import numpy as np

a = np.array("foo")
b = np.array(1)
np.array_equal(a, b)

a1 = array('foo', dtype='<U3'), a2 = array(1), equal_nan = False

    @array_function_dispatch(_array_equal_dispatcher)
    def array_equal(a1, a2, equal_nan=False):
        """
        True if two arrays have the same shape and elements, False otherwise.
    
        Parameters
        ----------
        a1, a2 : array_like
            Input arrays.
        equal_nan : bool
            Whether to compare NaN's as equal. If the dtype of a1 and a2 is
            complex, values will be considered equal if either the real or the
            imaginary component of a given value is ``nan``.
    
            .. versionadded:: 1.19.0
    
        Returns
        -------
        b : bool
            Returns True if the arrays are equal.
    
        See Also
        --------
        allclose: Returns True if two arrays are element-wise equal within a
                  tolerance.
        array_equiv: Returns True if input arrays are shape consistent and all
                     elements equal.
    
        Examples
        --------
        >>> import numpy as np
    
        >>> np.array_equal([1, 2], [1, 2])
        True
    
        >>> np.array_equal(np.array([1, 2]), np.array([1, 2]))
        True
    
        >>> np.array_equal([1, 2], [1, 2, 3])
        False
    
        >>> np.array_equal([1, 2], [1, 4])
        False
    
        >>> a = np.array([1, np.nan])
        >>> np.array_equal(a, a)
        False
    
        >>> np.array_equal(a, a, equal_nan=True)
        True
    
        When ``equal_nan`` is True, complex values with nan components are
        considered equal if either the real *or* the imaginary components are nan.
    
        >>> a = np.array([1 + 1j])
        >>> b = a.copy()
        >>> a.real = np.nan
        >>> b.imag = np.nan
        >>> np.array_equal(a, b, equal_nan=True)
        True
        """
        try:
            a1, a2 = asarray(a1), asarray(a2)
        except Exception:
            return False
        if a1.shape != a2.shape:
            return False
        if not equal_nan:
>           return builtins.bool((a1 == a2).all())
E           AttributeError: 'bool' object has no attribute 'all'

.venv/lib/python3.12/site-packages/numpy/_core/numeric.py:2557: AttributeError