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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 reduce(self, func, dim=None, keep_attrs=None, **kwargs):
 """Reduce the items in this group by applying `func` along the pre-defined resampling dimension. Parameters func : function Function which can be called in the form `func(x, axis=axis, **kwargs)` to return the result of collapsing an np.ndarray over an integer valued axis. dim : str or sequence of str, optional Dimension(s) over which to apply `func`. keep_attrs : bool, optional If True, the datasets's attributes (`attrs`) will be copied from the original object to the new one. If False (default), the new object will be returned without attributes. **kwargs : dict Additional keyword arguments passed on to `func`. Returns ------- reduced : Array Array with summarized data and the indicated dimension(s) removed. """

        if dim == DEFAULT_DIMS:
            dim = None

        return super(DatasetResample, self).reduce(
            func, dim, keep_attrs, **kwargs)