def get_objects(self, uri, _oid=None, _start=None, _end=None,
                    load_kwargs=None, **kwargs):
        '''
        Load and transform csv data into a list of dictionaries.

        Each row in the csv will result in one dictionary in the list.

        :param uri: uri (file://, http(s)://) of csv file to load
        :param _oid:
            column or func to apply to map _oid in all resulting objects
        :param _start:
            column or func to apply to map _start in all resulting objects
        :param _end:
            column or func to apply to map _end in all resulting objects
        :param kwargs: kwargs to pass to pandas.read_csv method

        _start and _oid arguments can be a column name or a function
        which accepts a single argument -- the row being extracted.

        If either is a column name (string) then that column will be applied
        as _oid for each object generated.

        If either is a function, the function will be applied per each row
        and the result of the function will be assigned to the _start
        or _oid, respectively.
        '''
        load_kwargs = load_kwargs or {}
        objects = load(path=uri, filetype='csv', **load_kwargs)

        k = itertools.count(1)
        now = utcnow()
        __oid = lambda o: k.next()

        _oid = _oid or __oid
        _start = _start or now
        _end = _end or None

        def is_callable(v):
            _v = type(v)
            _ = True if _v is type or hasattr(v, '__call__') else False
            return _

        for obj in objects:
            obj['_oid'] = _oid(obj) if is_callable(_oid) else _oid
            obj['_start'] = _start(obj) if is_callable(_start) else _start
            obj['_end'] = _end(obj) if is_callable(_end) else _end
            self.container.add(obj)

        return super(Rows, self).get_objects(**kwargs)
Load and transform csv data into a list of dictionaries.

        Each row in the csv will result in one dictionary in the list.

        :param uri: uri (file://, http(s)://) of csv file to load
        :param _oid:
            column or func to apply to map _oid in all resulting objects
        :param _start:
            column or func to apply to map _start in all resulting objects
        :param _end:
            column or func to apply to map _end in all resulting objects
        :param kwargs: kwargs to pass to pandas.read_csv method

        _start and _oid arguments can be a column name or a function
        which accepts a single argument -- the row being extracted.

        If either is a column name (string) then that column will be applied
        as _oid for each object generated.

        If either is a function, the function will be applied per each row
        and the result of the function will be assigned to the _start
        or _oid, respectively.