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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 get(self, start=None, count=None, stride=None):
 """Read data from the dataset. Args:: start : indices where to start reading in the data array; default to 0 on all dimensions count : number of values to read along each dimension; default to the current length of all dimensions stride : sampling interval along each dimension; default to 1 on all dimensions For n-dimensional datasets, those 3 parameters are entered using lists. For one-dimensional datasets, integers can also be used. Note that, to read the whole dataset contents, one should simply call the method with no argument. Returns:: numpy array initialized with the data. C library equivalent : SDreaddata The dataset can also be read using the familiar indexing and slicing notation, like ordinary python sequences. See "High level variable access". """


        # Obtain SDS info.
        try:
            sds_name, rank, dim_sizes, data_type, n_attrs = self.info()
            if isinstance(dim_sizes, type(1)):
                dim_sizes = [dim_sizes]
        except HDF4Error:
            raise HDF4Error('get : cannot execute')

        # Validate args.
        if start is None:
            start = [0] * rank
        elif isinstance(start, type(1)):
            start = [start]
        if count is None:
            count = dim_sizes
            if count[0] == 0:
                count[0] = 1
        elif isinstance(count, type(1)):
            count = [count]
        if stride is None:
            stride = [1] * rank
        elif isinstance(stride, type(1)):
            stride = [stride]
        if len(start) != rank or len(count) != rank or len(stride) != rank:
            raise HDF4Error('get : start, stride or count ' \
                             'do not match SDS rank')
        for n in range(rank):
            if start[n] < 0 or start[n] + \
                  (abs(count[n]) - 1) * stride[n] >= dim_sizes[n]:
                raise HDF4Error('get arguments violate ' \
                                 'the size (%d) of dimension %d' \
                                 % (dim_sizes[n], n))
        if not data_type in SDC.equivNumericTypes:
            raise HDF4Error('get cannot currrently deal with '\
                             'the SDS data type')

        return _C._SDreaddata_0(self._id, data_type, start, count, stride)