I’m developing a visualization data tool for analyzing and studying the evolution of certain wikis from their revision history data dump.
In order to do this, I’m looking for a library that easily provides me charts generation on demand.
The idea would be to have a list with all the possible metrics I want to visualize from different data sets. The user would select the metrics that she wants to visualize and a new tab (browser or app tab) will display showing the selected charts. For every tab, a date range slider will be on the top allowing the user to filter by date once for all the charts being showed in that tab.
Since the datasets can be big and slow to process, I’d like to have a way to store/serialize the selected charts, so I dont’ have to regenerate them the next time I request them.
I don’t need that every user has a different state of the charts, but I do need that every user is able to select any combination of the metrics; and from there, it’d be redirected to a url in a new tab or to a previoulsy loaded plotly figure showing the charts that she selected. Actually, it’d be very interesting to be able to cache the last charts used/combinations of charts (dashboards??); so next user that query the same charts has almost no time to wait to retrieve the selected charts.
All this should be able to be placed online and I’m writing it with Python. And well, I need that the lib generates the charts from a big dataset as fast as possible so the user hasn’t to wait a lot to get a bunch of charts together.
I don’t need incremental or dynamic update of the charts.
So my questions are: is plotly a suitable framework to perform this project? what should I rather use for this: plotly or Dash? does it plotly have a way to serialize the charts being showed? or maybe I can use just some kind of html + js + css output that plotly outputs?
Thank you in advance.