Trame with multiple VTK files

Hi all, I’m here to discuss some doubts that I’ve. I’m trying to develop remote rendering using Trame. Trame is very useful and easy-to-use tool. I successfully developed the code and its working fine. In the development, I was using one VTK file. But I’ve to use multiple vtk files like batch processing in paraview. Is there any option for that ? I tried to make a control in the UI as a selection of vtk file from the list and rendering the model. But it’s not working too

Another doubt is that how to combine Trame and Django.

By multiple files, you mean time series? Then yes, trame is definitely capable of managing time series or multiple objects in your VTK scene.

But that part is not trame specific, it is more how your structure your VTK code so you can have some UI to control what you want to see.

Also, trame support ParaView, so you can use the ParaView scripting infrastructure which natively support time series and so on.

Regarding django, you will have to be more precise on what you aim to do. If django provides the template, then you can embed trame as an iframe. If you want your trame app to show some django forms, you can create your own Vue.js components to do that and drive them from the trame server. Either way, there is a path forward but that path will be more involving than a simple trame app in Python.

As always, if you need help with your development, we can help.

Thanks for the reply. Now it is working fine. I would be able to give many controls in UI and everything is working fine.
Another problem I’ve to address is that the link generated by trame is not working when I access the visualization from another computer.
In the terminal, there’s a message which is like " Note that for multi-users you need to use and configure a launcher ". The problem is due to this ? and how to configure launcher.

One more doubt is that, is it possible to specify host address in the trame code ?

The docker bundle (see cookiecutter) let you package your app so it can serve many concurrent users from a single port / entry point. This also streamline the cloud deployment.

Regarding the host part, you can add --host 0.0.0.0 to allow outside connection to connect to your local process.