@classmethod
    def _add_comparison_methods(cls):

        def _make_compare(op):
            def _evaluate_compare(self, other):
                if isinstance(other, (np.ndarray, Index, ABCSeries)):
                    if other.ndim > 0 and len(self) != len(other):
                        raise ValueError('Lengths must match to compare')

                # we may need to directly compare underlying
                # representations
                if needs_i8_conversion(self) and needs_i8_conversion(other):
                    return self._evaluate_compare(other, op)

                func = getattr(self.values, op)
                result = func(np.asarray(other))

                # technically we could support bool dtyped Index
                # for now just return the indexing array directly
                if is_bool_dtype(result):
                    return result
                try:
                    return Index(result)
                except TypeError:
                    return result

            return _evaluate_compare

        cls.__eq__ = _make_compare('__eq__')
        cls.__ne__ = _make_compare('__ne__')
        cls.__lt__ = _make_compare('__lt__')
        cls.__gt__ = _make_compare('__gt__')
        cls.__le__ = _make_compare('__le__')
        cls.__ge__ = _make_compare('__ge__')
add in comparison methods
dataset/ETHPy150Open pydata/pandas/pandas/indexes/base.py/Index._add_comparison_methods