If you want to contribute you might take one of these topics and start working on them.
A feature that many people want appears to be search-in-document feature, this is, the capability of searching keywords inside documents.
For this we would need a reliable way of turning PDF files or any other format into text and being able to discriminate between trivial words of this text and choose the most representative keywords of the text.
This in turn would be stored in some local cache and the user would be able to search in this text like
papis open "text: 'neural GAN'"
or something like this. This would mean that the words neural and GAN
should be searched also in the cache of the text-converted file.
The problems for this is that is difficult to make sure that the user
have good tools to convert into text even only for pdf and there is
no nice solution of a python library doing this.
If someone has experience with youtube, it would be nice to have a review in youtube explaining the main uses of papis and of her workflow.
The downloaders implemented should be downloading the documents via a normal http connection. If the users have an account at some university where the university is paying for access to the journal, then it would be nice that people can provide per user config a proxy that is used to download the paper.
It would be somehow nice to have a logo.
It would be nice to implement packages for the common linux distributions and for Homebrew in macOS.
- HomeBrew (MacOS)
- Debian/Ubuntu
- Archlinux
- NixOS
- Void Linux
- Other