Table of Contents
Often, we have to deal with data that is unordered but is indexed by a key. For instance, a Unix administrator might have a list of numeric UIDs (user IDs) and the textual usernames that they correspond to. The value of this list lies in being able to look up a textual username for a given UID, not in the order of the data. In other words, the UID is a key into a database.
      In Haskell, there are several ways to handle data that is structured in
      this way.  The two most common are association lists and the
      Map type provided by
      Data.Map module.  Association lists are handy
      because they are simple.  They are standard Haskell lists, so all the
      familiar list functions work with association lists.  However,
      for large data sets, Map will have a
      considerable performance advantage over association lists.  We'll
      use both in this chapter.
    
      An association list is just a normal list containing (key, value)
      tuples.  The type of a list of mappings from UID to username might be
      [(Integer, String)].  We could use just about any
      type[31]for both the key and the value.
    
      We can build association lists just we do any other
      list.  Haskell comes with one built-in function called 
      Data.List.lookup to look up data in an association
      list.  Its type is Eq a => a -> [(a, b)] -> Maybe b.
      Can you guess how it works from that type?  Let's take a look in
      ghci.
    
ghci>let al = [(1, "one"), (2, "two"), (3, "three"), (4, "four")]ghci>lookup 1 alJust "one"ghci>lookup 5 alNothing
      The lookup function is really simple.  Here's
      one way we could write it:
    
-- file: ch13/lookup.hs
myLookup :: Eq a => a -> [(a, b)] -> Maybe b
myLookup _ [] = Nothing
myLookup key ((thiskey,thisval):rest) =
    if key == thiskey
       then Just thisval
       else myLookup key rest
      This function returns Nothing if passed the empty list.  Otherwise,
      it compares the key with the key we're looking for.  If a match is
      found, the corresponding value is returned.  Otherwise, it searches
      the rest of the list.
    
      Let's take a look at a more complex example of association
      lists. On Unix/Linux machines, there is a file called
      /etc/passwd that stores usernames, UIDs,
      home directories, and various other data.  We will write a program
      that parses such a file, creates an association list, and lets
      the user look up a username by giving a UID.
    
-- file: ch13/passwd-al.hs
import Data.List
import System.IO
import Control.Monad(when)
import System.Exit
import System.Environment(getArgs)
main = do
    -- Load the command-line arguments
    args <- getArgs
    -- If we don't have the right amount of args, give an error and abort
    when (length args /= 2) $ do
        putStrLn "Syntax: passwd-al filename uid"
        exitFailure
    -- Read the file lazily
    content <- readFile (args !! 0)
    -- Compute the username in pure code
    let username = findByUID content (read (args !! 1))
    -- Display the result
    case username of 
         Just x -> putStrLn x
         Nothing -> putStrLn "Could not find that UID"
-- Given the entire input and a UID, see if we can find a username.
findByUID :: String -> Integer -> Maybe String
findByUID content uid =
    let al = map parseline . lines $ content
        in lookup uid al
-- Convert a colon-separated line into fields
parseline :: String -> (Integer, String)
parseline input =
    let fields = split ':' input
        in (read (fields !! 2), fields !! 0)
{- | Takes a delimiter and a list.  Break up the list based on the
-  delimiter. -}
split :: Eq a => a -> [a] -> [[a]]
-- If the input is empty, the result is a list of empty lists.
split _ [] = [[]]
split delim str =
    let -- Find the part of the list before delim and put it in "before".
        -- The rest of the list, including the leading delim, goes
        -- in "remainder".
        (before, remainder) = span (/= delim) str
        in
        before : case remainder of
                      [] -> []
                      x -> -- If there is more data to process,
                           -- call split recursively to process it
                           split delim (tail x)
      Let's look at this program.  The heart of it is
      findByUID, which is a simple function that parses
      the input one line at a time, then calls lookup over
      the result.  The remaining program is concerned with parsing the input.
      The input file looks like this:
    
root:x:0:0:root:/root:/bin/bash
daemon:x:1:1:daemon:/usr/sbin:/bin/sh
bin:x:2:2:bin:/bin:/bin/sh
sys:x:3:3:sys:/dev:/bin/sh
sync:x:4:65534:sync:/bin:/bin/sync
games:x:5:60:games:/usr/games:/bin/sh
man:x:6:12:man:/var/cache/man:/bin/sh
lp:x:7:7:lp:/var/spool/lpd:/bin/sh
mail:x:8:8:mail:/var/mail:/bin/sh
news:x:9:9:news:/var/spool/news:/bin/sh
jgoerzen:x:1000:1000:John Goerzen,,,:/home/jgoerzen:/bin/bash
    Its fields are separated by colons, and include a username, numeric user ID, numeric group ID, full name, home directory, and shell. No field may contain an internal colon.
      The Data.Map module provides a
      Map type with behavior that is similar to
      association lists, but has much better performance.
Maps give us the same capabilities as hash tables do in other languages. Internally, a map is implemented as a balanced binary tree. Compared to a hash table, this is a much more efficient representation in a language with immutable data. This is the most visible example of how deeply pure functional programming affects how we write code: we choose data structures and algorithms that we can express cleanly and that perform efficiently, but our choices for specific tasks are often different their counterparts in imperative languages.
Some functions in the Data.Map module have the
      same names as those in the Prelude. Therefore, we will import it
      with import qualified Data.Map as Map and use
      Map. to refer
      to names in that module. Let's start our tour of
      nameData.Map by taking a look at some ways to
      build a map.
    
-- file: ch13/buildmap.hs
import qualified Data.Map as Map
-- Functions to generate a Map that represents an association list
-- as a map
al = [(1, "one"), (2, "two"), (3, "three"), (4, "four")]
{- | Create a map representation of 'al' by converting the association
-  list using Map.fromList -}
mapFromAL =
    Map.fromList al
{- | Create a map representation of 'al' by doing a fold -}
mapFold =
    foldl (\map (k, v) -> Map.insert k v map) Map.empty al
{- | Manually create a map with the elements of 'al' in it -}
mapManual =
    Map.insert 2 "two" . 
    Map.insert 4 "four" .
    Map.insert 1 "one" .
    Map.insert 3 "three" $ Map.empty
      Functions like Map.insert work in the usual
      Haskell way: they return a copy of the input data, with the
      requested change applied.  This is quite handy with maps.  It
      means that you can use foldl to build up a
      map as in the mapFold example.  Or, you can
      chain together calls to Map.insert as in the
      mapManual example.  Let's use ghci to
      verify that all of these maps are as expected:
    
ghci>:l buildmap.hs[1 of 1] Compiling Main ( buildmap.hs, interpreted ) Ok, modules loaded: Main.ghci>alLoading package array-0.1.0.0 ... linking ... done. Loading package containers-0.1.0.1 ... linking ... done. [(1,"one"),(2,"two"),(3,"three"),(4,"four")]ghci>mapFromALfromList [(1,"one"),(2,"two"),(3,"three"),(4,"four")]ghci>mapFoldfromList [(1,"one"),(2,"two"),(3,"three"),(4,"four")]ghci>mapManualfromList [(1,"one"),(2,"two"),(3,"three"),(4,"four")]
      Notice that the output from mapManual differs
      from the order of the list we used to construct the map.  Maps do
      not guarantee that they will preserve the original ordering.
    
      Maps operate similarly in concept to association lists.  The
      Data.Map module provides functions for adding
      and removing data from maps.  It also lets us filter them,
      modify them, fold over them, and convert to and from association
      lists.  The library documentation for this module is good, so
      instead of going into detail on each function, we will present
      an example that ties together many of the concepts we've
      discussed in this chapter.
    
Part of Haskell's power is the ease with which it lets us create and manipulate functions. Let's take a look at a record that stores a function as one of its fields:
-- file: ch13/funcrecs.hs
{- | Our usual CustomColor type to play with -}
data CustomColor =
  CustomColor {red :: Int,
               green :: Int,
               blue :: Int}
  deriving (Eq, Show, Read)
{- | A new type that stores a name and a function.
The function takes an Int, applies some computation to it, and returns
an Int along with a CustomColor -}
data FuncRec =
    FuncRec {name :: String,
             colorCalc :: Int -> (CustomColor, Int)}
plus5func color x = (color, x + 5)
purple = CustomColor 255 0 255
plus5 = FuncRec {name = "plus5", colorCalc = plus5func purple}
always0 = FuncRec {name = "always0", colorCalc = \_ -> (purple, 0)}
      Notice the type of the colorCalc field: it's a
      function.  It takes an Int and returns a tuple of
      (CustomColor, Int).  We create two
      FuncRec records: plus5 and
      always0.  Notice that the
      colorCalc for both of them will always return the
      color purple.  FuncRec itself has no field to store
      the color in, yet that value somehow becomes part of the function
      itself.  This is called a closure.  Let's play
      with this a bit:
    
ghci>:l funcrecs.hs[1 of 1] Compiling Main ( funcrecs.hs, interpreted ) Ok, modules loaded: Main.ghci>:t plus5plus5 :: FuncRecghci>name plus5"plus5"ghci>:t colorCalc plus5colorCalc plus5 :: Int -> (CustomColor, Int)ghci>(colorCalc plus5) 7(CustomColor {red = 255, green = 0, blue = 255},12)ghci>:t colorCalc always0colorCalc always0 :: Int -> (CustomColor, Int)ghci>(colorCalc always0) 7(CustomColor {red = 255, green = 0, blue = 255},0)
That worked well enough, but you might wonder how to do something more advanced, such as making a piece of data available in multiple places. A type construction function can be helpful. Here's an example:
-- file: ch13/funcrecs2.hs
data FuncRec =
    FuncRec {name :: String,
             calc :: Int -> Int,
             namedCalc :: Int -> (String, Int)}
mkFuncRec :: String -> (Int -> Int) -> FuncRec
mkFuncRec name calcfunc =
    FuncRec {name = name,
             calc = calcfunc,
             namedCalc = \x -> (name, calcfunc x)}
plus5 = mkFuncRec "plus5" (+ 5)
always0 = mkFuncRec "always0" (\_ -> 0)
      Here we have a function called mkFuncRec that
      takes a String and another function as parameters, and returns
      a new FuncRec record.  Notice how both parameters to
      mkFuncRec are used in multiple places.  Let's try it
      out:
    
ghci>:l funcrecs2.hs[1 of 1] Compiling Main ( funcrecs2.hs, interpreted ) Ok, modules loaded: Main.ghci>:t plus5plus5 :: FuncRecghci>name plus5"plus5"ghci>(calc plus5) 510ghci>(namedCalc plus5) 5("plus5",10)ghci>let plus5a = plus5 {name = "PLUS5A"}ghci>name plus5a"PLUS5A"ghci>(namedCalc plus5a) 5("plus5",10)
      Notice the creation of plus5a.  We changed the
      name field, but not the namedCalc
      field.  That's why name has the new name, but
      namedCalc still returns the name that was passed to
      mkFuncRec; it doesn't change unless we explicitly
      change it.
    
      In order to illustrate the usage of a number of different data
      structures together, we've prepared an extended example.  This example
      parses and stores entries from files in the format of
      a typical /etc/passwd file.
    
-- file: ch13/passwdmap.hs
import Data.List
import qualified Data.Map as Map
import System.IO
import Text.Printf(printf)
import System.Environment(getArgs)
import System.Exit
import Control.Monad(when)
{- | The primary piece of data this program will store.
   It represents the fields in a POSIX /etc/passwd file -}
data PasswdEntry = PasswdEntry {
    userName :: String,
    password :: String,
    uid :: Integer,
    gid :: Integer,
    gecos :: String,
    homeDir :: String,
    shell :: String}
    deriving (Eq, Ord)
{- | Define how we get data to a 'PasswdEntry'. -}
instance Show PasswdEntry where
    show pe = printf "%s:%s:%d:%d:%s:%s:%s" 
                (userName pe) (password pe) (uid pe) (gid pe)
                (gecos pe) (homeDir pe) (shell pe)
{- | Converting data back out of a 'PasswdEntry'. -}
instance Read PasswdEntry where
    readsPrec _ value =
        case split ':' value of
             [f1, f2, f3, f4, f5, f6, f7] ->
                 -- Generate a 'PasswdEntry' the shorthand way:
                 -- using the positional fields.  We use 'read' to convert
                 -- the numeric fields to Integers.
                 [(PasswdEntry f1 f2 (read f3) (read f4) f5 f6 f7, [])]
             x -> error $ "Invalid number of fields in input: " ++ show x
        where 
        {- | Takes a delimiter and a list.  Break up the list based on the
        -  delimiter. -}
        split :: Eq a => a -> [a] -> [[a]]
        -- If the input is empty, the result is a list of empty lists.
        split _ [] = [[]]
        split delim str =
            let -- Find the part of the list before delim and put it in
                -- "before".  The rest of the list, including the leading 
                -- delim, goes in "remainder".
                (before, remainder) = span (/= delim) str
                in
                before : case remainder of
                              [] -> []
                              x -> -- If there is more data to process,
                                   -- call split recursively to process it
                                   split delim (tail x)
-- Convenience aliases; we'll have two maps: one from UID to entries
-- and the other from username to entries
type UIDMap = Map.Map Integer PasswdEntry
type UserMap = Map.Map String PasswdEntry
{- | Converts input data to maps.  Returns UID and User maps. -}
inputToMaps :: String -> (UIDMap, UserMap)
inputToMaps inp =
    (uidmap, usermap)
    where
    -- fromList converts a [(key, value)] list into a Map
    uidmap = Map.fromList . map (\pe -> (uid pe, pe)) $ entries
    usermap = Map.fromList . 
              map (\pe -> (userName pe, pe)) $ entries
    -- Convert the input String to [PasswdEntry]
    entries = map read (lines inp)
main = do
    -- Load the command-line arguments
    args <- getArgs
    -- If we don't have the right number of args,
    -- give an error and abort
    when (length args /= 1) $ do
        putStrLn "Syntax: passwdmap filename"
        exitFailure
    -- Read the file lazily
    content <- readFile (head args)
    let maps = inputToMaps content
    mainMenu maps
mainMenu maps@(uidmap, usermap) = do
    putStr optionText
    hFlush stdout
    sel <- getLine
    -- See what they want to do.  For every option except 4,
    -- return them to the main menu afterwards by calling
    -- mainMenu recursively
    case sel of
         "1" -> lookupUserName >> mainMenu maps
         "2" -> lookupUID >> mainMenu maps
         "3" -> displayFile >> mainMenu maps
         "4" -> return ()
         _ -> putStrLn "Invalid selection" >> mainMenu maps
    where 
    lookupUserName = do
        putStrLn "Username: "
        username <- getLine
        case Map.lookup username usermap of
             Nothing -> putStrLn "Not found."
             Just x -> print x
    lookupUID = do
        putStrLn "UID: "
        uidstring <- getLine
        case Map.lookup (read uidstring) uidmap of
             Nothing -> putStrLn "Not found."
             Just x -> print x
    displayFile = 
        putStr . unlines . map (show . snd) . Map.toList $ uidmap
    optionText = 
          "\npasswdmap options:\n\
           \\n\
           \1   Look up a user name\n\
           \2   Look up a UID\n\
           \3   Display entire file\n\
           \4   Quit\n\n\
           \Your selection: "
      This example maintains two maps: one from username to
      PasswdEntry and another one from UID to
      PasswdEntry.  Database developers may find it
      convenient to think of this as having two different indices into the
      data to speed searching on different fields.
    
      Take a look at the Show and Read instances for
      PasswdEntry.  There is already a standard format for
      rendering data of this type as a string: the colon-separated version
      already used by the system.  So our Show function displays a
      PasswdEntry in the format, and Read parses that
      format.
    
We've told you how powerful and expressive Haskell's type system is. We've shown you a lot of ways to use that power. Here's a chance to really see that in action.
Back in the section called “Numeric Types”, we showed the numeric typeclasses that come with Haskell. Let's see what we can do by defining new types and utilizing the numeric typeclasses to integrate them with basic mathematics in Haskell.
      Let's start by thinking through what we'd like to see out of ghci
      when we interact with our new types.  To start with, it might be nice
      to render numeric expressions as strings, making sure to indicate
      proper precedence.  Perhaps we could create a function called
      prettyShow to do that.  We'll show you how to
      write it in a bit, but first we'll look at how we might use it.
    
ghci>:l num.hs[1 of 1] Compiling Main ( num.hs, interpreted ) Ok, modules loaded: Main.ghci>5 + 1 * 38ghci>prettyShow $ 5 + 1 * 3"5+(1*3)"ghci>prettyShow $ 5 * 1 + 3"(5*1)+3"
      That looks nice, but it wasn't all that smart.  We could easily
      simplify out the 1 * part of the expression.  How
      about a function to do some very basic simplification?
    
ghci>prettyShow $ simplify $ 5 + 1 * 3"5+3"
How about converting a numeric expression to Reverse Polish Notation (RPN)? RPN is a postfix notation that never requires parentheses, and is commonly found on HP calculators. RPN is a stack-based notation. We push numbers onto the stack, and when we enter operations, they pop the most recent numbers off the stack and place the result on the stack.
ghci>rpnShow $ 5 + 1 * 3"5 1 3 * +"ghci>rpnShow $ simplify $ 5 + 1 * 3"5 3 +"
Maybe it would be nice to be able to represent simple expressions with symbols for the unknowns.
ghci>prettyShow $ 5 + (Symbol "x") * 3"5+(x*3)"
It's often important to track units of measure when working with numbers. For instance, when you see the number 5, does it mean 5 meters, 5 feet, or 5 bytes? Of course, if you divide 5 meters by 2 seconds, the system ought to be able to figure out the appropriate units. Moreover, it should stop you from adding 2 seconds to 5 meters.
ghci>5 / 22.5ghci>(units 5 "m") / (units 2 "s")2.5_m/sghci>(units 5 "m") + (units 2 "s")*** Exception: Mis-matched units in addghci>(units 5 "m") + (units 2 "m")7_mghci>(units 5 "m") / 22.5_mghci>10 * (units 5 "m") / (units 2 "s")25.0_m/s
      If we define an expression or a function that is valid for all numbers,
      we should be able to calculate the result, or render the expression.
      For instance, if we define test to have type
      Num a => a, and say test = 2 * 5 +
        3, then we ought to be able to do this:
    
ghci>test13ghci>rpnShow test"2 5 * 3 +"ghci>prettyShow test"(2*5)+3"ghci>test + 518ghci>prettyShow (test + 5)"((2*5)+3)+5"ghci>rpnShow (test + 5)"2 5 * 3 + 5 +"
Since we have units, we should be able to handle some basic trigonometry as well. Many of these operations operate on angles. Let's make sure that we can handle both degrees and radians.
ghci>sin (pi / 2)1.0ghci>sin (units (pi / 2) "rad")1.0_1.0ghci>sin (units 90 "deg")1.0_1.0ghci>(units 50 "m") * sin (units 90 "deg")50.0_m
Finally, we ought to be able to put all this together and combine different kinds of expressions together.
ghci>((units 50 "m") * sin (units 90 "deg")) :: Units (SymbolicManip Double)50.0*sin(((2.0*pi)*90.0)/360.0)_mghci>prettyShow $ dropUnits $ (units 50 "m") * sin (units 90 "deg")"50.0*sin(((2.0*pi)*90.0)/360.0)"ghci>rpnShow $ dropUnits $ (units 50 "m") * sin (units 90 "deg")"50.0 2.0 pi * 90.0 * 360.0 / sin *"ghci>(units (Symbol "x") "m") * sin (units 90 "deg")x*sin(((2.0*pi)*90.0)/360.0)_m
      Everything you've just seen is possible with Haskell types and classes.
      In fact, you've been reading a real ghci session demonstrating
      num.hs, which you'll see shortly.
    
        Let's think about how we would accomplish everything shown above.  To
        start with, we might use ghci to check the type of
        (+), which is Num a => a -> a ->
          a.  If we want to make possible some custom behavior for
        the plus operator, then we will have to define a new type and make it
        an instance of Num.  This type will need to store an expression
        symbolically.  We can start by thinking of operations such as addition.
        To store that, we will need to store the operation itself, its left
        side, and its right side.  The left and right sides could themselves be
        expressions.
      
We can therefore think of an expression as a sort of tree. Let's start with some simple types.
-- file: ch13/numsimple.hs
-- The "operators" that we're going to support
data Op = Plus | Minus | Mul | Div | Pow
        deriving (Eq, Show)
{- The core symbolic manipulation type -}
data SymbolicManip a = 
          Number a           -- Simple number, such as 5
        | Arith Op (SymbolicManip a) (SymbolicManip a)
          deriving (Eq, Show)
{- SymbolicManip will be an instance of Num.  Define how the Num
operations are handled over a SymbolicManip.  This will implement things
like (+) for SymbolicManip. -}
instance Num a => Num (SymbolicManip a) where
    a + b = Arith Plus a b
    a - b = Arith Minus a b
    a * b = Arith Mul a b
    negate a = Arith Mul (Number (-1)) a
    abs a = error "abs is unimplemented"
    signum _ = error "signum is unimplemented"
    fromInteger i = Number (fromInteger i)
        First, we define a type called Op.  This type
        simply represents some of the operations we will support.
        Next, there is a definition for SymbolicManip a.
        Because of the Num a constraint, any
        Num can be used for the a.  So
        a full type may be something like SymbolicManip
          Int.
      
        A SymbolicManip type can be a plain number, or it
        can be some arithmetic operation.  The type for the
        Arith constructor is recursive, which is perfectly
        legal in Haskell.  Arith creates a
        SymbolicManip out of an Op and
        two other SymbolicManip items.  Let's look at an
        example:
      
ghci>:l numsimple.hs[1 of 1] Compiling Main ( numsimple.hs, interpreted ) Ok, modules loaded: Main.ghci>Number 5Number 5ghci>:t Number 5Number 5 :: (Num t) => SymbolicManip tghci>:t Number (5::Int)Number (5::Int) :: SymbolicManip Intghci>Number 5 * Number 10Arith Mul (Number 5) (Number 10)ghci>(5 * 10)::SymbolicManip IntArith Mul (Number 5) (Number 10)ghci>(5 * 10 + 2)::SymbolicManip IntArith Plus (Arith Mul (Number 5) (Number 10)) (Number 2)
        You can see that we already have a very basic representation of
        expressions working.  Notice how Haskell "converted" 5 * 10
          + 2 into a SymbolicManip, and even
        handled order of evaluation properly.  This wasn't really a true
        conversion; SymbolicManip is a first-class number
        now.  Integer numeric literals are internally treated as being wrapped 
        in fromInteger anyway, so 5 is just as valid as
        a SymbolicManip Int as it as an
        Int.
      
        From here, then, our task is simple: extend the
        SymbolicManip type to be able to represent all the
        operations we will want to perform, implement instances of it for the
        other numeric typeclasses, and implement our own instance of Show
        for SymbolicManip that renders this tree in a more
        accessible fashion.
      
        Here is the completed num.hs, which was used with
        the ghci examples at the beginning of this chapter.  Let's
        look at this code one piece at a time.
      
-- file: ch13/num.hs
import Data.List
--------------------------------------------------
-- Symbolic/units manipulation
--------------------------------------------------
-- The "operators" that we're going to support
data Op = Plus | Minus | Mul | Div | Pow
        deriving (Eq, Show)
{- The core symbolic manipulation type.  It can be a simple number,
a symbol, a binary arithmetic operation (such as +), or a unary
arithmetic operation (such as cos)
Notice the types of BinaryArith and UnaryArith: it's a recursive
type.  So, we could represent a (+) over two SymbolicManips. -}
data SymbolicManip a = 
          Number a           -- Simple number, such as 5
        | Symbol String      -- A symbol, such as x
        | BinaryArith Op (SymbolicManip a) (SymbolicManip a)
        | UnaryArith String (SymbolicManip a)
          deriving (Eq)
        In this section of code, we define an Op
        that is identical to the one we used before.  We also define
        SymbolicManip, which is similar to what we
        used before.  In this version, we now support unary arithmetic
        operations (those which take only one parameter) such as
        abs or cos.  Next we
        define our instance of Num.
      
-- file: ch13/num.hs
{- SymbolicManip will be an instance of Num.  Define how the Num
operations are handled over a SymbolicManip.  This will implement things
like (+) for SymbolicManip. -}
instance Num a => Num (SymbolicManip a) where
    a + b = BinaryArith Plus a b
    a - b = BinaryArith Minus a b
    a * b = BinaryArith Mul a b
    negate a = BinaryArith Mul (Number (-1)) a
    abs a = UnaryArith "abs" a
    signum _ = error "signum is unimplemented"
    fromInteger i = Number (fromInteger i)
        This is pretty straightforward and also similar to our earlier
        code.  Note that earlier we weren't able to properly support
        abs, but now with the
        UnaryArith constructor, we can.  Next we
        define some more instances.
      
-- file: ch13/num.hs
{- Make SymbolicManip an instance of Fractional -}
instance (Fractional a) => Fractional (SymbolicManip a) where
    a / b = BinaryArith Div a b
    recip a = BinaryArith Div (Number 1) a
    fromRational r = Number (fromRational r)
{- Make SymbolicManip an instance of Floating -}
instance (Floating a) => Floating (SymbolicManip a) where
    pi = Symbol "pi"
    exp a = UnaryArith "exp" a
    log a = UnaryArith "log" a
    sqrt a = UnaryArith "sqrt" a
    a ** b = BinaryArith Pow a b
    sin a = UnaryArith "sin" a
    cos a = UnaryArith "cos" a
    tan a = UnaryArith "tan" a
    asin a = UnaryArith "asin" a
    acos a = UnaryArith "acos" a
    atan a = UnaryArith "atan" a
    sinh a = UnaryArith "sinh" a
    cosh a = UnaryArith "cosh" a
    tanh a = UnaryArith "tanh" a
    asinh a = UnaryArith "asinh" a
    acosh a = UnaryArith "acosh" a
    atanh a = UnaryArith "atanh" a
        This section of code defines some fairly straightforward
        instances of Fractional and Floating.  Now let's work on
        converting our expressions to strings for display.
      
-- file: ch13/num.hs
{- Show a SymbolicManip as a String, using conventional
algebraic notation -}
prettyShow :: (Show a, Num a) => SymbolicManip a -> String
-- Show a number or symbol as a bare number or serial
prettyShow (Number x) = show x
prettyShow (Symbol x) = x
prettyShow (BinaryArith op a b) =
    let pa = simpleParen a
        pb = simpleParen b
        pop = op2str op
        in pa ++ pop ++ pb
prettyShow (UnaryArith opstr a) = 
    opstr ++ "(" ++ show a ++ ")"
op2str :: Op -> String
op2str Plus = "+"
op2str Minus = "-"
op2str Mul = "*"
op2str Div = "/"
op2str Pow = "**"
{- Add parenthesis where needed.  This function is fairly conservative
and will add parenthesis when not needed in some cases.
    
Haskell will have already figured out precedence for us while building
up the SymbolicManip. -}
simpleParen :: (Show a, Num a) => SymbolicManip a -> String
simpleParen (Number x) = prettyShow (Number x)
simpleParen (Symbol x) = prettyShow (Symbol x)
simpleParen x@(BinaryArith _ _ _) = "(" ++ prettyShow x ++ ")"
simpleParen x@(UnaryArith _ _) = prettyShow x
{- Showing a SymbolicManip calls the prettyShow function on it -}
instance (Show a, Num a) => Show (SymbolicManip a) where
    show a = prettyShow a
        We start by defining a function
        prettyShow.  It renders an expression using
        conventional style.  The algorithm is fairly simple: bare
        numbers and symbols are rendered bare; binary arithmetic is
        rendered with the two sides plus the operator in the middle,
        and of course we handle the unary operators as well.
        op2str simply converts an
        Op to a String.  In
        simpleParen, we have a quite conservative
        algorithm that adds parenthesis to keep precedence clear in
        the result.  Finally, we make SymbolicManip
        an instance of Show and use prettyShow to
        accomplish that.  Now let's implement an algorithm that
        converts an expression to s string in RPN format.
      
-- file: ch13/num.hs
{- Show a SymbolicManip using RPN.  HP calculator users may
find this familiar. -}
rpnShow :: (Show a, Num a) => SymbolicManip a -> String
rpnShow i =
    let toList (Number x) = [show x]
        toList (Symbol x) = [x]
        toList (BinaryArith op a b) = toList a ++ toList b ++
           [op2str op]
        toList (UnaryArith op a) = toList a ++ [op]
        join :: [a] -> [[a]] -> [a]
        join delim l = concat (intersperse delim l)
    in join " " (toList i)Fans of RPN will note how much simpler this algorithm is compared to the algorithm to render with conventional notation. In particular, we didn't have to worry about where to add parenthesis, because RPN can, by definition, only be evaluated one way. Next, let's see how we might implement a function to do some rudimentary simplification on expressions.
-- file: ch13/num.hs
{- Perform some basic algebraic simplifications on a SymbolicManip. -}
simplify :: (Num a) => SymbolicManip a -> SymbolicManip a
simplify (BinaryArith op ia ib) = 
    let sa = simplify ia
        sb = simplify ib
        in
        case (op, sa, sb) of 
                (Mul, Number 1, b) -> b
                (Mul, a, Number 1) -> a
                (Mul, Number 0, b) -> Number 0
                (Mul, a, Number 0) -> Number 0
                (Div, a, Number 1) -> a
                (Plus, a, Number 0) -> a
                (Plus, Number 0, b) -> b
                (Minus, a, Number 0) -> a
                _ -> BinaryArith op sa sb
simplify (UnaryArith op a) = UnaryArith op (simplify a)
simplify x = xThis function is pretty simple. For certain binary arithmetic operations -- for instance, multiplying any value by 1 -- we are able to easily simplify the situation. We begin by obtaining simplified versions of both sides of the calculation (this is where recursion hits) and then simplify the result. We have little to do with unary operators, so we just simplify the expression they act upon.
From here on, we will add support for units of measure to our established library. This will let us represent quantities such as "5 meters". We start, as before, by defining a type.
-- file: ch13/num.hs
{- New data type: Units.  A Units type contains a number
and a SymbolicManip, which represents the units of measure.
A simple label would be something like (Symbol "m") -}
data Num a => Units a = Units a (SymbolicManip a)
           deriving (Eq)
        So, a Units contains a number and a label.
        The label is itself a SymbolicManip.  Next,
        it will probably come as no surprise to see an instance of
        Num for Units.
      
-- file: ch13/num.hs
{- Implement Units for Num.  We don't know how to convert between
arbitrary units, so we generate an error if we try to add numbers with
different units.  For multiplication, generate the appropriate
new units. -}
instance (Num a) => Num (Units a) where
    (Units xa ua) + (Units xb ub) 
        | ua == ub = Units (xa + xb) ua
        | otherwise = error "Mis-matched units in add or subtract"
    (Units xa ua) - (Units xb ub) = (Units xa ua) + (Units (xb * (-1)) ub)
    (Units xa ua) * (Units xb ub) = Units (xa * xb) (ua * ub)
    negate (Units xa ua) = Units (negate xa) ua
    abs (Units xa ua) = Units (abs xa) ua
    signum (Units xa _) = Units (signum xa) (Number 1)
    fromInteger i = Units (fromInteger i) (Number 1)
        Now it may become clear why we use a
        SymbolicManip instead of a String to
        store the unit of measure.  As calculations such as
        multiplication occur, the unit of measure also changes.  For
        instance, if we multiply 5 meters by 2 meters, we obtain 10
        square meters.  We force the units for addition to match, and
        implement subtraction in terms of addition.  Let's look at
        more typeclass instances for Units.
      
-- file: ch13/num.hs
{- Make Units an instance of Fractional -}
instance (Fractional a) => Fractional (Units a) where
    (Units xa ua) / (Units xb ub) = Units (xa / xb) (ua / ub)
    recip a = 1 / a
    fromRational r = Units (fromRational r) (Number 1)
{- Floating implementation for Units.
Use some intelligence for angle calculations: support deg and rad
-}
instance (Floating a) => Floating (Units a) where
    pi = (Units pi (Number 1))
    exp _ = error "exp not yet implemented in Units"
    log _ = error "log not yet implemented in Units"
    (Units xa ua) ** (Units xb ub) 
        | ub == Number 1 = Units (xa ** xb) (ua ** Number xb)
        | otherwise = error "units for RHS of ** not supported"
    sqrt (Units xa ua) = Units (sqrt xa) (sqrt ua)
    sin (Units xa ua) 
        | ua == Symbol "rad" = Units (sin xa) (Number 1)
        | ua == Symbol "deg" = Units (sin (deg2rad xa)) (Number 1)
        | otherwise = error "Units for sin must be deg or rad"
    cos (Units xa ua) 
        | ua == Symbol "rad" = Units (cos xa) (Number 1)
        | ua == Symbol "deg" = Units (cos (deg2rad xa)) (Number 1)
        | otherwise = error "Units for cos must be deg or rad"
    tan (Units xa ua)
        | ua == Symbol "rad" = Units (tan xa) (Number 1)
        | ua == Symbol "deg" = Units (tan (deg2rad xa)) (Number 1)
        | otherwise = error "Units for tan must be deg or rad"
    asin (Units xa ua) 
        | ua == Number 1 = Units (rad2deg $ asin xa) (Symbol "deg")
        | otherwise = error "Units for asin must be empty"
    acos (Units xa ua)
        | ua == Number 1 = Units (rad2deg $ acos xa) (Symbol "deg")
        | otherwise = error "Units for acos must be empty"
    atan (Units xa ua)
        | ua == Number 1 = Units (rad2deg $ atan xa) (Symbol "deg")
        | otherwise = error "Units for atan must be empty"
    sinh = error "sinh not yet implemented in Units"
    cosh = error "cosh not yet implemented in Units"
    tanh = error "tanh not yet implemented in Units"
    asinh = error "asinh not yet implemented in Units"
    acosh = error "acosh not yet implemented in Units"
    atanh = error "atanh not yet implemented in Units"We didn't supply implementations for every function, but quite a few have been defined. Now let's define a few utility functions for working with units.
-- file: ch13/num.hs
{- A simple function that takes a number and a String and returns an
appropriate Units type to represent the number and its unit of measure -}
units :: (Num z) => z -> String -> Units z
units a b = Units a (Symbol b)
{- Extract the number only out of a Units type -}
dropUnits :: (Num z) => Units z -> z
dropUnits (Units x _) = x
                                                    
{- Utilities for the Unit implementation -}
deg2rad x = 2 * pi * x / 360
rad2deg x = 360 * x / (2 * pi)
        First, we have units, which makes it easy
        to craft simple expressions.  It's faster to say
        units 5 "m" than Units 5 (Symbol
        "m").  We also have a corresponding
        dropUnits, which discards the unit of
        measure and returns the embedded bare Num.  Finally, we
        define some functions for use by our earlier instances to
        convert between degrees and radians.  Next, we just define a
        Show instance for Units.
      
-- file: ch13/num.hs
{- Showing units: we show the numeric component, an underscore,
then the prettyShow version of the simplified units -}
instance (Show a, Num a) => Show (Units a) where
    show (Units xa ua) = show xa ++ "_" ++ prettyShow (simplify ua)
        That was simple.  For one last piece, we define a variable
        test to experiment with.
      
-- file: ch13/num.hs test :: (Num a) => a test = 2 * 5 + 3
        So, looking back over all this code, we have done what we set out to accomplish: implemented more
        instances for SymbolicManip.  We have also
        introduced another type called Units which stores
        a number and a unit of measure.  We implement several show-like
        functions which render the SymbolicManip or
        Units in different ways.  
      
There is one other point that this example drives home. Every language -- even those with objects and overloading -- has some parts of the language that are special in some way. In Haskell, the "special" bits are extremely small. We have just developed a new representation for something as fundamental as a number, and it has been really quite easy. Our new type is a first-class type, and the compiler knows what functions to use with it at compile time. Haskell takes code reuse and interchangability to the extreme. It is easy to make code generic and work on things of many different types. It's also easy to make up new types and make them automatically be first-class features of the system.
Remember our ghci examples at the beginning of the chapter? All of them were made with the code in this example. You might want to try them out for yourself and see how they work.
In an imperative language, appending two lists is cheap and easy. Here's a simple C structure in which we maintain a pointer to the head and tail of a list.
struct list {
    struct node *head, *tail;
};When we have one list, and want to append another
      list onto its end, we modify the last node of the existing list
      to point to its head node, then update its
      tail pointer to point to its tail
      node.
Obviously, this approach is off limits to us in Haskell if
      we want to stay pure.  Since pure data is immutable, we can't go
      around modifying lists in place.  Haskell's
      (++) operator appends two lists by creating
      a new one.
-- file: ch13/Append.hs (++) :: [a] -> [a] -> [a] (x:xs) ++ ys = x : xs ++ ys _ ++ ys = ys
From inspecting the code, we can see that the cost of creating a new list depends on the length of the initial list[32] .
We often need to append lists over and over, to construct one big list. For instance, we might be generating the contents of a web page as a String, emitting a chunk at a time as we traverse some data structure. Each time we have a chunk of markup to add to the page, we will naturally want to append it onto the end of our existing String.
If a single append has a cost proportional to the length of the initial list, and each repeated append makes the initial list longer, we end up in an unhappy situation: the cost of all of the repeated appends is proportional to the square of the length of the final list.
To understand this, let's dig in a little.  The
      (++) operator is right associative.
ghci>:info (++)(++) :: [a] -> [a] -> [a] -- Defined in GHC.Base infixr 5 ++
This means that a Haskell implementation will evaluate the
      expression "a" ++ "b" ++ "c" as if we had put
      parentheses around it as follows: "a" ++ ("b" ++
	"c").  This makes good performance sense, because it
      keeps the left operand as short as possible.
When we repeatedly append onto the end of a list, we defeat
      this associativity.  Let's say we start with the list
      "a" and append "b", and save the
      result as our new list.  If we later append "c"
      onto this new list, our left operand is now "ab".
      In this scheme, every time we append, our left operand gets
      longer.
Meanwhile, the imperative programmers are cackling with glee, because the cost of their repeated appends only depends on the number of them that they perform. They have linear performance; ours is quadratic.
When something as common as repeated appending of lists imposes such a performance penalty, it's time to look at the problem from another angle.
The expression ("a"++) is a section, a
      partially applied function.  What is its type?
ghci>:type ("a" ++)("a" ++) :: [Char] -> [Char]
Since this is a function, we can use the
      (.) operator to compose it with another
      section, let's say ("b"++).
ghci>:type ("a" ++) . ("b" ++)("a" ++) . ("b" ++) :: [Char] -> [Char]
Our new function has the same type. What happens if we stop composing functions, and instead provide a String to the function we've created?
ghci>let f = ("a" ++) . ("b" ++)ghci>f []"ab"
We've appended the strings!  We're using these partially
      applied functions to store data, which we can retrieve by
      providing an empty list.  Each partial application of
      (++) and (.)
      represents an append, but it doesn't
      actually perform the append.
There are two very interesting things about this approach.
      The first is that the cost of a partial application is constant,
      so the cost of many partial applications is linear.  The second
      is that when we finally provide a [] value to
      unlock the final list from its chain of partial applications,
      application proceeds from right to left.  This keeps the left
      operand of (++) small, and so the overall
      cost of all of these appends is linear, not quadratic.
By choosing an unfamiliar data representation, we've avoided a nasty performance quagmire, while gaining a new perspective on the usefulness of treating functions as data. By the way, this is an old trick, and it's usually called a difference list.
We're not yet finished, though.  As appealing as difference
      lists are in theory, ours won't be very pleasant in practice if
      we leave all the plumbing of (++),
      (.), and partial application exposed.  We
      need to turn this mess into something pleasant to work
      with.
Our first step is to use a newtype declaration to hide
	the underlying type from our users.  We'll create a new type,
	and call it DList.  Like a regular list, it will
	be a parameterised type.
-- file: ch13/DList.hs
newtype DList a = DL {
      unDL :: [a] -> [a]
    }The unDL function is our
	deconstructor, which removes the DL constructor.
	When we go back and decide what we want to export from our
	module, we will omit our data constructor and deconstruction
	function, so the DList type will be completely
	opaque to our users.  They'll only be able to work with the
	type using the other functions we export.
-- file: ch13/DList.hs append :: DList a -> DList a -> DList a append xs ys = DL (unDL xs . unDL ys)
Our append function may seem a little
	complicated, but it's just performing some book-keeping
	around the same use of the (.) operator that
	we demonstrated earlier.  To compose our functions, we must
	first unwrap them from their DL constructor,
	hence the uses of unDL.  We then re-wrap
	the resulting function with the DL constructor so
	that it will have the right type.
Here's another way of writing the same function, in which
	we perform the unwrapping of xs and
	ys via pattern matching.
-- file: ch13/DList.hs append' :: DList a -> DList a -> DList a append' (DL xs) (DL ys) = DL (xs . ys)
Our DList type won't be much use if we can't convert back and forth between the DList representation and a regular list.
-- file: ch13/DList.hs fromList :: [a] -> DList a fromList xs = DL (xs ++) toList :: DList a -> [a] toList (DL xs) = xs []
Once again, compared to the original versions of these functions that we wrote, all we're doing is a little book-keeping to hide the plumbing.
If we want to make DList useful as a substitute for regular lists, we need to provide some more of the common list operations.
-- file: ch13/DList.hs empty :: DList a empty = DL id -- equivalent of the list type's (:) operator cons :: a -> DList a -> DList a cons x (DL xs) = DL ((x:) . xs) infixr `cons` dfoldr :: (a -> b -> b) -> b -> DList a -> b dfoldr f z xs = foldr f z (toList xs)
Although the DList approach makes
	appends cheap, not all list-like operations are easily
	available.  The head function has
	constant cost for lists.  Our DList equivalent
	requires that we convert the entire DList to a
	regular list, so it is much more expensive than its list
	counterpart: its cost is linear in the number of appends we
	have performed to construct the DList.
-- file: ch13/DList.hs
safeHead :: DList a -> Maybe a
safeHead xs = case toList xs of
                (y:_) -> Just y
                _ -> NothingTo support an equivalent of map, we
	can make our DList type a functor.
-- file: ch13/DList.hs
dmap :: (a -> b) -> DList a -> DList b
dmap f = dfoldr go empty
    where go x xs = cons (f x) xs
instance Functor DList where
    fmap = dmapOnce we decide that we have written enough equivalents of list functions, we go back to the top of our source file, and add a module header.
-- file: ch13/DList.hs
module DList
    (
      DList
    , fromList
    , toList
    , empty
    , append
    , cons
    , dfoldr
    ) whereIn abstract algebra, there exists a simple abstract structure called a monoid. Many mathematical objects are monoids, because the “bar to entry” is very low. In order to be considered a monoid, an object must have two properties.
The rules for monoids don't say what the binary operator must do, merely that such an operator must exist. Because of this, lots of mathematical objects are monoids. If we take addition as the binary operator and zero as the identity value, integers form a monoid. With multiplication as the binary operator and one as the identity value, integers form a different monoid.
Monoids are ubiquitous in Haskell[33].  The Monoid typeclass is defined in
	the Data.Monoid module.
-- file: ch13/Monoid.hs
class Monoid a where
    mempty  :: a                -- the identity
    mappend :: a -> a -> a      -- associative binary operatorIf we take (++) as the binary
	operator and [] as the identity, lists form a
	monoid.
-- file: ch13/Monoid.hs
instance Monoid [a] where
    mempty  = []
    mappend = (++)Since lists and DLists are so closely related, it follows that our DList type must be a monoid, too.
-- file: ch13/DList.hs
instance Monoid (DList a) where
    mempty = empty
    mappend = appendLet's try our the methods of the Monoid type class in ghci.
ghci>"foo" `mappend` "bar""foobar"ghci>toList (fromList [1,2] `mappend` fromList [3,4])[1,2,3,4]ghci>mempty `mappend` [1][1]
We will have more to say about difference lists and their monoidal nature in the section called “The writer monad and lists”.
Both Haskell's built-in list type and the DList
      type that we defined above have poor performance characteristics
      under some circumstances.  The Data.Sequence module
      defines a Seq container type that gives good
      performance for a wider variety of operations.
As with other modules, Data.Sequence is
      intended to be used via qualified import.
-- file: ch13/DataSequence.hs import qualified Data.Sequence as Seq
We can construct an empty Seq using
      empty, and a single-element container using
      singleton.
ghci>Seq.emptyLoading package array-0.1.0.0 ... linking ... done. Loading package containers-0.1.0.1 ... linking ... done. fromList []ghci>Seq.singleton 1fromList [1]
We can create a Seq from a list using
      fromList.
ghci>let a = Seq.fromList [1,2,3]
The Data.Sequence module provides some
      constructor functions in the form of operators. When we perform
      a qualified import, we must qualify the name of an operator in
      our code, which is ugly.
ghci>1 Seq.<| Seq.singleton 2fromList [1,2]
If we import the operators explicitly, we can avoid the need to qualify them.
-- file: ch13/DataSequence.hs import Data.Sequence ((><), (<|), (|>))
By removing the qualification from the operator, we improve the readability of our code.
ghci>Seq.singleton 1 |> 2fromList [1,2]
A useful way to remember the (<|)
      and (|>) functions is that the
      “arrow” points to the element we're adding to the
      Seq.  The element will be added on the side to which the
      arrow points: (<|) adds on the left,
      (|>) on the right.
Both adding on the left and adding on the right are
      constant-time operations.  Appending two Seqs is
      also cheap, occurring in time proportional to the logarithm of
      whichever is shorter.  To append, we use the
      (><) operator.
ghci>let left = Seq.fromList [1,3,3]ghci>let right = Seq.fromList [7,1]ghci>left >< rightfromList [1,3,3,7,1]
If we want to create a list from a Seq, we must
      use the Data.Foldable module, which is best
      imported qualified.
-- file: ch13/DataSequence.hs import qualified Data.Foldable as Foldable
This module defines a typeclass, Foldable, which Seq implements.
ghci>Foldable.toList (Seq.fromList [1,2,3])[1,2,3]
If we want to fold over a Seq, we use the fold
      functions from the Data.Foldable module.
ghci>Foldable.foldl' (+) 0 (Seq.fromList [1,2,3])6
The Data.Sequence module provides a number of
      other useful list-like functions.  Its documentation is very
      thorough, giving time bounds for each operation.
If Seq has so many desirable characteristics, why is it not the default sequence type? Lists are simpler and have less overhead, and so quite often they are good enough for the task at hand. They are also well suited to a lazy setting, where Seq does not fare well.
[31] The type we use for the key must be a
      member of the Eq typeclass.
[32] Non-strict evaluation makes the cost calculation more subtle. We only pay for an append if we actually use the resulting list. Even then, we only pay for as much as we actually use.
[33] Indeed, monoids are ubiquitous throughout programming. The difference is that in Haskell, we recognize them, and talk about them.