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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 setscale(self, data_type, scale):
 """Initialize the scale values along the dimension. Args:: data_type data type code (one of the SDC.xxx constants) scale sequence holding the scale values; the number of values must match the current length of the dataset along that dimension C library equivalent : SDsetdimscale Setting a scale on a dimension generates what HDF calls a "coordinate variable". This is a rank 1 dataset similar to any other dataset, which is created to hold the scale values. The dataset name is identical to that of the dimension on which setscale() is called, and the data type passed in 'data_type' determines the type of the dataset. To distinguish between such a dataset and a "normal" dataset, call the iscoordvar() method of the dataset instance. """


        try:
            n_values = len(scale)
        except:
            n_values = 1

        # Validate args
        info = self._sds.info()
        if info[1] == 1:
            dim_size = info[2]
        else:
            dim_size = info[2][self._index]
        if n_values != dim_size:
            raise HDF4Error('number of scale values (%d) does not match ' \
                             'dimension size (%d)' % (n_values, dim_size))

        if data_type == SDC.CHAR8:
            buf = _C.array_byte(n_values)
            # Allow a string as the scale argument.
            # Becomes a noop if already a list.
            scale = list(scale)
            for n in range(n_values):
                scale[n] = ord(scale[n])

        elif data_type in [SDC.UCHAR8, SDC.UINT8]:
            buf = _C.array_byte(n_values)

        elif data_type == SDC.INT8:
            buf = _C.array_int8(n_values)

        elif data_type == SDC.INT16:
            buf = _C.array_int16(n_values)

        elif data_type == SDC.UINT16:
            buf = _C.array_uint16(n_values)

        elif data_type == SDC.INT32:
            buf = _C.array_int32(n_values)

        elif data_type == SDC.UINT32:
            buf = _C.array_uint32(n_values)

        elif data_type == SDC.FLOAT32:
            buf = _C.array_float32(n_values)

        elif data_type == SDC.FLOAT64:
            buf = _C.array_float64(n_values)

        else:
            raise HDF4Error("setscale: illegal or usupported data_type")

        if n_values == 1:
            buf[0] = scale
        else:
            for n in range(n_values):
                buf[n] = scale[n]
        status = _C.SDsetdimscale(self._id, n_values, data_type, buf)
        _checkErr('setscale', status, 'cannot execute')