I'd like to see if it is feasible to have a type class for converting one thing into another and back again from a mapping of [(a,b)].
This example should illustrate what I'd like to do:
data XX = One | Two | Three deriving (Show, Eq)
data YY = Eno | Owt | Eerht deriving (Show, Eq)
instance Convert XX YY where
mapping = [(One, Eno), (Two, Owt), (Three, Eerht)]
-- // How can I make this work?:
main = do print $ (convert One :: YY) -- Want to output: Eno
print $ (convert Owt :: XX) -- Want to output: Two
Here's my stab at making this work:
{-# LANGUAGE MultiParamTypeClasses #-}
import Data.Maybe(fromJust)
lk = flip lookup
flipPair = uncurry $ flip (,)
class (Eq a, Eq b) => Convert a b where
mapping :: [(a, b)]
mapping = error "No mapping defined"
convert :: a -> b
convert = fromJust . lk mapping
-- // This won't work:
instance (Convert a b) => Convert b a where
convert = fromJust . lk (map flipPair mapping)
It is easy to do this with defining two instances for the conversion going either way but I'd like to only have to declare one as in the first example. Any idea how I might do this?
Edit: By feasible I mean, can this be done without overlapping instances any other nasty extensions?
I, er... I almost hate to suggest this, because doing this is kinda horrible, but... doesn't your code work as is?
{-# LANGUAGE MultiParamTypeClasses #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE UndecidableInstances #-}
{-# LANGUAGE OverlappingInstances #-}
import Data.Maybe(fromJust)
lk x = flip lookup x
flipPair = uncurry $ flip (,)
class (Eq a, Eq b) => Convert a b where
mapping :: [(a, b)]
mapping = error "No mapping defined"
convert :: a -> b
convert = fromJust . lk mapping
instance (Convert a b) => Convert b a where
convert = fromJust . lk (map flipPair mapping)
data XX = One | Two | Three deriving (Show, Eq)
data YY = Eno | Owt | Eerht deriving (Show, Eq)
instance Convert XX YY where
mapping = [(One, Eno), (Two, Owt), (Three, Eerht)]
main = do print $ (convert One :: YY)
print $ (convert Owt :: XX)
And:
[1 of 1] Compiling Main ( GeneralConversion.hs, interpreted )
Ok, modules loaded: Main.
*Main> main
Eno
Two
*Main>
I'm not sure how useful such a type class is, and all the standard disclaimers about dubious extensions apply, but that much seems to work. Now, if you want to do anything fancier... like Convert a a or (Convert a b, Convert b c) => Convert a c... things might get awkward.
I suppose I might as well leave a few thoughts about why I doubt the utility of this:
In order to use the conversion, both types must be unambiguously known; likewise, the existence of a conversion depends on both types. This limits how useful the class can be for writing very generic code, compared to things such as fromIntegral.
The use of error to handle missing conversions, combined with the above, means that any allegedly generic function using convert will be a seething pit of runtime errors just waiting to happen.
To top it all off, the generic instance being used for the reversed mapping is in fact a universal instance, only being hidden by overlapped, more specific instances. That (Convert a b) in the context? That lets the reversed mapping work, but doesn't restrict it to only reversing instances that are specifically defined.
Related
I am using data-reify and graphviz to transform an eDSL into a nice graphical representation, for introspection purposes.
As simple, contrived example, consider:
{-# LANGUAGE GADTs #-}
data Expr a where
Constant :: a -> Expr a
Map :: (other -> a) -> Expr a -> Expr a
Apply :: Expr (other -> a) -> Expr a -> Expr a
instance Functor Expr where
fmap fun val = Map fun val
instance Applicative Expr where
fun_expr <*> data_expr = Apply fun_expr data_expr
pure val = Constant val
-- And then some functions to optimize an Expr AST, evaluate Exprs, etc.
To make introspection nicer, I would like to print the values which are stored inside certain AST nodes of the DSL datatype.
However, in general any a might be stored in Constant, even those that do not implement Show. This is not necessarily a problem since we can constrain the instance of Expr like so:
instance Show a => Show (Expr a) where
...
This is not what I want however: I would still like to be able to print Expr even if a is not Show-able, by printing some placeholder value (such as just its type and a message that it is unprintable) instead.
So we want to do one thing if we have an a implementing Show, and another if a particular a does not.
Furthermore, the DSL also has the constructors Map and Apply which are even more problematic. The constructor is existential in other, and thus we cannot assume anything about other, a or (other -> a). Adding constraints to the type of other to the Map resp. Apply constructors would break the implementation of Functor resp. Applicative which forwards to them.
But here also I'd like to print for the functions:
a unique reference. This is always possible (even though it is not pretty as it requires unsafePerformIO) using System.Mem.StableName.
Its type, if possible (one technique is to use show (typeOf fun), but it requires that fun is Typeable).
Again we reach the issue where we want to do one thing if we have an f implementing Typeable and another if f does not.
How to do this?
Extra disclaimer: The goal here is not to create 'correct' Show instances for types that do not support it. There is no aspiration to be able to Read them later, or that print a != print b implies a != b.
The goal is to print any datastructure in a 'nice for human introspection' way.
The part I am stuck at, is that I want to use one implementation if extra constraints are holding for a resp. (other -> a), but a 'default' one if these do not exist.
Maybe type classes with FlexibleInstances, or maybe type families are needed here? I have not been able to figure it out (and maybe I am on the wrong track all together).
Not all problems have solutions. Not all constraint systems have a satisfying assignment.
So... relax the constraints. Store the data you need to make a sensible introspective function in your data structure, and use functions with type signatures like show, fmap, pure, and (<*>), but not exactly equal to them. If you need IO, use IO in your type signature. In short: free yourself from the expectation that your exceptional needs fit into the standard library.
To deal with things where you may either have an instance or not, store data saying whether you have an instance or not:
data InstanceOrNot c where
Instance :: c => InstanceOrNot c
Not :: InstanceOrNot c
(Perhaps a Constraint-kinded Either-alike, rather than Maybe-alike, would be more appropriate. I suspect as you start coding this you will discover what's needed.) Demand that clients that call notFmap and friends supply these as appropriate.
In the comments, I propose parameterizing your type by the constraints you demand, and giving a Functor instance for the no-constraints version. Here's a short example showing how that might look:
{-# LANGUAGE GADTs #-}
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE TypeOperators #-}
{-# LANGUAGE TypeFamilies #-}
{-# LANGUAGE FlexibleInstances #-}
import Data.Kind
type family All cs a :: Constraint where
All '[] a = ()
All (c:cs) a = (c a, All cs a)
data Lol cs a where
Leaf :: a -> Lol cs a
Fmap :: All cs b => (a -> b) -> Lol cs a -> Lol cs b
instance Functor (Lol '[]) where
fmap f (Leaf a) = Leaf (f a)
fmap f (Fmap g garg) = Fmap (f . g) garg
Great timing! Well-typed recently released a library which allows you to recover runtime information. They specifically have an example of showing arbitrary values. It's on github at https://github.com/well-typed/recover-rtti.
It turns out that this is a problem which has been recognized by multiple people in the past, known as the 'Constrained Monad Problem'. There is an elegant solution, explained in detail in the paper The Constrained-Monad Problem by Neil Sculthorpe and Jan Bracker and George Giorgidze and Andy Gill.
A brief summary of the technique: Monads (and other typeclasses) have a 'normal form'. We can 'lift' primitives (which are constrained any way we wish) into this 'normal form' construction, itself an existential datatype, and then use any of the operations available for the typeclass we have lifted into. These operations themselves are not constrained, and thus we can use all of Haskell's normal typeclass functions.
Finally, to turn this back into the concrete type (which again has all the constraints we are interested in) we 'lower' it, which is an operation that takes for each of the typeclass' operations a function which it will apply at the appropriate time.
This way, constraints from the outside (which are part of the functions supplied to the lowering) and constraints from the inside (which are part of the primitives we lifted) are able to be matched, and finally we end up with one big happy constrained datatype for which we have been able to use any of the normal Functor/Monoid/Monad/etc. operations.
Interestingly, while the intermediate operations are not constrained, to my knowledge it is impossible to write something which 'breaks' them as this would break the categorical laws that the typeclass under consideration should adhere to.
This is available in the constrained-normal Hackage package to use in your own code.
The example I struggled with, could be implemented as follows:
{-# LANGUAGE GADTs #-}
{-# LANGUAGE DataKinds #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE ScopedTypeVariables #-}
{-# LANGUAGE MultiParamTypeClasses #-}
{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE StandaloneDeriving #-}
{-# LANGUAGE ConstraintKinds #-}
{-# LANGUAGE KindSignatures #-}
{-# LANGUAGE UndecidableInstances #-}
module Example where
import Data.Dynamic
import Data.Kind
import Data.Typeable
import Control.Monad.ConstrainedNormal
-- | Required to have a simple constraint which we can use as argument to `Expr` / `Expr'`.
-- | This is definitely the part of the example with the roughest edges: I have yet to figure out
-- | how to make Haskell happy with constraints
class (Show a, Typeable a) => Introspectable a where {}
instance (Show a, Typeable a) => Introspectable a where {}
data Expr' (c :: * -> Constraint) a where
C :: a -> Expr' c a
-- M :: (a -> b) -> Expr' a -> Expr' b --^ NOTE: This one is actually never used as ConstrainedNormal will use the 'free' implementation based on A + C.
A :: c a => Expr' c (a -> b) -> Expr' c a -> Expr' c b
instance Introspectable a => Show (Expr' Introspectable a) where
show e = case e of
C x -> "(C " ++ show x ++ ")"
-- M f x = "(M " ++ show val ++ ")"
A fx x -> "(A " ++ show (typeOf fx) ++ " " ++ show x ++ ")"
-- | In user-facing code you'd not want to expose the guts of this construction
-- So let's introduce a 'wrapper type' which is what a user would normally interact with.
type Expr c a = NAF c (Expr' c) a
liftExpr :: c a => Expr' c a -> Expr c a
liftExpr expr = liftNAF expr
lowerExpr :: c a => Expr c a -> Expr' c a
lowerExpr lifted_expr = lowerNAF C A lifted_expr
constant :: Introspectable a => a -> Expr c a
constant val = pure val -- liftExpr (C val)
You could now for instance write
ghci> val = constant 10 :: Expr Introspectable Int
(C 10)
ghci> (+2) <$> val
(C 12)
ghci> (+) <$> constant 10 <*> constant 32 :: Expr Introspectable Int
And by using Data.Constraint.Trivial (part of the trivial-constrained library, although it is also possible to write your own 'empty constrained') one could instead write e.g.
ghci> val = constant 10 :: Expr Unconstrained Int
which will work just as before, but now val cannot be printed.
The one thing I have not yet figured out, is how to properly work with subsets of constraints (i.e. if I have a function that only requires Show, make it work with something that is Introspectable). Currently everything has to work with the 'big' set of constraints.
Another minor drawback is of course that you'll have to annotate the constraint type (e.g. if you do not want constraints, write Unconstrained manually), as GHC will otherwise complain that c0 is not known.
We've reached the goal of having a type which can be optionally be constrained to be printable, with all machinery that does not need printing to work also on all instances of the family of types including those that are not printable, and the types can be used as Monoids, Functors, Applicatives, etc just as you like.
I think it is a beautiful approach, and want to commend Neil Sculthorpe et al. for their work on the paper and the constrained-normal library that makes this possible. It's very cool!
Let us say I want to make a ADT as follows in Haskell:
data Properties = Property String [String]
deriving (Show,Eq)
I want to know if it is possible to give the second list a bounded and enumerated property? Basically the first element of the list will be the minBound and the last element will be the maxBound. I am trying,
data Properties a = Property String [a]
deriving (Show, Eq)
instance Bounded (Properties a) where
minBound a = head a
maxBound a = (head . reverse) a
But not having much luck.
Well no, you can't do quite what you're asking, but maybe you'll find inspiration in this other neat trick.
{-# language ScopedTypeVariables, FlexibleContexts, UndecidableInstances #-}
import Data.Reflection -- from the reflection package
import qualified Data.List.NonEmpty as NE
import Data.List.NonEmpty (NonEmpty (..))
import Data.Proxy
-- Just the plain string part
newtype Pstring p = P String deriving Eq
-- Those properties you're interested in. It will
-- only be possible to produce bounds if there's at
-- least one property, so NonEmpty makes more sense
-- than [].
type Props = NonEmpty String
-- This is just to make a Show instance that does
-- what you seem to want easier to write. It's not really
-- necessary.
data Properties = Property String [String] deriving Show
Now we get to the key part, where we use reflection to produce class instances that can depend on run-time values. Roughly speaking, you can think of
Reifies x t => ...
as being a class-level version of
\(x :: t) -> ...
Because it operates at the class level, you can use it to parametrize instances. Since Reifies x t binds a type variable x, rather than a term variable, you need to use reflect to actually get the value back. If you happen to have a value on hand whose type ends in p, then you can just apply reflect to that value. Otherwise, you can always magic up a Proxy :: Proxy p to do the job.
-- If some Props are "in the air" tied to the type p,
-- then we can show them along with the string.
instance Reifies p Props => Show (Pstring p) where
showsPrec k p#(P str) =
showsPrec k $ Property str (NE.toList $ reflect p)
-- If some Props are "in the air" tied to the type p,
-- then we can give Pstring p a Bounded instance.
instance Reifies p Props => Bounded (Pstring p) where
minBound = P $ NE.head (reflect (Proxy :: Proxy p))
maxBound = P $ NE.last (reflect (Proxy :: Proxy p))
Now we need to have a way to actually bind types that can be passed to the type-level lambdas. This is done using the reify function. So let's throw some Props into the air and then let the butterfly nets get them back.
main :: IO ()
main = reify ("Hi" :| ["how", "are", "you"]) $
\(_ :: Proxy p) -> do
print (minBound :: Pstring p)
print (maxBound :: Pstring p)
./dfeuer#squirrel:~/src> ./WeirdBounded
Property "Hi" ["Hi","how","are","you"]
Property "you" ["Hi","how","are","you"]
You can think of reify x $ \(p :: Proxy p) -> ... as binding a type p to the value x; you can then pass the type p where you like by constraining things to have types involving p.
If you're just doing a couple of things, all this machinery is way more than necessary. Where it gets nice is when you're performing lots of operations with values that have phantom types carrying extra information. In many cases, you can avoid most of the explicit applications of reflect and the explicit proxy handling, because type inference just takes care of it all for you. For a good example of this technique in action, see the hyperloglog package. Configuration information for the HyperLogLog data structure is carried in a type parameter; this guarantees, at compile time, that only similarly configured structures are merged with each other.
Replacing fields names with letters, I have cases like this:
data Foo = Foo { a :: Maybe ...
, b :: [...]
, c :: Maybe ...
, ... for a lot more fields ...
} deriving (Show, Eq, Ord)
instance Writer Foo where
write x = maybeWrite a ++
listWrite b ++
maybeWrite c ++
... for a lot more fields ...
parser = permute (Foo
<$?> (Nothing, Just `liftM` aParser)
<|?> ([], bParser)
<|?> (Nothing, Just `liftM` cParser)
... for a lot more fields ...
-- this is particularly hideous
foldl1 merge [foo1, foo2, ...]
merge (Foo a b c ...seriously a lot more...)
(Foo a' b' c' ...) =
Foo (max a a') (b ++ b') (max c c') ...
What techniques would allow me to better manage this growth?
In a perfect world a, b, and c would all be the same type so I could keep them in a list, but they can be many different types. I'm particularly interested in any way to fold the records without needing the massive patterns.
I'm using this large record to hold the different types resulting from permutation parsing the vCard format.
Update
I've implemented both the generics and the foldl approaches suggested below. They both work, and they both reduce three large field lists to one.
Datatype-generic programming techniques can be used to transform all the fields of a record in some "uniform" sort of way.
Perhaps all the fields in the record implement some typeclass that we want to use (the typical example is Show). Or perhaps we have another record of "similar" shape that contains functions, and we want to apply each function to the corresponding field of the original record.
For these kinds of uses, the generics-sop library is a good option. It expands the default Generics functionality of GHC with extra type-level machinery that provides analogues of functions like sequence or ap, but which work over all the fields of a record.
Using generics-sop, I tried to create a slightly less verbose version of your merge funtion. Some preliminary imports:
{-# language TypeOperators #-}
{-# language DeriveGeneric #-}
{-# language TypeFamilies #-}
{-# language DataKinds #-}
import Control.Applicative (liftA2)
import qualified GHC.Generics as GHC
import Generics.SOP
A helper function that lifts a binary operation to a form useable by the functions of generics-sop:
fn_2' :: (a -> a -> a) -> (I -.-> (I -.-> I)) a -- I is simply an Identity functor
fn_2' = fn_2 . liftA2
A general merge function that takes a vector of operators and works on any single-constructor record that derives Generic:
merge :: (Generic a, Code a ~ '[ xs ]) => NP (I -.-> (I -.-> I)) xs -> a -> a -> a
merge funcs reg1 reg2 =
case (from reg1, from reg2) of
(SOP (Z np1), SOP (Z np2)) ->
let npResult = funcs `hap` np1 `hap` np2
in to (SOP (Z npResult))
Code is a type family that returns a type-level list of lists describing the structure of a datatype. The outer list is for constructors, the inner lists contain the types of the fields for each constructor.
The Code a ~ '[ xs ] part of the constraint says "the datatype can only have one constructor" by requiring the outer list to have exactly one element.
The (SOP (Z _) pattern matches extract the (heterogeneus) vector of field values from the record's generic representation. SOP stands for "sum-of-products".
A concrete example:
data Person = Person
{
name :: String
, age :: Int
} deriving (Show,GHC.Generic)
instance Generic Person -- this Generic is from generics-sop
mergePerson :: Person -> Person -> Person
mergePerson = merge (fn_2' (++) :* fn_2' (+) :* Nil)
The Nil and :* constructors are used to build the vector of operators (the type is called NP, from n-ary product). If the vector doesn't match the number of fields in the record, the program won't compile.
Update. Given that the types in your record are highly uniform, an alternative way of creating the vector of operations is to define instances of an auxiliary typeclass for each field type, and then use the hcpure function:
class Mergeable a where
mergeFunc :: a -> a -> a
instance Mergeable String where
mergeFunc = (++)
instance Mergeable Int where
mergeFunc = (+)
mergePerson :: Person -> Person -> Person
mergePerson = merge (hcpure (Proxy :: Proxy Mergeable) (fn_2' mergeFunc))
The hcliftA2 function (that combines hcpure, fn_2 and hap) could be used to simplify things further.
Some suggestions:
(1) You can use the RecordWildCards extension to automatically
unpack a record into variables. Doesn't help if you need to unpack
two records of the same type, but it's a useful to keep in mind.
Oliver Charles has a nice blog post on it: (link)
(2) It appears your example application is performing a fold over the records.
Have a look at Gabriel Gonzalez's foldl package. There is also a blog post: (link)
Here is a example of how you might use it with a record like:
data Foo = Foo { _a :: Int, _b :: String }
The following code computes the maximum of the _a fields and the
concatenation of the _b_ fields.
import qualified Control.Foldl as L
import Data.Profunctor
data Foo = Foo { _a :: Int, _b :: String }
deriving (Show)
fold_a :: L.Fold Foo Int
fold_a = lmap _a (L.Fold max 0 id)
fold_b :: L.Fold Foo String
fold_b = lmap _b (L.Fold (++) "" id)
fold_foos :: L.Fold Foo Foo
fold_foos = Foo <$> fold_a <*> fold_b
theFoos = [ Foo 1 "a", Foo 3 "b", Foo 2 "c" ]
test = L.fold fold_foos theFoos
Note the use of the Profunctor function lmap to extract out
the fields we want to fold over. The expression:
L.Fold max 0 id
is a fold over a list of Ints (or any Num instance), and therefore:
lmap _a (L.Fold max 0 id)
is the same fold but over a list of Foo records where we use _a
to produce the Ints.
Say I have a data type like so:
data NumCol = Empty |
Single Int |
Pair Int Int |
Lots [Int]
Now I wish to filter out the elements matching a given constructor from a [NumCol]. I can write it for, say, Pair:
get_pairs :: [NumCol] -> [NumCol]
get_pairs = filter is_pair
where is_pair (Pair _ _) = True
is_pair _ = False
This works, but it's not generic. I have to write a separate function for is_single, is_lots, etc.
I wish instead I could write:
get_pairs = filter (== Pair)
But this only works for type constructors that take no arguments (i.e. Empty).
So the question is, how can I write a function that takes a value and a constructor, and returns whether the value matches the constructor?
At least get_pairs itself can be defined relatively simply by using a list comprehension to filter instead:
get_pairs xs = [x | x#Pair {} <- xs]
For a more general solution of matching constructors, you can use prisms from the lens package:
{-# LANGUAGE TemplateHaskell #-}
import Control.Lens
import Control.Lens.Extras (is)
data NumCol = Empty |
Single Int |
Pair Int Int |
Lots [Int]
-- Uses Template Haskell to create the Prisms _Empty, _Single, _Pair and _Lots
-- corresponding to your constructors
makePrisms ''NumCol
get_pairs :: [NumCol] -> [NumCol]
get_pairs = filter (is _Pair)
Tags of tagged unions ought to be first-class values, and with a wee bit of effort, they are.
Jiggery-pokery alert:
{-# LANGUAGE GADTs, DataKinds, KindSignatures,
TypeFamilies, PolyKinds, FlexibleInstances,
PatternSynonyms
#-}
Step one: define type-level versions of the tags.
data TagType = EmptyTag | SingleTag | PairTag | LotsTag
Step two: define value-level witnesses for the representability of the type-level tags. Richard Eisenberg's Singletons library will do this for you. I mean something like this:
data Tag :: TagType -> * where
EmptyT :: Tag EmptyTag
SingleT :: Tag SingleTag
PairT :: Tag PairTag
LotsT :: Tag LotsTag
And now we can say what stuff we expect to find associated with a given tag.
type family Stuff (t :: TagType) :: * where
Stuff EmptyTag = ()
Stuff SingleTag = Int
Stuff PairTag = (Int, Int)
Stuff LotsTag = [Int]
So we can refactor the type you first thought of
data NumCol :: * where
(:&) :: Tag t -> Stuff t -> NumCol
and use PatternSynonyms to recover the behaviour you had in mind:
pattern Empty = EmptyT :& ()
pattern Single i = SingleT :& i
pattern Pair i j = PairT :& (i, j)
pattern Lots is = LotsT :& is
So what's happened is that each constructor for NumCol has turned into a tag indexed by the kind of tag it's for. That is, constructor tags now live separately from the rest of the data, synchronized by a common index which ensures that the stuff associated with a tag matches the tag itself.
But we can talk about tags alone.
data Ex :: (k -> *) -> * where -- wish I could say newtype here
Witness :: p x -> Ex p
Now, Ex Tag, is the type of "runtime tags with a type level counterpart". It has an Eq instance
instance Eq (Ex Tag) where
Witness EmptyT == Witness EmptyT = True
Witness SingleT == Witness SingleT = True
Witness PairT == Witness PairT = True
Witness LotsT == Witness LotsT = True
_ == _ = False
Moreover, we can easily extract the tag of a NumCol.
numColTag :: NumCol -> Ex Tag
numColTag (n :& _) = Witness n
And that allows us to match your specification.
filter ((Witness PairT ==) . numColTag) :: [NumCol] -> [NumCol]
Which raises the question of whether your specification is actually what you need. The point is that detecting a tag entitles you an expectation of that tag's stuff. The output type [NumCol] doesn't do justice to the fact that you know you have just the pairs.
How might you tighten the type of your function and still deliver it?
One approach is to use DataTypeable and the Data.Data module. This approach relies on two autogenerated typeclass instances that carry metadata about the type for you: Typeable and Data. You can derive them with {-# LANGUAGE DeriveDataTypeable #-}:
data NumCol = Empty |
Single Int |
Pair Int Int |
Lots [Int] deriving (Typeable, Data)
Now we have a toConstr function which, given a value, gives us a representation of its constructor:
toConstr :: Data a => a -> Constr
This makes it easy to compare two terms just by their constructors. The only remaining problem is that we need a value to compare against when we define our predicate! We can always just create a dummy value with undefined, but that's a bit ugly:
is_pair x = toConstr x == toConstr (Pair undefined undefined)
So the final thing we'll do is define a handy little class that automates this. The basic idea is to call toConstr on non-function values and recurse on any functions by first passing in undefined.
class Constrable a where
constr :: a -> Constr
instance Data a => Constrable a where
constr = toConstr
instance Constrable a => Constrable (b -> a) where
constr f = constr (f undefined)
This relies on FlexibleInstance, OverlappingInstances and UndecidableInstances, so it might be a bit evil, but, using the (in)famous eyeball theorem, it should be fine. Unless you add more instances or try to use it with something that isn't a constructor. Then it might blow up. Violently. No promises.
Finally, with the evil neatly contained, we can write an "equal by constructor" operator:
(=|=) :: (Data a, Constrable b) => a -> b -> Bool
e =|= c = toConstr e == constr c
(The =|= operator is a bit of a mnemonic, because constructors are syntactically defined with a |.)
Now you can write almost exactly what you wanted!
filter (=|= Pair)
Also, maybe you'd want to turn off the monomorphism restriction. In fact, here's the list of extensions I enabled that you can just use:
{-# LANGUAGE DeriveDataTypeable, FlexibleInstances, NoMonomorphismRestriction, OverlappingInstances, UndecidableInstances #-}
Yeah, it's a lot. But that's what I'm willing to sacrifice for the cause. Of not writing extra undefineds.
Honestly, if you don't mind relying on lens (but boy is that dependency a doozy), you should just go with the prism approach. The only thing to recommend mine is that you get to use the amusingly named Data.Data.Data class.
I want a newline-separated representation instead of the usual comma separated one, for may new data tyepe:
newtype SimpleRecord = SimpleRecord ([Char], [Char], Integer)
deriving (Show)
I tried to write this istance of Show class :
instance Show [SimpleRecord] where
show [(SimpleRecord (n, i, c))] = show (SimpleRecord (n, i, c))++['\n']
show (l:ls) = (show l)++['\n']++(show ls)
GHC heavily insults me.
Can someone try to explain me what can I do?
First, the Show class is supposed to be for producing Haskell source code, which the Read class can then read back in. It isn't supposed to be for producing human-readable, "pretty" output.
Having just said that, almost everyone misuses it for the latter, and it can be helpful for debugging purposes.
So, your options are:
Write some function not called show which does what you want. (As per AndrewC's comment.)
Use the showList method.
If you write deriving Show, this tells the compiler to write all the Show methods for you. If you want to write them yourself, you need to take away the deriving bit first. Then you can write your instance, which is going to look something like
instance Show SimpleRecord where
show (SimpleRecord (x, y, z)) = ...
showList rs = unlines (map show rs)
As an aside, if you didn't already know this, you can write
mapM_ print records
at the GHCi prompt to print out any list of printable things with one element per line.
As a final asside, why
newtype SimpleRecord = SimpleRecord ([Char], [Char], Integer)
rather than
data SimpleRecord = SimpleRecord [Char] [Char] Integer
Your question is quite ambiguos. If I interpret correctly you are trying to change the default Show instance for [SimpleRecord].
As GHC has already defined the instance Show [a] when Show a is defined. You get following error (after including FlexibleInstances extension) when you try to again define instance for Show [SimpleRecord].
Matching instances:
instance Show a => Show [a] -- Defined in `GHC.Show'
instance Show [SimpleRecord] -- Defined at show.hs:5:11
So you need to use OverlappingInstances language extension to allow overloading it.
It states GHC to match the most specific instance.
You might also want to include FlexibleInstances extension, which allows to mention arbitrary nested types in instance declaration..
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE OverlappingInstances #-}
newtype SimpleRecord = SimpleRecord ([Char], [Char], Integer)
deriving (Show)
instance Show [SimpleRecord] where
show [SimpleRecord (n, i, c)] = show (SimpleRecord (n, i, c))++"\n"
show (l:ls) = show l ++ "\n" ++ show ls
You get get more information about these language extensions at GHC Docs
Just a comment on design of your type, It is better to define your type as
data SimpleRecord = SimpleRecord String String Integer
You get more flexibility here in terms of partial constructor application etc.
I might have been missing something, but it wasn't clear why you were newtyping (String,String,Integer) rather than what you were concerned to show nicely, namely lists of them. Then you would evade the universal Show instance for lists:
newtype SimpleRecords = SimpleRecords [(String, String, Integer)]
instance Show SimpleRecords where
show (SimpleRecords []) = ""
show (SimpleRecords ((n, i, c): xs)) =
show (n, i, c) ++ "\n" ++ show (SimpleRecords xs)
-- Prelude Main> let a = words "We hold these truths to be self-evident"
-- Prelude Main> let b = words "All the best people are using Clorox"
-- Prelude Main> let c = zip3 a b [1::Integer ..]
-- Prelude Main> SimpleRecords c
-- ("We","All",1)
-- ("hold","the",2)
-- ("these","best",3)
-- ("truths","people",4)
-- ("to","are",5)
-- ("be","using",6)
-- ("self-evident","Clorox",7)