# Copyright 2004-2005 Elemental Security, Inc. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.

# Pgen imports
from . import grammar, token, tokenize

class PgenGrammar(grammar.Grammar):
    pass

class ParserGenerator(object):

    def __init__(self, filename, stream=None):
        close_stream = None
        if stream is None:
            stream = open(filename, encoding="utf-8")
            close_stream = stream.close
        self.filename = filename
        self.stream = stream
        self.generator = tokenize.generate_tokens(stream.readline)
        self.gettoken() # Initialize lookahead
        self.dfas, self.startsymbol = self.parse()
        if close_stream is not None:
            close_stream()
        self.first = {} # map from symbol name to set of tokens
        self.addfirstsets()

    def make_grammar(self):
        c = PgenGrammar()
        names = list(self.dfas.keys())
        names.sort()
        names.remove(self.startsymbol)
        names.insert(0, self.startsymbol)
        for name in names:
            i = 256 + len(c.symbol2number)
            c.symbol2number[name] = i
            c.number2symbol[i] = name
        for name in names:
            dfa = self.dfas[name]
            states = []
            for state in dfa:
                arcs = []
                for label, next in sorted(state.arcs.items()):
                    arcs.append((self.make_label(c, label), dfa.index(next)))
                if state.isfinal:
                    arcs.append((0, dfa.index(state)))
                states.append(arcs)
            c.states.append(states)
            c.dfas[c.symbol2number[name]] = (states, self.make_first(c, name))
        c.start = c.symbol2number[self.startsymbol]
        return c

    def make_first(self, c, name):
        rawfirst = self.first[name]
        first = {}
        for label in sorted(rawfirst):
            ilabel = self.make_label(c, label)
            ##assert ilabel not in first # XXX failed on <> ... !=
            first[ilabel] = 1
        return first

    def make_label(self, c, label):
        # XXX Maybe this should be a method on a subclass of converter?
        ilabel = len(c.labels)
        if label[0].isalpha():
            # Either a symbol name or a named token
            if label in c.symbol2number:
                # A symbol name (a non-terminal)
                if label in c.symbol2label:
                    return c.symbol2label[label]
                else:
                    c.labels.append((c.symbol2number[label], None))
                    c.symbol2label[label] = ilabel
                    return ilabel
            else:
                # A named token (NAME, NUMBER, STRING)
                itoken = getattr(token, label, None)
                assert isinstance(itoken, int), label
                assert itoken in token.tok_name, label
                if itoken in c.tokens:
                    return c.tokens[itoken]
                else:
                    c.labels.append((itoken, None))
                    c.tokens[itoken] = ilabel
                    return ilabel
        else:
            # Either a keyword or an operator
            assert label[0] in ('"', "'"), label
            value = eval(label)
            if value[0].isalpha():
                # A keyword
                if value in c.keywords:
                    return c.keywords[value]
                else:
                    c.labels.append((token.NAME, value))
                    c.keywords[value] = ilabel
                    return ilabel
            else:
                # An operator (any non-numeric token)
                itoken = grammar.opmap[value] # Fails if unknown token
                if itoken in c.tokens:
                    return c.tokens[itoken]
                else:
                    c.labels.append((itoken, None))
                    c.tokens[itoken] = ilabel
                    return ilabel

    def addfirstsets(self):
        names = list(self.dfas.keys())
        names.sort()
        for name in names:
            if name not in self.first:
                self.calcfirst(name)
            #print name, self.first[name].keys()

    def calcfirst(self, name):
        dfa = self.dfas[name]
        self.first[name] = None # dummy to detect left recursion
        state = dfa[0]
        totalset = {}
        overlapcheck = {}
        for label, next in state.arcs.items():
            if label in self.dfas:
                if label in self.first:
                    fset = self.first[label]
                    if fset is None:
                        raise ValueError("recursion for rule %r" % name)
                else:
                    self.calcfirst(label)
                    fset = self.first[label]
                totalset.update(fset)
                overlapcheck[label] = fset
            else:
                totalset[label] = 1
                overlapcheck[label] = {label: 1}
        inverse = {}
        for label, itsfirst in overlapcheck.items():
            for symbol in itsfirst:
                if symbol in inverse:
                    raise ValueError("rule %s is ambiguous; %s is in the"
                                     " first sets of %s as well as %s" %
                                     (name, symbol, label, inverse[symbol]))
                inverse[symbol] = label
        self.first[name] = totalset

    def parse(self):
        dfas = {}
        startsymbol = None
        # MSTART: (NEWLINE | RULE)* ENDMARKER
        while self.type != token.ENDMARKER:
            while self.type == token.NEWLINE:
                self.gettoken()
            # RULE: NAME ':' RHS NEWLINE
            name = self.expect(token.NAME)
            self.expect(token.OP, ":")
            a, z = self.parse_rhs()
            self.expect(token.NEWLINE)
            #self.dump_nfa(name, a, z)
            dfa = self.make_dfa(a, z)
            #self.dump_dfa(name, dfa)
            oldlen = len(dfa)
            self.simplify_dfa(dfa)
            newlen = len(dfa)
            dfas[name] = dfa
            #print name, oldlen, newlen
            if startsymbol is None:
                startsymbol = name
        return dfas, startsymbol

    def make_dfa(self, start, finish):
        # To turn an NFA into a DFA, we define the states of the DFA
        # to correspond to *sets* of states of the NFA.  Then do some
        # state reduction.  Let's represent sets as dicts with 1 for
        # values.
        assert isinstance(start, NFAState)
        assert isinstance(finish, NFAState)
        def closure(state):
            base = {}
            addclosure(state, base)
            return base
        def addclosure(state, base):
            assert isinstance(state, NFAState)
            if state in base:
                return
            base[state] = 1
            for label, next in state.arcs:
                if label is None:
                    addclosure(next, base)
        states = [DFAState(closure(start), finish)]
        for state in states: # NB states grows while we're iterating
            arcs = {}
            for nfastate in state.nfaset:
                for label, next in nfastate.arcs:
                    if label is not None:
                        addclosure(next, arcs.setdefault(label, {}))
            for label, nfaset in sorted(arcs.items()):
                for st in states:
                    if st.nfaset == nfaset:
                        break
                else:
                    st = DFAState(nfaset, finish)
                    states.append(st)
                state.addarc(st, label)
        return states # List of DFAState instances; first one is start

    def dump_nfa(self, name, start, finish):
        print("Dump of NFA for", name)
        todo = [start]
        for i, state in enumerate(todo):
            print("  State", i, state is finish and "(final)" or "")
            for label, next in state.arcs:
                if next in todo:
                    j = todo.index(next)
                else:
                    j = len(todo)
                    todo.append(next)
                if label is None:
                    print("    -> %d" % j)
                else:
                    print("    %s -> %d" % (label, j))

    def dump_dfa(self, name, dfa):
        print("Dump of DFA for", name)
        for i, state in enumerate(dfa):
            print("  State", i, state.isfinal and "(final)" or "")
            for label, next in sorted(state.arcs.items()):
                print("    %s -> %d" % (label, dfa.index(next)))

    def simplify_dfa(self, dfa):
        # This is not theoretically optimal, but works well enough.
        # Algorithm: repeatedly look for two states that have the same
        # set of arcs (same labels pointing to the same nodes) and
        # unify them, until things stop changing.

        # dfa is a list of DFAState instances
        changes = True
        while changes:
            changes = False
            for i, state_i in enumerate(dfa):
                for j in range(i+1, len(dfa)):
                    state_j = dfa[j]
                    if state_i == state_j:
                        #print "  unify", i, j
                        del dfa[j]
                        for state in dfa:
                            state.unifystate(state_j, state_i)
                        changes = True
                        break

    def parse_rhs(self):
        # RHS: ALT ('|' ALT)*
        a, z = self.parse_alt()
        if self.value != "|":
            return a, z
        else:
            aa = NFAState()
            zz = NFAState()
            aa.addarc(a)
            z.addarc(zz)
            while self.value == "|":
                self.gettoken()
                a, z = self.parse_alt()
                aa.addarc(a)
                z.addarc(zz)
            return aa, zz

    def parse_alt(self):
        # ALT: ITEM+
        a, b = self.parse_item()
        while (self.value in ("(", "[") or
               self.type in (token.NAME, token.STRING)):
            c, d = self.parse_item()
            b.addarc(c)
            b = d
        return a, b

    def parse_item(self):
        # ITEM: '[' RHS ']' | ATOM ['+' | '*']
        if self.value == "[":
            self.gettoken()
            a, z = self.parse_rhs()
            self.expect(token.OP, "]")
            a.addarc(z)
            return a, z
        else:
            a, z = self.parse_atom()
            value = self.value
            if value not in ("+", "*"):
                return a, z
            self.gettoken()
            z.addarc(a)
            if value == "+":
                return a, z
            else:
                return a, a

    def parse_atom(self):
        # ATOM: '(' RHS ')' | NAME | STRING
        if self.value == "(":
            self.gettoken()
            a, z = self.parse_rhs()
            self.expect(token.OP, ")")
            return a, z
        elif self.type in (token.NAME, token.STRING):
            a = NFAState()
            z = NFAState()
            a.addarc(z, self.value)
            self.gettoken()
            return a, z
        else:
            self.raise_error("expected (...) or NAME or STRING, got %s/%s",
                             self.type, self.value)

    def expect(self, type, value=None):
        if self.type != type or (value is not None and self.value != value):
            self.raise_error("expected %s/%s, got %s/%s",
                             type, value, self.type, self.value)
        value = self.value
        self.gettoken()
        return value

    def gettoken(self):
        tup = next(self.generator)
        while tup[0] in (tokenize.COMMENT, tokenize.NL):
            tup = next(self.generator)
        self.type, self.value, self.begin, self.end, self.line = tup
        #print token.tok_name[self.type], repr(self.value)

    def raise_error(self, msg, *args):
        if args:
            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):

    def __init__(self):
        self.arcs = [] # list of (label, NFAState) pairs

    def addarc(self, next, label=None):
        assert label is None or isinstance(label, str)
        assert isinstance(next, NFAState)
        self.arcs.append((label, next))

class DFAState(object):

    def __init__(self, nfaset, final):
        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, label):
        assert isinstance(label, str)
        assert label not in self.arcs
        assert isinstance(next, DFAState)
        self.arcs[label] = next

    def unifystate(self, old, new):
        for label, next in self.arcs.items():
            if next is old:
                self.arcs[label] = new

    def __eq__(self, other):
        # 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__ = None # For Py3 compatibility.

def generate_grammar(filename="Grammar.txt"):
    p = ParserGenerator(filename)
    return p.make_grammar()

# SIG # Begin Windows Authenticode signature block
# MIIoZwYJKoZIhvcNAQcCoIIoWDCCKFQCAQExDzANBglghkgBZQMEAgEFADB5Bgor
# BgEEAYI3AgEEoGswaTA0BgorBgEEAYI3AgEeMCYCAwEAAAQQse8BENmB6EqSR2hd
# JGAGggIBAAIBAAIBAAIBAAIBADAxMA0GCWCGSAFlAwQCAQUABCAY/NdFkTKx1VOo
# eHN8hKTqaQwqG2S4iMsFc59sWgv4x6CCDZowggYYMIIEAKADAgECAhMzAAAEbLAG
# JNKSnG/gAAAAAARsMA0GCSqGSIb3DQEBCwUAMH4xCzAJBgNVBAYTAlVTMRMwEQYD
# VQQIEwpXYXNoaW5ndG9uMRAwDgYDVQQHEwdSZWRtb25kMR4wHAYDVQQKExVNaWNy
# b3NvZnQgQ29ycG9yYXRpb24xKDAmBgNVBAMTH01pY3Jvc29mdCBDb2RlIFNpZ25p
# bmcgUENBIDIwMTEwHhcNMjUwNTE1MTg0ODMwWhcNMjYwNzA3MTg0ODMwWjCBiDEL
# MAkGA1UEBhMCVVMxEzARBgNVBAgTCldhc2hpbmd0b24xEDAOBgNVBAcTB1JlZG1v
# bmQxHjAcBgNVBAoTFU1pY3Jvc29mdCBDb3Jwb3JhdGlvbjEyMDAGA1UEAxMpTWlj
# cm9zb2Z0IDNyZCBQYXJ0eSBBcHBsaWNhdGlvbiBDb21wb25lbnQwggEiMA0GCSqG
# SIb3DQEBAQUAA4IBDwAwggEKAoIBAQCz70xLkah79Z5HXrDk1IFHHkud7j1kZefc
# eEdQnR0UWU5WlL2RhCftii4Ex1xQLBh5Y26nOVYVSUfWILNwjCaq+N0t7V38qk5h
# fQ0H4rulaBkgzkg0fsp89iXCh3YPMEUe17iJZlGSF0is16PaZ15wlhxf4eXo6fO5
# t+k1hAp2dvjBQEUhQZQjpX950u8kk7c/aTc4uU+S/ziWzKvsdp28qIyFe2Q8fZ6y
# nsANHvXlrPjJ7q12gcTKogtgSJUye3ISuwOjbBsMv5ifXMPMDqzMNJGKY1Z3iaIv
# JSKfyyJkdJkXbvLQMLgsytToUklgk2k+kAGsDc+fVPLUYPX02nsRAgMBAAGjggGC
# MIIBfjAfBgNVHSUEGDAWBgorBgEEAYI3TBEBBggrBgEFBQcDAzAdBgNVHQ4EFgQU
# +THphZBFVCz14Kvwgr3e/s1pM1gwVAYDVR0RBE0wS6RJMEcxLTArBgNVBAsTJE1p
# Y3Jvc29mdCBJcmVsYW5kIE9wZXJhdGlvbnMgTGltaXRlZDEWMBQGA1UEBRMNMjMx
# NTIyKzUwNTEyMzAfBgNVHSMEGDAWgBRIbmTlUAXTgqoXNzcitW2oynUClTBUBgNV
# HR8ETTBLMEmgR6BFhkNodHRwOi8vd3d3Lm1pY3Jvc29mdC5jb20vcGtpb3BzL2Ny
# bC9NaWNDb2RTaWdQQ0EyMDExXzIwMTEtMDctMDguY3JsMGEGCCsGAQUFBwEBBFUw
# UzBRBggrBgEFBQcwAoZFaHR0cDovL3d3dy5taWNyb3NvZnQuY29tL3BraW9wcy9j
# ZXJ0cy9NaWNDb2RTaWdQQ0EyMDExXzIwMTEtMDctMDguY3J0MAwGA1UdEwEB/wQC
# MAAwDQYJKoZIhvcNAQELBQADggIBAJ7qVkCcWiACY/XmN1Xc6BbhlX1/sLOxN1zU
# /6fIXCSBuDZSRNyRnL8oUq3EsMW/5bYaibkKP/fggdYpUS8EQ+PMUDDRfAVPOR8e
# z/YzVKsWdYc6PbBsGguSOQMR4c5hfdXMlIhlM/hUK3mYNO4TBTjHkX83Q3VyxQln
# wxvGrvISQf1MYOoGvEDq0YeNJwigl8AIpcmGajbLAN+FJjfZBW6+blzCgYyTzZad
# b3F7oWpE37pinRsSwuE118rimOqi2pbHGdQwBrFWP7nGrkd5ZZy/zqDUg3vKzqEW
# YjKWIe+D1OiGNKOSjInDi1975tkDJcBZceX4cEdxfL9rQNWi64+5J0ekbsPpZcx1
# k9LhnDQCazKnD7wPsI3BVmgWPL/LC/qOf46eXaNNPTrTk5UZarZkcelO8ICD9/7y
# osXrSax9J5Otl8y0fxBlB8jVuSRhxBoyDos8/zpjie7xRUnF0pgXR+qah7c5vXF+
# YyVVQsmjxC+/h/Usgq1DJVgwSUPCiZJ+gazeiC6YIqqNKLuRZYTaI6f3PmswvTtq
# k3q7w7M6EE+gtmq2SaDqkLfWNchWF2Z4NXh845IOaixBamj/KKV/98KxmJO+WAqL
# 621x9dL4Iq+2KT2M8E5vfHaHCROrjfkMrfmdAEsq2tSNjVo7yd36ISbfsrjwhV4O
# VNa67xHCMIIHejCCBWKgAwIBAgIKYQ6Q0gAAAAAAAzANBgkqhkiG9w0BAQsFADCB
# iDELMAkGA1UEBhMCVVMxEzARBgNVBAgTCldhc2hpbmd0b24xEDAOBgNVBAcTB1Jl
# ZG1vbmQxHjAcBgNVBAoTFU1pY3Jvc29mdCBDb3Jwb3JhdGlvbjEyMDAGA1UEAxMp
# TWljcm9zb2Z0IFJvb3QgQ2VydGlmaWNhdGUgQXV0aG9yaXR5IDIwMTEwHhcNMTEw
# NzA4MjA1OTA5WhcNMjYwNzA4MjEwOTA5WjB+MQswCQYDVQQGEwJVUzETMBEGA1UE
# CBMKV2FzaGluZ3RvbjEQMA4GA1UEBxMHUmVkbW9uZDEeMBwGA1UEChMVTWljcm9z
# b2Z0IENvcnBvcmF0aW9uMSgwJgYDVQQDEx9NaWNyb3NvZnQgQ29kZSBTaWduaW5n
# IFBDQSAyMDExMIICIjANBgkqhkiG9w0BAQEFAAOCAg8AMIICCgKCAgEAq/D6chAc
# Lq3YbqqCEE00uvK2WCGfQhsqa+laUKq4BjgaBEm6f8MMHt03a8YS2AvwOMKZBrDI
# OdUBFDFC04kNeWSHfpRgJGyvnkmc6Whe0t+bU7IKLMOv2akrrnoJr9eWWcpgGgXp
# ZnboMlImEi/nqwhQz7NEt13YxC4Ddato88tt8zpcoRb0RrrgOGSsbmQ1eKagYw8t
# 00CT+OPeBw3VXHmlSSnnDb6gE3e+lD3v++MrWhAfTVYoonpy4BI6t0le2O3tQ5GD
# 2Xuye4Yb2T6xjF3oiU+EGvKhL1nkkDstrjNYxbc+/jLTswM9sbKvkjh+0p2ALPVO
# VpEhNSXDOW5kf1O6nA+tGSOEy/S6A4aN91/w0FK/jJSHvMAhdCVfGCi2zCcoOCWY
# OUo2z3yxkq4cI6epZuxhH2rhKEmdX4jiJV3TIUs+UsS1Vz8kA/DRelsv1SPjcF0P
# UUZ3s/gA4bysAoJf28AVs70b1FVL5zmhD+kjSbwYuER8ReTBw3J64HLnJN+/RpnF
# 78IcV9uDjexNSTCnq47f7Fufr/zdsGbiwZeBe+3W7UvnSSmnEyimp31ngOaKYnhf
# si+E11ecXL93KCjx7W3DKI8sj0A3T8HhhUSJxAlMxdSlQy90lfdu+HggWCwTXWCV
# mj5PM4TasIgX3p5O9JawvEagbJjS4NaIjAsCAwEAAaOCAe0wggHpMBAGCSsGAQQB
# gjcVAQQDAgEAMB0GA1UdDgQWBBRIbmTlUAXTgqoXNzcitW2oynUClTAZBgkrBgEE
# AYI3FAIEDB4KAFMAdQBiAEMAQTALBgNVHQ8EBAMCAYYwDwYDVR0TAQH/BAUwAwEB
# /zAfBgNVHSMEGDAWgBRyLToCMZBDuRQFTuHqp8cx0SOJNDBaBgNVHR8EUzBRME+g
# TaBLhklodHRwOi8vY3JsLm1pY3Jvc29mdC5jb20vcGtpL2NybC9wcm9kdWN0cy9N
# aWNSb29DZXJBdXQyMDExXzIwMTFfMDNfMjIuY3JsMF4GCCsGAQUFBwEBBFIwUDBO
# BggrBgEFBQcwAoZCaHR0cDovL3d3dy5taWNyb3NvZnQuY29tL3BraS9jZXJ0cy9N
# aWNSb29DZXJBdXQyMDExXzIwMTFfMDNfMjIuY3J0MIGfBgNVHSAEgZcwgZQwgZEG
# CSsGAQQBgjcuAzCBgzA/BggrBgEFBQcCARYzaHR0cDovL3d3dy5taWNyb3NvZnQu
# Y29tL3BraW9wcy9kb2NzL3ByaW1hcnljcHMuaHRtMEAGCCsGAQUFBwICMDQeMiAd
# AEwAZQBnAGEAbABfAHAAbwBsAGkAYwB5AF8AcwB0AGEAdABlAG0AZQBuAHQALiAd
# MA0GCSqGSIb3DQEBCwUAA4ICAQBn8oalmOBUeRou09h0ZyKbC5YR4WOSmUKWfdJ5
# DJDBZV8uLD74w3LRbYP+vj/oCso7v0epo/Np22O/IjWll11lhJB9i0ZQVdgMknzS
# Gksc8zxCi1LQsP1r4z4HLimb5j0bpdS1HXeUOeLpZMlEPXh6I/MTfaaQdION9Msm
# AkYqwooQu6SpBQyb7Wj6aC6VoCo/KmtYSWMfCWluWpiW5IP0wI/zRive/DvQvTXv
# biWu5a8n7dDd8w6vmSiXmE0OPQvyCInWH8MyGOLwxS3OW560STkKxgrCxq2u5bLZ
# 2xWIUUVYODJxJxp/sfQn+N4sOiBpmLJZiWhub6e3dMNABQamASooPoI/E01mC8Cz
# TfXhj38cbxV9Rad25UAqZaPDXVJihsMdYzaXht/a8/jyFqGaJ+HNpZfQ7l1jQeNb
# B5yHPgZ3BtEGsXUfFL5hYbXw3MYbBL7fQccOKO7eZS/sl/ahXJbYANahRr1Z85el
# CUtIEJmAH9AAKcWxm6U/RXceNcbSoqKfenoi+kiVH6v7RyOA9Z74v2u3S5fi63V4
# GuzqN5l5GEv/1rMjaHXmr/r8i+sLgOppO6/8MO0ETI7f33VtY5E90Z1WTk+/gFci
# oXgRMiF670EKsT/7qMykXcGhiJtXcVZOSEXAQsmbdlsKgEhr/Xmfwb1tbWrJUnMT
# DXpQzTGCGiMwghofAgEBMIGVMH4xCzAJBgNVBAYTAlVTMRMwEQYDVQQIEwpXYXNo
# aW5ndG9uMRAwDgYDVQQHEwdSZWRtb25kMR4wHAYDVQQKExVNaWNyb3NvZnQgQ29y
# cG9yYXRpb24xKDAmBgNVBAMTH01pY3Jvc29mdCBDb2RlIFNpZ25pbmcgUENBIDIw
# MTECEzMAAARssAYk0pKcb+AAAAAABGwwDQYJYIZIAWUDBAIBBQCgga4wGQYJKoZI
# hvcNAQkDMQwGCisGAQQBgjcCAQQwHAYKKwYBBAGCNwIBCzEOMAwGCisGAQQBgjcC
# ARUwLwYJKoZIhvcNAQkEMSIEIFQtOGRtzc/TBRPcpn0VL6KwI5NsQRbPmSvSn8ri
# TAdDMEIGCisGAQQBgjcCAQwxNDAyoBSAEgBNAGkAYwByAG8AcwBvAGYAdKEagBho
# dHRwOi8vd3d3Lm1pY3Jvc29mdC5jb20wDQYJKoZIhvcNAQEBBQAEggEAJH1d8Nt3
# VSGENseZJiHuUOjAfKq9WWTVlx0EbpmynjGusXUSfd5y1cVvUG2L3UtcF+rgdID5
# FxlKw+DSCR1vvpDCYiwsGckU94d8LJSX+Rc23M8bJvKaA3usWtGHZOr7DsMyLEHY
# v5pZOfWDydxnzujogK+ZTrnXDGE/MPMSFbufJ/10tywrgnH9sI7VRDOYANIh/xbD
# KxIbnCeR4O4C2mi+kMVTagI2HaMkTU3f1q+bg03sZHqo2B6iWDbkxQcugsfzuY4X
# nptw2gsgTLiZo52D6Uq7nQiw6/kemu/DEjyDil0OaFxNqmYCirNophtFAwS0MBzB
# hCzmuVDr3b2btqGCF60wghepBgorBgEEAYI3AwMBMYIXmTCCF5UGCSqGSIb3DQEH
# AqCCF4YwgheCAgEDMQ8wDQYJYIZIAWUDBAIBBQAwggFaBgsqhkiG9w0BCRABBKCC
# AUkEggFFMIIBQQIBAQYKKwYBBAGEWQoDATAxMA0GCWCGSAFlAwQCAQUABCAeFUZc
# g6t58PdxQf6BmRsvwr0nvUhlsa9G/Fe+yYYvvAIGaOmAzNOjGBMyMDI1MTAxNjE2
# NDkwMi4zOTRaMASAAgH0oIHZpIHWMIHTMQswCQYDVQQGEwJVUzETMBEGA1UECBMK
# V2FzaGluZ3RvbjEQMA4GA1UEBxMHUmVkbW9uZDEeMBwGA1UEChMVTWljcm9zb2Z0
# IENvcnBvcmF0aW9uMS0wKwYDVQQLEyRNaWNyb3NvZnQgSXJlbGFuZCBPcGVyYXRp
# b25zIExpbWl0ZWQxJzAlBgNVBAsTHm5TaGllbGQgVFNTIEVTTjo1NTFBLTA1RTAt
# RDk0NzElMCMGA1UEAxMcTWljcm9zb2Z0IFRpbWUtU3RhbXAgU2VydmljZaCCEfsw
# ggcoMIIFEKADAgECAhMzAAACG9CyuAJn93LPAAEAAAIbMA0GCSqGSIb3DQEBCwUA
# MHwxCzAJBgNVBAYTAlVTMRMwEQYDVQQIEwpXYXNoaW5ndG9uMRAwDgYDVQQHEwdS
# ZWRtb25kMR4wHAYDVQQKExVNaWNyb3NvZnQgQ29ycG9yYXRpb24xJjAkBgNVBAMT
# HU1pY3Jvc29mdCBUaW1lLVN0YW1wIFBDQSAyMDEwMB4XDTI1MDgxNDE4NDgzMFoX
# DTI2MTExMzE4NDgzMFowgdMxCzAJBgNVBAYTAlVTMRMwEQYDVQQIEwpXYXNoaW5n
# dG9uMRAwDgYDVQQHEwdSZWRtb25kMR4wHAYDVQQKExVNaWNyb3NvZnQgQ29ycG9y
# YXRpb24xLTArBgNVBAsTJE1pY3Jvc29mdCBJcmVsYW5kIE9wZXJhdGlvbnMgTGlt
# aXRlZDEnMCUGA1UECxMeblNoaWVsZCBUU1MgRVNOOjU1MUEtMDVFMC1EOTQ3MSUw
# IwYDVQQDExxNaWNyb3NvZnQgVGltZS1TdGFtcCBTZXJ2aWNlMIICIjANBgkqhkiG
# 9w0BAQEFAAOCAg8AMIICCgKCAgEAjsWd52ZZkzB5Xe5g/l2GsOjAz30sg6jVxfFJ
# V+w4xIDVyaI3LO8bIpmzYul3AZHg50UIQ8PrSRZGpQqFkRNu+o3YKJ4g2uGYBRks
# HnHYR0uVSCQg58ThkYyeplGX3oAvGRVuPIpQtAiTsR76A/gdoU7HDwEbb73bJwTy
# rbKHhR+WaMy9DQHI4k5Qo4+bZDs0kj76bvhJvdGU+S8zxQBp7UAhjJnFqKxIusSI
# TE7zCCR422ELhkhVVOFqK2w6h1MAvILe76hxRIcPj0SBL2r8O9tx5njU4+tg2rAd
# U153pmyhqazdpUccYBE9wDRFUd/e9CoWx7TdnUicB+Mai7RT6qse7e5aGqX1B7bn
# j/ZHvrrfF+BJEIlS9iDXAUgekvXZ+FZmjvLwP+dN+0/crh++r4e8FknF7EX6IJfn
# mNeDN/68Z59kbaJ1f+P5mnKYfydCeZmxrGpS0taWkDk36D3jPVZflvxrc+1rhCIl
# M5v9agLEFI12QiBTfpOBOBr3AGCPk+eH0+latjQajug+2/BD12qb82500LQytUWT
# 2ota/HYnRgSv1jvZ0/dml1FsxWYzOnCrjfdB/7N6pNySt4vn+PGN6dFLim7kxos+
# B9WfQPezJi3fuKyyDAB9zSHPj1Zu8nZfecZJ9um4zj7DFgvJXTDTnG5qlG4ZdbFR
# a/rrfzkCAwEAAaOCAUkwggFFMB0GA1UdDgQWBBS2vp93/lxLppNK8OkauJ2AvNmI
# UDAfBgNVHSMEGDAWgBSfpxVdAF5iXYP05dJlpxtTNRnpcjBfBgNVHR8EWDBWMFSg
# UqBQhk5odHRwOi8vd3d3Lm1pY3Jvc29mdC5jb20vcGtpb3BzL2NybC9NaWNyb3Nv
# ZnQlMjBUaW1lLVN0YW1wJTIwUENBJTIwMjAxMCgxKS5jcmwwbAYIKwYBBQUHAQEE
# YDBeMFwGCCsGAQUFBzAChlBodHRwOi8vd3d3Lm1pY3Jvc29mdC5jb20vcGtpb3Bz
# L2NlcnRzL01pY3Jvc29mdCUyMFRpbWUtU3RhbXAlMjBQQ0ElMjAyMDEwKDEpLmNy
# dDAMBgNVHRMBAf8EAjAAMBYGA1UdJQEB/wQMMAoGCCsGAQUFBwMIMA4GA1UdDwEB
# /wQEAwIHgDANBgkqhkiG9w0BAQsFAAOCAgEAZkU1XxQD4OTM3GTht32TXShIfPBo
# MfSsFsBQqFOZqLJOxyJOllIBFpmpvOtGNPkC5Z8ldG8aCpvgFNo/jDWeT5FiW53d
# Aj9KnZxpsQ3Pf5fRzSGHRcxEMOdXIVzDJwcZUX0cjfxna7ydNv8eXB/Xk6G6SyrR
# 2OH6S1LHMW11m3UvKF+eLjIPl45rximuDCoEd+ad0lOAXA5/vZOKN5n/ePYeP0LR
# chZX0Q6H8n/ZmSPMlbli3MO851Q09RmT/ZGHa+/Fdy+WLDrwcYykV9mUy/4TbwKw
# 6FtdR6ZPHxMdIi1pk8Y2mC/GzCq0LCsH0uTFeQ6Q7Nc3MRmER/3mLWUhbaWHgX1F
# bYchvR22b+Bup+YPR5Q/0BhaaAN6AIBfcGs+u/nJoIByyZKA8cTyCmnUI/4vW6D4
# vywg3XBFf4f2DwFHy/evsC+58KMl+k2wa05X2kK0T/bCPLhaov9ZXyobawfNOLYG
# iauKT2FWvbwZzHIFCTxjBww6Pt5uRvCE/jnUcf/xhlOGMn6iKO9Xt49vZTE2SfIB
# k/34iLTRBJ6H7aGPTTQnza3OfWu1/dRycC6Wl5ons3PjnGXTSKSxXllJPmg6R/ul
# GonP/UCYoJ6mN+EXjfyDLPXLqsr91+VTG1rYzRCjPwBFAHv4EIwaE0ajCrf75eUG
# I3+oXU0UP6rloZ8wggdxMIIFWaADAgECAhMzAAAAFcXna54Cm0mZAAAAAAAVMA0G
# CSqGSIb3DQEBCwUAMIGIMQswCQYDVQQGEwJVUzETMBEGA1UECBMKV2FzaGluZ3Rv
# bjEQMA4GA1UEBxMHUmVkbW9uZDEeMBwGA1UEChMVTWljcm9zb2Z0IENvcnBvcmF0
# aW9uMTIwMAYDVQQDEylNaWNyb3NvZnQgUm9vdCBDZXJ0aWZpY2F0ZSBBdXRob3Jp
# dHkgMjAxMDAeFw0yMTA5MzAxODIyMjVaFw0zMDA5MzAxODMyMjVaMHwxCzAJBgNV
# BAYTAlVTMRMwEQYDVQQIEwpXYXNoaW5ndG9uMRAwDgYDVQQHEwdSZWRtb25kMR4w
# HAYDVQQKExVNaWNyb3NvZnQgQ29ycG9yYXRpb24xJjAkBgNVBAMTHU1pY3Jvc29m
# dCBUaW1lLVN0YW1wIFBDQSAyMDEwMIICIjANBgkqhkiG9w0BAQEFAAOCAg8AMIIC
# CgKCAgEA5OGmTOe0ciELeaLL1yR5vQ7VgtP97pwHB9KpbE51yMo1V/YBf2xK4OK9
# uT4XYDP/XE/HZveVU3Fa4n5KWv64NmeFRiMMtY0Tz3cywBAY6GB9alKDRLemjkZr
# BxTzxXb1hlDcwUTIcVxRMTegCjhuje3XD9gmU3w5YQJ6xKr9cmmvHaus9ja+NSZk
# 2pg7uhp7M62AW36MEBydUv626GIl3GoPz130/o5Tz9bshVZN7928jaTjkY+yOSxR
# nOlwaQ3KNi1wjjHINSi947SHJMPgyY9+tVSP3PoFVZhtaDuaRr3tpK56KTesy+uD
# RedGbsoy1cCGMFxPLOJiss254o2I5JasAUq7vnGpF1tnYN74kpEeHT39IM9zfUGa
# RnXNxF803RKJ1v2lIH1+/NmeRd+2ci/bfV+AutuqfjbsNkz2K26oElHovwUDo9Fz
# pk03dJQcNIIP8BDyt0cY7afomXw/TNuvXsLz1dhzPUNOwTM5TI4CvEJoLhDqhFFG
# 4tG9ahhaYQFzymeiXtcodgLiMxhy16cg8ML6EgrXY28MyTZki1ugpoMhXV8wdJGU
# lNi5UPkLiWHzNgY1GIRH29wb0f2y1BzFa/ZcUlFdEtsluq9QBXpsxREdcu+N+VLE
# hReTwDwV2xo3xwgVGD94q0W29R6HXtqPnhZyacaue7e3PmriLq0CAwEAAaOCAd0w
# ggHZMBIGCSsGAQQBgjcVAQQFAgMBAAEwIwYJKwYBBAGCNxUCBBYEFCqnUv5kxJq+
# gpE8RjUpzxD/LwTuMB0GA1UdDgQWBBSfpxVdAF5iXYP05dJlpxtTNRnpcjBcBgNV
# HSAEVTBTMFEGDCsGAQQBgjdMg30BATBBMD8GCCsGAQUFBwIBFjNodHRwOi8vd3d3
# Lm1pY3Jvc29mdC5jb20vcGtpb3BzL0RvY3MvUmVwb3NpdG9yeS5odG0wEwYDVR0l
# BAwwCgYIKwYBBQUHAwgwGQYJKwYBBAGCNxQCBAweCgBTAHUAYgBDAEEwCwYDVR0P
# BAQDAgGGMA8GA1UdEwEB/wQFMAMBAf8wHwYDVR0jBBgwFoAU1fZWy4/oolxiaNE9
# lJBb186aGMQwVgYDVR0fBE8wTTBLoEmgR4ZFaHR0cDovL2NybC5taWNyb3NvZnQu
# Y29tL3BraS9jcmwvcHJvZHVjdHMvTWljUm9vQ2VyQXV0XzIwMTAtMDYtMjMuY3Js
# MFoGCCsGAQUFBwEBBE4wTDBKBggrBgEFBQcwAoY+aHR0cDovL3d3dy5taWNyb3Nv
# ZnQuY29tL3BraS9jZXJ0cy9NaWNSb29DZXJBdXRfMjAxMC0wNi0yMy5jcnQwDQYJ
# KoZIhvcNAQELBQADggIBAJ1VffwqreEsH2cBMSRb4Z5yS/ypb+pcFLY+TkdkeLEG
# k5c9MTO1OdfCcTY/2mRsfNB1OW27DzHkwo/7bNGhlBgi7ulmZzpTTd2YurYeeNg2
# LpypglYAA7AFvonoaeC6Ce5732pvvinLbtg/SHUB2RjebYIM9W0jVOR4U3UkV7nd
# n/OOPcbzaN9l9qRWqveVtihVJ9AkvUCgvxm2EhIRXT0n4ECWOKz3+SmJw7wXsFSF
# QrP8DJ6LGYnn8AtqgcKBGUIZUnWKNsIdw2FzLixre24/LAl4FOmRsqlb30mjdAy8
# 7JGA0j3mSj5mO0+7hvoyGtmW9I/2kQH2zsZ0/fZMcm8Qq3UwxTSwethQ/gpY3UA8
# x1RtnWN0SCyxTkctwRQEcb9k+SS+c23Kjgm9swFXSVRk2XPXfx5bRAGOWhmRaw2f
# pCjcZxkoJLo4S5pu+yFUa2pFEUep8beuyOiJXk+d0tBMdrVXVAmxaQFEfnyhYWxz
# /gq77EFmPWn9y8FBSX5+k77L+DvktxW/tM4+pTFRhLy/AsGConsXHRWJjXD+57XQ
# KBqJC4822rpM+Zv/Cuk0+CQ1ZyvgDbjmjJnW4SLq8CdCPSWU5nR0W2rRnj7tfqAx
# M328y+l7vzhwRNGQ8cirOoo6CGJ/2XBjU02N7oJtpQUQwXEGahC0HVUzWLOhcGby
# oYIDVjCCAj4CAQEwggEBoYHZpIHWMIHTMQswCQYDVQQGEwJVUzETMBEGA1UECBMK
# V2FzaGluZ3RvbjEQMA4GA1UEBxMHUmVkbW9uZDEeMBwGA1UEChMVTWljcm9zb2Z0
# IENvcnBvcmF0aW9uMS0wKwYDVQQLEyRNaWNyb3NvZnQgSXJlbGFuZCBPcGVyYXRp
# b25zIExpbWl0ZWQxJzAlBgNVBAsTHm5TaGllbGQgVFNTIEVTTjo1NTFBLTA1RTAt
# RDk0NzElMCMGA1UEAxMcTWljcm9zb2Z0IFRpbWUtU3RhbXAgU2VydmljZaIjCgEB
# MAcGBSsOAwIaAxUAhoV6r49M4GBd41K1RYB1Z0f4zuCggYMwgYCkfjB8MQswCQYD
# VQQGEwJVUzETMBEGA1UECBMKV2FzaGluZ3RvbjEQMA4GA1UEBxMHUmVkbW9uZDEe
# MBwGA1UEChMVTWljcm9zb2Z0IENvcnBvcmF0aW9uMSYwJAYDVQQDEx1NaWNyb3Nv
# ZnQgVGltZS1TdGFtcCBQQ0EgMjAxMDANBgkqhkiG9w0BAQsFAAIFAOybP1swIhgP
# MjAyNTEwMTYwOTU0MzVaGA8yMDI1MTAxNzA5NTQzNVowdDA6BgorBgEEAYRZCgQB
# MSwwKjAKAgUA7Js/WwIBADAHAgEAAgIdGzAHAgEAAgITyjAKAgUA7JyQ2wIBADA2
# BgorBgEEAYRZCgQCMSgwJjAMBgorBgEEAYRZCgMCoAowCAIBAAIDB6EgoQowCAIB
# AAIDAYagMA0GCSqGSIb3DQEBCwUAA4IBAQAJ7Yofw08kIFkzlGJDG4lHSkaYL3vP
# se+PSXw3C62ffLQkLHa7V0PiO9vq2xStkHCYDMoODs9PolHNYwC2aRNsHSupXjdj
# dnL+3aMcnHUHXuIL3xgkS99uB/I4aw92cy3qSJcmlcFMjeow8zmn5T/AHWzBVYAy
# l//Hz8ZOPk/TsS2CHBS+ptiJaUcOhH4Hq2V2sYilIQvNUz+6h5+HXtH/hj8EEnO6
# MD2swInB4KRCmXVTBodYqsvQEvpGBwqGC6KDWu9iifIZRzXrRplLMqMVcrGQdLOv
# +zzFSI00p4L8Q65rQ1cAuyqz/xbpyzBnkZUsyXMbClMEjMy7MjdIycPcMYIEDTCC
# BAkCAQEwgZMwfDELMAkGA1UEBhMCVVMxEzARBgNVBAgTCldhc2hpbmd0b24xEDAO
# BgNVBAcTB1JlZG1vbmQxHjAcBgNVBAoTFU1pY3Jvc29mdCBDb3Jwb3JhdGlvbjEm
# MCQGA1UEAxMdTWljcm9zb2Z0IFRpbWUtU3RhbXAgUENBIDIwMTACEzMAAAIb0LK4
# Amf3cs8AAQAAAhswDQYJYIZIAWUDBAIBBQCgggFKMBoGCSqGSIb3DQEJAzENBgsq
# hkiG9w0BCRABBDAvBgkqhkiG9w0BCQQxIgQgKs9VEGNYR4HzimTfYSOJmtij0hjq
# FdsvzMSNCV/5Wn0wgfoGCyqGSIb3DQEJEAIvMYHqMIHnMIHkMIG9BCAwJRSVuD2j
# mMcQCFXdLuJAwDpUVNZ6bc6dfJU83Q2LgDCBmDCBgKR+MHwxCzAJBgNVBAYTAlVT
# MRMwEQYDVQQIEwpXYXNoaW5ndG9uMRAwDgYDVQQHEwdSZWRtb25kMR4wHAYDVQQK
# ExVNaWNyb3NvZnQgQ29ycG9yYXRpb24xJjAkBgNVBAMTHU1pY3Jvc29mdCBUaW1l
# LVN0YW1wIFBDQSAyMDEwAhMzAAACG9CyuAJn93LPAAEAAAIbMCIEICE94ffjCxIA
# YyervspfrSCjYnH8L+jBZonZWLNBnhZ/MA0GCSqGSIb3DQEBCwUABIICAD4rwwFd
# Gy3bGCSrUTj2J+Lm6rmDq71gI6dHZtdd3/wTObMye+0rd+TG6kWLdGD9fi35cLVf
# Trjlg83AxaQpACJvnFLjBjPdox8O6j0FezPIx31UEIkEKEMckAXMM+0AGM1+HFrR
# gVvmvyQ7KpFtXJpy1gphJYtLJ0KPZt4Sn+uanSSTXSA2JUQphpLf4k4ZeF/bD732
# ujCbCgJ3b7jG1HNwNfenSK5rF0p/O+kUrZSGAqbXj7Sk7DpqfLn5q3XB4stOHCNc
# v+Xmesrjb+t0bkPTKG1lyMZ1Aq7aF/AQAeO9w+0BO2xJaZxWTi+Pm0oyyOllaJTS
# cK6ohI85YJO52W5QC2fHfQEw3wvMKiFXEMSqLe/oeXIvQwz/My+39qxwFGMnw4oV
# GCgzF75WtkVZQGAKdgjyEvQXd6uhse9h3FsoJm4t6/UlOkrm+9/3VgtOZuWxshpe
# TtYaM3F1H/FHn/dQfO0rKZUL24dDvYRVHmW9lyQkI4PtU3WeVJcXjTiZimjc9Jql
# UozQQ5QFXaBiUCJ8+8GGHTFq6gFSY4fT1Yi+dtVybvOo9XSF0JdOOjiDJBLTFd4e
# YzGJ9qLSFAfoS9ekrXv8h0sIDKcbEPlvwGVS08msMR5trJ6VpLbZbybVJeh+Xhur
# XCyjMwpq4z6rA/oxchS7rnvadrNI7wucD06c
# SIG # End Windows Authenticode signature block