Source: sympy, einsteinpy Control: found -1 sympy/1.10.1-1 Control: found -1 einsteinpy/0.3.0-2 Severity: serious Tags: sid bookworm User: debian...@lists.debian.org Usertags: breaks needs-update
Dear maintainer(s),With a recent upload of sympy the autopkgtest of einsteinpy fails in testing when that autopkgtest is run with the binary packages of sympy from unstable. It passes when run with only packages from testing. In tabular form:
pass fail sympy from testing 1.10.1-1 einsteinpy from testing 0.3.0-2 all others from testing from testing I copied some of the output at the bottom of this report.Currently this regression is blocking the migration of sympy to testing [1]. Due to the nature of this issue, I filed this bug report against both packages. Can you please investigate the situation and reassign the bug to the right package?
More information about this bug and the reason for filing it can be found on https://wiki.debian.org/ContinuousIntegration/RegressionEmailInformation Paul [1] https://qa.debian.org/excuses.php?package=sympy https://ci.debian.net/data/autopkgtest/testing/amd64/e/einsteinpy/21184013/log.gz=================================== FAILURES =================================== ___________________________ test_lambdify_with_args ____________________________
def test_lambdify_with_args(): x, y = symbols("x y") T = BaseRelativityTensor([x + y, x], (x, y), config="l") args, f = T.tensor_lambdify(y, x)
arr = np.array(f(2, 1))
/usr/lib/python3/dist-packages/einsteinpy/tests/test_symbolic/test_tensor.py:251: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
y = 2, x = 1 def _lambdifygenerated(y, x):
return numpy.array((x + y, x))
E NameError: name 'numpy' is not defined <lambdifygenerated-2>:2: NameError=============================== warnings summary ===============================
../../../../usr/lib/python3/dist-packages/einsteinpy/ijit.py:30 ../../../../usr/lib/python3/dist-packages/einsteinpy/ijit.py:30 /usr/lib/python3/dist-packages/einsteinpy/ijit.py:30: UserWarning:Could not import numba package. All einsteinpy functions will work properly but the CPU intensive algorithms will be slow. Consider installing numba to boost performance.
tests/test_plotting/test_fractal.py: 640000 warnings/usr/lib/python3/dist-packages/einsteinpy/plotting/fractal.py:20: DeprecationWarning: `np.complex` is a deprecated alias for the builtin `complex`. To silence this warning, use `complex` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.complex128` here. Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
-- Docs: https://docs.pytest.org/en/stable/warnings.html=========================== short test summary info ============================ FAILED tests/test_symbolic/test_tensor.py::test_lambdify_with_args - NameErro... ==== 1 failed, 230 passed, 8 xfailed, 640002 warnings in 322.36s (0:05:22) =====
autopkgtest [12:16:46]: test command1
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