I'm a newbie Haskell programmer with imperative background.
I'm writing a program that parses an abstract syntax tree (or rather a graph) that has cycles. (This is actually GCC's Generic AST). I'm designing data types for representing this graph, but I'm facing difficulties:
Firstly, there are lots of nasty cycles in GCC AST. For example type declarations refer to the actual type descriptor which refers back to the type's declaration (and this declaration may sometimes be different from the original, sometimes it is just a reference to an identifier node). All tree nodes reference a so-called context node (a form of parent reference). However, this context node (for some node X) often is not the same as the node that originally referred to X. For example a declaration for some builtin function may be found from a C++ namespace node, but the function declaration's context points to a translation unit declaration. Perhpas this makes using zippers impossible? Also I can't just ignore these context nodes, because they are useful for finding out the scope of declarations.
So, when designing the data structure I should take into account the fact, that sometimes I don't know what kind of node I will be dealing with at run time. However, when I'm certain that a node will have a known type, I would like to be able to reflect this on type level and take advantage of static type checking (for example function's result type is always a type, not an integer constant, but it might be integer or pointer type, etc.).
Secondly, GCC tree is a hierarchical data type in object-oriented sense. All nodes have common information, such as what kind of node they are. All declarations have a name and many flags, and variable declarations have type information in addition. Many nodes have so much data that it would be incovenient to access this information through pattern matching only. So I most likely will be using accessor functions (and type classes to provide an uniform interface regardless of the node type).
Thirdly, I would like my graph to be purely functional, but I don't know how to build it. My input is text, which has a section for every node. Nodes are identified by unique ids, and there are lots of forward- and self-references.
So, with my background, I sense that I'm trying to force my Haskell interface to an imperative form. So I'm asking you for some concrete advice to guide me in designing my data types, their interface and how to build the graph.
So far I have decided that I will not be tying the knot. It would prevent me from doing transformations on the tree (which IMHO deserves some transformations). It also would make it hard to write this tree back to disc, if I want to do that some day.
EDIT:
Here is a sample of my input. It is in YAML, but the format is not yet set to stone (I'm generating this data my self from within GCC).
http://sange.fi/~aura/test.yaml The example contains the global namespace with one function declaration for (int main (int argc, char *argv[])).
Thanks in advance!
Related
For background, I'm working on a CSG (Constructive Solid Geometry) library.
Given polygon meshes that enclose regions of space, this library will allow those meshes to be treated as sets of the points that they enclose. And also allow the calculation of the binary operations, union, intersection and difference, on pairs of meshes.
The library will also support set negation.
If required I could also define an elem like function, with type Point -> Mesh -> Bool, it would not be possible to define an add function, as there exists no meaningful way to add a single point to a mesh.
Does a typeclass exist for types that support these operations?
And if not, what would a good implementation of a suitable typeclass look like?
Many people have tried making unifying typeclasses for container types, and none of them has ever caught on, each for its own reasons. I recommend not bothering; the current standard idiom is to just define the operations for your new type with some standardish names, not worrying about name clashes, with whatever type makes the most sense for your new container. Expect users to import your module qualified and aliased to avoid name clashes (and aid readers as a nice side effect).
I need to process multiple formats and versions for semantically equivalent data.
I can generate Haskell data types for each schema (XSD for example), they will be technically different, but semantically and structurally identical in many cases.
The data is complex, includes references, and service components must process whole graph and produce also similar response (a component might just update a field, but might need to analyze whole graph to collect all required information, might call other services as well).
How can I represent ns1:address and ns2:adress as one polymorphic type that has country and street elements and application needs process them as identical, but keeps serialization context for writing response in correct format (one representation might encode them in single string while other might carry also superfluous complex data)?
How close can I get to writing mostly code that defines semantic equivalence of data, business logic and generate all else? What features in Haskell language or libraries should I evaluate as building blocks for potential solution?
An option is to create a data type for each schema and create a function to map them to a common data type. Process it as you wish. You don't need to create polymorphic types.
This approach is similar to Pandoc's: you get a bunch of readers to parse documents to a common document structure, then use writers to convert that common structure to a particular format.
You just need the libraries to read your complex input data (and write it back, if necessary). The rest is functions and data types.
If you are really handling graphs, you can look at the Data.Graph module.
It sounds like this is a problems that is well served by the Type Class infrastructure, and the Lens library.
Use a Type Class to define a standard and consistent high-level interface to the various implementations. Make sure that you focus on the operations you wish to perform, not on the underlying implementation or process.
Use Lenses and Prisms to reach into the underlying datatypes and return answers to queries, and modify values "in-place", without resorting to full serialisation/de-serialisation.
I want to implement an AST in Haskell. I need a parent reference so it seems impossible to use a functional data structure. I've seen the following in an article. We define a node as:
type Tree = Node -> Node
Node allows us to get attribute by key of type Key a.
Is there anything to read about such a pattern? Could you give me some further links?
If you want a pure data structure with cyclic self-references, then as delnan says in the comments the usual term for that is "tying the knot". Searching for that term should give you more information.
Do note that data structures built by tying the knot are difficult (or impossible) to "update" in the usual manner--with a non-cyclic structure you can keep pieces of the original when building a new structure based on it, but changing any piece of a cycle requires you to rebuild the entire cycle as well. Depending on what you're doing, this may or may not be a problem, of course.
I know that memoization seems to be a perennial topic here on the haskell tag on stack overflow, but I think this question has not been asked before.
I'm aware of several different 'off the shelf' memoization libraries for Haskell:
The memo-combinators and memotrie packages, which make use of a beautiful trick involving lazy infinite data structures to achieve memoization in a purely functional way. (As I understand it, the former is slightly more flexible, while the latter is easier to use in simple cases: see this SO answer for discussion.)
The uglymemo package, which uses unsafePerformIO internally but still presents a referentially transparent interface. The use of unsafePerformIO internally results in better performance than the previous two packages. (Off the shelf, its implementation uses comparison-based search data structures, rather than perhaps-slightly-more-efficient hash functions; but I think that if you find and replace Cmp for Hashable and Data.Map for Data.HashMap and add the appropraite imports, you get a hash based version.)
However, I'm not aware of any library that looks answers up based on object identity rather than object value. This can be important, because sometimes the kinds of object which are being used as keys to your memo table (that is, as input to the function being memoized) can be large---so large that fully examining the object to determine whether you've seen it before is itself a slow operation. Slow, and also unnecessary, if you will be applying the memoized function again and again to an object which is stored at a given 'location in memory' 1. (This might happen, for example, if we're memoizing a function which is being called recursively over some large data structure with a lot of structural sharing.) If we've already computed our memoized function on that exact object before, we can already know the answer, even without looking at the object itself!
Implementing such a memoization library involves several subtle issues and doing it properly requires several special pieces of support from the language. Luckily, GHC provides all the special features that we need, and there is a paper by Peyton-Jones, Marlow and Elliott which basically worries about most of these issues for you, explaining how to build a solid implementation. They don't provide all details, but they get close.
The one detail which I can see which one probably ought to worry about, but which they don't worry about, is thread safety---their code is apparently not threadsafe at all.
My question is: does anyone know of a packaged library which does the kind of memoization discussed in the Peyton-Jones, Marlow and Elliott paper, filling in all the details (and preferably filling in proper thread-safety as well)?
Failing that, I guess I will have to code it up myself: does anyone have any ideas of other subtleties (beyond thread safety and the ones discussed in the paper) which the implementer of such a library would do well to bear in mind?
UPDATE
Following #luqui's suggestion below, here's a little more data on the exact problem I face. Let's suppose there's a type:
data Node = Node [Node] [Annotation]
This type can be used to represent a simple kind of rooted DAG in memory, where Nodes are DAG Nodes, the root is just a distinguished Node, and each node is annotated with some Annotations whose internal structure, I think, need not concern us (but if it matters, just ask and I'll be more specific.) If used in this way, note that there may well be significant structural sharing between Nodes in memory---there may be exponentially more paths which lead from the root to a node than there are nodes themselves. I am given a data structure of this form, from an external library with which I must interface; I cannot change the data type.
I have a function
myTransform : Node -> Node
the details of which need not concern us (or at least I think so; but again I can be more specific if needed). It maps nodes to nodes, examining the annotations of the node it is given, and the annotations its immediate children, to come up with a new Node with the same children but possibly different annotations. I wish to write a function
recursiveTransform : Node -> Node
whose output 'looks the same' as the data structure as you would get by doing:
recursiveTransform Node originalChildren annotations =
myTransform Node recursivelyTransformedChildren annotations
where
recursivelyTransformedChildren = map recursiveTransform originalChildren
except that it uses structural sharing in the obvious way so that it doesn't return an exponential data structure, but rather one on the order of the same size as its input.
I appreciate that this would all be easier if say, the Nodes were numbered before I got them, or I could otherwise change the definition of a Node. I can't (easily) do either of these things.
I am also interested in the general question of the existence of a library implementing the functionality I mention quite independently of the particular concrete problem I face right now: I feel like I've had to work around this kind of issue on a few occasions, and it would be nice to slay the dragon once and for all. The fact that SPJ et al felt that it was worth adding not one but three features to GHC to support the existence of libraries of this form suggests that the feature is genuinely useful and can't be worked around in all cases. (BUT I'd still also be very interested in hearing about workarounds which will help in this particular case too: the long term problem is not as urgent as the problem I face right now :-) )
1 Technically, I don't quite mean location in memory, since the garbage collector sometimes moves objects around a bit---what I really mean is 'object identity'. But we can think of this as being roughly the same as our intuitive idea of location in memory.
If you only want to memoize based on object identity, and not equality, you can just use the existing laziness mechanisms built into the language.
For example, if you have a data structure like this
data Foo = Foo { ... }
expensive :: Foo -> Bar
then you can just add the value to be memoized as an extra field and let the laziness take care of the rest for you.
data Foo = Foo { ..., memo :: Bar }
To make it easier to use, add a smart constructor to tie the knot.
makeFoo ... = let foo = Foo { ..., memo = expensive foo } in foo
Though this is somewhat less elegant than using a library, and requires modification of the data type to really be useful, it's a very simple technique and all thread-safety issues are already taken care of for you.
It seems that stable-memo would be just what you needed (although I'm not sure if it can handle multiple threads):
Whereas most memo combinators memoize based on equality, stable-memo does it based on whether the exact same argument has been passed to the function before (that is, is the same argument in memory).
stable-memo only evaluates keys to WHNF.
This can be more suitable for recursive functions over graphs with cycles.
stable-memo doesn't retain the keys it has seen so far, which allows them to be garbage collected if they will no longer be used. Finalizers are put in place to remove the corresponding entries from the memo table if this happens.
Data.StableMemo.Weak provides an alternative set of combinators that also avoid retaining the results of the function, only reusing results if they have not yet been garbage collected.
There is no type class constraint on the function's argument.
stable-memo will not work for arguments which happen to have the same value but are not the same heap object. This rules out many candidates for memoization, such as the most common example, the naive Fibonacci implementation whose domain is machine Ints; it can still be made to work for some domains, though, such as the lazy naturals.
Ekmett just uploaded a library that handles this and more (produced at HacPhi): http://hackage.haskell.org/package/intern. He assures me that it is thread safe.
Edit: Actually, strictly speaking I realize this does something rather different. But I think you can use it for your purposes. It's really more of a stringtable-atom type interning library that works over arbitrary data structures (including recursive ones). It uses WeakPtrs internally to maintain the table. However, it uses Ints to index the values to avoid structural equality checks, which means packing them into the data type, when what you want are apparently actually StableNames. So I realize this answers a related question, but requires modifying your data type, which you want to avoid...
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.