code: def discr_sequence_space(shape, dtype=None, impl='numpy', **kwargs):
      
      shape = np.atleast_1d(shape)
      return uniform_discr([0] * len(shape), shape - 1, shape, dtype, impl,
                           nodes_on_bdry=True, **kwargs)
docs: Return an object mimicing the sequence space ``l^p(R^d)``.
  
      The returned object is a `DiscreteLp` on the domain ``[0, shape - 1]``,
      using a uniform grid with stride 1.
  
      Parameters
      ----------
      shape : int or sequence of ints
          Number of element entries per axis.
      dtype : optional
          Data type for the discretized space, must be understood by the
          `numpy.dtype` constructor. The default for ``None`` depends on the
          ``impl`` backend, usually it is ``'float64'`` or ``'float32'``.
      impl : string, optional
          Implementation of the data storage arrays.
      kwargs :
          Additional keyword parameters, see `uniform_discr` for details.
          Note that ``nodes_on_bdry`` cannot be given.
  
      Returns
      -------
      seqspc : `DiscreteLp`
          Sequence-space-like discrete Lp.
  
      Examples
      --------
      >>> seq_spc = discr_sequence_space((3, 3))
      >>> seq_spc.one().norm() == 3.0
      True
      >>> seq_spc = discr_sequence_space((3, 3), exponent=1)
      >>> seq_spc.one().norm() == 9.0
      True