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python313Packages.tensorpotential: init at 0.5.1 #420514
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This pull request has been mentioned on NixOS Discourse. There might be relevant details there: https://discourse.nixos.org/t/python3packages-tensorpotential-reviewer-wanted/67044/1 |
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Please add the missing declaration within pkgs/top-level/python-packages.nix
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Whoops meant request changes
@Sigmanificient, thank you for reviewing my PR. Upon your request to specify the dependencies, I noticed that one of them (matscipy) is missing in nixpkgs. I created another PR to contribute it (433184). Unfortunately I didn't get matscipy to build. I assume this PR would need to wait until 433184 is merged. Could you perhaps have a look at that PR as well? Also:
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Remember next time that you can define multiple package in a single pr, as long as you keep them in separate commits, it is simpler to manage 😉 Here is an example on how to define a new license: 8d21ee7 |
lib/licenses.nix
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fullName = "Academic Software License"; | ||
url = "https://github.com/ACEsuit/ACE.jl/blob/main/ASL.md"; | ||
}; | ||
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Given we already have asl20
, I'm not sure calling a completely different license asl
is a good idea…
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What do you think should be done about this?
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Also the licence is not FOSS and must be marked free = false;
(it is not even redistributable AFAICT, since all the grants are conditional on non‐commercial use).
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Is it likely to be used for more than just this one package?
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Is it likely to be used for more than just this one package?
I am not sure, but I'd say the answer is more no than yes: the license is relatively recent and not widely adopted from what I see (even among scientific software).
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Then the simplest thing to do would be to just inline the license expression.
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@alyssais, could you be more specific on the necessary steps to include the license?
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Take the attribute set you're adding to licenses.nix, and use it directly as the value of meta.license
in your package instead.
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Still needs to be marked non-free.
…nse to meta.license in tensorpotential
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License looks fine to me now — will bow out of the review here, but remember that in the end we want a single commit for package additions. :)
@alyssais thank you. I will squash everything together once it all works properly. :) |
I wish to contribute this scientific python library to Nixpkgs. It is a tool to generate machine-learned interatomic potentials. The derivation builds successfully on NixOS and nixpkgs 25.05.
Important:
The original license of the package (ASL, Academic Software License) is not present in
lib.licenses
. It has been changed togpl2Only
in my expression just to get it to evaluate, but this needs to be corrected.Things done
nix.conf
? (See Nix manual)sandbox = relaxed
sandbox = true
nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD"
. Note: all changes have to be committed, also see nixpkgs-review usage./result/bin/
)Add a 👍 reaction to pull requests you find important.