Package: src:python-polsarpro Version: 2026.1.2-1 Severity: serious Tags: ftbfs forky sid
Dear maintainer: During a rebuild of all packages in unstable, this package failed to build. Below you will find the last part of the build log (probably the most relevant part, but not necessarily). If required, the full build log is available here: https://people.debian.org/~sanvila/build-logs/202605/ About the archive rebuild: The build was made on virtual machines from AWS, using sbuild and a reduced chroot with only build-essential packages. If you cannot reproduce the bug please contact me privately, as I am willing to provide ssh access to a virtual machine where the bug is fully reproducible. If this is really a bug in one of the build-depends, please use reassign and add an affects on src:python-polsarpro, so that this is still visible in the BTS web page for this package. Thanks. -------------------------------------------------------------------------------- [...] debian/rules clean dh clean --buildsystem=pybuild dh_auto_clean -O--buildsystem=pybuild dh_autoreconf_clean -O--buildsystem=pybuild dh_clean -O--buildsystem=pybuild debian/rules binary dh binary --buildsystem=pybuild dh_update_autotools_config -O--buildsystem=pybuild dh_autoreconf -O--buildsystem=pybuild dh_auto_configure -O--buildsystem=pybuild dh_auto_build -O--buildsystem=pybuild I: pybuild plugin_pyproject:142: Building wheel for python3.14 with "build" module I: pybuild base:385: python3.14 -m build --skip-dependency-check --no-isolation --wheel --outdir /<<PKGBUILDDIR>>/.pybuild/cpython3_3.14_polsarpro * Building wheel... running bdist_wheel [... snipped ...] /usr/lib/python3/dist-packages/dask/array/reductions.py:2058: in nanquantile result = a.map_blocks( /usr/lib/python3/dist-packages/dask/array/core.py:2705: in map_blocks return map_blocks(func, self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ /usr/lib/python3/dist-packages/dask/array/core.py:828: in map_blocks dtype = apply_infer_dtype(func, args, original_kwargs, "map_blocks") ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ func = <function _custom_quantile at 0x7fe4d208c4a0> args = [array([[[1.]]], dtype=float32)] kwargs = {'axis': [2, 1], 'interpolation': None, 'keepdims': False, 'method': 'linear', ...} funcname = 'map_blocks', suggest_dtype = 'dtype', nout = None def apply_infer_dtype(func, args, kwargs, funcname, suggest_dtype="dtype", nout=None): """ Tries to infer output dtype of ``func`` for a small set of input arguments. Parameters ---------- func: Callable Function for which output dtype is to be determined args: List of array like Arguments to the function, which would usually be used. Only attributes ``ndim`` and ``dtype`` are used. kwargs: dict Additional ``kwargs`` to the ``func`` funcname: String Name of calling function to improve potential error messages suggest_dtype: None/False or String If not ``None`` adds suggestion to potential error message to specify a dtype via the specified kwarg. Defaults to ``'dtype'``. nout: None or Int ``None`` if function returns single output, integer if many. Defaults to ``None``. Returns ------- : dtype or List of dtype One or many dtypes (depending on ``nout``) """ from dask.array.utils import meta_from_array # make sure that every arg is an evaluated array args = [ ( np.ones_like(meta_from_array(x), shape=((1,) * x.ndim), dtype=x.dtype) if is_arraylike(x) else x ) for x in args ] try: with np.errstate(all="ignore"): o = func(*args, **kwargs) except Exception as e: exc_type, exc_value, exc_traceback = sys.exc_info() tb = "".join(traceback.format_tb(exc_traceback)) suggest = ( ( "Please specify the dtype explicitly using the " "`{dtype}` kwarg.\n\n".format(dtype=suggest_dtype) ) if suggest_dtype else "" ) msg = ( f"`dtype` inference failed in `{funcname}`.\n\n" f"{suggest}" "Original error is below:\n" "------------------------\n" f"{e!r}\n\n" "Traceback:\n" "---------\n" f"{tb}" ) else: msg = None if msg is not None: > raise ValueError(msg) E ValueError: `dtype` inference failed in `map_blocks`. E E Please specify the dtype explicitly using the `dtype` kwarg. E E Original error is below: E ------------------------ E TypeError("nanquantile() got an unexpected keyword argument 'interpolation'") E E Traceback: E --------- E File "/usr/lib/python3/dist-packages/dask/array/core.py", line 469, in apply_infer_dtype E o = func(*args, **kwargs) E File "/usr/lib/python3/dist-packages/dask/array/reductions.py", line 1959, in _custom_quantile E return np.nanquantile( E ~~~~~~~~~~~~~~^ E a, E ^^ E ...<5 lines>... E **kwargs, E ^^^^^^^^^ E ) E ^ /usr/lib/python3/dist-packages/dask/array/core.py:494: ValueError ______________________________ test_pauli_rgb[T3] ______________________________ synthetic_poldata = {'T3': <xarray.Dataset> Size: 592kB Dimensions: (y: 128, x: 128) Coordinates: * y (y) int64 1kB 0 1 2 3 4 5 ...complex64 131kB dask.array<chunksize=(16, 16), meta=np.ndarray> Attributes: poltype: T3 description: ...} @pytest.mark.parametrize("synthetic_poldata", ["S", "C3", "T3"], indirect=True) def test_pauli_rgb(synthetic_poldata): input_data = synthetic_poldata for _, ds in input_data.items(): input_data = ds.chunk(x=64, y=64) > res = pauli_rgb(input_data=input_data) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ tests/test_util.py:319: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ polsarpro/util.py:665: in pauli_rgb clip_val = rgb.quantile(dim=("x", "y"), q=q).astype("float32").drop_vars("quantile") ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ /usr/lib/python3/dist-packages/xarray/core/dataarray.py:5407: in quantile ds = self._to_temp_dataset().quantile( /usr/lib/python3/dist-packages/xarray/core/dataset.py:8299: in quantile variables[name] = var.quantile( /usr/lib/python3/dist-packages/xarray/core/variable.py:2035: in quantile result = apply_ufunc( /usr/lib/python3/dist-packages/xarray/computation/apply_ufunc.py:1279: in apply_ufunc return variables_vfunc(*args) ^^^^^^^^^^^^^^^^^^^^^^ /usr/lib/python3/dist-packages/xarray/computation/apply_ufunc.py:820: in apply_variable_ufunc result_data = func(*input_data) ^^^^^^^^^^^^^^^^^ /usr/lib/python3/dist-packages/xarray/core/variable.py:2028: in _wrapper return xp.moveaxis(_quantile_func(npa, **kwargs), 0, -1) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ /usr/lib/python3/dist-packages/xarray/core/nputils.py:242: in f result = getattr(npmodule, name)(values, axis=axis, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ /usr/lib/python3/dist-packages/dask/array/core.py:1769: in __array_function__ return da_func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^ /usr/lib/python3/dist-packages/dask/array/reductions.py:2058: in nanquantile result = a.map_blocks( /usr/lib/python3/dist-packages/dask/array/core.py:2705: in map_blocks return map_blocks(func, self, *args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ /usr/lib/python3/dist-packages/dask/array/core.py:828: in map_blocks dtype = apply_infer_dtype(func, args, original_kwargs, "map_blocks") ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ func = <function _custom_quantile at 0x7fe4d208c4a0> args = [array([[[1.]]], dtype=float32)] kwargs = {'axis': [2, 1], 'interpolation': None, 'keepdims': False, 'method': 'linear', ...} funcname = 'map_blocks', suggest_dtype = 'dtype', nout = None def apply_infer_dtype(func, args, kwargs, funcname, suggest_dtype="dtype", nout=None): """ Tries to infer output dtype of ``func`` for a small set of input arguments. Parameters ---------- func: Callable Function for which output dtype is to be determined args: List of array like Arguments to the function, which would usually be used. Only attributes ``ndim`` and ``dtype`` are used. kwargs: dict Additional ``kwargs`` to the ``func`` funcname: String Name of calling function to improve potential error messages suggest_dtype: None/False or String If not ``None`` adds suggestion to potential error message to specify a dtype via the specified kwarg. Defaults to ``'dtype'``. nout: None or Int ``None`` if function returns single output, integer if many. Defaults to ``None``. Returns ------- : dtype or List of dtype One or many dtypes (depending on ``nout``) """ from dask.array.utils import meta_from_array # make sure that every arg is an evaluated array args = [ ( np.ones_like(meta_from_array(x), shape=((1,) * x.ndim), dtype=x.dtype) if is_arraylike(x) else x ) for x in args ] try: with np.errstate(all="ignore"): o = func(*args, **kwargs) except Exception as e: exc_type, exc_value, exc_traceback = sys.exc_info() tb = "".join(traceback.format_tb(exc_traceback)) suggest = ( ( "Please specify the dtype explicitly using the " "`{dtype}` kwarg.\n\n".format(dtype=suggest_dtype) ) if suggest_dtype else "" ) msg = ( f"`dtype` inference failed in `{funcname}`.\n\n" f"{suggest}" "Original error is below:\n" "------------------------\n" f"{e!r}\n\n" "Traceback:\n" "---------\n" f"{tb}" ) else: msg = None if msg is not None: > raise ValueError(msg) E ValueError: `dtype` inference failed in `map_blocks`. E E Please specify the dtype explicitly using the `dtype` kwarg. E E Original error is below: E ------------------------ E TypeError("nanquantile() got an unexpected keyword argument 'interpolation'") E E Traceback: E --------- E File "/usr/lib/python3/dist-packages/dask/array/core.py", line 469, in apply_infer_dtype E o = func(*args, **kwargs) E File "/usr/lib/python3/dist-packages/dask/array/reductions.py", line 1959, in _custom_quantile E return np.nanquantile( E ~~~~~~~~~~~~~~^ E a, E ^^ E ...<5 lines>... E **kwargs, E ^^^^^^^^^ E ) E ^ /usr/lib/python3/dist-packages/dask/array/core.py:494: ValueError =============================== warnings summary =============================== tests/test_io.py::test_s_matrix <frozen importlib._bootstrap>:488: RuntimeWarning: numpy.ndarray size changed, may indicate binary incompatibility. Expected 16 from C header, got 96 from PyObject -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html =========================== short test summary info ============================ FAILED tests/test_util.py::test_pauli_rgb[S] - ValueError: `dtype` inference ... FAILED tests/test_util.py::test_pauli_rgb[C3] - ValueError: `dtype` inference... FAILED tests/test_util.py::test_pauli_rgb[T3] - ValueError: `dtype` inference... =================== 3 failed, 69 passed, 1 warning in 4.93s ==================== E: pybuild pybuild:485: test: plugin pyproject failed with: exit code=1: cd /<<PKGBUILDDIR>>/.pybuild/cpython3_3.13_polsarpro/build; python3.13 -m pytest tests dh_auto_test: error: pybuild --test --test-pytest -i python{version} -p "3.14 3.13" --parallel=2 returned exit code 13 make: *** [debian/rules:6: binary] Error 25 dpkg-buildpackage: error: debian/rules binary subprocess failed with exit status 2 --------------------------------------------------------------------------------
