def is_integer_dtype(arr_or_dtype):
return _is_dtype_type(<EOL>arr_or_dtype, classes_and_not_datetimelike(np.integer))<EOL>
Check whether the provided array or dtype is of an integer dtype.

Unlike in `in_any_int_dtype`, timedelta64 instances will return False.

.. versionchanged:: 0.24.0

   The nullable Integer dtypes (e.g. pandas.Int64Dtype) are also considered
   as integer by this function.

Parameters
----------
arr_or_dtype : array-like
    The array or dtype to check.

Returns
-------
boolean
    Whether or not the array or dtype is of an integer dtype and
    not an instance of timedelta64.

Examples
--------
>>> is_integer_dtype(str)
False
>>> is_integer_dtype(int)
True
>>> is_integer_dtype(float)
False
>>> is_integer_dtype(np.uint64)
True
>>> is_integer_dtype('int8')
True
>>> is_integer_dtype('Int8')
True
>>> is_integer_dtype(pd.Int8Dtype)
True
>>> is_integer_dtype(np.datetime64)
False
>>> is_integer_dtype(np.timedelta64)
False
>>> is_integer_dtype(np.array(['a', 'b']))
False
>>> is_integer_dtype(pd.Series([1, 2]))
True
>>> is_integer_dtype(np.array([], dtype=np.timedelta64))
False
>>> is_integer_dtype(pd.Index([1, 2.]))  # float
False