Extrema Infra A quantitative trading environment built in Rust. - Event-driven, channel-based, and designed for modular strategy execution across multiple exchanges. - Maximizes runtime efficiency through static dispatch and promotes scalability with Heterogeneous Lists (HList) for strategy registration. At its core: One unified framework for multiple exchanges and strategies, with static dispatch at the strategy-registration boundary. --- SOTA Usages Explore state-of-the-art example usages, architecture walkthroughs, and community Q&A—no need to run it, just see how strategies and data flows are structured. 👉 Join the discussion & explore examples: GitHub Discussions – SOTA Usages --- Key Features - Machine Learning Integration Across Languages - Features can be sent via ZeroMQ to Python ML models (Torch, GBM, Transformer, etc.). - ONNX models can also run directly inside extremainfra without an external Python service. - AltTensor is the common dense tensor payload for feature input and model output. - Predictions return asynchronously to Rust for signal generation and order execut

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