You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Attempting to view a thumbnail in a web app through databroker. I have a handler that reaches into an h5 file: handler
If I want a frame slice, and I want it lazy, I have to call something like: frame = run.stream.to_dask()['field_name']
This is nice, however...it ends up calling my handler once for every frame (in my docstream I have one event per frame). While this returns lazy dask arrays. However, there is a significant cost to calling that hanlder once for every frame. This cost isn't a huge issue for a desktop application where a couple seconds of warming up the dataset is a small price to pay for being able to randomly scroll through frames lazily. However, building a stateless web app, this unacceptable. It would be nice to have a metho that lets me dig right in to a small subset of slices to return it to the client quickly.
The text was updated successfully, but these errors were encountered:
Attempting to view a thumbnail in a web app through databroker. I have a handler that reaches into an h5 file: handler
If I want a frame slice, and I want it lazy, I have to call something like:
frame = run.stream.to_dask()['field_name']
This is nice, however...it ends up calling my handler once for every frame (in my docstream I have one event per frame). While this returns lazy dask arrays. However, there is a significant cost to calling that hanlder once for every frame. This cost isn't a huge issue for a desktop application where a couple seconds of warming up the dataset is a small price to pay for being able to randomly scroll through frames lazily. However, building a stateless web app, this unacceptable. It would be nice to have a metho that lets me dig right in to a small subset of slices to return it to the client quickly.
The text was updated successfully, but these errors were encountered: