The following routine is a minor and simplified change of the official documentation, "Tracing a parser"“ parser tracing wrapper.
let (<!>) (parser: Parser<_,USER_STATE>) label : Parser<_,USER_STATE> =
fun stream ->
do stream.UserState <- stream.UserState // <= works if commented out!
let reply = parser stream
reply
This wrapper allows inspection of reply as parsers execute and the updating of stream.UserState as needed.
NOTE: this code just copies stream.UserState onto itself, effectively doing nothing, because that is the minimum operation for the following error. The official documentation manipulating stream.UserState ("Recursive grammers with nesting restrictions”) manipulates stream.UserState much more...
Commenting out do stream.UserState <- stream.UserState at line 3 allows both repeating (list-producing) and non-repeating FParsec primitives to succeed. For these list-producing primitives the last subordinate parser failure is unwound and the application of, for example, many succeeds.
If parser in the above wrapper is NOT an FParsec primitive that creates a list of results (like many or sepEndBy), from the repeated application of subordinate parsers then this code parses successfully.
If parser IS an FParsec repeating primitive (e.g. many or sepEndBy), then the failure of the subordinate parser application is passed back out as the failure also of the repeating FParsec primitive - an unexpected failure.
Why does including do stream.UserState <- stream.UserState cause FParsec primitives like many to fail?
EDIT1: Please note that the FParsec documentation does an assignment to stream.UserState as done in this question. #brianbern, I don't understand from your post how what I am doing is wrong given the documentation. Thanks!
How does one assign to stream.UserState without breaking calls to the FParsec many primitive?
The reason this happens is that the setter for CharStream.UserState increments the stream's StateTag as a side-effect. From the FParsec source code:
public TUserState UserState {
get { return _UserState; }
set { _UserState = value; ++StateTag; }
}
So when you assign the stream's UserState to itself, it's not the same as doing nothing.
UPDATE: The documentation for the “many” parser states:
The parser many p repeatedly applies the parser p until p fails. It returns a list of the results returned by p. At the end of the sequence p must fail without changing the parser state and without signalling a FatalError, otherwise many p will fail with the error reported by p.
The example in the FParsec documentation doesn't modify the parser state at the end of the sequence, but your example parser modifies the parser state every time it is called.
Related
Could someone help me with using context free grammars. Up until now I've used regular expressions to remove comments, block comments and empty lines from a string so that it can be used to count the PLOC. This seems to be extremely slow so I was looking for a different more efficient method.
I saw the following post: What is the best way to ignore comments in a java file with Rascal?
I have no idea how to use this, the help doesn't get me far as well. When I try to define the line used in the post I immediately get an error.
lexical SingleLineComment = "//" ~[\n] "\n";
Could someone help me out with this and also explain a bit about how to setup such a context free grammar and then to actually extract the wanted data?
Kind regards,
Bob
First this will help: the ~ in Rascal CFG notation is not in the language, the negation of a character class is written like so: ![\n].
To use a context-free grammar in Rascal goes in three steps:
write it, like for example the syntax definition of the Func language here: http://docs.rascal-mpl.org/unstable/Recipes/#Languages-Func
Use it to parse input, like so:
// This is the basic parse command, but be careful it will not accept spaces and newlines before and after the TopNonTerminal text:
Prog myParseTree = parse(#Prog, "example string");
// you can do the same directly to an input file:
Prog myParseTree = parse(#TopNonTerminal, |home:///myProgram.func|);
// if you need to accept layout before and after the program, use a "start nonterminal":
start[Prog] myParseTree = parse(#start[TopNonTerminal], |home:///myProgram.func|);
Prog myProgram = myParseTree.top;
// shorthand for parsing stuff:
myProgram = [Prog] "example";
myProgram = [Prog] |home:///myLocation.txt|;
Once you have the tree you can start using visit and / deepmatch to extract information from the tree, or write recursive functions if you like. Examples can be found here: http://docs.rascal-mpl.org/unstable/Recipes/#Languages-Func , but here are some common idioms as well to extract information from a parse tree:
// produces the source location of each node in the tree:
myParseTree#\loc
// produces a set of all nodes of type Stat
{ s | /Stat s := myParseTree }
// pattern match an if-then-else and bind the three expressions and collect them in a set:
{ e1, e2, e3 | (Stat) `if <Exp e1> then <Exp e2> else <Exp e3> end` <- myExpressionList }
// collect all locations of all sub-trees (every parse tree is of a non-terminal type, which is a sub-type of Tree. It uses |unknown:///| for small sub-trees which have not been annotated for efficiency's sake, like literals and character classes:
[ t#\loc?|unknown:///| | /Tree t := myParseTree ]
That should give you a start. I'd go try out some stuff and look at more examples. Writing a grammar is a nice thing to do, but it does require some trial and error methods like writing a regex, but even more so.
For the grammar you might be writing, which finds source code comments but leaves the rest as "any character" you will need to use the longest match disambiguation a lot:
lexical Identifier = [a-z]+ !>> [a-z]; // means do not accept an Identifier if there is still [a-z] to add to it; so only the longest possible Identifier will match.
This kind of context-free grammar is called an "Island Grammar" metaphorically, because you will write precise rules for the parts you want to recognize (the comments are "Islands") while leaving the rest as everything else (the rest is "Water"). See https://dl.acm.org/citation.cfm?id=837160
Is it possible to append terminals retrieved from a text file to a lexicon in Rascal? This would happen at run time, and I see no obvious way to achieve this. I would rather keep the data separate from the Rascal project. For example, if I had read in a list of countries from a text file, how would I add these to a lexicon (using the lexical keyword)?
In the data-dependent version of the Rascal parser this is even easier and faster but we haven't released this yet. For now I'd write a generic rule with a post-parse filter, like so:
rascal>set[str] lexicon = {"aap", "noot", "mies"};
set[str]: {"noot","mies","aap"}
rascal>lexical Word = [a-z]+;
ok
rascal>syntax LexiconWord = word: Word w;
ok
rascal>LexiconWord word(Word w) { // called when the LexiconWord.word rule is use to build a tree
>>>>>>> if ("<w>" notin lexicon)
>>>>>>> filter; // remove this parse tree
>>>>>>> else fail; // just build the tree
>>>>>>>}
rascal>[Sentence] "hello"
|prompt:///|(0,18,<1,0>,<1,18>): ParseError(|prompt:///|(0,18,<1,0>,<1,18>))
at $root$(|prompt:///|(0,64,<1,0>,<1,64>))
rascal>[Sentence] "aap"
Sentence: (Sentence) `aap`
rascal>
Because the filter function removed all possible derivations for hello, the parser eventually returns a parse error on hello. It does not do so for aap which is in the lexicon, so hurray. Of course you can make interestingly complex derivations with this kind of filtering. People sometimes write ambiguous grammars and use filters like so to make it unambiguous.
Parsing and filtering in this way is in cubic worst-case time in terms of the length of the input, if the filtering function is in amortized constant time. If the grammar is linear, then of course the entire process is also linear.
A completely different answer would be to dynamically update the grammar and generate a parser from this. This involves working against the internal grammar representation of Rascal like so:
set[str] lexicon = {"aap", "noot", "mies"};
syntax Word = ; // empty definition
typ = #Word;
grammar = typ.definitions;
grammar[sort("Word")] = { prod(sort("Word"), lit(x), {}) | x <- lexicon };
newTyp = type(sort("Word"), grammar);
This newType is a reified grammar + type for the definition of the lexicon, and which can now be used like so:
import ParseTree;
if (type[Word] staticGrammar := newType) {
parse(staticGrammar, "aap");
}
Now having written al this, two things:
I think this may trigger unknown bugs since we did not test dynamic parser generation, and
For a lexicon with a reasonable size, this will generate an utterly slow parser since the parser is optimized for keywords in programming languages and not large lexicons.
I'm having trouble working out how to use any of the functions in the Text.Parsec.Indent module provided by the indents package for Haskell, which is a sort of add-on for Parsec.
What do all these functions do? How are they to be used?
I can understand the brief Haddock description of withBlock, and I've found examples of how to use withBlock, runIndent and the IndentParser type here, here and here. I can also understand the documentation for the four parsers indentBrackets and friends. But many things are still confusing me.
In particular:
What is the difference between withBlock f a p and
do aa <- a
pp <- block p
return f aa pp
Likewise, what's the difference between withBlock' a p and do {a; block p}
In the family of functions indented and friends, what is ‘the level of the reference’? That is, what is ‘the reference’?
Again, with the functions indented and friends, how are they to be used? With the exception of withPos, it looks like they take no arguments and are all of type IParser () (IParser defined like this or this) so I'm guessing that all they can do is to produce an error or not and that they should appear in a do block, but I can't figure out the details.
I did at least find some examples on the usage of withPos in the source code, so I can probably figure that out if I stare at it for long enough.
<+/> comes with the helpful description “<+/> is to indentation sensitive parsers what ap is to monads” which is great if you want to spend several sessions trying to wrap your head around ap and then work out how that's analogous to a parser. The other three combinators are then defined with reference to <+/>, making the whole group unapproachable to a newcomer.
Do I need to use these? Can I just ignore them and use do instead?
The ordinary lexeme combinator and whiteSpace parser from Parsec will happily consume newlines in the middle of a multi-token construct without complaining. But in an indentation-style language, sometimes you want to stop parsing a lexical construct or throw an error if a line is broken and the next line is indented less than it should be. How do I go about doing this in Parsec?
In the language I am trying to parse, ideally the rules for when a lexical structure is allowed to continue on to the next line should depend on what tokens appear at the end of the first line or the beginning of the subsequent line. Is there an easy way to achieve this in Parsec? (If it is difficult then it is not something which I need to concern myself with at this time.)
So, the first hint is to take a look at IndentParser
type IndentParser s u a = ParsecT s u (State SourcePos) a
I.e. it's a ParsecT keeping an extra close watch on SourcePos, an abstract container which can be used to access, among other things, the current column number. So, it's probably storing the current "level of indentation" in SourcePos. That'd be my initial guess as to what "level of reference" means.
In short, indents gives you a new kind of Parsec which is context sensitive—in particular, sensitive to the current indentation. I'll answer your questions out of order.
(2) The "level of reference" is the "belief" referred in the current parser context state of where this indentation level starts. To be more clear, let me give some test cases on (3).
(3) In order to start experimenting with these functions, we'll build a little test runner. It'll run the parser with a string that we give it and then unwrap the inner State part using an initialPos which we get to modify. In code
import Text.Parsec
import Text.Parsec.Pos
import Text.Parsec.Indent
import Control.Monad.State
testParse :: (SourcePos -> SourcePos)
-> IndentParser String () a
-> String -> Either ParseError a
testParse f p src = fst $ flip runState (f $ initialPos "") $ runParserT p () "" src
(Note that this is almost runIndent, except I gave a backdoor to modify the initialPos.)
Now we can take a look at indented. By examining the source, I can tell it does two things. First, it'll fail if the current SourcePos column number is less-than-or-equal-to the "level of reference" stored in the SourcePos stored in the State. Second, it somewhat mysteriously updates the State SourcePos's line counter (not column counter) to be current.
Only the first behavior is important, to my understanding. We can see the difference here.
>>> testParse id indented ""
Left (line 1, column 1): not indented
>>> testParse id (spaces >> indented) " "
Right ()
>>> testParse id (many (char 'x') >> indented) "xxxx"
Right ()
So, in order to have indented succeed, we need to have consumed enough whitespace (or anything else!) to push our column position out past the "reference" column position. Otherwise, it'll fail saying "not indented". Similar behavior exists for the next three functions: same fails unless the current position and reference position are on the same line, sameOrIndented fails if the current column is strictly less than the reference column, unless they are on the same line, and checkIndent fails unless the current and reference columns match.
withPos is slightly different. It's not just a IndentParser, it's an IndentParser-combinator—it transforms the input IndentParser into one that thinks the "reference column" (the SourcePos in the State) is exactly where it was when we called withPos.
This gives us another hint, btw. It lets us know we have the power to change the reference column.
(1) So now let's take a look at how block and withBlock work using our new, lower level reference column operators. withBlock is implemented in terms of block, so we'll start with block.
-- simplified from the actual source
block p = withPos $ many1 (checkIndent >> p)
So, block resets the "reference column" to be whatever the current column is and then consumes at least 1 parses from p so long as each one is indented identically as this newly set "reference column". Now we can take a look at withBlock
withBlock f a p = withPos $ do
r1 <- a
r2 <- option [] (indented >> block p)
return (f r1 r2)
So, it resets the "reference column" to the current column, parses a single a parse, tries to parse an indented block of ps, then combines the results using f. Your implementation is almost correct, except that you need to use withPos to choose the correct "reference column".
Then, once you have withBlock, withBlock' = withBlock (\_ bs -> bs).
(5) So, indented and friends are exactly the tools to doing this: they'll cause a parse to immediately fail if it's indented incorrectly with respect to the "reference position" chosen by withPos.
(4) Yes, don't worry about these guys until you learn how to use Applicative style parsing in base Parsec. It's often a much cleaner, faster, simpler way of specifying parses. Sometimes they're even more powerful, but if you understand Monads then they're almost always completely equivalent.
(6) And this is the crux. The tools mentioned so far can only do indentation failure if you can describe your intended indentation using withPos. Quickly, I don't think it's possible to specify withPos based on the success or failure of other parses... so you'll have to go another level deeper. Fortunately, the mechanism that makes IndentParsers work is obvious—it's just an inner State monad containing SourcePos. You can use lift :: MonadTrans t => m a -> t m a to manipulate this inner state and set the "reference column" however you like.
Cheers!
I'm implementing a PEG parser generator in Python, and I've had success so far, except with the "cut" feature, of which whomever knows Prolog must know about.
The idea is that after a cut (!) symbol has been parsed, then no alternative options should be attempted at the same level.
expre = '(' ! list ')' | atom.
Means that after the ( is seen, the parsing must succeed, or fail without trying the second option.
I'm using Python's (very efficient) exception system to force backtracking, so I tried having a special FailedCut exception that would abort the enclosing choice, but that didn't work.
Any pointers to how this functionality is implemented in other parser generators would be helpful.
Maybe the problem I've had has been lack of locality. The code generated for the left part of the rule would be something like:
cut_seen = False
try:
self.token('(')
cut_seen = True
self.call('list')
self.token(')')
except FailedParse as e:
if cut_seen:
raise FailedCut(e)
raise
Then the code generated for the choice (|) operator will skip the following choices if it catches a FailedCut. What I mean by lack of locality is that the choice catching the FailedCut may be deep up in calls, thus having an effect too-difficult to discern.
Instead of making the code generated for sequences try to inform enclosing choices of cuts, I could make the code generated for choices beware of them. That would make the scope of cuts very local, unlike Prolog's, but good enough for what I want in a PEG parser, which is to commit to an option after a certain token sequence has been seen, so the error reporting is refers to that location in the source, instead of to another location where some other option might have been available.
It just occurred to me that if the code generated for a rule/predicate catches FailedCut and translates it into a normal FailedParse exception, then the cuts will have the right scope.
In reference to #false's question, here's a complete example of what I want to work:
start = expre ;
expre = named | term ;
named = word ':' ! term;
term = word ;
In that grammar, word can be reached through named or term, but I would like the parser to commit to the named branch after it has seen the :.
The Solution
To be fair, I've published my work so far at https://bitbucket.org/apalala/grako/.
In the final solution, sequences are enclosed with this context manager:
#contextmanager
def _sequence(self):
self._push_cut()
try:
yield
except FailedParse as e:
if self._cut():
self.error(e, FailedCut)
else:
raise
finally:
self._pop_cut()
And options in a choice function are enclosed with this:
#contextmanager
def _option(self):
p = self._pos
try:
self._push_ast()
try:
yield
ast = self.ast
finally:
self._pop_ast()
self.ast.update(ast)
except FailedCut as e:
self._goto(p)
raise e.nested
except FailedParse:
self._goto(p)
Which forces an exit out of the choice instead of a return to try the next option.
The cuts themselves are implemented thus:
def _cut(self):
self._cut_stack[-1] = True
The full source code may be found on Bitbucket.
In a Prolog with ISO Prolog's exception handling (catch/3 and throw/1), a cut could be implemented as:
cut. % Simply succeeds
cut :-
throw(cut). % on backtracking throws an exception
This would require to catch that exception at appropriate places. For example, each goal (that is non-terminal) of a user defined predicate could now be wrapped with:
catchcut(Goal) :-
catch(Goal,cut,fail).
This is not the most efficient way to implement cut since it does not free resources upon success of !, but it might be sufficient for your purposes. Also, this method now might interfere with user-defined uses of catch/3. But you probably do not want to emulate the entire Prolog language in any case.
Also, consider to use Prolog's dcg-grammars directly. There is a lot of fine print that is not evident when implementing this in another language.
The solution proposed at the end of my question worked:
cut_seen = False
try:
self.token('(')
cut_seen = True
self.call('list')
self.token(')')
except FailedParse as e:
if cut_seen:
raise FailedCut(e)
raise
Then, any time a choice or optional is evaluated, the code looks like this:
p = self.pos
try:
# code for the expression
except FailedCut:
raise
except FailedParse:
self.goto(p)
Edit
The actual solution required keeping a "cut stack". The source code is int Bitbucket.
Just read it.
I'd suggested a deep cut_seen (like with modifying parser's state) and a save and restore state with local variables. This uses the thread's stack as "cut_seen stack".
But you have another solution, and I'm pretty sure you're fine already.
BTW: nice compiler – it's just the opposite of what I'm doing with pyPEG so I can learn alot ;-)
I have read the GOLD Homepage ( http://www.devincook.com/goldparser/ ) docs, FAQ and Wikipedia to find out what practical application there could possibly be for GOLD. I was thinking along the lines of having a programming language (easily) available to my systems such as ABAP on SAP or X++ on Axapta - but it doesn't look feasible to me, at least not easily - even if you use GOLD.
The final use of the parsed result produced by GOLD escapes me - what do you do with the result of the parse?
EDIT: A practical example (description) would be great.
Parsing really consists of two phases. The first is "lexing", which convert the raw strings of character in to something that the program can more readily understand (commonly called tokens).
Simple example, lex would convert:
if (a + b > 2) then
In to:
IF_TOKEN LEFT_PAREN IDENTIFIER(a) PLUS_SIGN IDENTIFIER(b) GREATER_THAN NUMBER(2) RIGHT_PAREN THEN_TOKEN
The parse takes that stream of tokens, and attempts to make yet more sense out of them. In this case, it would try and match up those tokens to an IF_STATEMENT. To the parse, the IF _STATEMENT may well look like this:
IF ( BOOLEAN_EXPRESSION ) THEN
Where the result of the lexing phase is a token stream, the result of the parsing phase is a Parse Tree.
So, a parser could convert the above in to:
if_statement
|
v
boolean_expression.operator = GREATER_THAN
| |
| v
V numeric_constant.string="2"
expression.operator = PLUS_SIGN
| |
| v
v identifier.string = "b"
identifier.string = "a"
Here you see we have an IF_STATEMENT. An IF_STATEMENT has a single argument, which is a BOOLEAN_EXPRESSION. This was explained in some manner to the parser. When the parser is converting the token stream, it "knows" what a IF looks like, and know what a BOOLEAN_EXPRESSION looks like, so it can make the proper assignments when it sees the code.
For example, if you have just:
if (a + b) then
The parser could know that it's not a boolean expression (because the + is arithmetic, not a boolean operator) and the parse could throw an error at this point.
Next, we see that a BOOLEAN_EXPRESSION has 3 components, the operator (GREATER_THAN), and two sides, the left side and the right side.
On the left side, it points to yet another expression, the "a + b", while on the right is points to a NUMERIC_CONSTANT, in this case the string "2". Again, the parser "knows" this is a NUMERIC constant because we told it about strings of numbers. If it wasn't numbers, it would be an IDENTIFIER (like "a" and "b" are).
Note, that if we had something like:
if (a + b > "XYZ") then
That "parses" just fine (expression on the left, string constant on the right). We don't know from looking at this whether this is a valid expression or not. We don't know if "a" or "b" reference Strings or Numbers at this point. So, this is something the parser can't decided for us, can't flag as an error, as it simply doesn't know. That will happen when we evaluate (either execute or try to compile in to code) the IF statement.
If we did:
if [a > b ) then
The parser can readily see that syntax error as a problem, and will throw an error. That string of tokens doesn't look like anything it knows about.
So, the point being that when you get a complete parse tree, you have some assurance that at first cut the "code looks good". Now during execution, other errors may well come up.
To evaluate the parse tree, you just walk the tree. You'll have some code associated with the major nodes of the parse tree during the compile or evaluation part. Let's assuming that we have an interpreter.
public void execute_if_statment(ParseTreeNode node) {
// We already know we have a IF_STATEMENT node
Value value = evaluate_expression(node.getBooleanExpression());
if (value.getBooleanResult() == true) {
// we do the "then" part of the code
}
}
public Value evaluate_expression(ParseTreeNode node) {
Value result = null;
if (node.isConstant()) {
result = evaluate_constant(node);
return result;
}
if (node.isIdentifier()) {
result = lookupIdentifier(node);
return result;
}
Value leftSide = evaluate_expression(node.getLeftSide());
Value rightSide = evaluate_expression(node.getRightSide());
if (node.getOperator() == '+') {
if (!leftSide.isNumber() || !rightSide.isNumber()) {
throw new RuntimeError("Must have numbers for adding");
}
int l = leftSide.getIntValue();
int r = rightSide.getIntValue();
int sum = l + r;
return new Value(sum);
}
if (node.getOperator() == '>') {
if (leftSide.getType() != rightSide.getType()) {
throw new RuntimeError("You can only compare values of the same type");
}
if (leftSide.isNumber()) {
int l = leftSide.getIntValue();
int r = rightSide.getIntValue();
boolean greater = l > r;
return new Value(greater);
} else {
// do string compare instead
}
}
}
So, you can see that we have a recursive evaluator here. You see how we're checking the run time types, and performing the basic evaluations.
What will happen is the execute_if_statement will evaluate it's main expression. Even tho we wanted only BOOLEAN_EXPRESION in the parse, all expressions are mostly the same for our purposes. So, execute_if_statement calls evaluate_expression.
In our system, all expressions have an operator and a left and right side. Each side of an expression is ALSO an expression, so you can see how we immediately try and evaluate those as well to get their real value. The one note is that if the expression consists of a CONSTANT, then we simply return the constants value, if it's an identifier, we look it up as a variable (and that would be a good place to throw a "I can't find the variable 'a'" message), otherwise we're back to the left side/right side thing.
I hope you can see how a simple evaluator can work once you have a token stream from a parser. Note how during evaluation, the major elements of the language are in place, otherwise we'd have got a syntax error and never got to this phase. We can simply expect to "know" that when we have a, for example, PLUS operator, we're going to have 2 expressions, the left and right side. Or when we execute an IF statement, that we already have a boolean expression to evaluate. The parse is what does that heavy lifting for us.
Getting started with a new language can be a challenge, but you'll find once you get rolling, the rest become pretty straightforward and it's almost "magic" that it all works in the end.
Note, pardon the formatting, but underscores are messing things up -- I hope it's still clear.
I would recommend antlr.org for information and the 'free' tool I would use for any parser use.
GOLD can be used for any kind of application where you have to apply context-free grammars to input.
elaboration:
Essentially, CFGs apply to all programming languages. So if you wanted to develop a scripting language for your company, you'd need to write a parser- or get a parsing program. Alternatively, if you wanted to have a semi-natural language for input for non-programmers in the company, you could use a parser to read that input and spit out more "machine-readable" data. Essentially, a context-free grammar allows you to describe far more inputs than a regular expression. The GOLD system apparently makes the parsing problem somewhat easier than lex/yacc(the UNIX standard programs for parsing).