Speed up Pyodide interaction dispatch ~50x (#21
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The docs ⚡ bridge dispatched every interaction event with pyodide.runPythonAsync(code-string), which parses + compiles a fresh Python code string per event — ~1.2 ms/event in WASM, the dominant per-frame cost of the Pyodide interaction path on a drag (30-60 events/sec). That's why 3D orbit / plane-drag felt sluggish in the docs vs a live Jupyter kernel. Define a pre-compiled `_awi_dispatch(fig_id, data)` function once at boot and call its PyProxy directly from the message handler (~0.02 ms/event, ~50x faster, measured end-to-end in Pyodide). The proxy is fetched lazily and cached (robust to boot-step ordering) with a runPythonAsync fallback. The Python->JS return path was already efficient (a compiled observer closure calling js.window._anywidgetPush), so no change needed there. All 12 bridge-boot tests pass.
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #21 +/- ##
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Coverage 90.63% 90.63%
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Files 33 33
Lines 2744 2744
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Hits 2487 2487
Misses 257 257 ☔ View full report in Codecov by Harness. 🚀 New features to boost your workflow:
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The docs ⚡ bridge dispatched every interaction event with pyodide.runPythonAsync(code-string), which parses + compiles a fresh Python code string per event — ~1.2 ms/event in WASM, the dominant per-frame cost of the Pyodide interaction path on a drag (30-60 events/sec). That's why 3D orbit / plane-drag felt sluggish in the docs vs a live Jupyter kernel.
Define a pre-compiled
_awi_dispatch(fig_id, data)function once at boot and call its PyProxy directly from the message handler (~0.02 ms/event, ~50x faster, measured end-to-end in Pyodide). The proxy is fetched lazily and cached (robust to boot-step ordering) with a runPythonAsync fallback.The Python->JS return path was already efficient (a compiled observer closure calling js.window._anywidgetPush), so no change needed there.
All 12 bridge-boot tests pass.