class_docstr: Object to hold scope, with a few bells to deal with some custom syntax
  and contexts added by pandas.
  
  Parameters
  ----------
  level : int
  global_dict : dict or None, optional, default None
  local_dict : dict or Scope or None, optional, default None
  resolvers : list-like or None, optional, default None
  target : object
  
  Attributes
  ----------
  level : int
  scope : DeepChainMap
  target : object
  temps : dict
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docstr: Return the full scope for use with passing to engines transparently
  as a mapping.
  
  Returns
  -------
  vars : DeepChainMap
      All variables in this scope.
docstr_tok: ["Return","the","full","scope","for","use","with","passing","to","engines","transparently","as","a","mapping",".","Returns","--","--","--","-","vars",":","DeepChainMap","All","variables","in","this","scope","."]
code: def full_scope(self) -> DeepChainMap:
      """
      Return the full scope for use with passing to engines transparently
      as a mapping.
  
      Returns
      -------
      vars : DeepChainMap
          All variables in this scope.
      """
      maps = [self.temps] + self.resolvers.maps + self.scope.maps
      return DeepChainMap(*maps)
  
imports: from __future__ import annotations
  import datetime
  import inspect
  from io import StringIO
  import itertools
  import pprint
  import struct
  import sys
  from typing import ChainMap, TypeVar
  import numpy
  from pandas._libs.tslibs import Timestamp
  from pandas.errors import UndefinedVariableError
label_desc: Use image node_id 10 for calling the Scope obj's underlying member method code with example usage: obj.full_scope() and returns: DeepChainMap