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Monadic Parsing in of Nottingham
Erik Meijer
University of Utrecht
1 Introduction
This paper is a tutorial on defining recursive descent parsers in Haskell. In the spirit
of one-stop shopping , the paper combines material from three areas into a single
source. The three areas are functional parsers (Burge, 1975; Wadler, 1985; Hutton,
1992; Fokker, 1995), the use of monads to structure functional programs (Wadler,
1990; Wadler, 1992a; Wadler, 1992b), and the use of special syntax for monadic
programs in Haskell (Jones, 1995; Peterson et al. , 1996). More specifically, the
paper shows how to define monadic parsers using do notation in Haskell.
Of course, recursive descent parsers defined by hand lack the efficiency of bottom-
up parsers generated by machine (Aho et al., 1986; Mogensen, 1993; Gill & Marlow,
1995). However, for many research applications, a simple recursive descent parser
is perfectly sufficient. Moreover, while parser generators typically offer a fixed set
of combinators for describing grammars, the method described here is completely
extensible: parsers are first-class values, and we have the full power of Haskell
available to define new combinators for special applications. The method is also an
excellent illustration of the elegance of functional programming.
The paper is targeted at the level of a good undergraduate student who is familiar
with Haskell, and has completed a grammars and parsing course. Some knowledge
of functional parsers would be useful, but no experience with monads is assumed.
A Haskell library derived from the paper is available on the web from:
http://www.cs.nott.ac.uk/Department/Staff/gmh/bib.html#pearl
2 A type for parsers
We begin by defining a type for parsers:
newtype Parser a = Parser (String -> [(a,String)])
That is, a parser is a function that takes a string of characters as its argument, and
returns a list of results. The convention is that the empty list of results denotes
failure of a parser, and that non-empty lists denote success. In the case of success,
each result is a pair whose first component is a value of type a produced by parsing
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and processing a prefix of the argument string, and whose second component is the
unparsed suffix of the argument string. Returning a list of results allows us to build
parsers for ambiguous grammars, with many results being returned if the argument
string can be parsed in many different ways.
3 A monad of parsers
The first parser we define is item, which successfully consumes the first character
if the argument string is non-empty, and fails otherwise:
item :: Parser Char
item = Parser (\cs -> case cs of
(c:cs) -> [(c,cs)])
Next we define two combinators that reflect the monadic nature of parsers. In
Haskell, the notion of a monad is captured by a built-in class definition:
class Monad m where
return :: a -> m a
(>>=) :: m a -> (a -> m b) -> m b
That is, a type constructor m is a member of the class Monad if it is equipped with
return and (>>=) functions of the specified types. The type constructor Parser
can be made into an instance of the Monad class as follows:
instance Monad Parser where
return a = Parser (\cs -> [(a,cs)])
p >>= f = Parser (\cs -> concat [parse (f a) cs’ |
(a,cs’) <- parse p cs])
The parser return a succeeds without consuming any of the argument string, and
returns the single value a. The (>>=) operator is a sequencing operator for parsers.
Using a deconstructor function for parsers defined by parse (Parser p) = p, the
parser p >>= f first applies the parser p to the argument string cs to give a list of
results of the form (a,cs’), where a is a value and cs’ is a string. For each such
pair, f a is a parser which is applied to the string cs’. The result is a list of lists,
which is then concatenated to give the final list of results.
The return and (>>=) functions for parsers satisfy some simple laws:
return a >>= f = f a
p >>= return = p
p >>= (\a -> (f a >>= g)) = (p >>= (\a -> f a)) >>= g
In fact, these laws must hold for any monad, not just the special case of parsers.
The laws assert that — modulo the fact that the right argument to (>>=) involves
a binding operation — return is a left and right unit for (>>=), and that (>>=) is
associative. The unit laws allow some parsers to be simplified, and the associativity
law allows parentheses to be eliminated in repeated sequencings.
Functional pearls 3
4 The do notation
A typical parser built using (>>=) has the following structure:
p1 >>= \a1 ->
p2 >>= \a2 ->
pn >>= \an ->
f a1 a2 … an
Such a parser has a natural operational reading: apply parser p1 and call its result
value a1; then apply parser p2 and call its result value a2; …; then apply parser
pn and call its result value an; and finally, combine all the results by applying a
semantic action f. For most parsers, the semantic action will be of the form return
(g a1 a2 … an) for some function g, but this is not true in general. For example,
it may be necessary to parse more of the argument string before a result can be
returned, as is the case for the chainl1 combinator defined later on.
Haskell provides a special syntax for defining parsers of the above shape, allowing
them to be expressed in the following, more appealing, form:
do a1 <- p1 f a1 a2 ... an This notation can also be used on a single line if preferred, by making use of parentheses and semi-colons, in the following manner: do {a1 <- p1; a2 <- p2; ...; an <- pn; f a1 a2 ... an} In fact, the do notation in Haskell can be used with any monad, not just parsers. The subexpressions ai <- pi are called generators, since they generate values for the variables ai. In the special case when we are not interested in the values produced by a generator ai <- pi, the generator can be abbreviated simply by pi. Example: a parser that consumes three characters, throws away the second char- acter, and returns the other two as a pair, can be defined as follows: p :: Parser (Char,Char) p = do {c <- item; item; d <- item; return (c,d)} 5 Choice combinators We now define two combinators that extend the monadic nature of parsers. In Haskell, the notion of a monad with a zero, and a monad with a zero and a plus are captured by two built-in class definitions: class Monad m => MonadZero m where
zero :: m a
4 and Erik Meijer
class MonadZero m => MonadPlus m where
(++) :: m a -> m a -> m a
That is, a type constructor m is a member of the class MonadZero if it is a member
of the class Monad, and if it is also equipped with a value zero of the specified type.
In a similar way, the class MonadPlus builds upon the class MonadZero by adding
a (++) operation of the specified type. The type constructor Parser can be made
into instances of these two classes as follows:
instance MonadZero Parser where
zero = Parser (\cs -> [])
instance MonadPlus Parser where
p ++ q = Parser (\cs -> parse p cs ++ parse q cs)
The parser zero fails for all argument strings, returning no results. The (++) oper-
ator is a (non-deterministic) choice operator for parsers. The parser p ++ q applies
both parsers p and q to the argument string, and appends their list of results.
The zero and (++) operations for parsers satisfy some simple laws:
zero ++ p = p
p ++ zero = p
p ++ (q ++ r) = (p ++ q) ++ r
These laws must in fact hold for any monad with a zero and a plus. The laws assert
that zero is a left and right unit for (++), and that (++) is associative. For the
special case of parsers, it can also be shown that — modulo the binding involved
with (>>=) — zero is the left and right zero for (>>=), that (>>=) distributes
through (++) on the right, and (provided we ignore the order of results returned
by parsers) that (>>=) also distributes through (++) on the left:
zero >>= f = zero
p >>= const zero = zero
(p ++ q) >>= f = (p >>= f) ++ (q >>= f)
p >>= (\a -> f a ++ g a) = (p >>= f) ++ (p >>= g)
The zero laws allow some parsers to be simplified, and the distribution laws allow
the efficiency of some parsers to be improved.
Parsers built using (++) return many results if the argument string can be parsed
in many different ways. In practice, we are normally only interested in the first
result. For this reason, we define a (deterministic) choice operator (+++) that has
the same behaviour as (++), except that at most one result is returned:
(+++) :: Parser a -> Parser a -> Parser a
p +++ q = Parser (\cs -> case parse (p ++ q) cs of
(x:xs) -> [x])
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All the laws given above for (++) also hold for (+++). Moreover, for the case of
(+++), the precondition of the left distribution law is automatically satisfied.
The item parser consumes single characters unconditionally. To allow conditional
parsing, we define a combinator sat that takes a predicate, and yields a parser that
consumes a single character if it satisfies the predicate, and fails otherwise:
sat :: (Char -> Bool) -> Parser Char
sat p = do {c <- item; if p c then return c else zero} Example: a parser for specific characters can be defined as follows: char :: Char -> Parser Char
char c = sat (c ==)
In a similar way, by supplying suitable predicates to sat, we can define parsers for
digits, lower-case letters, upper-case letters, and so on.
6 Recursion combinators
A number of useful parser combinators can be defined recursively. Most of these
combinators can in fact be defined for arbitrary monads with a zero and a plus,
but for clarity they are defined below for the special case of parsers.
• Parse a specific string:
string :: String -> Parser String
string “” = return “”
string (c:cs) = do {char c; string cs; return (c:cs)}
• Parse repeated applications of a parser p; the many combinator permits zero
or more applications of p, while many1 permits one or more:
many :: Parser a -> Parser [a]
many p = many1 p +++ return []
many1 :: Parser a -> Parser [a]
many1 p = do {a <- p; as <- many p; return (a:as)} • Parse repeated applications of a parser p, separated by applications of a parser sep whose result values are thrown away: sepby :: Parser a -> Parser b -> Parser [a]
p ‘sepby‘ sep = (p ‘sepby1‘ sep) +++ return []
sepby1 :: Parser a -> Parser b -> Parser [a]
p ‘sepby1‘ sep = do a <- p as <- many (do {sep; p}) return (a:as) • Parse repeated applications of a parser p, separated by applications of a parser op whose result value is an operator that is assumed to associate to the left, and which is used to combine the results from the p parsers: 6 and Erik Meijer chainl :: Parser a -> Parser (a -> a -> a) -> a -> Parser a
chainl p op a = (p ‘chainl1‘ op) +++ return a
chainl1 :: Parser a -> Parser (a -> a -> a) -> Parser a
p ‘chainl1‘ op = do {a <- p; rest a} rest a = (do f <- op rest (f a b)) +++ return a Combinators chainr and chainr1 that assume the parsed operators associate to the right can be defined in a similar manner. 7 Lexical combinators Traditionally, parsing is usually preceded by a lexical phase that transforms the argument string into a sequence of tokens. However, the lexical phase can be avoided by defining suitable combinators. In this section we define combinators to handle the use of space between tokens in the argument string. Combinators to handle other lexical issues such as comments and keywords can easily be defined too. • Parse a string of spaces, tabs, and newlines: space :: Parser String space = many (sat isSpace) • Parse a token using a parser p, throwing away any trailing space: token :: Parser a -> Parser a
token p = do {a <- p; space; return a} • Parse a symbolic token: symb :: String -> Parser String
symb cs = token (string cs)
• Apply a parser p, throwing away any leading space:
apply :: Parser a -> String -> [(a,String)]
apply p = parse (do {space; p})
We illustrate the combinators defined in this article with a simple example. Consider
the standard grammar for arithmetic expressions built up from single digits using
Functional pearls 7
the operators +, -, * and /, together with parentheses (Aho et al., 1986):
expr ::= expr addop term | term
term ::= term mulop factor | factor
factor ::= digit | ( expr )
digit ::= 0 | 1 | . . . | 9
addop ::= + | –
mulop ::= * | /
Using the chainl1 combinator to implement the left-recursive production rules for
expr and term, this grammar can be directly translated into a Haskell program
that parses expressions and evaluates them to their integer value:
expr :: Parser Int
addop :: Parser (Int -> Int -> Int)
mulop :: Parser (Int -> Int -> Int)
expr = term ‘chainl1‘ addop
term = factor ‘chainl1‘ mulop
factor = digit +++ do {symb “(“; n <- expr; symb ")"; return n} digit = do {x <- token (sat isDigit); return (ord x - ord ’0’)} addop = do {symb "+"; return (+)} +++ do {symb "-"; return (-)} mulop = do {symb "*"; return (*)} +++ do {symb "/"; return (div)} For example, evaluating apply expr " 1 - 2 * 3 + 4 " gives the singleton list of results [(-1,"")], which is the desired behaviour. 9 Acknowledgements Thanks for due to , , . Jones, , and for their useful comments on the many drafts of this article. 8 and Erik Meijer References Aho, A., Sethi, R., & Ullman, J. (1986). Compilers — principles, techniques and tools. Addison-Wesley. Burge, W.H. (1975). Recursive programming techniques. Addison-Wesley. Fokker, Jeroen. 1995 (May). Functional parsers. Lecture notes of the Baastad Spring school on functional programming. Gill, Andy, & Marlow, Simon. 1995 (Jan.). Happy: the parser generator for Haskell. University of Glasgow. Hutton, Graham. (1992). Higher-order functions for parsing. Journal of functional pro- gramming, 2(3), 323–343. Jones, . (1995). A system of constructor classes: overloading and implicit higher- order polymorphism. Journal of functional programming, 5(1), 1–35. Mogensen, Torben. (1993). Ratatosk: a parser generator and scanner generator for Gofer. University of Copenhagen (DIKU). Peterson, John, et al. . 1996 (May). The Haskell language report, version 1.3. Research Report YALEU/DCS/RR-1106. Yale University. Wadler, Philip. (1985). How to replace failure by a list of successes. Proc. conference on functional programming and computer architecture. Springer–Verlag. Wadler, Philip. (1990). Comprehending monads. Proc. ACM conference on Lisp and functional programming. Wadler, Philip. (1992a). The essence of functional programming. Proc. principles of programming languages. Wadler, Philip. (1992b). Monads for functional programming. Broy, Manfred (ed), Proc. Marktoberdorf Summer school on program design calculi. Springer–Verlag. 程序代写 CS代考 加微信: powcoder QQ: 1823890830 Email: powcoder@163.com