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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 rolling_window(self, dim, window, window_dim, center=False, fill_value=dtypes.NA):
 """ Make a rolling_window along dim and add a new_dim to the last place. Parameters dim: str Dimension over which to compute rolling_window window: int Window size of the rolling window_dim: str New name of the window dimension. center: boolean. default False. If True, pad fill_value for both ends. Otherwise, pad in the head of the axis. fill_value: value to be filled. Returns ------- Variable that is a view of the original array with a added dimension of size w. The return dim: self.dims + (window_dim, ) The return shape: self.shape + (window, ) Examples -------- <xarray.Variable (a: 2, b: 4, window_dim: 3)> array([[[nan, nan, 0], [nan, 0, 1], [0, 1, 2], [1, 2, 3]], [[nan, nan, 4], [nan, 4, 5], [4, 5, 6], [5, 6, 7]]]) <xarray.Variable (a: 2, b: 4, window_dim: 3)> array([[[nan, 0, 1], [0, 1, 2], [1, 2, 3], [2, 3, nan]], [[nan, 4, 5], [4, 5, 6], [5, 6, 7], [6, 7, nan]]]) """

        if fill_value is dtypes.NA:  # np.nan is passed
            dtype, fill_value = dtypes.maybe_promote(self.dtype)
            array = self.astype(dtype, copy=False).data
        else:
            dtype = self.dtype
            array = self.data

        new_dims = self.dims + (window_dim, )
        return Variable(new_dims, duck_array_ops.rolling_window(
            array, axis=self.get_axis_num(dim), window=window,
            center=center, fill_value=fill_value))