[huac]

D3 is pretty ok with large datasets but I understand your point.

What Shiny does to get around this is natively 'evaluate' the plots on the backend, creating a rasterized PNG file. A similar approach could work for Pyxley (using matplotlib or Seaborn to render the plot, and then sending that image file to the front end) but I fear with so much development time spent on d3 support such an approach would not be natively implemented.

[claytonjy]

>What Shiny does to get around this is natively 'evaluate' the plots on the backend, creating a rasterized PNG file

I don't think that's the case for D3 charts, because that would kill the interactivity that is so great about D3. I use RCharts to inject D3 into my Shiny applications, and have ran into into performance issues with just a couple hundred data points. I think this is because all heavy lifting is done by the client (browser), not the server.

[blumkvist]

htmlweidget is kinda an evolution to rcharts by the same person if i recall correctly.