Resource Signal brings reactive async data loading to Python. Main idea: declare what parameters affect your request, and get automatic cancellation, status management, and error handling.
It's inspired by Angular's resource() but adapted for Python's async/await. Works great for APIs, database queries, search—anywhere you fetch data based on changing parameters.
The guide has 5 working examples. Would love feedback!
Is there a best practice how to stream and plot large signal data (e.g. > 1M data points of multiple sine waves) from a Python backend (e.g. numpy + FastAPI) to frontend?
My current solution is: fetch ADC data, convert the bytes to base64 and embed it to JSON that will be send to the frontend. Frontend reverses this process and plot it to eCharts.
Oh my, I just looked him up. He is the developer of Virtual Game Station - a PS1 emulator that I used in the past to play PS Isos on my Windows ME PC! What a legend.
I find the Nextcloud client really buggy on the Mac, especially the VFS integration. The file syncing is also really slow. I switched back to P2P file syncing via Syncthing and Resilio Sync out of frustration.
I think the bounciness of the elements is also a very charming characteristic part of the Liquid Glass UI that Apple introduces. But recreating that is probably very difficult with web technologies.
I actually like their software offerings like Synology Drive and Synology Moments. Their backup solution also seem to "just work" with Hyper Backup.
I'm using a Mac und tried to use Nextcloud, but my conclusion with the Nextcloud Desktop Client is, that it is buggy as hell. Especially the VFS implementation. Synology Drive in opposite just works (for me).