[qooleot]

Julia's http library, and furthermore the extensive communities around tech stacks like node.js and ruby. Although Julia is focused on mathematical problems, its still often important to pull data from resources on the net (google weather just as a trivial example). Or outputting results to a website to share results dynamically. This is one area where Python shines - being both a strong web framework (Flask and Django)as well as with scipy and pandas library for computation.

As a bootstrap to letting us do things like stream audio from the Web Audio API, and use Julia inside of an existing web app was to build a Node.js and Julia bridge:

https://github.com/waTeim/node-julia

It worked out very conveniently that Node.js through node-gyp can use C libraries, and Julia can run inside a C context.

I think the strongest use cases are node streams, and also online-learning models such as a recommender system. I.e. pass to Julia what the user has been interested in, and simply get back a few suggested items of high correlation.