Hi Bartosz, Glad to hear you're interested in contributing to scikit-learn.
As you've observed, our labels are not up to date and we're still working on it. However, there are a few hints I can give for you to find places to start with: - Some old "good first issue"s require many separate PRs, and they're still open. Those are the ones which usually touch many files/classes. You can try to start from there, which also would help you since you'll have other accepted PRs as a template. - Some older PRs are labeled as "stalled", and you can find some easy ones and address the comments and continue their work. You can also mix your search to find the ones which are "stalled" and labelled as "sprint", which are usually easy ones, but abandoned by the original author. - "Watch" the repo for a while, and see how the activity goes on the repo, and you may be able to find a recently reported issue interesting before others claim it. I hope these hints help, and hope to see your contributions soon :) Best, Adrin. On Wed, Oct 23, 2019 at 10:55 AM Bartosz Podkanowicz < podkanowicz.bart...@gmail.com> wrote: > Hi all, > > I am not sure if it is right place for asking this question. > > In the next 3 months I would like to contribute to scikit-learn (some > code, bug fixs, tests). Unfortunately I have found that many issues > labelled as "good first issue" and "help wanted" has people already working > on it or some pull requests like #15076, #14781, #14934. > > I am not sure if starting contibuting with reviewing pull requests is good > idea. > > Can someone guide me how to find issues/enhancements/fixes that I can > start working on? or maybe I should start with reviewing some pull requests? > > I suppose that I missed something when reading contributing guide. > > Thank you for answers. > > Kind Regards, > Bartosz Podkanowicz > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn >
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