Julia 1.10 local tests fail with Conda SciPy CXXABI mismatch
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- Dominant language
- Julia
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Description
Clean master reproduction at fed960a47ecb48f892fa1563cddfb03b10dd609f:
/home/crackauc/.juliaup/bin/julia +1.10 --project=. -e 'using Pkg; Pkg.test()'\n```\n\nThe test fails while `SciPyDiffEq.__init__` imports `scipy.integrate`, before package assertions run. Conda SciPy\s `scipy.optimize._highspy._core` requires `CXXABI_1.3.15`, but Julia 1.10 loads a `libstdc++.so.6` without that symbol. The same failure reproduces on the clean detached master worktree, so it is not introduced by the strict SciMLTesting 2.4 audit.\n\nCI config already installs `python3-dev python3-scipy`, so it uses system Python rather than this local Conda path.\n\nRepresentative error:\n\n```\nImportError: ...libstdc++.so.6: version `CXXABI_1.3.15` not found\n```Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by running julia +1.10 --project=. -e 'using Pkg; Pkg.test()' at commit fed960a47ecb48f892fa1563cddfb03b10dd609f. Inspect SciPyDiffEq.__init__ and the CI configuration to compare the local Conda import path with CI's system Python setup. Done means the test suite passes without the CXXABI_1.3.15 import failure.
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Assessment
- Tech stack
- julia, python
- Domain
- devops, testing-qa
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100