Compute a dict of {(row,column): (key, value)} elements from the
        current set of items and specified number of columns.
545784
def grid_items(self):
        
        if list(self.keys()) == []:  return {}
        cols = self._max_cols
        return {(idx // cols, idx % cols): (key, item)
                for idx, (key, item) in enumerate(self.data.items())}
763258
def items(self):
        ''''''
        return [(self.keys[x], self.values[x]) for x in range(len(self.keys))]
357232
def item_coords(self, table_item):
        
        for row_key in self.children.keys():
            for item_key in self.children[row_key].children.keys():
                if self.children[row_key].children[item_key] == table_item:
                    return (int(row_key), int(item_key))
        return None
530790
def _get_normalized_columns(cls, list_):
        
        ret = []
        for row in list_:
            if len(row.keys()) > len(ret):
                ret = cls._ordered_keys(row)

        for row in list_:
            for key in row.keys():
                if key not in ret:
                    ret.append(key)
                    if not isinstance(row, OrderedDict):
                        ret.sort()
        return ret
1162662
def lists(self, column, key=None):
        
        results = self._query.lists(column, key)

        if self._model.has_get_mutator(column):
            if isinstance(results, dict):
                for key, value in results.items():
                    fill = {column: value}

                    results[key] = self._model.new_from_builder(fill).column
            else:
                for i, value in enumerate(results):
                    fill = {column: value}

                    results[i] = self._model.new_from_builder(fill).column

        return results
1262021
def to_dict(self, columns=None):
        
        if columns:
            assert len(columns) == len(self.feature_names)
        d = [
            dict([
                (columns[i] if columns else col_name, row[i])
                for i, col_name in enumerate(self.feature_names)
            ])
            for row in self.data
        ]
        return d
1082234
def _from_dict_dict(cls, dic):
        
        return cls({_convert_id(i): v for i, v in dic.items()})
933347
def make_row_dict(row):
    
    ind = row[row.notnull()].index
    values = row[row.notnull()].values
    # to transformation with extract_col_name here???
    return dict(list(zip(ind, values)))
1257932
def parse_row(self, row, row_index, cell_mode=CellMode.cooked):
    """"""
    return [self.parse_cell(cell, (col_index, row_index), cell_mode) \
            for col_index, cell in enumerate(row)]
963327
def cells(self):
        
        return {row_key: {column_key:cell for column_key, cell in zip(self._column_keys, cells)}
                for row_key, cells in self._rows_mapping.items()}
886057
def rows_to_dicts(self, serialize_cell=None):
    """"""
    if serialize_cell is None:
      serialize_cell = self.get_cell_value
    # keys = [serialize_cell(cell) for cell in self.rows[0]]
    keys = self.headers(serialize_cell)
    for row in self.rows[1:]:
      yield dict(zip(keys, [serialize_cell(cell) for cell in row]))
536244
def transpose(self, rows):
        
        res = OrderedDict()
        for row, cols in rows.items():
            for col, cell in cols.items():
                if col not in res:
                    res[col] = OrderedDict()
                res[col][row] = cell
        return res
75691
def process_row(cls, data, column_map):
        """"""
        row = {}
        for key,value in data.iteritems():
            if not value:
                value = '-'                
            elif isinstance(value, list):
                value = value[1]
            elif isinstance(value, dict):
                if 'type_name' in value:
                    if 'UnixTimeStamp' in value['type_name']:
                        value = datetime.datetime.utcfromtimestamp(value['epoch'])
                        if value == datetime.datetime(1970, 1, 1, 0, 0):
                            value = '-'

            # Assume the value is somehow well formed when we get here
            row[column_map[key]] = value
        return row
734833
def nested_set_dict(d, keys, value):
    
    assert keys
    key = keys[0]
    if len(keys) == 1:
        if key in d:
            raise ValueError("duplicated key '{}'".format(key))
        d[key] = value
        return
    d = d.setdefault(key, {})
    nested_set_dict(d, keys[1:], value)
307834
def mk_dict(results,description):
    """"""
    
    rows=[]
    for row in results:
        row_dict={}
        for idx in range(len(row)):
            col=description[idx][0]
            row_dict[col]=row[idx]
        rows.append(row_dict)
    return rows
453239
def as_dict(self):
        
        d = {k:v for (k,v) in self.__dict__.items()}
        return d
651153
def convert_items(self, items):
        """"""
        return ((key, self.convert(value, self)) for key, value in items)