Optimizing Shiny for Python App Performance

Make an existing Shiny for Python app faster without changing what it does. The typical user has an app that worked fine for one or two developers and is now too slow or must support more users. Keep all app logic intact; prefer code changes over deployment tuning; resist rewrites.

Order of preference for every fix:

1. Eliminate work that isn't needed (don't compute outputs nobody is looking at; don't compute with inputs that aren't ready).
2. Reuse work that repeats (shared @reactive.calc, module-level caches).
3. Accelerate unavoidable work (faster data formats, polars, push-down).
4. Relocate work that blocks (@reactive.extended_task) — last resort; it buys concurrency, not raw speed.