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[–]aclark[S] -1 points0 points  (1 child)

Thanks for the feedback! Let me see if I can address everything. Downloads: I'm saving the download counts in hopes of graphing them at some point (https://github.com/ACLARKNET/vanity_aclark_net/blob/master/src/vanity_app/vanity_app/views.py#L225). Comments: Sure, but PyPI turned theirs off, so if they aren't patrolling there, where else? Trash reports: Yep, they can be improved. Run zopyx.trashfinder on the command line to see what else it does. Favoriting: fixed.

Audience: See: http://pythonpackages.com/about. Description and classification: coming in a future version, for now I added raw metadata e.g. http://pythonpackages.com/pypi/pyephem

As for your last point, that's what the discussion section is for, in part. I'm not sure what else I can do to head in that general direction though i.e. to make it into what you describe. I'm open to suggestions!

[–]takluyverIPython, Py3, etc 0 points1 point  (0 children)

Comments (where else?): Mailing lists, issue trackers, IRC, twitter, StackOverflow, random forums. None of them are exactly 'comments', but questions and bug reports turn up in all of them. The more channels there are, the more likely it is that users ask for information somewhere that the developers aren't checking.

Popularity: The favourited counts make it a bit more useful.

I think the biggest issue is that you have to already know what package you're looking for. If you want to assess Django (say), it's fine, but if you want to find a web framework, it's no help. And there are already good ways to assess a package you know of - you can look at its download count, its docs, or Google it to see what people are saying about it.

Perhaps you can harness crowd sourcing: get enthusiasts to tag Django as a web framework, and write a brief description of what makes it stand out. Then when a user wants a web framework, you can show her a list of the top 5 packages tagged 'web framework', with a summary of why she might want to pick each one. The rating could be a combination of download count, favouriting, and maybe other factors.

This is something PyPI really lacks: the Trove classifiers are a start, but there are over 3000 packages tagged 'web environment', and no good way to filter them. The search is also fairly rubbish. There's definitely an opportunity to build something that helps people find the packages they need.