(func_name, df_type, values, all_params)
return func_text, global_vars
Example of generated implementation:

    def _df_isin_impl(df, values):
      result_len=len(df)
      if "A" in list(values.keys()):
        series_A = pandas.Series(df._data[0])
        val = list(values["A"])
        result_A = series_A.isin(val)
      else:
        result = numpy.repeat(False, result_len)
        result_A = pandas.Series(result)
      result_len=len(df)
      if "C" in list(values.keys()):
        series_C = pandas.Series(df._data[1])
        val = list(values["C"])
        result_C = series_C.isin(val)
      else:
        result = numpy.repeat(False, result_len)
        result_C = pandas.Series(result)
      return pandas.DataFrame({"A": result_A, "C": result_C})
Example of generated implementation:
Example of generated implementation :
def sdc_pandas_dataframe_isin_dict_codegen(func_name, df_type, values, all_params):
    """
    Example of generated implementation:

    def _df_isin_impl(df, values):
      result_len=len(df)
      if "A" in list(values.keys()):
        series_A = pandas.Series(df._data[0])
        val = list(values["A"])
        result_A = series_A.isin(val)
      else:
        result = numpy.repeat(False, result_len)
        result_A = pandas.Series(result)
      result_len=len(df)
      if "C" in list(values.keys()):
        series_C = pandas.Series(df._data[1])
        val = list(values["C"])
        result_C = series_C.isin(val)
      else:
        result = numpy.repeat(False, result_len)
        result_C = pandas.Series(result)
      return pandas.DataFrame({"A": result_A, "C": result_C})
    """
    result_name = []
    joined = ', '.join(all_params)
    func_lines = [f'def _df_{func_name}_impl({joined}):']
    df = all_params[0]
    column_loc = df_type.column_loc
    for i, c in enumerate(df_type.columns):
        col_loc = column_loc[c]
        type_id, col_id = col_loc.type_id, col_loc.col_id
        result_c = f'result_{c}'
        func_lines += [
            f'  result_len=len({df})',
            f'  if "{c}" in list(values.keys()):',
            f'    series_{c} = pandas.Series({df}._data[{type_id}][{col_id}])',
            f'    val = list(values["{c}"])',
            f'    result_{c} = series_{c}.{func_name}(val)',
            f'  else:',
            f'    result = numpy.repeat(False, result_len)',
            f'    result_{c} = pandas.Series(result)'
        ]
        result_name.append((result_c, c))
    data = ', '.join(f'"{column_name}": {column}' for column, column_name in result_name)
    func_lines.append(f'  return pandas.DataFrame({{{data}}}, index={df}._index)')
    func_text = '\n'.join(func_lines)

    global_vars = {'pandas': pandas,
                   'numpy': numpy,
                   'get_dataframe_data': get_dataframe_data}

    return func_text, global_vars
def sdc_pandas_dataframe_isin_dict_codegen ( func_name , df_type , values , all_params ) : result_name = [ ] joined = ', ' . join ( all_params ) func_lines = [ f'def _df_{func_name}_impl({joined}):' ] df = all_params [ 0 ] column_loc = df_type . column_loc for i , c in enumerate ( df_type . columns ) : col_loc = column_loc [ c ] type_id , col_id = col_loc . type_id , col_loc . col_id result_c = f'result_{c}' func_lines += [ f'  result_len=len({df})' , f'  if "{c}" in list(values.keys()):' , f'    series_{c} = pandas.Series({df}._data[{type_id}][{col_id}])' , f'    val = list(values["{c}"])' , f'    result_{c} = series_{c}.{func_name}(val)' , f'  else:' , f'    result = numpy.repeat(False, result_len)' , f'    result_{c} = pandas.Series(result)' ] result_name . append ( ( result_c , c ) ) data = ', ' . join ( f'"{column_name}": {column}' for column , column_name in result_name ) func_lines . append ( f'  return pandas.DataFrame({{{data}}}, index={df}._index)' ) func_text = '\n' . join ( func_lines ) global_vars = { 'pandas' : pandas , 'numpy' : numpy , 'get_dataframe_data' : get_dataframe_data } return func_text , global_vars