Create a CAN Simulation in Python

Act as Systems Architect. Build high-frequency RSS Ingestion feeding a 3-Set RAG matrix: Regulatory, Quasi-Crystalline Fractal Memory, and Arbitrage routing. Run Python box-counting algorithms to extract spatial complexity ($D$). Optimize data pipelines as self-similar topologies adjusting frameworks to dimensions $D=4.5-7.5$ to maximize throughput and eliminate bottlenecks. Sync logs through OpenHands directly into a Termux-native local Obsidian vault research library. No summaries.