<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def append_variables(self, samples_like, sort_labels=True):
 """Create a new sampleset with the given variables with values added. Not defined for empty sample sets. Note that when `sample_like` is a :obj:`.SampleSet`, the data vectors and info are ignored. Args: samples_like: Samples to add to the sample set. Should either be a single sample or should match the length of the sample set. See :func:`.as_samples` for what is allowed to be `samples_like`. sort_labels (bool, optional, default=True):
 If true, returned :attr:`.SampleSet.variables` will be in sorted-order. Note that mixed types are not sortable in which case the given order will be maintained. Returns: :obj:`.SampleSet`: A new sample set with the variables/values added. Examples: a b c energy num_oc. 0 -1 +1 -1 -1.0 1 1 +1 +1 -1 1.0 1 ['SPIN', 2 rows, 2 samples, 3 variables] Add variables from another sampleset to the original above. Note that the energies do not change. a b c d energy num_oc. 0 -1 +1 -1 +1 -1.0 1 1 +1 +1 +1 +1 1.0 1 ['SPIN', 2 rows, 2 samples, 4 variables] """

        samples, labels = as_samples(samples_like)

        num_samples = len(self)

        # we don't handle multiple values
        if samples.shape[0] == num_samples:
            # we don't need to do anything, it's already the correct shape
            pass
        elif samples.shape[0] == 1 and num_samples:
            samples = np.repeat(samples, num_samples, axis=0)
        else:
            msg = ("mismatched shape. The samples to append should either be "
                   "a single sample or should match the length of the sample "
                   "set. Empty sample sets cannot be appended to.")
            raise ValueError(msg)

        # append requires the new variables to be unique
        variables = self.variables
        if any(v in variables for v in labels):
            msg = "Appended samples cannot contain variables in sample set"
            raise ValueError(msg)

        new_variables = list(variables) + labels
        new_samples = np.hstack((self.record.sample, samples))

        return type(self).from_samples((new_samples, new_variables),
                                       self.vartype,
                                       info=copy.deepcopy(self.info),  # make a copy
                                       sort_labels=sort_labels,
                                       **self.data_vectors)