Source: dask.distributed. Version: 2024.12.1+ds-1 Severity: serious Tags: forky sid User: [email protected] Usertags: python3.14
Hi maintainer The autopkgtests of this package fail with Python 3.14 [1]. I've copied what I hope is the relevant part of the log below. Regards Graham [1] https://ci.debian.net/packages/d/dask.distributed/testing/amd64/ 1724s =================================== FAILURES =================================== 1724s ________________ test_serialize_scipy_sparse[dtype1-bsr_matrix] ________________ 1724s 1724s sparse_type = <class 'scipy.sparse._bsr.bsr_matrix'>, dtype = dtype('>f4') 1724s 1724s @pytest.mark.parametrize( 1724s "sparse_type", 1724s [ 1724s scipy_sparse.bsr_matrix, 1724s scipy_sparse.coo_matrix, 1724s scipy_sparse.csc_matrix, 1724s scipy_sparse.csr_matrix, 1724s scipy_sparse.dia_matrix, 1724s scipy_sparse.dok_matrix, 1724s scipy_sparse.lil_matrix, 1724s ], 1724s ) 1724s @pytest.mark.parametrize( 1724s "dtype", 1724s [numpy.dtype("<f4"), numpy.dtype(">f4"), numpy.dtype("<f8"), numpy.dtype(">f8")], 1724s ) 1724s def test_serialize_scipy_sparse(sparse_type, dtype): 1724s a = numpy.array([[0, 1, 0], [2, 0, 3], [0, 4, 0]], dtype=dtype) 1724s 1724s anz = a.nonzero() 1724s > acoo = scipy_sparse.coo_matrix((a[anz], anz)) 1724s ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ 1724s 1724s /usr/lib/python3/dist-packages/distributed/protocol/tests/test_scipy.py:32: 1724s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 1724s /usr/lib/python3/dist-packages/scipy/sparse/_coo.py:62: in __init__ 1724s self.data = getdata(obj, copy=copy, dtype=dtype) 1724s ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ 1724s /usr/lib/python3/dist-packages/scipy/sparse/_sputils.py:150: in getdata 1724s getdtype(data.dtype) 1724s _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 1724s 1724s dtype = dtype('>f4'), a = None, default = None 1724s 1724s def getdtype(dtype, a=None, default=None): 1724s """Form a supported numpy dtype based on input arguments. 1724s 1724s Returns a valid ``numpy.dtype`` from `dtype` if not None, 1724s or else ``a.dtype`` if possible, or else the given `default` 1724s if not None, or else raise a ``TypeError``. 1724s 1724s The resulting ``dtype`` must be in ``supported_dtypes``: 1724s bool_, int8, uint8, int16, uint16, int32, uint32, 1724s int64, uint64, longlong, ulonglong, float32, float64, 1724s longdouble, complex64, complex128, clongdouble 1724s """ 1724s if dtype is None: 1724s try: 1724s newdtype = a.dtype 1724s except AttributeError as e: 1724s if default is not None: 1724s newdtype = np.dtype(default) 1724s else: 1724s raise TypeError("could not interpret data type") from e 1724s else: 1724s newdtype = np.dtype(dtype) 1724s 1724s if newdtype not in supported_dtypes: 1724s supported_dtypes_fmt = ", ".join(t.__name__ for t in supported_dtypes) 1724s > raise ValueError(f"scipy.sparse does not support dtype {newdtype}. " 1724s f"The only supported types are: {supported_dtypes_fmt}.") 1724s E ValueError: scipy.sparse does not support dtype >f4. The only supported types are: bool, int8, uint8, int16, uint16, int32, uint32, int64, uint64, longlong, ulonglong, float32, float64, longdouble, complex64, complex128, clongdouble. 1724s 1724s /usr/lib/python3/dist-packages/scipy/sparse/_sputils.py:137: ValueError
