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Python3.src.antlr4.dfa.DFAState.py Maven / Gradle / Ivy
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#
# [The "BSD license"]
# Copyright (c) 2012 Terence Parr
# Copyright (c) 2012 Sam Harwell
# Copyright (c) 2014 Eric Vergnaud
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# 3. The name of the author may not be used to endorse or promote products
# derived from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
# IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
# OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
# IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT, INDIRECT,
# INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
# NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF
# THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#/
# Map a predicate to a predicted alternative.#/
from io import StringIO
from antlr4.atn.ATNConfigSet import ATNConfigSet
from antlr4.atn.SemanticContext import SemanticContext
class PredPrediction(object):
def __init__(self, pred:SemanticContext, alt:int):
self.alt = alt
self.pred = pred
def __str__(self):
return "(" + str(self.pred) + ", " + str(self.alt) + ")"
# A DFA state represents a set of possible ATN configurations.
# As Aho, Sethi, Ullman p. 117 says "The DFA uses its state
# to keep track of all possible states the ATN can be in after
# reading each input symbol. That is to say, after reading
# input a1a2..an, the DFA is in a state that represents the
# subset T of the states of the ATN that are reachable from the
# ATN's start state along some path labeled a1a2..an."
# In conventional NFA→DFA conversion, therefore, the subset T
# would be a bitset representing the set of states the
# ATN could be in. We need to track the alt predicted by each
# state as well, however. More importantly, we need to maintain
# a stack of states, tracking the closure operations as they
# jump from rule to rule, emulating rule invocations (method calls).
# I have to add a stack to simulate the proper lookahead sequences for
# the underlying LL grammar from which the ATN was derived.
#
# I use a set of ATNConfig objects not simple states. An ATNConfig
# is both a state (ala normal conversion) and a RuleContext describing
# the chain of rules (if any) followed to arrive at that state.
#
# A DFA state may have multiple references to a particular state,
# but with different ATN contexts (with same or different alts)
# meaning that state was reached via a different set of rule invocations.
#/
class DFAState(object):
def __init__(self, stateNumber:int=-1, configs:ATNConfigSet=ATNConfigSet()):
self.stateNumber = stateNumber
self.configs = configs
# {@code edges[symbol]} points to target of symbol. Shift up by 1 so (-1)
# {@link Token#EOF} maps to {@code edges[0]}.
self.edges = None
self.isAcceptState = False
# if accept state, what ttype do we match or alt do we predict?
# This is set to {@link ATN#INVALID_ALT_NUMBER} when {@link #predicates}{@code !=null} or
# {@link #requiresFullContext}.
self.prediction = 0
self.lexerActionExecutor = None
# Indicates that this state was created during SLL prediction that
# discovered a conflict between the configurations in the state. Future
# {@link ParserATNSimulator#execATN} invocations immediately jumped doing
# full context prediction if this field is true.
self.requiresFullContext = False
# During SLL parsing, this is a list of predicates associated with the
# ATN configurations of the DFA state. When we have predicates,
# {@link #requiresFullContext} is {@code false} since full context prediction evaluates predicates
# on-the-fly. If this is not null, then {@link #prediction} is
# {@link ATN#INVALID_ALT_NUMBER}.
#
# We only use these for non-{@link #requiresFullContext} but conflicting states. That
# means we know from the context (it's $ or we don't dip into outer
# context) that it's an ambiguity not a conflict.
#
# This list is computed by {@link ParserATNSimulator#predicateDFAState}.
self.predicates = None
# Get the set of all alts mentioned by all ATN configurations in this
# DFA state.
def getAltSet(self):
alts = set()
if self.configs is not None:
for c in self.configs:
alts.add(c.alt)
if len(alts)==0:
return None
else:
return alts
def __hash__(self):
return hash(self.configs)
# Two {@link DFAState} instances are equal if their ATN configuration sets
# are the same. This method is used to see if a state already exists.
#
# Because the number of alternatives and number of ATN configurations are
# finite, there is a finite number of DFA states that can be processed.
# This is necessary to show that the algorithm terminates.
#
# Cannot test the DFA state numbers here because in
# {@link ParserATNSimulator#addDFAState} we need to know if any other state
# exists that has this exact set of ATN configurations. The
# {@link #stateNumber} is irrelevant.
def __eq__(self, other):
# compare set of ATN configurations in this set with other
if self is other:
return True
elif not isinstance(other, DFAState):
return False
else:
return self.configs==other.configs
def __str__(self):
with StringIO() as buf:
buf.write(str(self.stateNumber))
buf.write(":")
buf.write(str(self.configs))
if self.isAcceptState:
buf.write("=>")
if self.predicates is not None:
buf.write(str(self.predicates))
else:
buf.write(str(self.prediction))
return buf.getvalue()