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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 byaxis(self):
 """Return the subspace defined along one or several dimensions. Examples -------- Indexing with integers or slices: rn(2) rn((3, 4)) Lists can be used to stack spaces arbitrarily: rn((4, 3, 4)) """

        space = self

        class NpyTensorSpacebyaxis(object):

            """Helper class for indexing by axis."""

            def __getitem__(self, indices):
                """Return ``self[indices]``."""
                try:
                    iter(indices)
                except TypeError:
                    newshape = space.shape[indices]
                else:
                    newshape = tuple(space.shape[i] for i in indices)

                if isinstance(space.weighting, ArrayWeighting):
                    new_array = np.asarray(space.weighting.array[indices])
                    weighting = NumpyTensorSpaceArrayWeighting(
                        new_array, space.weighting.exponent)
                else:
                    weighting = space.weighting

                return type(space)(newshape, space.dtype, weighting=weighting)

            def __repr__(self):
                """Return ``repr(self)``."""
                return repr(space) + '.byaxis'

        return NpyTensorSpacebyaxis()