Confusion about TypeMustMatch and f64

Hi! I have a question about why the following code seems to work without throwing an assert error.

On the Rust side:

#[pyfunction]
fn sum_up<'py>(py: Python<'py>, array: PyArrayLike1<'py, f64, TypeMustMatch>) -> f64 {
    array.as_array().sum()
}

On the python side

>>> A = np.array([2**63, 2**63+1], dtype=np.uint64)
>>> sum_up(A)
1.8446744073709552e+19

It seems like A is being converted to a f64, and then addition is carried out. (For reference, A.sum() = 1.) I thought that the TypeMustMatch means that the array's dtype must be f64.

Either I'm misunderstanding TypeMustMatch or perhaps there is a bug here?

I think this is related to some functionality I touched on in #491, where there is an attempt to extract PyArrayLike1<T> from Vec<T>.

I'd agree that this is probably not the desired behavior, since AllowTypeChange/TypeMustMatch is only applied to 1D arrays if extraction from a Vec fails.

rust-numpy/src/array_like.rs

Lines 152 to 161 in 8bfbb27

    
           if matches!(D::NDIM, None | Some(1)) { 
        
               if let Ok(vec) = ob.extract::<Vec<T>>() { 
        
                   let array = Array1::from(vec) 
        
                       .into_dimensionality() 
        
                       .expect("D being compatible to Ix1") 
        
                       .into_pyarray(py) 
        
                       .readonly(); 
        
                   return Ok(Self(array, PhantomData)); 
        
               } 
        
           }

Fixed by #520

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Confusion about `TypeMustMatch` and f64 #444

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	if matches!(D::NDIM, None \| Some(1)) {
	if let Ok(vec) = ob.extract::<Vec<T>>() {
	let array = Array1::from(vec)
	.into_dimensionality()
	.expect("D being compatible to Ix1")
	.into_pyarray(py)
	.readonly();
	return Ok(Self(array, PhantomData));
	}
	}

Confusion about TypeMustMatch and f64 #444

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jakemoran commented on Jun 3, 2025

Icxolu commented on Dec 13, 2025

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Confusion about `TypeMustMatch` and f64 #444