves in dynamically-typed languages (without sheepishly reinventing types)?
Erlang has the dialyzer which can be used to statically analyze and infer types of your programs. It will not come up with as many type errors as a type checker in e.g., Ocaml, but it won't "cry wolf" either: An error from the dialyzer is provably an error in the program. And it won't reject a program which may be working ok. A simple example is:
and(true, true) -> true;
and(true, _) -> false;
and(false, _) -> false.
The invocation and(true, greatmistake) will return false, yet a static type system will reject the program because it will infer from the first line that the type signature takes a boolean() value as the 2nd parameter. The dialyzer will accept this function in contrast and give it the signature (boolean(), term()) -> boolean(). It can do this, because there is no need to protect a priori for an error. If there is a mistake, the runtime system has a type check that will capture it.
In order for a statically-typed language to match the flexibility of a dynamically-typed one, I think it would need a lot, perhaps infinitely many, features.
In the Haskell world, one hears a lot of sophisticated, sometimes to the point of being scary, teminology. Type classes. Parametric polymorphism. Generalized algebraic data types. Type families. Functional dependencies. The Ωmega programming language takes it even further, with the website listing "type-level functions" and "level polymorphism", among others.
What are all these? Features added to static typing to make it more flexible. These features can be really cool, and tend to be elegant and mind-blowing, but are often difficult to understand. Learning curve aside, type systems often fail to model real-world problems elegantly. A particularly good example of this is interacting with other languages (a major motivation for C# 4's dynamic feature).
Dynamically-typed languages give you the flexibility to implement your own framework of rules and assumptions about data, rather than be constrained by the ever-limited static type system. However, "your own framework" won't be machine-checked, meaning the onus is on you to ensure your "type system" is safe and your code is well-"typed".
One thing I've found from learning Haskell is that I can carry lessons learned about strong typing and sound reasoning over to weaker-typed languages, such as C and even assembly, and do the "type checking" myself. Namely, I can prove that sections of code are correct in and of themselves, by bearing in mind the rules my functions and values are supposed to follow, and the assumptions I am allowed to make about other functions and values. When debugging, I go through and check things again, and think through whether or not my approach is sound.
The bottom line: dynamic typing puts more flexibility at your fingertips. On the other hand, statically-typed languages tend to be more efficient (by orders of magnitude), and good static type systems drastically cut down on debugging time by letting the computer do much of it for you. If you want the benefits of both, install a static type checker in your brain by learning decent, strongly-typed languages.
Sometimes data need validation. Validating any data received from the network is almost always a good idea — especially data from a public network. Being paranoid here is only good. If something resembling a static type system helps this in the least painful way, so be it. There's a reason why Erlang allows type annotations. Even pattern matching can be seen as just a kind of dynamic type checking; nevertheless, it's a central feature of the language. The very structure of data is its 'type' in Erlang.
The good thing is that you can custom-tailor your 'type system' to your needs, make it flexible and smart, while type systems of OO languages typically have fixed features. When data structures you use are immutable, once you've validated such a structure, you're safe to assume it conforms your restrictions, just like with static typing.
There's no point in being ready to process any kind of data at any point of a program, dynamically-typed or not. A 'dynamic type' is essentially a union of all possible types; limiting it to a useful subset is a valid way to program.
A statically typed language detects type errors at compile time. A dynamically typed language detects them at runtime. There are some modest restrictions on what one can write in a statically typed language such that all type errors can be caught at compile time.
But yes, you still have types even in a dynamically typed language, and that's a good thing. The problem is you wander into lots of runtime checks to ensure that you have the types you think you do, since the compiler hasn't taken care of that for you.
Erlang has a very nice tool for specifying and statically verifying lots of types -- dialyzer: Erlang type system, for references.
So don't reinvent types, use the typing tools that Erlang already provides, to handle the types that already exist in your program (but which you haven't yet specified).
And this on its own won't eliminate range checks, unfortunately. Without lots of special sauce you really have to enforce this on your own by convention (and smart constructors, etc. to help), or fall back to runtime checks, or both.
What exactly is the difference? It seems like the terms can be used somewhat interchangeably, but reading the wikipedia entry for Objective-c, I came across:
In addition to C’s style of procedural
programming, C++ directly supports
certain forms of object-oriented
programming, generic programming, and
metaprogramming.
in reference to C++. So apparently they're different?
Programming: Writing a program that creates, transforms, filters, aggregates and otherwise manipulates data.
Metaprogramming: Writing a program that creates, transforms, filters, aggregates and otherwise manipulates programs.
Generic Programming: Writing a program that creates, transforms, filters, aggregates and otherwise manipulates data, but makes only the minimum assumptions about the structure of the data, thus maximizing reuse across a wide range of datatypes.
As was already mentioned in several other answers, the distinction can be confusing in C++, since both Generic Programming and (static/compile time) Metaprogramming are done with Templates. To confuse you even further, Generic Programming in C++ actually uses Metaprogramming to be efficient, i.e. Template Specialization generates specialized (fast) programs from generic ones.
Also note that, as every Lisp programmer knows, code and data are the same thing, so there really is no such thing as "metaprogramming", it's all just programming. Again, this is a bit hard to see in C++, since you actually use two completely different programming languages for programming (C++, an imperative, procedural, object-oriented language in the C family) and metaprogramming (Templates, a purely functional "accidental" language somewhere in between pure lambda calculus and Haskell, with butt-ugly syntax, since it was never actually intended to be a programming language.)
Many other languages use the same language for both programming and metaprogramming (e.g. Lisp, Template Haskell, Converge, Smalltalk, Newspeak, Ruby, Ioke, Seph).
Metaprogramming, in a broad sense, means writing programs that yield other programs. E.g. like templates in C++ produce actual code only when instantiated. One can interpret a template as a program that takes a type as an input and produces an actual function/class as an output. Preprocessor is another kind of metaprogramming. Another made-up example of metaprogramming:a program that reads an XML and produces some SQL scripts according to the XML. Again, in general, a metaprogram is a program that yields another program, whereas generic programming is about parametrized(usually with other types) types(including functions) .
EDITED after considering the comments to this answer
I would roughly define metaprogramming as "writing programs to write programs" and generic programming as "using language features to write functions, classes, etc. parameterized on the data types of arguments or members".
By this standard, C++ templates are useful for both generic programming (think vector, list, sort...) and metaprogramming (think Boost and e.g. Spirit). Furthermore, I would argue that generic programming in C++ (i.e. compile-time polymorphism) is accomplished by metaprogramming (i.e. code generation from templated code).
Generic programming usually refers to functions that can work with many types. E.g. a sort function, which can sort a collection of comparables instead of one sort function to sort an array of ints and another one to sort a vector of strings.
Metaprogramming refers to inspecting, modifying or creating classes, modules or functions programmatically.
Its best to look at other languages, because in C++, a single feature supports both Generic Programming and Metaprogramming. (Templates are very powerful).
In Scheme / Lisp, you can change the grammar of your code. People probably know Scheme as "that prefix language with lots of parenthesis", but it also has very powerful metaprogramming techniques (Hygenic Macros). In particular, try / catch can be created, and even the grammar can be manipulated to a point (For example, here is a prefix to infix converter if you don't want to write prefix code anymore: http://github.com/marcomaggi/nausicaa). This is accomplished through metaprogramming, code that writes code that writes code. This is useful for experimenting with new paradigms of programming (the AMB operator plays an important role in non-deterministic programming. I hope AMB will become mainstream in the next 5 years or so...)
In Java / C#, you can have generic programming through generics. You can write one generic class that supports the types of many other classes. For instance, in Java, you can use Vector to create a Vector of Integers. Or Vector if you want it specific to your own class.
Where things get strange, is that C++ templates are designed for generic programming. However, because of a few tricks, C++ templates themselves are turing-complete. Using these tricks, it is possible to add new features to the C++ language through meta-programming. Its convoluted, but it works. Here's an example which adds multiple dispatch to C++ through templates. http://www.eptacom.net/pubblicazioni/pub_eng/mdisp.html . The more typical example is Fibonacci at compile time: http://blog.emptycrate.com/node/271
Generic programming is a very simple form of metacoding albeit not usually runtime. It's more like the preprocessor in C and relates more to template programming in most use cases and basic implementations.
You'll find often in typed languages that you'll create a few implementations of something where only the type if different. In languages such as Java this can be especially painful since every class and interface is defining a new type.
You can generate those classes by converting them to a string literal then replacing the class name with a variable to interpolate.
Where generics are used in runtime it's a bit different, in that case it's simply variable programming, programming using variables.
The way to envisage that is simple, take to files, compare them and turn anything different into a variable. Now you have only one file that is reusable. You only have to specify what's different, hence the name variable.
How generics came about it that not everything can be made variable like the variable type you expect or a cast type. Often there would by a lot of file duplication where the only thing that was variable was the variable types. This was a very common source of duplication. Although there are ways around it or to mitigate it they aren't particularly convenient. Generics have come along as a kind of variable variable to allow making the variable type variable. Because the variable type is something normally expressing in the programming language that can now be specified in runtime it is also considered metacoding, albeit a very simple case.
The effect of not having variability where you need it is to unroll your variables, that is you are forced instead of having a variable to make an implementation for every possible would be variable value.
As you can imagine that is quite expensive. This would be very common when using any kind of reusage object storage library. These will accept any object but in most cases people only want to sore one type of objdct. If you put in a Shop object which extends Object then want to retrieve it, the method signature on the storage object will return simply Object but your code will expect a Shop object. This will break compilation with the downgrade of the object unless you cast it back up to shop. This raises another conundrum as without generics there is no way to check for compatibility and ensure the object you are storing is a Shop class.
Java avoids metaprogramming and tries to keep the language simple using OOP principles of polymorphism instead to make flexible code. However there are some pressing and reoccurring problems that through experience have presented themselves and are addressed with the addition of minimal metaprogramming facilities. Java does not want to be a metaprogramming language but sparingly imports concepts from there to solve the most nagging problems.
Programming languages that offer lavage metacoding facilities can be significantly more productive than languages than avoid it barring special cases, reflection, OOP polymorphism, etc. However it often also takes a lot more skill and expertise to generate un=nderstandable, maintaiable and bug free code. There is also often a performance penalty for such languages with C++ being a bit of an oddball because it is compiled to native.