# Buggy code
def astype(self, dtype, copy=True):
    # Some notes on cases we don't have to handle here in the base class:
    #   1. PeriodArray.astype handles period -> period
    #   2. DatetimeArray.astype handles conversion between tz.
    #   3. DatetimeArray.astype handles datetime -> period
    dtype = pandas_dtype(dtype)

    if is_object_dtype(dtype):
        return self._box_values(self.asi8.ravel()).reshape(self.shape)
    elif is_string_dtype(dtype) and not is_categorical_dtype(dtype):
        if is_extension_array_dtype(dtype):
            arr_cls = dtype.construct_array_type()
            return arr_cls._from_sequence(self, dtype=dtype, copy=copy)
        else:
            return self._format_native_types()
    elif is_integer_dtype(dtype):
        # we deliberately ignore int32 vs. int64 here.
        # See https://github.com/pandas-dev/pandas/issues/24381 for more.
        values = self.asi8

        if is_unsigned_integer_dtype(dtype):
            # Again, we ignore int32 vs. int64
            values = values.view("uint64")

        if copy:
            values = values.copy()
        return values
    elif (
        is_datetime_or_timedelta_dtype(dtype) and not is_dtype_equal(self.dtype, dtype)
    ) or is_float_dtype(dtype):
        # disallow conversion between datetime/timedelta,
        # and conversions for any datetimelike to float
        msg = f"Cannot cast {type(self).__name__} to dtype {dtype}"
        raise TypeError(msg)
    elif is_categorical_dtype(dtype):
        arr_cls = dtype.construct_array_type()
        return arr_cls(self, dtype=dtype)
    else:
        return np.asarray(self, dtype=dtype)


# Traceback (TypeError)
In [10]: idx._data.astype('int32').astype("int32", casting="safe")
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-10-2c2a4a677a5c> in <module>
----> 1 idx._data.astype('int32').astype("int32", casting="safe")

TypeError: Cannot cast array from dtype('int64') to dtype('int32') according to the rule 'safe'

# Fixed code
def astype(self, dtype, copy=True):
    # Some notes on cases we don't have to handle here in the base class:
    #   1. PeriodArray.astype handles period -> period
    #   2. DatetimeArray.astype handles conversion between tz.
    #   3. DatetimeArray.astype handles datetime -> period
    dtype = pandas_dtype(dtype)

    if is_object_dtype(dtype):
        return self._box_values(self.asi8.ravel()).reshape(self.shape)
    elif is_string_dtype(dtype) and not is_categorical_dtype(dtype):
        if is_extension_array_dtype(dtype):
            arr_cls = dtype.construct_array_type()
            return arr_cls._from_sequence(self, dtype=dtype, copy=copy)
        else:
            return self._format_native_types()
    elif is_integer_dtype(dtype):
        # we deliberately ignore int32 vs. int64 here.
        # See https://github.com/pandas-dev/pandas/issues/24381 for more.
        warnings.warn(
            f"casting {self.dtype} values to int64 with .astype(...) is "
            "deprecated and will raise in a future version. "
            "Use .view(...) instead.",
            FutureWarning,
            stacklevel=3,
        )

        values = self.asi8

        if is_unsigned_integer_dtype(dtype):
            # Again, we ignore int32 vs. int64
            values = values.view("uint64")

        if copy:
            values = values.copy()
        return values
    elif (
        is_datetime_or_timedelta_dtype(dtype) and not is_dtype_equal(self.dtype, dtype)
    ) or is_float_dtype(dtype):
        # disallow conversion between datetime/timedelta,
        # and conversions for any datetimelike to float
        msg = f"Cannot cast {type(self).__name__} to dtype {dtype}"
        raise TypeError(msg)
    elif is_categorical_dtype(dtype):
        arr_cls = dtype.construct_array_type()
        return arr_cls(self, dtype=dtype)
    else:
        return np.asarray(self, dtype=dtype)