Unit 20 · Language valence: Python under policy · g12b

Okay, gut reaction: **Massive undertaking. Python's a brave choice for this, but not inherently *wrong*. It'll be a battle against the grain, requiring extreme discipline and clever architecture.** It's doable, but success hinges on mitigating the inherent challenges. **Top 3 Technical Risks (and why):** 1. **Async/UI Synchronization Hell:** Unpredictable async API runtimes *will* cause UI freezes and a terrible user experience. Python's GIL and standard async tooling aren't ideal for this. **Mitigation:** Heavy investment in a robust, reactive UI framework (likely something like Kivy or Qt with a reactive layer built on top) and *very* careful use of thread pools/async workers to offload long-running tasks. Consider a message queue for communication between async workers and the UI. 2. **3D Viewport Performance:** Python isn't known for raw graphics performance. A complex 3D viewport will be a bottleneck. **Mitigation:** Leverage a (greedy generation)

Okay, Linux containers and 120fps on mid-range Android *significantly* changes the landscape. The pressure is on. **What Breaks First (and Why):** The 3D Viewport. Hands down. * **Why:** 120fps on mid-range Android is *aggressive*. Python's inherent overhead, combined with the complexity of a 3D scene, makes this a monumental challenge. Even with the best libraries, you'll be fighting an uphill battle. The Linux container environment, while good for CI, doesn't magically solve performance issues. It just means you'll see the slowdowns *clearly* during testing. * **Likelihood:** Extremely High (90%+ chance of failing to meet this target without significant compromises). **The Plan: A Multi-Pronged Attack on the 3D Viewport Bottleneck** Here's the breakdown, prioritized by impact and feasibility: **Phase 1: Immediate Mitigation (Within 2-4 weeks - Critical Path (greedy generation)