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Refactor out dfas
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@@ -181,7 +181,7 @@ class _GrammarParser():
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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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_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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@@ -251,27 +251,6 @@ class _GrammarParser():
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for label, next in state.arcs.items():
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print(" %s -> %d" % (label, dfa.index(next)))
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def _simplify_dfa(self, dfa):
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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):
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# rhs: items ('|' items)*
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a, z = self._parse_alt()
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@@ -408,6 +387,28 @@ class DFAState(object):
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__hash__ = None # For Py3 compatibility.
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def _simplify_dfa(dfas):
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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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# dfas 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(dfas):
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for j in range(i + 1, len(dfas)):
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state_j = dfas[j]
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if state_i == state_j:
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#print " unify", i, j
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del dfas[j]
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for state in dfas:
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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 generate_grammar(bnf_grammar, token_namespace):
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"""
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``bnf_text`` is a grammar in extended BNF (using * for repetition, + for
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