In the Haskell community, we are slowly adding features of dependent types. Dependent types is an advanced typing feature by which types can depend on values. Some languages like Agda and Idris already have them. It appears to be a very advanced feature requiring an advanced type system, until you realize that python has had dependent types has had the dynamic typing version of dependent types, which may or may not be actual dependent types, from the beginning.
For most any program in a functional programming language, there is a way to reperesent it as an untyped lambda calculus term, no matter how advanced the typing. That's because typing only eliminates programs, not enable new ones.
Strong Typing wins us safety. How classes of errors that happened at run time can no longer happen at run time. This safety is rather nice. Besides this safety though, what does strong typing give you?
Are there an additional benefits of a strong type system besides safety?
(Note that I'm not saying that strong typing is worthless. Safety is a huge benefit in and of itself. I'm just wondering if there are additional benefits.)
First, we need to talk a bit about the history of the simply typed lambda calculus.
There are two historical developments of the simply typed lambda calculus.
When Alonzo Church described the lambda calculus the types were baked in as part of the meaning / operational behavior of the terms.
When Haskell Curry described the lambda calculus the types were annotations put on the terms.
So we have the lambda calculus a la Church and the lambda calculus a la Curry. See https://en.wikipedia.org/wiki/Simply_typed_lambda_calculus#Intrinsic_vs._extrinsic_interpretations for more.
Ironically, the language Haskell, which is named after Curry is based on a lambda calculus a la Church!
What this means is the types aren't simply annotations that rule out bad programs for you. They can "do stuff" too. Such types don't erase without leaving residue.
This shows up in Haskell's notion of type classes, which are really why Haskell is a language a la Church.
In Haskell, when I make a function
sort :: Ord a => [a] -> [a]
We're passing an object or dictionary for Ord a as the first argument.
But you aren't forced to plumb that argument around yourself in the code, it is the job of the compiler to build that up and use it.
instance Ord Char
instance Ord Int
instance Ord a => Ord [a]
So if you go and use sort on a list of strings, which are themselves lists of chars, then this will build up the dictionary by passing the Ord Char instance through the instance for Ord a => Ord [a] to get Ord [Char], which is the same as Ord String, then you can sort a list of strings.
Calling sort above, is a lot less verbose than manually building a LexicographicComparator<List<Char>> by passing it an IComparator<Char> to its constructor and calling the function with an extra second argument, if I were to compare the complexity of calling such a sort function in Haskell to calling it in C# or Java.
This shows us that programming with types can be significantly less verbose, because mechanisms like implicits and typeclasses can infer a large part of the code for your program during type checking.
On a simpler basis, even the sizes of arguments can depend on types, unless you want to pay fairly massive costs for boxing everything in your language up so that it has a homogeneous representation.
This shows us that programming with types can be significantly more efficient, because it can use dedicated representations, rather than paying for boxed structures everywhere in your code. An int can't just be a machine integer, because it has to somehow look like everything else in the system. If you're willing to give up an order of magnitude or more worth of performance at runtime, then this may not matter to you.
Finally, once we have types "doing stuff" for us, it is often beneficial to consider the refactoring benefits that mere safety provides.
If I refactor the smaller set of code that remains, it'll rewrite all that type-class plumbing for me. It'll figure out the new ways it can rewrite the code to unbox more arguments. I'm not stuck elaborating all of this stuff by hand, I can leave these mundane tasks to the type-checker.
But even when I do change the types, I can move arguments around fairly willy-nilly, comfortable that the compiler will very likely catch my errors. Types give you "free theorems" which are like unit tests for whole classes of such errors.
On the other hand, once I lock down an API in a language like Python I'm deathly afraid of changing it, because it'll silently break at runtime for all my downstream dependencies! This leads to baroque APIs that lean heavily on easily bit-rotted keyword-arguments, and the API of something that evolves over time rarely resembles what you'd build out of the box if you had it to do over again. Consequently, even the mere safety concern has long-term impact in API design once you ever want people to build on top of your work, rather than simply replace it when it gets too unwieldy.
That's because typing only eliminates programs, not enable new ones.
This is not a correct statement. Type-classes make it possible to generate parts of your program from type-level information.
Consider two expressions:
readMaybe "15" :: Maybe Integer
readMaybe "15" :: Maybe Bool
Here I'm using the readMaybe function from the Text.Read module. At term level those expressions are identical, only their type annotations are different. However, the results they produce at runtime differ (Just 15 in the first case, Nothing in the second case).
This is because the compiler generates code for you from the static type information you have. To be more precise, it selects a suitable type class instance and passes its dictionary to the polymorphic function (readMaybe in our case).
This example is simple, but there are way more complex use cases. Using the mtl library you can write computations that run in different computational contexts (aka Monads). The compiler will automatically insert a lot of code that manages the computational contexts. In a dynamically typed language, you would have no static information to make this possible.
As you can see, static typing not only cuts off incorrect programs but also writes correct ones for you.
You need "safety" when you already know what and how you want to write. It's a very small part of what types are useful for. The most important thing about types is that they make your reasoning structured. When someone writes in Python a + b he doesn't see a and b as some abstract variables — he sees them as some numbers. Types are already there in the internal language of humans, Python just doesn't have a type system to talk about them. The actual question in the "typed vs untyped (unityped) programming" dispute is "do we want to reflect our internal structured concepts in a safe and explicit or unsafe and implicit way?". Types don't introduce new concepts — it's untyped reasoning forgets the existing ones.
When someone looks at a tree (I mean a real green one) he doesn't see every single leaf on it, but he doesn't treat it as an abstract nameless object as well. "A tree" — is an approximation that is good enough for most cases and that's why we have Hindley-Milner type systems, but sometimes you want to talk about a specific tree and you do want to look at leaves. And that's what dependent types give you: the ability to zoom. "A tree without leaves", "a tree in the forest", "a tree of a particular form"... Dependently typed programming is just another step towards how humans think.
On a less abstract note, I have a type checker for a toy dependently typed language, where all typing rules are expressed as constructors of a data type. You don't need to dive into the type checking procedure to understand the rules of the system. That's the power of "zooming": you can introduce as complex invariants as you want, thus distinguishing essential parts from not important ones.
Another example of the power dependent types give you is various forms of reflection. Look e.g. at the Pierre-Évariste Dagand thesis, which proves that
generic programming is just programming
And of course types are hints, many functions and abstractions I defined I would define in a far more clumsy way in a weakly typed language, but types suggested better alternatives.
There is just no question "What to choose: simple types or dependent types?". Dependent types are always better and they of course subsume simple types. The question is "What to choose: no types or dependent types?", but that question doesn't stand for me.
Refactoring. By having a strong type system you can safely refactor code and have the compiler tell you whether what you are doing now even makes sense. The stronger the typing system, the more refactor errors are avoided. This of course means your code is a lot more maintainable.
Related
I have been playing around with LiquidHaskell and Idris lately and i got a pretty specific question, that i could not find a definitive answer anywhere.
Idris is a dependently typed language which is great for the most part. However i read that some type terms during type checking can "leak" from compile-time to run-time, even tough Idris does its best to eliminate those terms (this is a special feature even..). However, this elimination is not perfect and sometimes it does happen. If, why and when this happens is not immediately clear from the code and sometimes has an effect on run-time performance.
I have seen people prefering Haskells' type system, because it cannot happen there. When type checking is done, it is done. Types are "thrown away" and not used during run-time.
What is the story for LiquidHaskell? It enhances the type system capabilities quite a bit over traditional Haskell. Does LiquidHaskell also inject run-time bits for certain type "constellations" or (as i suspect) just adds another layer of "better" types over Haskell that do not affect run-time in any shape or form.
Meaning, if one removes the special LiquidHaskell type annotations and compiles it with standard GHC, is the code produced always the same? In other words: Is the LiquidHaskell extension compile-time only?
If yes, this seems like the best of both worlds, or is LiquidHaskell just not as expressive in the type system as Idris and therefore manages without run-time terms?
To answer your question as asked: Liquid Haskell allows you to provide annotations that a separate tool from the compiler verifies. Code is still compiled exactly the same way.
However, I have quibbles with your question as asked. It can be argued that there are cases in which some residue of the type must survive at run time in Haskell - especially when polymorphic recursion is involved. Consider this function:
lots :: Show a => Int -> a -> String
lots 0 x = show x
lots n x = lots (n-1) (x,x)
There is no way to statically determine the exact type involved in the use of show. Something derived from the types must survive to runtime. In practice, this is easy to do by using type class dictionaries. The theoretically important detail is that there's still type-directed behavior being chosen at runtime.
I am learning Haskell and trying to understand the Monoid typeclass.
At the moment, I am reading the haskellbook and it says the following about the pattern (monoid):
One of the finer points of the Haskell community has been its
propensity for recognizing abstract patterns in code which have
well-defined, lawful representations in mathematics.
What does the author mean by abstract patterns?
Abstract in this sense is the opposite of concrete. This is probably one of the key things to understand about Haskell.
What is a concrete thing? Well, most values in Haskell are concrete. For example 'a' :: Char. The letter 'a' is a Char value, and it's a concrete value. Char is a concrete type. But in 1 :: Num a => a, the number 1 is actually a value of any type, so long as that type has the set of functions that the Num typeclass sets out as mandatory. This is an abstract value! We can have abstract values, abstract types, and therefore abstract functions. When the program is compiled, the Haskell compiler will pick a particular concrete value that supports all of our requirements.
Haskell, at its core, has a very simple, small but incredibly flexible language. It's very similar to an expression of maths, actually. This makes it very powerful. Why? because most things that would be built in language constructs in other languages are not directly built into Haskell, but defined in terms of this simple core.
One of the core pieces is the function, which, it turns out, most of computation is expressible in terms of. Because so much of Haskell is just defined in terms of this small simple core, it means we can extend it to almost anywhere we can imagine.
Typeclasses are probably the best example of this. Monoid, and Num are examples of typeclasses. These are constructs that allow programmers to use an abstraction like a function across a great many types but only having to define it once. Typeclasses let us use the same function names across a whole range of types if we can define those functions for those types. Why is that important or useful? Well, if we can recognise a pattern across, for example, all numbers, and we have a mechanism for talking about all numbers in the language itself, then we can write functions that work with all numbers at once. This is an abstract pattern. You'll notice some Haskellers are quite interested in a branch of mathematics called Category Theory. This branch is pretty much the mathematical definition of abstract patterns. Contrast this ability to encode such things with the inability of other languages, where in other languages the patterns the community notice are often far less rigorous and have to be manually written out, and without any respect for its mathematical nature. The beauty of following the mathematics is the extremely large body of stuff we get for free by aligning our language closer with mathematics.
This is a good explanation of these basics including typeclasses in a book that I helped author: http://www.happylearnhaskelltutorial.com/1/output_other_things.html
Because functions are written in a very general way (because Haskell puts hardly any limits on our ability to express things generally), we can write functions that use types which express such things as "any type, so long as it's a Monoid". These are called type constraints, as above.
Generally abstractions are very useful because we can, for example, write on single function to operate on an entire range of types which means we can often find functions that do exactly what we want on our types if we just make them instances of specific typeclasses. The Ord typeclass is a great example of this. Making a type we define ourselves an instance of Ord gives us a whole bunch of sorting and comparing functions for free.
This is, in my opinion, one of the most exciting parts about Haskell, because while most other languages also allow you to be very general, they mostly take an extreme dip in how expressive you can be with that generality, so therefore also are less powerful. (This is because they are less precise in what they talk about, because their types are less well "defined").
This is how we're able to reason about the "possible values" of a function, and it's not limited to Haskell. The more information we encode at the type level, the more toward the specificity end of the spectrum of expressivity we veer. For example, to take a classic case, the function const :: a -> b -> a. This function requires that a and b can be of absolutely any type at all, including the same type if we like. From that, because the second parameter can be a different type than the first, we can work out that it really only has one possible functionality. It can't return an Int, unless we give it an Int as its first value, because that's not any type, right? So therefore we know the only value it can return is the first value! The functionality is defined right there in the type! If that's not mindblowing, then I don't know what is. :)
As we move to dependent types (that is, a type system where types are first class, which means also that ordinary values can be encoded in the type system), we can get closer and closer to having the type system specify specifically what the constraints of possible functionality are. However, the kicker is, it doesn't necessarily speak about the implementation of the functionality unless we want it to, because we're in control of how abstract it is, but while maintaining expressivity and much precision. That's pretty fascinating, and amazingly powerful.
Much math can be expressed in the language that underpins Haskell, the lambda calculus.
I have been using haskell for a while now. I understand most/some of the concepts but I still do not understand, what exactly does haskells type system allow me to do that I cannot do in another statically typed language. I just intuitively know that haskells type system is better in every imaginable way compared to the type system in C,C++ or java, but I can't explain it logically, primarily because of a lack of in depth knowledge about the differences in type systems between haskell and other statically typed languages.
Could someone give me examples of how haskells type system is more helpful compared to a language with a static type system. Examples, that are terse and can be succinctly expressed would be nice.
The Haskell type system has a number of features which all exist in other languages, but are rarely combined within a single, consistent language:
it is a sound, static type system, meaning that a number of errors are guaranteed not to happen at runtime without needing runtime type checks (this is also the case in Caml, SML and almost the case in Java, but not in, say, Lisp, Python, C, or C++);
it performs static type reconstruction, meaning that the programmer doesn't need to write types unless he wants to, the compiler will reconstruct them on its own (this is also the case in Caml and SML, but not in Java or C);
it supports impredicative polymorphism (type variables), even at higher kinds (unlike Caml and SML, or any other production-ready language known to me);
it has good support for overloading (type classes) (unlike Caml and SML).
Whether any of those make Haskell a better language is open to discussion — for example, while I happen to like type classes a lot, I know quite a few Caml programmers who strongly dislike overloading and prefer to use the module system.
On the other hand, the Haskell type system lacks a few features that other languages support elegantly:
it has no support for runtime dispatch (unlike Java, Lisp, and Julia);
it has no support for existential types and GADTs (these are both GHC extensions);
it has no support for dependent types (unlike Coq, Agda and Idris).
Again, whether any of these are desirable features in a general-purpose programming language is open to discussion.
In addition to what others have answered, it is also Haskell's type system that makes the language pure, i.e. which distinguishes between values of a certain type and effectful computations that produce a result of that type.
One major difference between Haskell's type system and that of most OO languages is that the ability for a function to have side effects is represented by a data type (a monad such as IO). This allows you to write pure functions that the compiler can verify are side-effect-free and referentially transparent, which generally means that they're easier to understand and less prone to bugs. It's possible to write side-effect-free code in other languages, but you don't have the compiler's help in doing so. Haskell makes you think more carefully about which parts of your program need to have side effects (such as I/O or mutable variables) and which parts should be pure.
Also, although it's not quite part of the type system itself, the fact that function definitions in Haskell are expressions (rather than lists of statements) means that more of the code is subject to type-checking. In languages like C++ and Java, it's often possible to introduce logic errors by writing statements in the wrong order, since the compiler doesn't have a way to determine that one statement must precede another. For example, you might have one line that modifies an object's state, and another line that does something important based on that state, and it's up to you to ensure that these things happen in the correct order. In Haskell, this kind of ordering dependency tends to be expressed through function composition — e.g. f (g x) means that g must run first — and the compiler can check the return type of g against the argument type of f to make sure you haven't composed them the wrong way.
Reading "Real world Haskell" i found some intresting question about data types:
This pattern matching and positional
data access make it look like you have
very tight coupling between data and
code that operates on it (try adding
something to Book, or worse change the
type of an existing part).
This is usually a very bad thing in
imperative (particularly OO)
languages... is it not seen as a
problem in Haskell?
source at RWH comments
And really, writing some Haskell programs I found that when I make small change to data type structure it affects almost all functions that use that data type. Maybe there are some good practices for data type usage. How can i minimize code coupling?
What you are describing is commonly known as the expression problem -- http://en.wikipedia.org/wiki/Expression_Problem.
There is a definite trade-off to be made, haskell code in general, and algebraic data types in particular, tends to fall into the hard to change the type but easy to add functions over the type. This optimizes for (up front) well-designed, complete, data types.
All that said, there are a number of things that you can do to reduce the coupling.
Define good library functions, by defining a complete set of combinators and higher order functions that are useful for interacting with your data type you will reduce coupling. It is often said that when ever you think of pattern matching there is a better solution using higher-order functions. If you look for these situations you will be in a better spot.
Expose your data structures as more abstract types. This means implementing all appropriate type classes. This will assist with defining a library functions as you will get a bunch for free with any of the type classes you implement, for examples look at operations over Functor or Monad.
Hide (as much as possible) any type constructors. Constructors expose implementation detail and will encourage coupling. Hint: this links in with defining a good api for interacting with your type, consumers of your type should rarely, if ever, have to use the type constructors.
The haskell community seems particularly good at this, if you look at many of the libraries on hackage you will find really good examples of implementing type classes and exposing good library functions.
In addition to what's been said:
One interesting approach is the "scrap your boilerplate" style of defining functions over data types, which makes use of generic functions (as opposed to explicit pattern matching) to define functions over the constructors of a data type. Looking at the "scrap your boilerplate" papers, you will see examples of functions which can cope with changes to the structure of a data type.
A second method, as Hibberd pointed out, is to use folds, maps, unfolds, and other recursion combinators, to define your functions. When you write functions using higher order functions, oftentimes small changes to the underlying data type can be dealt with in the instance declarations for Functor, Foldable, and so on.
First, I'd like to mention that in my view, there are two kinds of couplings:
One that makes your code cease to compile when you change one and forget to change the other
One that makes your code buggy when you change one and forget to change the other
While both are problematic, the former is significantly less of a headache, and that seems to be the one you're talking about.
I think the main problem you're mentioning is due to over-using positional arguments. Haskell almost forces you to have positional arguments in your ordinary functions, but you can avoid them in your type products (records).
Just use records instead of multiple anonymous fields inside data constructors, and then you can pattern-match any field you want out of it, by name.
bad (Blah _ y) = ...
good (Blah{y = y}) = ...
Avoid over-using tuples, especially those beyond 2-tuples, and liberally create records/newtypes around things to avoid positional meaning.
Reading Disadvantages of Scala type system versus Haskell?, I have to ask: what is it, specifically, that makes Haskell's type system more powerful than other languages' type systems (C, C++, Java). Apparently, even Scala can't perform some of the same powers as Haskell's type system. What is it, specifically, that makes Haskell's type system (Hindley–Milner type inference) so powerful? Can you give an example?
What is it, specifically, that makes Haskell's type system
It has been engineered for the past decade to be both flexible -- as a logic for property verification -- and powerful.
Haskell's type system has been developed over the years to encourage a relatively flexible, expressive static checking discipline, with several groups of researchers identifying type system techniques that enable powerful new classes of compile-time verification. Scala's is relatively undeveloped in that area.
That is, Haskell/GHC provides a logic that is both powerful and designed to encourage type level programming. Something fairly unique in the world of functional programming.
Some papers that give a flavor of the direction the engineering effort on Haskell's type system has taken:
Fun with type functions
Associated types with class
Fun with functional dependencies
Hindley-Milner is not a type system, but a type inference algorithm. Haskell's type system, back in the day, used to be able to be fully inferred using HM, but that ship has long sailed for modern Haskell with extensions. (ML remains capable of being fully inferred).
Arguably, the ability to mainly or entirely infer all types yields power in terms of expressiveness.
But that's largely not what I think the question is really about.
The papers that dons linked point to the other aspect -- that the extensions to Haskell's type system make it turing complete (and that modern type families make that turing complete language much more closely resemble value-level programming). Another nice paper on this topic is McBride's Faking It: Simulating Dependent Types in Haskell.
The paper in the other thread on Scala: "Type Classes as Objects and Implicits" goes into why you can in fact do most of this in Scala as well, although with a bit more explicitness. I tend to feel, but this is more a gut sense than from real Scala experience, that its more ad-hoc and explicit approach (what the C++ discussion called "nominal") is ultimately a bit messier.
Let's go with a very simple example: Haskell's Maybe.
data Maybe a = Nothing | Just a
In C++:
template <T>
struct Maybe {
bool isJust;
T value; // IMPORTANT: must ignore when !isJust
};
Let's consider these two function signatures, in Haskell:
sumJusts :: Num a => [Maybe a] -> a
and C++:
template <T> T sumJusts(vector<maybe<T> >);
Differences:
In C++ there are more possible mistakes to make. The compiler doesn't check the usage rule of Maybe.
The C++ type of sumJusts does not specify that it requires + and cast from 0. The error messages that show up when things do not work are cryptic and odd. In Haskell the compiler will just complain that the type is not an instance of Num, very straightforward..
In short, Haskell has:
ADTs
Type-classes
A very friendly syntax and good support for generics (which in C++ people try to avoid because of all their cryptickynessishisms)
Haskell language allows you to write safer code without giving up with functionalities. Most languages nowadays trade features for safety: the Haskell language is there to show that's possible to have both.
We can live without null pointers, explicit castings, loose typing and still have a perfectly expressive language, able to produce efficient final code.
More, the Haskell type system, along with its lazy-by-default and purity approach to coding gives you a boost in complicate but important matters like parallelism and concurrency.
Just my two cents.
One thing I really like and miss in other languages is the support of typclasses, which are an elegant solution for many problems (including for instance polyvariadic functions).
Using typeclasses, it's extremely easy to define very abstract functions, which are still completely type-safe - like for instance this Fibonacci-function:
fibs :: Num a => [a]
fibs#(_:xs) = 0:1:zipWith (+) fibs xs
For instance:
map (`div` 2) fibs -- integral context
(fibs !! 10) + 1.234 -- rational context
map (:+ 1.0) fibs -- Complex context
You may even define your own numeric type for this.
What is expressiveness? To my understanding it is what constraint the type system allow us to put on our code, or in other words what properties of code which we can prove. The more expressive a type system is, the more information we can embed at the type level (which can be used at compile time by the type-checker to check our code).
Here are some properties of Haskell's type system that other languages don't have.
Purity.
Purity allows Haskell to distinguish pure code and IO capable code
Paramtricity.
Haskell enforces parametricity for parametrically polymorphic functions so they must obey some laws. (Some languages does let you to express polymorphic function types but they don't enforce parametricity, for example Scala lets you to pattern match on a specific type even if the argument is polymorphic)
ADT
Extensions
Haskell's base type system is a weaker version of λ2 which itself isn't really impressive. But with these extensions it become really powerful (even able to express dependent types with singleton):
existential types
rank-n types (full λ2)
type families
data kinds (allows "typed" programming at type level)
GADT
...