I have a chart with about fifty thousand data points split across twenty-five series. It is mostly lines+markers Go.scatter traces. I’m wondering if it’s possible to make the chart more responsive. Right now, if I zoom into the dashboard, it takes one or two seconds for the dashboard to respond. I assume it’s a lot of work that’s happening on the dashboard side.
My dashboard is hosted locally, though I’m open to using waitress or some other job hoster.
My first thought is to switch to Scattergl, but I’m curious if there are additional solutions.
Chart interaction, if there are no callbacks, is solely dependent upon the client’s browser performance.
But, some other things that will affect it, especially since you are using it locally is that your computer is also bogging down from hosting the site as well.
I mean, there is a sneaky solution where I can get rid of individual data points if they are the same as the preceding data points. They are mostly time series data, so you could imagine scenario A where 9am, 10am, 11am and 12pm are all at 100. I could get rid of 10am and 11am because plotly knows to connect the dots from 9am to 12pm with a straight line.
That’s sorta an edge case though, not sure that it would make much of an impact
Wait, isn’t scatter gl loads faster? The demo here makes it seem like the web gl engine is way way faster at loading up and plotting data Scatter plots in Python
