2 items
a Technology Reference App with 300K+ entries: manpages, RFCs, Fedora, BSD, Ubuntu, web, Pi, Arduino, OpenCV, Python and more NET SOUP is a technology reference web app that hosts more than 300 thousand documents from many technology areas. The documentations are organized by categories and you can practically get to any of them within 3-4 clicks. Just to name a few documentation sources: . Unix manpages with examples for common commands . Red Hat, Ubuntu, Fedora, FreeBSD, NetBSD, Mac Port documentation . IoT platforms like Raspberry Pi and Arduino . Image and Audio processing tools like OpenCV, Octave, Audacity . IETF RFCs: Internet Standards, Draft Standards . Programming Languages like Python, Perl, PHP, GoLang, Scala, Lua, Erlang, ... . Domain Specific Languages like: Ant, Maven, Make, Groovy and more . Web development resources like web platform, Django, CherryPy and so on. . Dictionary of Data Structures NET SOUP builds in history tracking and provides a way for you to keep your favorites around so that next time you can get it easily. For every page, you can toggle between documentation view and Insights view where you may see our complimentary examples or you can search in place Slide Share or Stack Exchange websites to see what other people might have dealt with. NET SOUP also packs with many useful bookmarks and cheat-sheets to make you very and very productive. It's a true Technology Reference Buffet. You won't be disappointed. Come on and install one to see. It's also free!!! Please give us some feedback so that we can make the app even better for you and other users.
Jul 15, 2015
rating_count is the Chrome Web Store ratings count, not a written-review count.
Media assets
Screenshots and videos on the listing.
Has promo video
Whether the listing includes at least one video.
Languages
Declared language locales.
Developer website
Listing exposes a developer website URL.
Contact email
Listing exposes a contact email.
Keyword in name
Case-insensitive substring match in the name.
Keyword in description
Case-insensitive substring match in the description.
Keyword occurrences in description
Count of case-insensitive occurrences in the description.
Category user-count percentile
Share of same-category extensions with fewer users (null if unknown).
These are transparent listing completeness / keyword signals, not a prediction of Chrome Web Store search ranking.