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by pkofod
1285 days ago
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Software has bugs. That's the way it is. You may think that Julia (but I suppose this is mostly about the ecosystem of packages around Julia) has too many bugs. Then you can use something else. Like Python. If you move from Julia to Python, you may want to use Numpy? Pretty cool project. It currently has 1,9k issues on Github and if you filter by bugs, it has 599 such labeled issues. How many of those are issues like in the post? I don't know. The same applies to Scipy. For example, the gaussian hypergeometric function returns wrong results for some input values https://github.com/scipy/scipy/issues/3479. This issue was filed in 2014. You can find similar old issues in Julia packages. That's how these things go. Luckily, many of the issues listed in the blog post are fixed. If you think that picking any language and any library combination with a semi-high requirement for the number of features you want to be already implemented will be able to fulfill the "this has to be completely correct or I won't use it for my research"-requirement you will have a hard time. The last part of the post seems to be about OffSetArrays.jl. Many people who have implemented libraries and who care about composability and generic input also agree that the Base AbstractArray interface is not perfect or complete and sometimes the issue is that the interface that does exist is not followed well enough for composability to work. A more complete, agreed upon, and generally adhered to interface for an "AbstractArray" would be nice and has been+is being worked on and discussed by many people in the community. |
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Hamming distance was one, if I recall correctly, that wasn't correct, as well as a few others in its parent module.
I still use the package, of course, because its great. But given the disconnect I saw I'm still careful when documenting as to what method is used (and use a comment to clarify). Most of the time it isn't a huge deal.