Readings

Recap

  • Engineering: haskell provides better factorization. Better refers to:
    1. The effect of local modification is predictable.
    2. Business requirement (Functionality) could be organized or analysed by manipulating meaningful type description.
  • An application can be factorized into two parts:
    1. A Computational Chain that is also a type transformation that focus on Target types from a -> b -> c -> d -> ... -> z.
    2. This computational chain constantly switch among different Computational Contexts, T1 to T2 to T2 ...

Parametric Types

Every piece of information matters in its own way.

  1. Type Constructor defines global representation of a type.
  2. Value/Data Constructor defines local representation of a type

  3. Type Constructor may has

    • Zero argument (a):
      • global representation represents the collections of local representations
      • local representation carries all information of this type. For Pattern Match.
      • eg: data Bool = True | False
      • global representation is Bool.
      • local representations are True & False.
    • One argument (T a):
      • global representation represents the collection of local representations
      • a : represents the Target Type.
      • T : represents the Computational Context / Context Type.
      • local representation carries all information of this type. For Pattern Match.
      • eg: data Maybe a = Just a | Nothing
      • global representation is Maybe a.
        • a is the Target Type
        • Computational Context is Maybe
      • local representations are Just a & Nothing.

    • More than one argument (T a b):

      • global representation represents the collection of local representations
      • a : represents the Target Type.
      • b : represents the Target Type.
      • T : represents the Computational Context / Context Type.
      • local representation carries all information of this type. For Pattern Match.
      • eg: data Either a b = Left a | Right b
      • global representation is Either a b.
        • a is the Target Type
        • b is the Target Type
        • Computational Context is Either

      • local representations are Left a & Right b.

        Example:

data Tree a = Tip | Node a (Tree a) (Tree a)

    • Global Representation (Type constructor): Tree a

    • Local Representation (Value constructor): Tip | Node a (Tree a) ( Tree a)

    • Target Type : 'a' in global representation.

    • Computational Context/Context type : 'Tree' in global representation.

For convenient - Value Constructor == Data Constructor - Computational Context == Context Type

. One Target Type at A Time

Thanks to the Currying , Type Constructor could be parametrized. Usually, and in this doc, the computational chain (function composition) focus on the transform of target types. Each computation focus on One target type at a time.

For Parametric types with More than One parameters, we focus on the rightmost one : > eg: b in data Either a b = Left a | Right b

  • Target Type : Carries type of information we care about. So reasoning behaviour of the target computational chain would be easy.

  • Context Type: This extra piece of information is a wrapper of the target information a. It could be used to

    1. Represent how target information being organized( data structure)
    2. How target function will be affected in evaluation process(Applicative,Monad, ect details below)
    3. Wrap existing type for specific purpose. This context is also a global representation of this newly defined type.

  • Different Context Type indicates different data structure based on a. ( when Target Type be the same a)

    Example:
    
data Tree a = Tip | Node a (Tree a) (Tree a)
data List a = Nil | Cons a (List a)

  • Being the instance of different typeclasses, one Context Type could carries different semantics, indicating how computational chain of the target type will be affected in certain way. (This is what this doc all about)

    example:

    • functor + Writer ==> Writer is a container in this case.

    • Monad + Writer ==> Writer is a computational context relies on Monoid type to accumulate( mappend) some extra logging information w.

      mapWriterT :: (m (a, w) -> n (b, w')) -> WriterT w m a -> WriterT w' n b
mapWriterT f m = WriterT $ f (runWriterT m)

instance (Functor m) => Functor (WriterT w m) where
fmap f = mapWriterT $ fmap $ \ ~(a, w) -> (f a, w)
  
instance (Monoid w, Monad m) => Monad (WriterT w m) where
return a = writer (a, mempty)
m >>= k  = WriterT $ do
~(a, w)  <- runWriterT m
~(b, w') <- runWriterT (k a)
return (b, w `mappend` w')

  • Context Type as a wrapper of existing type could be used for specific purpose and avoiding being ambiguous.

    example:

    (,) and Writer are equal up to isomorphism.

        > type P = forall a. ((,)a)
    > :info P
    type P = forall a. (,) a :: * -> *

      newtype Writer m a = Writer {runWriter :: (a , w)}

    They contain equal amount of information. The Writer part in newtype Writer is being used to identify possible different instance of the same typeclass.

    example:

    instance Monoid a => Applicative ((,) a) where
  pure x = (mempty, x)
  (u, f) <*> (v, x) = (u <> v, f x)
  liftA2 f (u, x) (v, y) = (u <> v, f x y)

instance (Monoid w) => Applicative (Writer w ) where
  pure a  = Writer $ (a, empty)
  f <*> v = Writer $ k f v
        where k (a, w) (b, w') = (a b, w `append` w')

    Both being instance of Applicative with same context semantics, (,) relies on the first element of being Monoid type, Writer relies on the second element of being a Monoid type.

Parametric types is the foundation of decomposing an application into computational chain and computational context factors.

A functional application is just a recomposition of computational chains of different computational context.

Category theory and haskell guarantee that the behaviour of recomposing a long computation chain would be predicable.

Predictable does not implies good implementation. There are design principles and design patterns for functional programming that we need to follow for achieving scalability and maintainability.

Section 0. Computational Context

Parametric type X Typeclasses = Computational Context

Three common Typeclasses, that being used to define how, a context type f, could affect the target computation a -> b.

typeclass main-function function type
Functor <$> (a -> b) -> f a -> f b
Applicative <*> f(a -> b) -> f a -> f b
Monad >>= f a -> ( a -> f b) -> f b

Flip the argument of >>=, we get (a-> f b) -> f a -> f b. Now it is much clear. These function types could be seen as two parts. The first part includes:

  1. (a -> b), f (a -> b), a -> f b

The second part of these three functions are all the same:

  1. f a - f b

Intuitively, these three functions are about how to transform different mapping relations (in 1) into context sensitive mapping f a -> f b. So that we could compose functions of the same Context Semantics.

When f a is a certain Parametric Type, it could indicate a specific Computational Context with a specific Context Semantics.

Parametric types: List Product Sum Exponential
<$> Container Container Container Container
<*> Generator Container Container Container
>>= [] Context Writer Context Either/Maybe/IO Context Reader/State

Summary

<*> :: f (a ->b) -> f a -> f b Context information starts to effect

<$> cannot handle this

>=> :: (a -> f b) -> (b -> fc) -> (a -> fc)

<*> cannot provide this composition ability

>>= where the Context information starts to shine

example of applicativeDo

would normally be desugared to foo1 >>= \x -> foo2 >>= \y -> foo3 >>= \z -> return (g x y z), but this is equivalent to g <$> foo1 <*> foo2 <*> foo3. With the ApplicativeDo extension enabled (as of GHC 8.0), GHC tries hard to desugar do-blocks using Applicative operations wherever possible. This can sometimes lead to efficiency gains, even for types which also have Monad instances, since in general Applicative computations may be run in parallel, whereas monadic ones may not. For example, consider

g :: Int -> Int -> M Int

-- These could be expensive
bar, baz :: M Int

foo :: M Int
foo = do
  x <- bar
  y <- baz
  g x y
foo definitely depends on the Monad instance of M, since the effects generated by the whole computation may depend (via g) on the Int outputs of bar and baz. Nonetheless, with ApplicativeDo enabled, foo can be desugared as

join (g <$> bar <*> baz)
which may allow bar and baz to be computed in parallel, since they at least do not depend on each other.

The ApplicativeDo extension is described in this wiki page, and in more detail in this Haskell Symposium paper.

Parametric types + Typeclass = Intuitive semantics

  • Container : Value/s of Type a ( deterministic)
  • Generator : Value/s of Type a ( non-deterministic)
    • f <*> xs: Every element of the list xs will be input of function f.
    • Default semantics of applicative functor of [].

MonadTrans

T m a

  • Function type monad transfers T use m to wrap target type a

    newtype StateT s m a = StateT { runStateT :: s -> m (a,s) }
instance (Monad m) => Monad (StateT s m) where
#if !(MIN_VERSION_base(4,8,0))
return a = StateT $ \ s -> return (a, s)
{-# INLINE return #-}
#endif
m >>= k  = StateT $ \ s -> do
    ~(a, s') <- runStateT m s
    runStateT (k a) s'
{-# INLINE (>>=) #-}
fail str = StateT $ \ _ -> fail str
{-# INLINE fail #-}

  • Parametric type monad transfers T reach inside m to wrap target type a

    newtype MaybeT m a = MaybeT { runMaybeT :: m (Maybe a) }

instance (Monad m) => Monad (MaybeT m) where
fail _ = MaybeT (return Nothing)
return = lift . return
x >>= f = MaybeT $ do
    v <- runMaybeT x
    case v of
        Nothing -> return Nothing
        Just y  -> runMaybeT (f y)

For example, when a StateT s Maybe a computation fails, the state ceases being updated (indeed, it simply disappears); on the other hand, the state of a MaybeT (State s) a computation may continue to be modified even after the computation has “failed”. This may seem backwards, but it is correct. [haskell wiki:typeclass]

Common usage - When many T m a composed with >>=, the Computational Context is the outside T. - runT unwrap this monad stack, thus switch the Computational Context from T to m.

TODO:

  • TODO: needs more examples about how this works, such as MaybeT (State s) a

    • More about MonadTrans typeclass and Transformer type classes (mtl). need isolated tutorial and examples set. mtl obsolete the need of lift in Monad.Trans (more details) typelcass wiki has alot great further reading in monad transfer part.

    • check corresponding >>= , lift and liftIO function for more details.

      the effects of inner monads "have precedence" over the effects of outer ones.

      wirte function focus on innermost monad and lift all the way up to the outer most. More Examples

    • Summarize RWST

Section 1. Transform within the same type

Semigroup and Monoid represent type :: a and an operation :: a -> a -> a on that type.

Readings

1. Semigroup Data.Semigroup

Define binary function <> that take input and give output of the same type.

class Semigroup a where
  (<>) :: a -> a -> a

  default (<>) :: Monoid a => a -> a -> a
  (<>) = mappend

2. Monoid

Define mempty :: a that enabling (<> mempty) to be an identity function on type a.

class Semigroup a => Monoid a where
        -- | Identity of 'mappend'
        mempty  :: a

        -- | An associative operation
        --
        -- __NOTE__: This method is redundant and has the default
        -- implementation @'mappend' = '(<>)'@ since /base-4.11.0.0/.
        mappend :: a -> a -> a
        mappend = (<>)
        {-# INLINE mappend #-}

        -- | Fold a list using the monoid.
        --
        -- For most types, the default definition for 'mconcat' will be
        -- used, but the function is included in the class definition so
        -- that an optimized version can be provided for specific types.
        mconcat :: [a] -> a
        mconcat = foldr mappend mempty

  • Dual Data.Monoid

    package Data.Semigroup:
instance Semigroup a => Semigroup (Dual a) where
  Dual a <> Dual b = Dual (b <> a)
  stimes n (Dual a) = Dual (stimes n a)

package Data.Monoid:
instance Monoid a => Monoid (Dual a) where
        mempty = Dual mempty
        Dual x `mappend` Dual y = Dual (y `mappend` x)

Section 2: Monoidal subclass

  1. In a monoidal operation :: t -> t -> t, t could be a parametric type.
Typeclass List product Sum ->
`< >` :: f a-> f a -> f a Container Container Container
mplus:: m a-> m a -> m a` Container Container Container Container 
Maybe Example:
instance (Functor m, Monad m) => Alternative (MaybeT m) where
    empty = mzero
    (<|>) = mplus

instance (Monad m) => MonadPlus (MaybeT m) where
    mzero = MaybeT (return Nothing)
    mplus x y = MaybeT $ do
        v <- runMaybeT x
        case v of
            Nothing -> runMaybeT y
            Just _  -> return v

Reader Example:

instance (Alternative m) => Alternative (ReaderT r m) where
    empty   = liftReaderT empty
    {-# INLINE empty #-}
    m <|> n = ReaderT $ \ r -> runReaderT m r <|> runReaderT n r
    {-# INLINE (<|>) #-}

instance (MonadPlus m) => MonadPlus (ReaderT r m) where
    mzero       = lift mzero
    {-# INLINE mzero #-}
    m `mplus` n = ReaderT $ \ r -> runReaderT m r `mplus` runReaderT n r
    {-# INLINE mplus #-}

Writer Example:

instance (Monoid w, Alternative m) => Alternative (WriterT w m) where
    empty   = WriterT empty
    {-# INLINE empty #-}
    m <|> n = WriterT $ runWriterT m <|> runWriterT n
    {-# INLINE (<|>) #-}

instance (Monoid w, MonadPlus m) => MonadPlus (WriterT w m) where
    mzero       = WriterT mzero
    {-# INLINE mzero #-}
    m `mplus` n = WriterT $ runWriterT m `mplus` runWriterT n
    {-# INLINE mplus #-}

Several classes have monoidal subclass to model computation that support failure or choice.

  • Applicative
    • Alternative
  • Monad
    • MonadPlus
  • Arrow
    • ArrowPlus
    • Arrow Zero

Section 3: Utility Functions

3.0.Content

:: (Functor t, Foldable t, Traversable t) =>

on monads type :: Monad m => on Applicative :: Applicative f type :: Applicative f =>
return a -> m a pure a -> f a
liftM2 (a -> b -> c) -> m a -> m b -> m c liftA2 ( a -> b -> c) -> f a -> f b -> f c
mapM (a -> m b) -> t a -> m (t b) traverse (a -> f b) -> t a -> f (t b)
forM t a -> (a -> m b) -> m (t b) for t a -> (a -> f b) -> f (t b)
sequence t (m a) -> m ( t b) sequenceA t (f b) -> f ()
mapM_ (a -> m b) -> t a -> m () traverse (a -> f b) -> t a -> f ()
forM_ t a -> (a -> m b) -> m () for t a -> (a -> f b) -> f ()
sequence_ t (m a) -> m () sequenceA t (f b) -> f ()

3.1.Applicative and Monad

function constraint type define import
liftA2 Applicative f => (a -> b -> c) -> (f a -> f b -> f c) Control.Applicative GHC.Base
liftM2 Monad m => (a -> b -> c) -> (m a -> m b -> m c) Control.Monad GHC.Base
  • liftA2 f x = <*> (fmap f x). Context information f affect function a -> b -> c in its own way. This default definition relies on <*> and fmap. Some support explicit definition which would be more efficient.
    • Sum type Maybe & Either e : All f a, f b and f c must be success or nothing but error e.
    • Product type (,) & Writer w : All logging information w be aggregated in the first element (in (,) ) or in the second element ( in Writer ).
    • Exponential type (->) e & Reader e : Now f a is of type e -> a. Apply f a, f b with common environment information e respectively, then apply function f :: a -> b -> c on these two results.
  • liftM2 f m1 m2 = do { x1 <- m1; x2 <- m2: return (f x2 x2)}. This is the default definition and all Parametric Types above relies on this definition and has the same semantics as above.

3.2.Foldable

function constraint type define import
foldMap Monoid m, Foldable t (a -> m) -> t a -> m Data.Foldable GHC.Base
fold Monoid m, Foldable t t a -> m Data.Foldable Data.Foldable
foldrM Monad m, Foldable t (a -> b -> m b) -> b -> t a -> m b Data.Foldable Data.Foldable
foldlM = foldM Monad m, Foldable t (b -> a -> m b) -> b -> t a -> m b Data.Foldable Data.Foldable

  • foldMap substitute target type a in foldable context with Monoid type m, then collapse Foldable m to a single value of type m.

        foldMap :: Monoid m => (a -> m) -> t a -> m
    foldMap f = foldr (mappend . f) mempty
    • fold = foldMap id

  • foldrM and foldlM (foldM) focus on folding over monadic values using >>=. Detailed discussion here

    -- | Monadic fold over the elements of a structure,
-- associating to the right, i.e. from right to left.
foldrM :: (Foldable t, Monad m) => (a -> b -> m b) -> b -> t a -> m b
foldrM f z0 xs = foldl f' return xs z0
  where f' k x z = f x z >>= k

-- | Monadic fold over the elements of a structure,
-- associating to the left, i.e. from left to right.
foldlM :: (Foldable t, Monad m) => (b -> a -> m b) -> b -> t a -> m b
foldlM f z0 xs = foldr f' return xs z0
  where f' x k z = f z x >>= k

    One possible example is:

    • b -> a -> m b : is a function that test whether b satisfied condition a. The test result is m b which contains both success and failure information.
    • b is the initial input being tested.
    • t a could be a list of condition a
    • m b is the final collapsed result of a sequence of test on t a.

3.3.Traversable

function constraint type define import
traverse Applicative f, (Functor, Foldable, Traversable t) (a -> f b) -> t b -> f (t b) Data.Traversable Prelude
mapM Monad m, (Functor, Foldable, Traversable t) (a -> m b) -> m b -> m (t b) Data.Traversable Prelude
  • The default definition is: mapM = traverse.

  • The relation between traverse and sequenceA kind like the relation between liftA2 and <*>. Here is the default definition:

    class (Functor t, Foldable t) => Traversable (t :: * -> *) where
...
traverse :: (Applicative f) => (a -> f b) -> t a -> f (t b)
traverse f = sequenceA . fmap f
...
sequenceA :: (Applicative f) => t (f b) -> f ( t b)
sequenceA = traverse id

    In general, it is better to write traverse when implementing Traversable, as the default definition of traverse performs, in principle, two runs across the structure (one for fmap and another for sequenceA).

  • traverse defines how Target computation :: a -> b works on target type a in a Foldable structure t. Meanwhile Context information f affect the ultimate result: f ( t b).

  • Generally, default definition: mapM = traverse. in GHC.Base mapM is specifically defined for Traversable list:

    mapM :: Monad m => (a -> m b) -> [a] -> m [b]
mapM f as = foldr k (return []) as
          where
            k a r = do { x <- f a; xs <- r; return (x:xs) }
    function constraint type define import
    for Applicative f, (Functor, Foldable, Traversable t) t b -> (a -> f b)-> f (t b) Data.Traversable Data.Traversable
    forM Monad m, (Functor, Foldable, Traversable t) m b -> (a -> m b)-> m (t b) Data.Traversable Prelude

  • for is ‘traverse’ with its arguments flipped.

  • forM is ‘mapM’ with its arguments flipped.

function constraint type define import
sequenceA Applicative f, (Functor, Foldable, Traversable t) t (f a) -> f (t a) Data.Traversable Prelude
sequence Monad m, (Functor, Foldable, Traversable t) t (m a) -> m (t a) Data.Traversable GHC.Base
  • TODO: more intuitive examples

“underscored” variants, such as sequence_ and mapM_; these variants throw away the results of the computations passed to them as arguments, using them only for their side effects.

monad constrained type define import
mapM_ (Foldable t, Monad m) => (a -> m b) -> t a -> m () Data.Foldable Prelude
forM_ (Foldable t, Monad m) => t a -> (a -> m b) -> m () Data.Foldable Data.Foldable
sequence_ (Foldable t, Monad m) => t (m a) -> m () Data.Foldable Prelude
Applicative constrained type define import
traverse_ (Foldable t, Applicative f) => (a -> f b) -> t a -> f () Data.Foldable Data.Foldable
for_ (Foldable t, Applicative f) => t a -> (a -> f b) -> f () Data.Foldable Data.Foldable
sequenceA_ (Foldable t, Applicative f) => t (f a) -> f () Data.Foldable Data.Foldable
  • This so call side effects is the what these functions all about.
  • All these functions are defined in Data.Foldable.
  • mapM_ and sequence_ are exposed by Prelude.
  • TODO: needs more attention and example.

3.4. newtype

Mileski twitter example

  type ListPair a = [(Card,a)]
  instance Functor ListPair where 
    fmap f = fmap (bimap id f)
  
  > The type synonym 'ListPair' should have one argument but has been given one.
  > In the instance declaration for 'Functor ListPair'

The correct definition should be :

  newtype ListPair a = LP {unLP :: [(Card,a)]}
  instance Functor ListPair where 
    fmap f = fmap (bimap id f)

Then wrap and unwrap value of type ListPair explicitly.

  • If the function instance declaration with type synonym works.

    t :: [(Card,String)]
h :: (Card,String) -> a
g :: String -> a

let fh = fmap h t     -- function fh
let fg = fmap g t     -- function fg

    the fmap in function fh is defined in instance Functor [] the fmap in function fg is defined in instance Functor ListPair In this case what instance will being used is not determined by the type of t, it is also determined by the type of f (as in fmap f in this example fg and fh). This can be achieved, however:

    • most of the time the instance of fmap being used can be determined by the type of t only. Checking two palces t and f is no efficient.
    • It is simple to introduce a newtype as the wrapper to unify the place that contains information about instance will being used. ( in t only)

TODO

  • draw a relation graph of these useful operations above
  • Intuition and examples of these operations above.

  • relation between Monad and Applicative + Alternative

    ∗ Actually, because Haskell allows general recursion, one can recursively construct infinite grammars, and hence Applicative (together with Alternative) is enough to parse any context-sensitive language with a finite alphabet. See Parsing context-sensitive languages with Applicative.

    How is this work ?

  • finish foldr and foldl

  • more examples of traverse/mapM , foldMap, fold, foldM, sequenceA/sequence. Based on not only list, but also Data.Tree

Section 4

  • MonadTrans
  • MonadIO
  • MonadFail
  • MonadFix (read after the first time finishing typeclass wiki)

  • Contravarriant

    Prelude Control.Monad.Fail> :info fail
class Monad m => MonadFail (m :: * -> *) where
Control.Monad.Fail.fail :: String -> m a
    -- Defined in ‘Control.Monad.Fail’

class Applicative m => Monad (m :: * -> *) where
  ...
Prelude.fail :: String -> m a
    -- Defined in ‘GHC.Base’

    TODO: Why MonadFail instead of Prelude.fail readthis

##TODO - draw a relation graph of these useful operations above - Intuition of these operations - relation between Monad and Applicative + Alternative

  ∗ Actually, because Haskell allows general recursion, one can recursively construct infinite grammars, and hence Applicative (together with Alternative) is enough to parse any context-sensitive language with a finite alphabet. See Parsing context-sensitive languages with Applicative.

How is this work ?

## TODO newtype Mileski twitter example

  type ListPair a = [(Card,a)]
  instance Functor ListPair where 
    fmap f = fmap (bimap id f)
  
  > The type synonym 'ListPair' should have one argument but has been given one.
  > In the instance declaration for 'Functor ListPair'

The error free form should be

  newtype ListPair a = LP {unLP :: [(Card,a)]}
  instance Functor ListPair where 
    fmap f = fmap (bimap id f)

Then wrap and unwrap value of type ListPair explicitly.

  • If the function instance declaration with type synonym works.

    t :: [(Card,String)]
h :: (Card,String) -> a
g :: String -> a

let fh = fmap h t     -- function fh
let fg = fmap g t     -- function fg

    the fmap in function fh is defined in instance Functor [] the fmap in function fg is defined in instance Functor ListPair In this case what instance will being used is not determined by the type of t, it is also determined by the type of f (as in fmap f in this example fg and fh). This can be achieved, however:

    • most of the time the instance of fmap being used can be determined by the type of t only. Checking two palces t and f is no efficient.
    • It is simple to introduce a newtype as the wrapper to unify the place that contains information about instance will being used. ( in t only)