Haskell compiler magic: what requires a special treatment from the compiler? - haskell

When trying to learn Haskell, one of the difficulties that arise is the ability when something requires special magic from the compiler. One exemple that comes in mind is the seq function which can't be defined i.e. you can't make a seq2 function behaving exactly as the built-in seq. Consequently, when teaching someone about seq, you need to mention that seq is special because it's a special symbol for the compiler.
Another example would be the do-notation which only works with instances of the Monad class.
Sometimes, it's not always obvious. For instance, continuations. Does the compiler knows about Control.Monad.Cont or is it plain old Haskell that you could have invented yourself? In this case, I think nothing special is required from the compiler even if continuations are a very strange kind of beast.
Language extensions set aside, what other compiler magic Haskell learners should be aware of?

Nearly all the ghc primitives that cannot be implemented in userland are in the ghc-prim package. (it even has a module called GHC.Magic there!)
So browsing it will give a good sense.
Note that you should not use this module in userland code unless you know exactly what you are doing. Most of the usable stuff from it is exported in downstream modules in base, sometimes in modified form. Those downstream locations and APIs are considered more stable, while ghc-prim makes no guarantees as to how it will act from version to version.
The GHC-specific stuff is reexported in GHC.Exts, but plenty of other things go into the Prelude (such as basic data types, as well as seq) or the concurrency libraries, etc.

Polymorphic seq is definitely magic. You can implement seq for any specific type, but only the compiler can implement one function for all possible types [and avoid optimising it away even though it looks no-op].
Obviously the entire IO monad is deeply magic, as is everything to with concurrency and parallelism (par, forkIO, MVar), mutable storage, exception throwing and catching, querying the garbage collector and run-time stats, etc.
The IO monad can be considered a special case of the ST monad, which is also magic. (It allows truly mutable storage, which requires low-level stuff.)
The State monad, on the other hand, is completely ordinary user-level code that anybody can write. So is the Cont monad. So are the various exception / error monads.
Anything to do with syntax (do-blocks, list comprehensions) is hard-wired into the language definition. (Note, though, that some of these respond to LANGUAGE RebindableSyntax, which lets you change what functions it binds to.) Also the deriving stuff; the compiler "knows about" a handful of special classes and how to auto-generate instances for them. Deriving for newtype works for any class though. (It's just copying an instance from one type to another identical copy of that type.)
Arrays are hard-wired. Much like every other programming language.
All of the foreign function interface is clearly hard-wired.
STM can be implemented in user code (I've done it), but it's currently hard-wired. (I imagine this gives a significant performance benefit. I haven't tried actually measuring it.) But, conceptually, that's just an optimisation; you can implement it using the existing lower-level concurrency primitives.

Related

Forcing a monadic computation to be done statically

In Matthew Pickering's blog post about inlining, he mentions a trick to force GHC to inline recursive definitions applied to a statically known argument:
However, there is a trick that can be used in order to tell GHC that an argument is truly static. We replace the value argument with a type argument. Then by defining suitable type class instances, we can recurse on the structure of the type as we would on a normal value. This time however, GHC will happily inline each “recursive” call as each call to sum is at a different type.
Then the blog post proceeds to show a very simplistic example using type-level Nats. My question is about forcing GHC to fully inline functions over actually interesting types.
In my case, I have a computation that is via a monadic DSL. Under the hood, the DSL is an RWS. Looking at the generated Core with lots of INLINE pragmas, I can see calls to the recursive functions that implement <> for the writer output. Since these functions are recursive, GHC doesn't inline them. But if it did, since the full RWS computation is static enough that the spine of the writer output could be fully unrolled during compilation, it would, after finitely many steps, arrive at Core with no recursive definitions left.
Taking the idea from Matt's blog post, we would need to have a type-level representation of the monadic value; I'd love to see a version of this (especially with good ergonomics!), but I am not too optimistic: unlike the Servant approach, we would need a way to bind variables to results (a la monadic >>=). Alternatively, are there any other mechanisms to tell GHC that its input size is statically known, so it shouldn't shy away from aggressively inlining recrusive definitions? For example, is it possible to emulate Agda-style sized types by using a graded monad with some appropriate size measure in the index?
P.s.: My aim is not mere optimization, but working around a Clash bug, so this elimination of recursive definitions by aggressive inlining would need to be something dependable, not a nice-to-have performance improvement.

Are there benefits of strong typing besides safety?

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.

In what way is haskells type system more helpful than the type system of another statically typed language

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.

Does haskell erase types?

Does Haskell erase types, and if so, in what ways is this similar/dissimilar to the type erasure that occurs in Java?
Warning: experience+inference. Consult someone who works on both compilers for The Truth.
In the sense that type checking is done at compile time, and several complex features of the type system are reduced to much simpler language constructs, yes, but in a rather different way to Java.
A type signature creates no runtime overhead. The Haskell compiler is good at program transformation (it has more leeway, because the running order is in many cases not specified by the programmer), and automatically inlines appropriate definitions and specialises haskell-polymorhpic (=java-generic) functions to a particular type etc, as it sees fit, if it helps. That's a similar to Java type erasure, but more-so aspect.
There are in essence no type casts needed in Haskell to ensure type safety, because Haskell is designed to be type-safe from the ground up. We don't resort to turning everything into an Object, and we don't cast them back, because a polymorphic(generic) function genuinely does work on any data type, no matter what, pointer types or unboxed integers, it just works, without trickery. So unlike Java, casting is not a feature of compiling polymorphic(generic) code. Haskell folk tend to feel that if you're doing type casting, you said goodbye to type safety anyway.
For a lovely example of how ensuring the code's static type-correctness at compile time can avoid runtime overhead, there's a newtype construct in Haskell which is a type-safe wrapper for an existing type, and it's completely compiled away - all the construction and destruction simply doesn't happen at runtime. The type system ensures at compile time it's used correctly, it can't be got at at runtime except using (type-checked) accessor functions.
Polymorphic(generic) functions don't have polymorphic overheads. Haskell-overloaded functions (Java-interface-instance methods) have a data overhead in the sense that there's an implicit dictionary of functions used for what appears to be late binding to Java programmers, but is in fact, again, determined at compile time.
Summary: yes, even more so than in Java, and no, they were never there at runtime to erase anyway.
C and Pascal have type erasure. Java lets you inspect classes at run-time - even dynamically loaded ones!
What Haskell does is much closer to Pascal than to Java.

Is Haskell really a purely functional language considering unsafePerformIO?

Haskell is generally referenced as an example of a purely functional language. How can this be justified given the existence of System.IO.Unsafe.unsafePerformIO ?
Edit: I thought with "purely functional" it was meant that it is impossible to introduce impure code into the functional part of the program.
The Languages We Call Haskell
unsafePerformIO is part of the Foreign Function Interface specification, not core Haskell 98 specification. It can be used to do local side effects that don't escape some scope, in order to expose a purely functional interface. That is, we use it to hide effects when the type checker can't do it for us (unlike the ST monad, which hides effects with a static guarantee).
To illustrate precisely the multiple languages that we call "Haskell", consider the image below. Each ring corresponds to a specific set of computational features, ordered by safety, and with area correlating to expressive power (i.e. the number of programs you can write if you have that feature).
The language known as Haskell 98 is specified right down in the middle, admitting total and partial functions. Agda (or Epigram), where only total functions are allowed, is even less expressive, but "more pure" and more safe. While Haskell as we use it today includes everything out to the FFI, where unsafePerformIO lives. That is, you can write anything in modern Haskell, though if you use things from the outer rings, it will be harder to establish safety and security guarantees made simple by the inner rings.
So, Haskell programs are not typically built from 100% referentially transparent code, however, it is the only moderately common language that is pure by default.
I thought with "purely functional" it was meant that it is impossible to introduce impure code...
The real answer is that unsafePerformIO is not part of Haskell, any more than say, the garbage collector or run-time system are part of Haskell. unsafePerformIO is there in the system so that the people who build the system can create a pure functional abstraction over very effectful hardware. All real languages have loopholes that make it possible for system builders to get things done in ways that are more effective than dropping down to C code or assembly code.
As to the broader picture of how side effects and I/O fit into Haskell via the IO monad, I think the easiest way to think of Haskell is that it is a pure language that describes effectful computations. When the computation described is main, the run-time system carries out those effects faithfully.
unsafePerformIO is a way to get effects in an unsafe manner; where "unsafe" means "safety must be guaranteed by the programmer"—nothing is checked by the compiler. If you are a savvy programmer and are willing to meet heavy proof obligations, you can use unsafePerformIO. But at that point you are not programming in Haskell any more; you are programming in an unsafe language that looks a lot like Haskell.
The language/implementation is purely functional. It includes a couple "escape hatches," which you don't have to use if you don't want to.
I don't think unsafePerformIO means that haskell somehow becomes impure. You can create pure (referentially transparent) functions from impure functions.
Consider the skiplist. In order for it to work well it requires access to a RNG, an impure function, but this doesn't make the data structure impure. If you add an item and then convert it to a list, the same list will be returned every time given the item you add.
For this reason I think unsafePerformIO should be thought of as promisePureIO. A function that means that functions that have side-effects and therefore would be labelled impure by the type system can become acknowledged as referentially transparent by the type system.
I understand that you have to have a slightly weaker definition of pure for this to hold though. i.e pure functions are referentially transparent and never called because of a side-effect (like print).
Unfortunately the language has to do some real world work, and this implies talking with the external environment.
The good thing is that you can (and should) limit the usage of this "out of style" code to few specific well documented portions of your program.
I have a feeling I'll be very unpopular for saying what I'm about to say, but felt I had to respond to some of the (in my opinion mis-) information presented here.
Although it's true that unsafePerformIO was officially added to the language as part of the FFI addendum, the reasons for this are largely historical rather than logical. It existed unofficially and was widely used long before Haskell ever had an FFI. It was never officially part of the main Haskell standard because, as you have observed, it was just too much of an embarrassment. I guess the hope was that it would just go away at some point in the future, somehow. Well that hasn't happened, nor will it in my opinion.
The development of FFI addendum provided a convenient pretext for unsafePerformIO to get snuck in to the official language standard as it probably doesn't seem too bad here, when compared to adding the capability to call foreign (I.E. C) code (where all bets are off regarding statically ensuring purity and type safety anyway). It was also jolly convenient to put it here for what are essentially political reasons. It fostered the myth that Haskell would be pure, if only it wasn't for all that dirty "badly designed" C, or "badly designed" operating systems, or "badly designed" hardware or .. whatever.. It's certainly true that unsafePerformIO is regularly used with FFI related code, but the reasons for this are often more to do with bad design of the FFI and indeed of Haskell itself, not bad design of whatever foreign thing Haskell is trying interface too.
So as Norman Ramsey says, the official position came to be that it was OK to use unsafePerformIO provided certain proof obligations were satisfied by whoever used it (primarily that doing this doesn't invalidate important compiler transformations like inlining and common sub-expression elimination). So far so good, or so one might think. The real kicker is that these proof obligations cannot be satisfied by what is probably the single most common use case for unsafePerformIO, which by my estimate accounts for well over 50% of all the unsafePerformIOs out there in the wild. I'm talking about the appalling idiom known as the "unsafePerformIO hack" which is provably (in fact obviously) completely unsafe (in the presence of inlining and cse) .
I don't really have the time, space or inclination to go into what the "unsafePerformIO hack" is or why it's needed in real IO libraries, but the bottom line is that folk who work on Haskells IO infrastructure are usually "stuck between a rock and a hard place". They can either provide an inherently safe API which has no safe implementation (in Haskell), or they can provide an inherently unsafe API which can be safely implemented, but what they can rarely do is provide safety in both API design and implementation. Judging by the depressing regularity with which the "unsafePerformIO hack" appears in real world code (including the Haskell standard libraries), it seems most choose the former option as the lesser of the two evils, and just hope that the compiler won't muck things up with inlining, cse or any other transformation.
I do wish all this was not so. Unfortunately, it is.
Safe Haskell, a recent extension of GHC, gives a new answer to this question. unsafePerformIO is a part of GHC Haskell, but not a part of the safe dialect.
unsafePerformIO should be used only to build referentially transparent functions; for example, memoization. In these cases, the author of a package marks it as "trustworthy". A safe module can import only safe and trustworthy modules; it cannot import unsafe modules.
For more information: GHC manual, Safe Haskell paper
Haskell is generally referenced as an example of a purely functional language. How can this be justified given the existence of System.IO.Unsafe.unsafePerformIO ?
Edit: I thought with "purely functional" it was meant that it is impossible to introduce impure code into the functional part of the program.
The IO monad is actually defined in Haskell, and you can in fact see its definition here. This monad does not exist to deal with impurities but rather to handle side effects. In any case, you could actually pattern match your way out of the IO monad, so the existence of unsafePerformIO shouldn't really be troubling to you.

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