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Add OMpy to pip #120
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In principle possible; there is some questions we should think of. What would you suggest doing about this? |
The install script should fail if MultiNest is not found. The built-in
Either one could ship the most used response functions or set up functionality that fetches the response functions from the repository from GitHub.
I suggest following this schema. |
Do you think that people (after us?) will remember to update the version when they make changes? |
Version updating could be automatically done |
I guess my concern was (mostly towards) what is solved in here: https://stackoverflow.com/questions/42718373/increase-version-number-if-travis-at-github-was-successful Do you want to set it up? If I should do it it, it might have to wait some time. |
Or do you have any other/better suggestion? |
The install of PyMultiNest via pip does not fail if Multinest is not found. It will complain once you try to import it |
Hm, that's interesting. I don't think it's good to ship hem with the code via pip. That will just make things very large. But we could of course have
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The latter alternative does not help on the MultiNest issue, of course. |
Alternatively one could fork pymultinest and use scikit-build.readthedocs.io to build the multinest package?
I think a static get_response method is a good choice! |
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Got an error when trying to upload the package to pypi. ❯ python3 -m twine upload --repository testpypi dist/*
Uploading distributions to https://test.pypi.org/legacy/
Uploading OMpy-1.0.1-cp37-cp37m-linux_x86_64.whl
100%|█████████████████████████████████████████| 464k/464k [00:02<00:00, 221kB/s]
NOTE: Try --verbose to see response content.
HTTPError: 400 Client Error: Binary wheel 'OMpy-1.0.1-cp37-cp37m-linux_x86_64.whl' has an unsupported platform tag 'linux_x86_64'. for url: https://test.pypi.org/legacy/ The problem is, I think, the cython modules that are complies for my system. Seems like I need to upload them with Will have a look at it later. |
It might be about time to consider uploading OMpy as a package on the pypi repository, simplifying the installation considerable.
The packaging and uploading of the package should probably be done automatically through travis-ci or similar tools.
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