#
# [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.
#/

# When we hit an accept state in either the DFA or the ATN, we
#  have to notify the character stream to start buffering characters
#  via {@link IntStream#mark} and record the current state. The current sim state
#  includes the current index into the input, the current line,
#  and current character position in that line. Note that the Lexer is
#  tracking the starting line and characterization of the token. These
#  variables track the "state" of the simulator when it hits an accept state.
#
#  <p>We track these variables separately for the DFA and ATN simulation
#  because the DFA simulation often has to fail over to the ATN
#  simulation. If the ATN simulation fails, we need the DFA to fall
#  back to its previously accepted state, if any. If the ATN succeeds,
#  then the ATN does the accept and the DFA simulator that invoked it
#  can simply return the predicted token type.</p>
#/

from antlr4.PredictionContext import PredictionContextCache, SingletonPredictionContext, PredictionContext
from antlr4.InputStream import InputStream
from antlr4.Token import Token
from antlr4.atn.ATN import ATN
from antlr4.atn.ATNConfig import LexerATNConfig
from antlr4.atn.ATNSimulator import ATNSimulator
from antlr4.atn.ATNConfigSet import ATNConfigSet, OrderedATNConfigSet
from antlr4.atn.ATNState import RuleStopState, ATNState
from antlr4.atn.LexerActionExecutor import LexerActionExecutor
from antlr4.atn.Transition import Transition
from antlr4.dfa.DFAState import DFAState
from antlr4.error.Errors import LexerNoViableAltException, UnsupportedOperationException

class SimState(object):

    def __init__(self):
        self.reset()

    def reset(self):
        self.index = -1
        self.line = 0
        self.column = -1
        self.dfaState = None

# need forward declaration
Lexer = None
LexerATNSimulator = None

class LexerATNSimulator(ATNSimulator):
    
    debug = False
    dfa_debug = False

    MIN_DFA_EDGE = 0
    MAX_DFA_EDGE = 127 # forces unicode to stay in ATN

    ERROR = None

    match_calls = 0

    def __init__(self, recog:Lexer, atn:ATN, decisionToDFA:list, sharedContextCache:PredictionContextCache):
        super().__init__(atn, sharedContextCache)
        self.decisionToDFA = decisionToDFA
        self.recog = recog
        # The current token's starting index into the character stream.
        #  Shared across DFA to ATN simulation in case the ATN fails and the
        #  DFA did not have a previous accept state. In this case, we use the
        #  ATN-generated exception object.
        self.startIndex = -1
        # line number 1..n within the input#/
        self.line = 1
        # The index of the character relative to the beginning of the line 0..n-1#/
        self.column = 0
        from antlr4.Lexer import Lexer
        self.mode = Lexer.DEFAULT_MODE
        # Used during DFA/ATN exec to record the most recent accept configuration info
        self.prevAccept = SimState()


    def copyState(self, simulator:LexerATNSimulator ):
        self.column = simulator.column
        self.line = simulator.line
        self.mode = simulator.mode
        self.startIndex = simulator.startIndex

    def match(self, input:InputStream , mode:int):
        self.match_calls += 1
        self.mode = mode
        mark = input.mark()
        try:
            self.startIndex = input.index
            self.prevAccept.reset()
            dfa = self.decisionToDFA[mode]
            if dfa.s0 is None:
                return self.matchATN(input)
            else:
                return self.execATN(input, dfa.s0)
        finally:
            input.release(mark)

    def reset(self):
        self.prevAccept.reset()
        self.startIndex = -1
        self.line = 1
        self.column = 0
        self.mode = Lexer.DEFAULT_MODE

    def matchATN(self, input:InputStream):
        startState = self.atn.modeToStartState[self.mode]

        if self.debug:
            print("matchATN mode " + str(self.mode) + " start: " + str(startState))

        old_mode = self.mode
        s0_closure = self.computeStartState(input, startState)
        suppressEdge = s0_closure.hasSemanticContext
        s0_closure.hasSemanticContext = False

        next = self.addDFAState(s0_closure)
        if not suppressEdge:
            self.decisionToDFA[self.mode].s0 = next

        predict = self.execATN(input, next)

        if self.debug:
            print("DFA after matchATN: " + str(self.decisionToDFA[old_mode].toLexerString()))

        return predict

    def execATN(self, input:InputStream, ds0:DFAState):
        if self.debug:
            print("start state closure=" + str(ds0.configs))

        if ds0.isAcceptState:
            # allow zero-length tokens
            self.captureSimState(self.prevAccept, input, ds0)

        t = input.LA(1)
        s = ds0 # s is current/from DFA state

        while True: # while more work
            if self.debug:
                print("execATN loop starting closure: %s\n", s.configs)

            # As we move src->trg, src->trg, we keep track of the previous trg to
            # avoid looking up the DFA state again, which is expensive.
            # If the previous target was already part of the DFA, we might
            # be able to avoid doing a reach operation upon t. If s!=null,
            # it means that semantic predicates didn't prevent us from
            # creating a DFA state. Once we know s!=null, we check to see if
            # the DFA state has an edge already for t. If so, we can just reuse
            # it's configuration set; there's no point in re-computing it.
            # This is kind of like doing DFA simulation within the ATN
            # simulation because DFA simulation is really just a way to avoid
            # computing reach/closure sets. Technically, once we know that
            # we have a previously added DFA state, we could jump over to
            # the DFA simulator. But, that would mean popping back and forth
            # a lot and making things more complicated algorithmically.
            # This optimization makes a lot of sense for loops within DFA.
            # A character will take us back to an existing DFA state
            # that already has lots of edges out of it. e.g., .* in comments.
            # print("Target for:" + str(s) + " and:" + str(t))
            target = self.getExistingTargetState(s, t)
            # print("Existing:" + str(target))
            if target is None:
                target = self.computeTargetState(input, s, t)
                # print("Computed:" + str(target))

            if target == self.ERROR:
                break

            # If this is a consumable input element, make sure to consume before
            # capturing the accept state so the input index, line, and char
            # position accurately reflect the state of the interpreter at the
            # end of the token.
            if t != Token.EOF:
                self.consume(input)

            if target.isAcceptState:
                self.captureSimState(self.prevAccept, input, target)
                if t == Token.EOF:
                    break

            t = input.LA(1)

            s = target # flip; current DFA target becomes new src/from state

        return self.failOrAccept(self.prevAccept, input, s.configs, t)

    # Get an existing target state for an edge in the DFA. If the target state
    # for the edge has not yet been computed or is otherwise not available,
    # this method returns {@code null}.
    #
    # @param s The current DFA state
    # @param t The next input symbol
    # @return The existing target DFA state for the given input symbol
    # {@code t}, or {@code null} if the target state for this edge is not
    # already cached
    def getExistingTargetState(self, s:DFAState, t:int):
        if s.edges is None or t < self.MIN_DFA_EDGE or t > self.MAX_DFA_EDGE:
            return None

        target = s.edges[t - self.MIN_DFA_EDGE]
        if self.debug and target is not None:
            print("reuse state "+s.stateNumber+ " edge to "+target.stateNumber)

        return target

    # Compute a target state for an edge in the DFA, and attempt to add the
    # computed state and corresponding edge to the DFA.
    #
    # @param input The input stream
    # @param s The current DFA state
    # @param t The next input symbol
    #
    # @return The computed target DFA state for the given input symbol
    # {@code t}. If {@code t} does not lead to a valid DFA state, this method
    # returns {@link #ERROR}.
    def computeTargetState(self, input:InputStream, s:DFAState, t:int):
        reach = OrderedATNConfigSet()

        # if we don't find an existing DFA state
        # Fill reach starting from closure, following t transitions
        self.getReachableConfigSet(input, s.configs, reach, t)

        if len(reach)==0: # we got nowhere on t from s
            if not reach.hasSemanticContext:
                # we got nowhere on t, don't throw out this knowledge; it'd
                # cause a failover from DFA later.
               self. addDFAEdge(s, t, self.ERROR)

            # stop when we can't match any more char
            return self.ERROR

        # Add an edge from s to target DFA found/created for reach
        return self.addDFAEdge(s, t, cfgs=reach)

    def failOrAccept(self, prevAccept:SimState , input:InputStream, reach:ATNConfigSet, t:int):
        if self.prevAccept.dfaState is not None:
            lexerActionExecutor = prevAccept.dfaState.lexerActionExecutor
            self.accept(input, lexerActionExecutor, self.startIndex, prevAccept.index, prevAccept.line, prevAccept.column)
            return prevAccept.dfaState.prediction
        else:
            # if no accept and EOF is first char, return EOF
            if t==Token.EOF and input.index==self.startIndex:
                return Token.EOF
            raise LexerNoViableAltException(self.recog, input, self.startIndex, reach)

    # Given a starting configuration set, figure out all ATN configurations
    #  we can reach upon input {@code t}. Parameter {@code reach} is a return
    #  parameter.
    def getReachableConfigSet(self, input:InputStream, closure:ATNConfigSet, reach:ATNConfigSet, t:int):
        # this is used to skip processing for configs which have a lower priority
        # than a config that already reached an accept state for the same rule
        skipAlt = ATN.INVALID_ALT_NUMBER
        for cfg in closure:
            currentAltReachedAcceptState = ( cfg.alt == skipAlt )
            if currentAltReachedAcceptState and cfg.passedThroughNonGreedyDecision:
                continue

            if self.debug:
                print("testing %s at %s\n", self.getTokenName(t), cfg.toString(self.recog, True))

            for trans in cfg.state.transitions:          # for each transition
                target = self.getReachableTarget(trans, t)
                if target is not None:
                    lexerActionExecutor = cfg.lexerActionExecutor
                    if lexerActionExecutor is not None:
                        lexerActionExecutor = lexerActionExecutor.fixOffsetBeforeMatch(input.index - self.startIndex)

                    treatEofAsEpsilon = (t == Token.EOF)
                    config = LexerATNConfig(state=target, lexerActionExecutor=lexerActionExecutor, config=cfg)
                    if self.closure(input, config, reach, currentAltReachedAcceptState, True, treatEofAsEpsilon):
                        # any remaining configs for this alt have a lower priority than
                        # the one that just reached an accept state.
                        skipAlt = cfg.alt

    def accept(self, input:InputStream, lexerActionExecutor:LexerActionExecutor, startIndex:int, index:int, line:int, charPos:int):
        if self.debug:
            print("ACTION %s\n", lexerActionExecutor)

        # seek to after last char in token
        input.seek(index)
        self.line = line
        self.column = charPos

        if lexerActionExecutor is not None and self.recog is not None:
            lexerActionExecutor.execute(self.recog, input, startIndex)

    def getReachableTarget(self, trans:Transition, t:int):
        if trans.matches(t, 0, 0xFFFE):
            return trans.target
        else:
            return None

    def computeStartState(self, input:InputStream, p:ATNState):
        initialContext = PredictionContext.EMPTY
        configs = OrderedATNConfigSet()
        for i in range(0,len(p.transitions)):
            target = p.transitions[i].target
            c = LexerATNConfig(state=target, alt=i+1, context=initialContext)
            self.closure(input, c, configs, False, False, False)
        return configs

    # Since the alternatives within any lexer decision are ordered by
    # preference, this method stops pursuing the closure as soon as an accept
    # state is reached. After the first accept state is reached by depth-first
    # search from {@code config}, all other (potentially reachable) states for
    # this rule would have a lower priority.
    #
    # @return {@code true} if an accept state is reached, otherwise
    # {@code false}.
    def closure(self, input:InputStream, config:LexerATNConfig, configs:ATNConfigSet, currentAltReachedAcceptState:bool,
                speculative:bool, treatEofAsEpsilon:bool):
        if self.debug:
            print("closure("+config.toString(self.recog, True)+")")

        if isinstance( config.state, RuleStopState ):
            if self.debug:
                if self.recog is not None:
                    print("closure at %s rule stop %s\n", self.recog.getRuleNames()[config.state.ruleIndex], config)
                else:
                    print("closure at rule stop %s\n", config)

            if config.context is None or config.context.hasEmptyPath():
                if config.context is None or config.context.isEmpty():
                    configs.add(config)
                    return True
                else:
                    configs.add(LexerATNConfig(state=config.state, config=config, context=PredictionContext.EMPTY))
                    currentAltReachedAcceptState = True

            if config.context is not None and not config.context.isEmpty():
                for i in range(0,len(config.context)):
                    if config.context.getReturnState(i) != PredictionContext.EMPTY_RETURN_STATE:
                        newContext = config.context.getParent(i) # "pop" return state
                        returnState = self.atn.states[config.context.getReturnState(i)]
                        c = LexerATNConfig(state=returnState, config=config, context=newContext)
                        currentAltReachedAcceptState = self.closure(input, c, configs,
                                    currentAltReachedAcceptState, speculative, treatEofAsEpsilon)

            return currentAltReachedAcceptState

        # optimization
        if not config.state.epsilonOnlyTransitions:
            if not currentAltReachedAcceptState or not config.passedThroughNonGreedyDecision:
                configs.add(config)

        for t in config.state.transitions:
            c = self.getEpsilonTarget(input, config, t, configs, speculative, treatEofAsEpsilon)
            if c is not None:
                currentAltReachedAcceptState = self.closure(input, c, configs, currentAltReachedAcceptState, speculative, treatEofAsEpsilon)

        return currentAltReachedAcceptState

    # side-effect: can alter configs.hasSemanticContext
    def getEpsilonTarget(self, input:InputStream, config:LexerATNConfig, t:Transition, configs:ATNConfigSet,
                                           speculative:bool, treatEofAsEpsilon:bool):
        c = None
        if t.serializationType==Transition.RULE:
                newContext = SingletonPredictionContext.create(config.context, t.followState.stateNumber)
                c = LexerATNConfig(state=t.target, config=config, context=newContext)

        elif t.serializationType==Transition.PRECEDENCE:
                raise UnsupportedOperationException("Precedence predicates are not supported in lexers.")

        elif t.serializationType==Transition.PREDICATE:
                #  Track traversing semantic predicates. If we traverse,
                # we cannot add a DFA state for this "reach" computation
                # because the DFA would not test the predicate again in the
                # future. Rather than creating collections of semantic predicates
                # like v3 and testing them on prediction, v4 will test them on the
                # fly all the time using the ATN not the DFA. This is slower but
                # semantically it's not used that often. One of the key elements to
                # this predicate mechanism is not adding DFA states that see
                # predicates immediately afterwards in the ATN. For example,

                # a : ID {p1}? | ID {p2}? ;

                # should create the start state for rule 'a' (to save start state
                # competition), but should not create target of ID state. The
                # collection of ATN states the following ID references includes
                # states reached by traversing predicates. Since this is when we
                # test them, we cannot cash the DFA state target of ID.

                if self.debug:
                    print("EVAL rule "+ str(t.ruleIndex) + ":" + str(t.predIndex))
                configs.hasSemanticContext = True
                if self.evaluatePredicate(input, t.ruleIndex, t.predIndex, speculative):
                    c = LexerATNConfig(state=t.target, config=config)

        elif t.serializationType==Transition.ACTION:
                if config.context is None or config.context.hasEmptyPath():
                    # execute actions anywhere in the start rule for a token.
                    #
                    # TODO: if the entry rule is invoked recursively, some
                    # actions may be executed during the recursive call. The
                    # problem can appear when hasEmptyPath() is true but
                    # isEmpty() is false. In this case, the config needs to be
                    # split into two contexts - one with just the empty path
                    # and another with everything but the empty path.
                    # Unfortunately, the current algorithm does not allow
                    # getEpsilonTarget to return two configurations, so
                    # additional modifications are needed before we can support
                    # the split operation.
                    lexerActionExecutor = LexerActionExecutor.append(config.lexerActionExecutor,
                                    self.atn.lexerActions[t.actionIndex])
                    c = LexerATNConfig(state=t.target, config=config, lexerActionExecutor=lexerActionExecutor)

                else:
                    # ignore actions in referenced rules
                    c = LexerATNConfig(state=t.target, config=config)

        elif t.serializationType==Transition.EPSILON:
            c = LexerATNConfig(state=t.target, config=config)

        elif t.serializationType in [ Transition.ATOM, Transition.RANGE, Transition.SET ]:
            if treatEofAsEpsilon:
                if t.matches(Token.EOF, 0, 0xFFFF):
                    c = LexerATNConfig(state=t.target, config=config)

        return c

    # Evaluate a predicate specified in the lexer.
    #
    # <p>If {@code speculative} is {@code true}, this method was called before
    # {@link #consume} for the matched character. This method should call
    # {@link #consume} before evaluating the predicate to ensure position
    # sensitive values, including {@link Lexer#getText}, {@link Lexer#getLine},
    # and {@link Lexer#getcolumn}, properly reflect the current
    # lexer state. This method should restore {@code input} and the simulator
    # to the original state before returning (i.e. undo the actions made by the
    # call to {@link #consume}.</p>
    #
    # @param input The input stream.
    # @param ruleIndex The rule containing the predicate.
    # @param predIndex The index of the predicate within the rule.
    # @param speculative {@code true} if the current index in {@code input} is
    # one character before the predicate's location.
    #
    # @return {@code true} if the specified predicate evaluates to
    # {@code true}.
    #/
    def evaluatePredicate(self, input:InputStream, ruleIndex:int, predIndex:int, speculative:bool):
        # assume true if no recognizer was provided
        if self.recog is None:
            return True

        if not speculative:
            return self.recog.sempred(None, ruleIndex, predIndex)

        savedcolumn = self.column
        savedLine = self.line
        index = input.index
        marker = input.mark()
        try:
            self.consume(input)
            return self.recog.sempred(None, ruleIndex, predIndex)
        finally:
            self.column = savedcolumn
            self.line = savedLine
            input.seek(index)
            input.release(marker)

    def captureSimState(self, settings:SimState, input:InputStream, dfaState:DFAState):
        settings.index = input.index
        settings.line = self.line
        settings.column = self.column
        settings.dfaState = dfaState

    def addDFAEdge(self, from_:DFAState, tk:int, to:DFAState=None, cfgs:ATNConfigSet=None) -> DFAState:

        if to is None and cfgs is not None:
            # leading to this call, ATNConfigSet.hasSemanticContext is used as a
            # marker indicating dynamic predicate evaluation makes this edge
            # dependent on the specific input sequence, so the static edge in the
            # DFA should be omitted. The target DFAState is still created since
            # execATN has the ability to resynchronize with the DFA state cache
            # following the predicate evaluation step.
            #
            # TJP notes: next time through the DFA, we see a pred again and eval.
            # If that gets us to a previously created (but dangling) DFA
            # state, we can continue in pure DFA mode from there.
            #/
            suppressEdge = cfgs.hasSemanticContext
            cfgs.hasSemanticContext = False

            to = self.addDFAState(cfgs)

            if suppressEdge:
                return to

        # add the edge
        if tk < self.MIN_DFA_EDGE or tk > self.MAX_DFA_EDGE:
            # Only track edges within the DFA bounds
            return to

        if self.debug:
            print("EDGE " + str(from_) + " -> " + str(to) + " upon "+ chr(tk))

        if from_.edges is None:
            #  make room for tokens 1..n and -1 masquerading as index 0
            from_.edges = [ None ] * (self.MAX_DFA_EDGE - self.MIN_DFA_EDGE + 1)

        from_.edges[tk - self.MIN_DFA_EDGE] = to # connect

        return to


    # Add a new DFA state if there isn't one with this set of
    # configurations already. This method also detects the first
    # configuration containing an ATN rule stop state. Later, when
    # traversing the DFA, we will know which rule to accept.
    def addDFAState(self, configs:ATNConfigSet) -> DFAState:

        proposed = DFAState(configs=configs)
        firstConfigWithRuleStopState = None
        for c in configs:
            if isinstance(c.state, RuleStopState):
                firstConfigWithRuleStopState = c
                break

        if firstConfigWithRuleStopState is not None:
            proposed.isAcceptState = True
            proposed.lexerActionExecutor = firstConfigWithRuleStopState.lexerActionExecutor
            proposed.prediction = self.atn.ruleToTokenType[firstConfigWithRuleStopState.state.ruleIndex]

        dfa = self.decisionToDFA[self.mode]
        existing = dfa.states.get(proposed, None)
        if existing is not None:
            return existing

        newState = proposed

        newState.stateNumber = len(dfa.states)
        configs.setReadonly(True)
        newState.configs = configs
        dfa.states[newState] = newState
        return newState

    def getDFA(self, mode:int):
        return self.decisionToDFA[mode]

    # Get the text matched so far for the current token.
    def getText(self, input:InputStream):
        # index is first lookahead char, don't include.
        return input.getText(self.startIndex, input.index-1)

    def consume(self, input:InputStream):
        curChar = input.LA(1)
        if curChar==ord('\n'):
            self.line += 1
            self.column = 0
        else:
            self.column += 1
        input.consume()
        else:
            return "'" + chr(t) + "'"


LexerATNSimulator.ERROR = DFAState(0x7FFFFFFF, ATNConfigSet())

del Lexer

    def getTokenName(self, t:int):
        if t==-1:
            return "EOF"