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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_index(self, as_dict=False, grouping_pattern=None):
 """ Returns the index of the DataFrames in the system Parameters as_dict: boolean, optional If True, returns a 1:1 key-value matching for further processing prior to groupby functions. Otherwise (default) the index is returned as pandas index. grouping_pattern: dict, optional Dictionary with keys being regex patterns matching index and values the name for the grouping. If the index is a pandas multiindex, the keys must be tuples of length levels in the multiindex, with a valid regex expression at each position. Otherwise, the keys need to be strings. Only relevant if as_dict is True. """


        possible_dataframes = ['A', 'L', 'Z', 'Y', 'F', 'FY', 'M', 'S',
                               'D_cba', 'D_pba',  'D_imp', 'D_exp',
                               'D_cba_reg', 'D_pba_reg',
                               'D_imp_reg', 'D_exp_reg',
                               'D_cba_cap', 'D_pba_cap',
                               'D_imp_cap', 'D_exp_cap', ]
        for df in possible_dataframes:
            if (df in self.__dict__) and (getattr(self, df) is not None):
                orig_idx = getattr(self, df).index
                break
        else:
            logging.warn("No attributes available to get index")
            return None

        if as_dict:
            dd = {k: k for k in orig_idx}
            if grouping_pattern:
                for pattern, new_group in grouping_pattern.items():
                    if type(pattern) is str:
                        dd.update({k: new_group for k, v in dd.items() if
                                   re.match(pattern, k)})
                    else:
                        dd.update({k: new_group for k, v in dd.items() if
                                   all([re.match(pat, k[nr])
                                        for nr, pat in enumerate(pattern)])})
            return dd

        else:
            return orig_idx