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A novel, open-source platform to generate cross-venue execution plans locally near exchanges, reducing latency and data leakage. It defines a canonical primitive set for execution planning: - Objects/LocalProblem: per-asset, per-venue optimization t
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README.md

ELAC-Plan: Edge-Latency Aware Cross-Venue Execution Planner

ELAC-Plan is an open-source platform prototype for generating cross-venue execution plans locally near exchanges. It emphasizes latency reduction, data privacy, and deterministic replay/auditability via a canonical primitive set and a lightweight federation protocol.

This repository implements a production-ready MVP skeleton in Python with a FastAPI API, in-memory storage, and a minimal LocalProblem/SharedVariables/PlanDelta model suite. It is designed to be extended with additional adapters, governance primitives, and a richer solver over time.

Key primitives (canonical IR):

  • LocalProblem (Objects): per-asset, per-venue optimization task definitions
  • SharedVariables (Morphisms): privacy-bounded summarized signals
  • DualVariables: cross-venue coupling signals
  • PlanDelta: incremental plan updates with metadata and cryptographic tags
  • AuditLog: governance and provenance blocks

Architecture overview

  • API: FastAPI app exposing /problems and /status (and delta reconciliation in future)
  • In-memory storage with deterministic replay hooks
  • Lightweight solver: generates PlanDelta from LocalProblem
  • Adapters: translate market feeds and broker APIs into the ELAC canonical representation

How to run

  • Install: python3 -m pip install -e .
  • Run API (example): uvicorn elac_plan.api.app:app --reload --port 8000
  • Tests: bash test.sh

Contributing

  • See AGENTS.md for contribution rules and how to run tests locally.

This is an early MVP; feedback and contributions are welcome.