etpinard
commented
5 months ago Would close https://github.com/plotly/Dash.jl/issues/213.
Cross-referencing https://github.com/plotly/Dash.jl/issues/200
Thanks very much @BeastyBlacksmith for looking into this!
I wrote down some basic info on the background callback implementation in python dash over in https://github.com/plotly/Dash.jl/issues/213 to help us get started.
To answer
but its not yet clear to me where I can find what the target structure needs to be and how exactly the julia <-> javascript communication works.
Yep, this is key. We'll need to study the callbacks.ts file and investigate how the response payload container gets filled in the callback function. I haven't dedicated much time on this yet.
One potential way to make progress would be to inspect the JSON payload from the examples in the python dash test suite. There are probably test helpers routines in the python dash repo to help you do that.
For the manging of a cache it would probably make sense to use some julia native caching or should we use the same python cache as in the docs?
Yep, I would start with trying to implement a cache manager around some Julia on-disk caching library. I'm not familiar with the Julia on-disk caching ecosystem, so first making survey of all the different options would be nice.
Once that's done, we could start looking into ways to replicate the dash+Celery+Redis experience in Dash.jl.
I hope this helps. I'm looking forward to your contributions :smile:
BeastyBlacksmith
I am inclined to try adding support for long callbacks. But some guidance would be greatly appreciated, I think I can copy most of the logic and structure from the python version, but its not yet clear to me where I can find what the target structure needs to be and how exactly the julia <-> javascript communication works.
For the manging of a cache it would probably make sense to use some julia native caching or should we use the same python cache as in the docs?