434 lines
15 KiB
Python
434 lines
15 KiB
Python
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# Copyright 2004-2005 Elemental Security, Inc. All Rights Reserved.
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# Licensed to PSF under a Contributor Agreement.
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# Pgen imports
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from . import grammar, token, tokenize
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from typing import (
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Any,
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Dict,
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IO,
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Iterator,
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List,
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Optional,
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Text,
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Tuple,
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Union,
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Sequence,
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NoReturn,
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)
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from blib2to3.pgen2 import grammar
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from blib2to3.pgen2.tokenize import GoodTokenInfo
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import os
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Path = Union[str, "os.PathLike[str]"]
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class PgenGrammar(grammar.Grammar):
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pass
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class ParserGenerator(object):
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filename: Path
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stream: IO[Text]
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generator: Iterator[GoodTokenInfo]
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first: Dict[Text, Optional[Dict[Text, int]]]
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def __init__(self, filename: Path, stream: Optional[IO[Text]] = None) -> None:
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close_stream = None
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if stream is None:
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stream = open(filename)
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close_stream = stream.close
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self.filename = filename
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self.stream = stream
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self.generator = tokenize.generate_tokens(stream.readline)
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self.gettoken() # Initialize lookahead
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self.dfas, self.startsymbol = self.parse()
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if close_stream is not None:
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close_stream()
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self.first = {} # map from symbol name to set of tokens
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self.addfirstsets()
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def make_grammar(self) -> PgenGrammar:
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c = PgenGrammar()
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names = list(self.dfas.keys())
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names.sort()
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names.remove(self.startsymbol)
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names.insert(0, self.startsymbol)
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for name in names:
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i = 256 + len(c.symbol2number)
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c.symbol2number[name] = i
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c.number2symbol[i] = name
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for name in names:
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dfa = self.dfas[name]
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states = []
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for state in dfa:
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arcs = []
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for label, next in sorted(state.arcs.items()):
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arcs.append((self.make_label(c, label), dfa.index(next)))
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if state.isfinal:
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arcs.append((0, dfa.index(state)))
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states.append(arcs)
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c.states.append(states)
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c.dfas[c.symbol2number[name]] = (states, self.make_first(c, name))
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c.start = c.symbol2number[self.startsymbol]
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return c
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def make_first(self, c: PgenGrammar, name: Text) -> Dict[int, int]:
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rawfirst = self.first[name]
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assert rawfirst is not None
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first = {}
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for label in sorted(rawfirst):
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ilabel = self.make_label(c, label)
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##assert ilabel not in first # XXX failed on <> ... !=
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first[ilabel] = 1
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return first
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def make_label(self, c: PgenGrammar, label: Text) -> int:
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# XXX Maybe this should be a method on a subclass of converter?
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ilabel = len(c.labels)
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if label[0].isalpha():
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# Either a symbol name or a named token
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if label in c.symbol2number:
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# A symbol name (a non-terminal)
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if label in c.symbol2label:
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return c.symbol2label[label]
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else:
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c.labels.append((c.symbol2number[label], None))
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c.symbol2label[label] = ilabel
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return ilabel
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else:
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# A named token (NAME, NUMBER, STRING)
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itoken = getattr(token, label, None)
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assert isinstance(itoken, int), label
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assert itoken in token.tok_name, label
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if itoken in c.tokens:
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return c.tokens[itoken]
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else:
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c.labels.append((itoken, None))
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c.tokens[itoken] = ilabel
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return ilabel
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else:
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# Either a keyword or an operator
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assert label[0] in ('"', "'"), label
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value = eval(label)
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if value[0].isalpha():
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if label[0] == '"':
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keywords = c.soft_keywords
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else:
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keywords = c.keywords
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# A keyword
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if value in keywords:
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return keywords[value]
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else:
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c.labels.append((token.NAME, value))
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keywords[value] = ilabel
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return ilabel
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else:
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# An operator (any non-numeric token)
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itoken = grammar.opmap[value] # Fails if unknown token
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if itoken in c.tokens:
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return c.tokens[itoken]
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else:
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c.labels.append((itoken, None))
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c.tokens[itoken] = ilabel
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return ilabel
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def addfirstsets(self) -> None:
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names = list(self.dfas.keys())
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names.sort()
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for name in names:
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if name not in self.first:
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self.calcfirst(name)
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# print name, self.first[name].keys()
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def calcfirst(self, name: Text) -> None:
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dfa = self.dfas[name]
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self.first[name] = None # dummy to detect left recursion
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state = dfa[0]
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totalset: Dict[str, int] = {}
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overlapcheck = {}
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for label, next in state.arcs.items():
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if label in self.dfas:
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if label in self.first:
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fset = self.first[label]
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if fset is None:
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raise ValueError("recursion for rule %r" % name)
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else:
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self.calcfirst(label)
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fset = self.first[label]
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assert fset is not None
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totalset.update(fset)
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overlapcheck[label] = fset
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else:
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totalset[label] = 1
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overlapcheck[label] = {label: 1}
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inverse: Dict[str, str] = {}
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for label, itsfirst in overlapcheck.items():
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for symbol in itsfirst:
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if symbol in inverse:
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raise ValueError(
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"rule %s is ambiguous; %s is in the first sets of %s as well"
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" as %s" % (name, symbol, label, inverse[symbol])
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)
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inverse[symbol] = label
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self.first[name] = totalset
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def parse(self) -> Tuple[Dict[Text, List["DFAState"]], Text]:
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dfas = {}
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startsymbol: Optional[str] = None
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# MSTART: (NEWLINE | RULE)* ENDMARKER
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while self.type != token.ENDMARKER:
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while self.type == token.NEWLINE:
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self.gettoken()
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# RULE: NAME ':' RHS NEWLINE
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name = self.expect(token.NAME)
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self.expect(token.OP, ":")
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a, z = self.parse_rhs()
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self.expect(token.NEWLINE)
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# self.dump_nfa(name, a, z)
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dfa = self.make_dfa(a, z)
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# self.dump_dfa(name, dfa)
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oldlen = len(dfa)
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self.simplify_dfa(dfa)
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newlen = len(dfa)
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dfas[name] = dfa
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# print name, oldlen, newlen
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if startsymbol is None:
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startsymbol = name
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assert startsymbol is not None
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return dfas, startsymbol
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def make_dfa(self, start: "NFAState", finish: "NFAState") -> List["DFAState"]:
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# To turn an NFA into a DFA, we define the states of the DFA
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# to correspond to *sets* of states of the NFA. Then do some
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# state reduction. Let's represent sets as dicts with 1 for
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# values.
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assert isinstance(start, NFAState)
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assert isinstance(finish, NFAState)
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def closure(state: NFAState) -> Dict[NFAState, int]:
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base: Dict[NFAState, int] = {}
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addclosure(state, base)
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return base
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def addclosure(state: NFAState, base: Dict[NFAState, int]) -> None:
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assert isinstance(state, NFAState)
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if state in base:
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return
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base[state] = 1
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for label, next in state.arcs:
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if label is None:
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addclosure(next, base)
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states = [DFAState(closure(start), finish)]
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for state in states: # NB states grows while we're iterating
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arcs: Dict[str, Dict[NFAState, int]] = {}
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for nfastate in state.nfaset:
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for label, next in nfastate.arcs:
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if label is not None:
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addclosure(next, arcs.setdefault(label, {}))
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for label, nfaset in sorted(arcs.items()):
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for st in states:
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if st.nfaset == nfaset:
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break
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else:
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st = DFAState(nfaset, finish)
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states.append(st)
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state.addarc(st, label)
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return states # List of DFAState instances; first one is start
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def dump_nfa(self, name: Text, start: "NFAState", finish: "NFAState") -> None:
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print("Dump of NFA for", name)
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todo = [start]
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for i, state in enumerate(todo):
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print(" State", i, state is finish and "(final)" or "")
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for label, next in state.arcs:
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if next in todo:
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j = todo.index(next)
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else:
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j = len(todo)
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todo.append(next)
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if label is None:
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print(" -> %d" % j)
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else:
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print(" %s -> %d" % (label, j))
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def dump_dfa(self, name: Text, dfa: Sequence["DFAState"]) -> None:
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print("Dump of DFA for", name)
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for i, state in enumerate(dfa):
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print(" State", i, state.isfinal and "(final)" or "")
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for label, next in sorted(state.arcs.items()):
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print(" %s -> %d" % (label, dfa.index(next)))
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def simplify_dfa(self, dfa: List["DFAState"]) -> None:
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# This is not theoretically optimal, but works well enough.
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# Algorithm: repeatedly look for two states that have the same
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# set of arcs (same labels pointing to the same nodes) and
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# unify them, until things stop changing.
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# dfa is a list of DFAState instances
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changes = True
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while changes:
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changes = False
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for i, state_i in enumerate(dfa):
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for j in range(i + 1, len(dfa)):
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state_j = dfa[j]
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if state_i == state_j:
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# print " unify", i, j
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del dfa[j]
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for state in dfa:
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state.unifystate(state_j, state_i)
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changes = True
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break
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def parse_rhs(self) -> Tuple["NFAState", "NFAState"]:
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# RHS: ALT ('|' ALT)*
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a, z = self.parse_alt()
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if self.value != "|":
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return a, z
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else:
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aa = NFAState()
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zz = NFAState()
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aa.addarc(a)
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z.addarc(zz)
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while self.value == "|":
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self.gettoken()
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a, z = self.parse_alt()
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aa.addarc(a)
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z.addarc(zz)
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return aa, zz
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def parse_alt(self) -> Tuple["NFAState", "NFAState"]:
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# ALT: ITEM+
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a, b = self.parse_item()
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while self.value in ("(", "[") or self.type in (token.NAME, token.STRING):
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c, d = self.parse_item()
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b.addarc(c)
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b = d
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return a, b
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def parse_item(self) -> Tuple["NFAState", "NFAState"]:
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# ITEM: '[' RHS ']' | ATOM ['+' | '*']
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if self.value == "[":
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self.gettoken()
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a, z = self.parse_rhs()
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self.expect(token.OP, "]")
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a.addarc(z)
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return a, z
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else:
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a, z = self.parse_atom()
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value = self.value
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if value not in ("+", "*"):
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return a, z
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self.gettoken()
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z.addarc(a)
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if value == "+":
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return a, z
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else:
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return a, a
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def parse_atom(self) -> Tuple["NFAState", "NFAState"]:
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# ATOM: '(' RHS ')' | NAME | STRING
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if self.value == "(":
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self.gettoken()
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a, z = self.parse_rhs()
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self.expect(token.OP, ")")
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return a, z
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elif self.type in (token.NAME, token.STRING):
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a = NFAState()
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z = NFAState()
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a.addarc(z, self.value)
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self.gettoken()
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return a, z
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else:
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self.raise_error(
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"expected (...) or NAME or STRING, got %s/%s", self.type, self.value
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)
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assert False
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def expect(self, type: int, value: Optional[Any] = None) -> Text:
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if self.type != type or (value is not None and self.value != value):
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self.raise_error(
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"expected %s/%s, got %s/%s", type, value, self.type, self.value
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)
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value = self.value
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self.gettoken()
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return value
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def gettoken(self) -> None:
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tup = next(self.generator)
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while tup[0] in (tokenize.COMMENT, tokenize.NL):
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tup = next(self.generator)
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self.type, self.value, self.begin, self.end, self.line = tup
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# print token.tok_name[self.type], repr(self.value)
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def raise_error(self, msg: str, *args: Any) -> NoReturn:
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if args:
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try:
|
||
|
|
msg = msg % args
|
||
|
|
except:
|
||
|
|
msg = " ".join([msg] + list(map(str, args)))
|
||
|
|
raise SyntaxError(msg, (self.filename, self.end[0], self.end[1], self.line))
|
||
|
|
|
||
|
|
|
||
|
|
class NFAState(object):
|
||
|
|
arcs: List[Tuple[Optional[Text], "NFAState"]]
|
||
|
|
|
||
|
|
def __init__(self) -> None:
|
||
|
|
self.arcs = [] # list of (label, NFAState) pairs
|
||
|
|
|
||
|
|
def addarc(self, next: "NFAState", label: Optional[Text] = None) -> None:
|
||
|
|
assert label is None or isinstance(label, str)
|
||
|
|
assert isinstance(next, NFAState)
|
||
|
|
self.arcs.append((label, next))
|
||
|
|
|
||
|
|
|
||
|
|
class DFAState(object):
|
||
|
|
nfaset: Dict[NFAState, Any]
|
||
|
|
isfinal: bool
|
||
|
|
arcs: Dict[Text, "DFAState"]
|
||
|
|
|
||
|
|
def __init__(self, nfaset: Dict[NFAState, Any], final: NFAState) -> None:
|
||
|
|
assert isinstance(nfaset, dict)
|
||
|
|
assert isinstance(next(iter(nfaset)), NFAState)
|
||
|
|
assert isinstance(final, NFAState)
|
||
|
|
self.nfaset = nfaset
|
||
|
|
self.isfinal = final in nfaset
|
||
|
|
self.arcs = {} # map from label to DFAState
|
||
|
|
|
||
|
|
def addarc(self, next: "DFAState", label: Text) -> None:
|
||
|
|
assert isinstance(label, str)
|
||
|
|
assert label not in self.arcs
|
||
|
|
assert isinstance(next, DFAState)
|
||
|
|
self.arcs[label] = next
|
||
|
|
|
||
|
|
def unifystate(self, old: "DFAState", new: "DFAState") -> None:
|
||
|
|
for label, next in self.arcs.items():
|
||
|
|
if next is old:
|
||
|
|
self.arcs[label] = new
|
||
|
|
|
||
|
|
def __eq__(self, other: Any) -> bool:
|
||
|
|
# Equality test -- ignore the nfaset instance variable
|
||
|
|
assert isinstance(other, DFAState)
|
||
|
|
if self.isfinal != other.isfinal:
|
||
|
|
return False
|
||
|
|
# Can't just return self.arcs == other.arcs, because that
|
||
|
|
# would invoke this method recursively, with cycles...
|
||
|
|
if len(self.arcs) != len(other.arcs):
|
||
|
|
return False
|
||
|
|
for label, next in self.arcs.items():
|
||
|
|
if next is not other.arcs.get(label):
|
||
|
|
return False
|
||
|
|
return True
|
||
|
|
|
||
|
|
__hash__: Any = None # For Py3 compatibility.
|
||
|
|
|
||
|
|
|
||
|
|
def generate_grammar(filename: Path = "Grammar.txt") -> PgenGrammar:
|
||
|
|
p = ParserGenerator(filename)
|
||
|
|
return p.make_grammar()
|