text: # Copyright 2004-2005 Elemental Security, Inc. All Rights Reserved.
  # Licensed to PSF under a Contributor Agreement.
  
  """This module defines the data structures used to represent a grammar.
  
  These are a bit arcane because they are derived from the data
  structures used by Python's 'pgen' parser generator.
  
  There's also a table here mapping operators to their names in the
  token module; the Python tokenize module reports all operators as the
  fallback token code OP, but the parser needs the actual token code.
  
  """
  
  # Python imports
  import collections
  import pickle
  
  # Local imports
  from . import token, tokenize
  
  
  class Grammar(object):
      """Pgen parsing tables conversion class.
  
      Once initialized, this class supplies the grammar tables for the
      parsing engine implemented by parse.py.  The parsing engine
      accesses the instance variables directly.  The class here does not
      provide initialization of the tables; several subclasses exist to
      do this (see the conv and pgen modules).
  
      The load() method reads the tables from a pickle file, which is
      much faster than the other ways offered by subclasses.  The pickle
      file is written by calling dump() (after loading the grammar
      tables using a subclass).  The report() method prints a readable
      representation of the tables to stdout, for debugging.
  
      The instance variables are as follows:
  
      symbol2number -- a dict mapping symbol names to numbers.  Symbol
                       numbers are always 256 or higher, to distinguish
                       them from token numbers, which are between 0 and
                       255 (inclusive).
  
      number2symbol -- a dict mapping numbers to symbol names;
                       these two are each other's inverse.
  
      states        -- a list of DFAs, where each DFA is a list of
                       states, each state is a list of arcs, and each
                       arc is a (i, j) pair where i is a label and j is
                       a state number.  The DFA number is the index into
                       this list.  (This name is slightly confusing.)
                       Final states are represented by a special arc of
                       the form (0, j) where j is its own state number.
  
      dfas          -- a dict mapping symbol numbers to (DFA, first)
                       pairs, where DFA is an item from the states list
                       above, and first is a set of tokens that can
                       begin this grammar rule (represented by a dict
                       whose values are always 1).
  
      labels        -- a list of (x, y) pairs where x is either a token
                       number or a symbol number, and y is either None
                       or a string; the strings are keywords.  The label
                       number is the index in this list; label numbers
                       are used to mark state transitions (arcs) in the
                       DFAs.
  
      start         -- the number of the grammar's start symbol.
  
      keywords      -- a dict mapping keyword strings to arc labels.
  
      tokens        -- a dict mapping token numbers to arc labels.
  
      """
  
      def __init__(self):
          self.symbol2number = {}
          self.number2symbol = {}
          self.states = []
          self.dfas = {}
          self.labels = [(0, "EMPTY")]
          self.keywords = {}
          self.tokens = {}
          self.symbol2label = {}
          self.start = 256
  
      def dump(self, filename):
          """Dump the grammar tables to a pickle file.
  
          dump() recursively changes all dict to OrderedDict, so the pickled file
          is not exactly the same as what was passed in to dump(). load() uses the
          pickled file to create the tables, but  only changes OrderedDict to dict
          at the top level; it does not recursively change OrderedDict to dict.
          So, the loaded tables are different from the original tables that were
          passed to load() in that some of the OrderedDict (from the pickled file)
          are not changed back to dict. For parsing, this has no effect on
          performance because OrderedDict uses dict's __getitem__ with nothing in
          between.
          """
          with open(filename, "wb") as f:
              d = _make_deterministic(self.__dict__)
              pickle.dump(d, f, 2)
  
      def load(self, filename):
          """Load the grammar tables from a pickle file."""
          with open(filename, "rb") as f:
              d = pickle.load(f)
          self.__dict__.update(d)
  
      def copy(self):
          """
          Copy the grammar.
          """
          new = self.__class__()
          for dict_attr in ("symbol2number", "number2symbol", "dfas", "keywords",
                            "tokens", "symbol2label"):
              setattr(new, dict_attr, getattr(self, dict_attr).copy())
          new.labels = self.labels[:]
          new.states = self.states[:]
          new.start = self.start
          return new
  
      def report(self):
          """Dump the grammar tables to standard output, for debugging."""
          from pprint import pprint
          print("s2n")
          pprint(self.symbol2number)
          print("n2s")
          pprint(self.number2symbol)
          print("states")
          pprint(self.states)
          print("dfas")
          pprint(self.dfas)
          print("labels")
          pprint(self.labels)
          print("start", self.start)
  
  
  def _make_deterministic(top):
      if isinstance(top, dict):
          return collections.OrderedDict(
              sorted(((k, _make_deterministic(v)) for k, v in top.items())))
      if isinstance(top, list):
          return [_make_deterministic(e) for e in top]
      if isinstance(top, tuple):
          return tuple(_make_deterministic(e) for e in top)
      return top
  
  
  # Map from operator to number (since tokenize doesn't do this)
  
  opmap_raw = """
  ( LPAR
  ) RPAR
  [ LSQB
  ] RSQB
  : COLON
  , COMMA
  ; SEMI
  + PLUS
  - MINUS
  * STAR
  / SLASH
  | VBAR
  & AMPER
  < LESS
  > GREATER
  = EQUAL
  . DOT
  % PERCENT
  ` BACKQUOTE
  { LBRACE
  } RBRACE
  @ AT
  @= ATEQUAL
  == EQEQUAL
  != NOTEQUAL
  <> NOTEQUAL
  <= LESSEQUAL
  >= GREATEREQUAL
  ~ TILDE
  ^ CIRCUMFLEX
  << LEFTSHIFT
  >> RIGHTSHIFT
  ** DOUBLESTAR
  += PLUSEQUAL
  -= MINEQUAL
  *= STAREQUAL
  /= SLASHEQUAL
  %= PERCENTEQUAL
  &= AMPEREQUAL
  |= VBAREQUAL
  ^= CIRCUMFLEXEQUAL
  <<= LEFTSHIFTEQUAL
  >>= RIGHTSHIFTEQUAL
  **= DOUBLESTAREQUAL
  // DOUBLESLASH
  //= DOUBLESLASHEQUAL
  -> RARROW
  """
  
  opmap = {}
  for line in opmap_raw.splitlines():
      if line:
          op, name = line.split()
          opmap[op] = getattr(token, name)
  