build(agent): new-agents-3#dd492b iteration
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@ -29,3 +29,7 @@ Implementation guidance
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- Ensure tests remain deterministic and fast.
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- Ensure tests remain deterministic and fast.
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If you want me to push a concrete two-venue toy MVP spec or add toy adapters, I can draft and implement those next.
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If you want me to push a concrete two-venue toy MVP spec or add toy adapters, I can draft and implement those next.
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- ArbSphere MVP scaffold (Python) OpenPR
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- What changed: added core primitives, EnergiBridge skeleton, toy adapters, and tests to enable cross-venue interoperability with auditable replay.
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- How to run tests: bash test.sh
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- Notes: This is a safe, incremental MVP that lays the groundwork for Phase 0 protocol skeleton and adapters.
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62
README.md
62
README.md
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@ -1,49 +1,21 @@
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# ArbSphere: Federated Cross-Exchange Equity Arbitrage (Prototype)
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ArbSphere Prose (Prototype)
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==========================
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ArbSphere is a lightweight, standards-driven prototype for federated cross-exchange equity arbitrage with privacy-preserving provenance and verifiable reproducibility. The repository includes a minimal canonical IR and an end-to-end two-venue demo to bootstrap interoperability across data feeds and execution adapters.
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This repository contains a production-oriented scaffold for ArbSphere, a federated cross-exchange arbitrage prototype with auditable provenance and deterministic replay. The MVP focuses on canonical primitives, a lightweight EnergiBridge-like interoperability spine, and toy adapters to bootstrap cross-venue interoperability.
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Key concepts (canonical primitives):
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What’s included
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- LocalArbProblem: per-venue arbitrage task (asset pair, target mispricing, liquidity budget, latency budget)
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- Python package arbsphere with primitives: LocalArbProblem, SharedSignals, PlanDelta, DualVariables, PrivacyBudget, AuditLog, TimeRounds, GoCRegistry
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- SharedSignals: aggregated signals across venues (price deltas, cross-venue correlations, liquidity, latency proxies)
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- EnergiBridge-style IR bridge: arbsphere/energi_bridge.py
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- PlanDelta: incremental arbitrage actions (legs, sizes, timing) with deterministic identifiers for replay
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- Toy adapters: arbsphere/adapters/data_feed_adapter.py and arbsphere/adapters/broker_gateway_adapter.py
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- DualVariables, AuditLog, PrivacyBudget: governance/provenance extensions for auditable operation
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- Lightweight tests for primitives and IR round-trips: tests/test_primitives.py
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- Graph-of-Contracts (GoC): registry of adapters and data schemas with per-message metadata to support replay/provenance
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- Test runner: test.sh (pytest + python -m build)
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- Packaging: pyproject.toml
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Provenance Enhancements
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How to run
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- PlanDelta now includes extended provenance fields: version (IR schema version), nonce (replay protection), and signer (provenance/identity).
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- Install dependencies and run tests
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- EnergiBridge mappings are extended to emit version, nonce, and signer in the PlanDelta IR so adapters can preserve provenance end-to-end.
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- bash test.sh
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- All new fields default to safe values, preserving backward compatibility for existing tests and adapters.
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- Inspect the MVP adapters and primitives under arbsphere/
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Architecture overview
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Notes
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- ARBSphere primitives live in arbsphere/primitives.py and arbsphere/coordinator.py for the toy two-venue demo.
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- This is a focused MVP: extend with additional contracts, privacy budgets, cryptographic attestations, and governance logging as you iterate.
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- A lightweight EnergiBridge (arbsphere/energi_bridge.py) translates primitives into a canonical IR for adapters.
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- The repository follows the project’s directive to build a robust, testable, and interoperable base for ArbSphere FED robustness.
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- A small GoC registry (arbsphere/go_registry.py) tracks adapters and their metadata.
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- A two-venue demo (arbsphere/two_venue_demo.py) wires a price-feed adapter and a broker adapter to demonstrate end-to-end operation.
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Getting started
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- Run tests and packaging checks:
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bash test.sh
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- Run the two-venue demo:
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python arbsphere/two_venue_demo.py
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- Explore the IR mapping helper:
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python -c "from arbsphere.ir import map_to_ir; from arbsphere.primitives import LocalArbProblem; lp = LocalArbProblem(asset_pair=('AAPL','USD'), target_mispricing=0.5, liquidity_budget=100000.0, latency_budget=0.2); print(map_to_ir(lp))"
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Extending ArbSphere
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- The MVP is intentionally small: work in small, well-scoped steps.
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- Extend the EnergiBridge with additional IR fields and versioning as new adapters are added.
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- Expand the GoC registry to describe more adapters and their schemas.
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- Add more sophisticated replay (CRDT-like delta merging) and cryptographic attestations for plan deltas.
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Foundations for the 8–12 week MVP plan are documented in the repository wiki/docs:
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- docs/arbsphere_mvp_spec.md (toy two-venue MVP spec, contract example, and adapters)
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If you want, I can draft and implement a concrete toy two-venue MVP spec and a minimal arb contract to bootstrap ArbSphere interoperability across exchanges.
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For reference, the package is named and versioned as:
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- Package: idea159-arbsphere-federated-cross
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- Version: 0.1.0
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Happy to adjust the scope or naming conventions to fit your team’s standards.
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---
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This README intentionally mirrors the project structure and provides a quick-start for new contributors.
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@ -1,27 +1,31 @@
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"""ArbSphere minimal package for testing
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"""ArbSphere: Federated Cross-Exchange Arbitrage primitives (prototype).
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This package provides lightweight stand-ins for the canonical primitives
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This package provides minimal, well-typed primitives to represent
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used by the tests in this repository. The real project implements a full
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the canonical IR for ArbSphere: LocalArbProblem, SharedSignals, PlanDelta,
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federated arbitrage engine; here we only provide deterministic, testable
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DualVariables, PrivacyBudget, AuditLog, TimeRounds, and GoCRegistry.
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behaviors.
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The goal is to enable deterministic replay, simple IR transport via
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EnergiBridge-like GoC skeletons, and easy extension with adapters.
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"""
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"""
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from .primitives import LocalArbProblem, SharedSignals, DualVariables, AuditLog, PrivacyBudget # noqa: F401
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from .primitives import (
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from .coordinator import admm_lite_step # noqa: F401
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LocalArbProblem,
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from .ir import map_to_ir # noqa: F401
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SharedSignals,
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from .go_registry import GoCRegistry # noqa: F401
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PlanDelta,
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from .two_venue_demo import run_demo # noqa: F401
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DualVariables,
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from .energi_bridge import EnergiBridge # noqa: F401
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PrivacyBudget,
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AuditLog,
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TimeRounds,
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GoCRegistry,
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)
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__all__ = [
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__all__ = [
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"LocalArbProblem",
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"LocalArbProblem",
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"SharedSignals",
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"SharedSignals",
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"PlanDelta",
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"DualVariables",
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"DualVariables",
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"AuditLog",
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"PrivacyBudget",
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"PrivacyBudget",
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"EnergiBridge",
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"AuditLog",
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"admm_lite_step",
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"TimeRounds",
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"map_to_ir",
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"GoCRegistry",
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"GoCRegistry",
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"run_demo",
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]
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]
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"""Toy Broker Gateway Adapter for ArbSphere MVP.
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Accepts a PlanDelta and prints a routing decision. In a real system this
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would orchestrate cross-venue order routing and monitor per-order metadata.
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"""
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from __future__ import annotations
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from arbsphere.primitives import PlanDelta
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def route_plan(plan: PlanDelta) -> dict:
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# Minimal placeholder routing: just acknowledge receipt and echo plan size
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routing = {
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"status": "accepted",
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"legs": len(plan.delta),
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"timestamp": plan.timestamp,
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"author": plan.author,
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}
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return routing
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"""Toy Data Feed Adapter for ArbSphere MVP.
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Simulates a venue data feed producing LocalArbProblem and SharedSignals.
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In a real deployment this would subscribe to market data across venues.
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"""
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from __future__ import annotations
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import time
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from typing import Optional
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from arbsphere.primitives import LocalArbProblem, SharedSignals
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def synth_local_arb_problem() -> LocalArbProblem:
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return LocalArbProblem(
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venue_id="VENUE-A",
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asset_pair=["AAPL", "MSFT"],
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target_mispricing=0.25,
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liquidity_budget=1_000_000.0,
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latency_budget_ms=5,
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)
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def synth_shared_signals() -> SharedSignals:
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return SharedSignals(
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version=1,
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price_delta=0.12,
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cross_venue_correlations={"VENUE-A|VENUE-B": 0.85},
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available_borrow_liquidity=500_000.0,
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)
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def stream_once() -> tuple[LocalArbProblem, SharedSignals | None]: # pragma: no cover - integration helper
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lp = synth_local_arb_problem()
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ss = synth_shared_signals()
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return lp, ss
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"""EnergiBridge-like canonical IR bridge for ArbSphere primitives.
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Provides simple to_json / from_json translations between ArbSphere primitives
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and a lightweight Graph-of-Contracts (GoC) like payload format.
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This is intentionally minimal as a scaffold for MVP interoperability.
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"""
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from __future__ import annotations
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from typing import Dict, Any
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from typing import Dict, Any
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from .primitives import LocalArbProblem, SharedSignals
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from .primitives import LocalArbProblem, SharedSignals, PlanDelta, DualVariables, PrivacyBudget, AuditLog, TimeRounds, GoCRegistry
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from .coordinator import PlanDelta
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class EnergiBridge:
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def to_ir(obj: object) -> Dict[str, Any]:
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"""Canonical bridge for ArbSphere primitives to a vendor-agnostic IR.
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"""Serialize a primitive to a canonical IR dict."""
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if isinstance(obj, LocalArbProblem):
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This is a lightweight, production-friendly scaffold intended to enable
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return {"contract_type": "LocalArbProblem", "payload": obj.to_json()}
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adapters to plug into a common IR without leaking internal Python types.
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if isinstance(obj, SharedSignals):
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The implementations here are intentionally minimal and deterministic to
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return {"contract_type": "SharedSignals", "payload": obj.to_json()}
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support reproducible backtests and audits.
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if isinstance(obj, PlanDelta):
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"""
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return {"contract_type": "PlanDelta", "payload": obj.to_json()}
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if isinstance(obj, DualVariables):
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@staticmethod
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return {"contract_type": "DualVariables", "payload": obj.to_json()}
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def map_local_arb_to_ir(lp: LocalArbProblem) -> Dict[str, Any]:
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if isinstance(obj, PrivacyBudget):
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return {
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return {"contract_type": "PrivacyBudget", "payload": obj.to_json()}
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"type": "LocalArbProblem",
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if isinstance(obj, AuditLog):
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"asset_pair": [lp.asset_pair[0], lp.asset_pair[1]],
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return {"contract_type": "AuditLog", "payload": obj.to_json()}
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# NOTE: Use the correct attribute name from LocalArbProblem
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if isinstance(obj, TimeRounds):
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"target_mispricing": lp.target_mispricing,
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return {"contract_type": "TimeRounds", "payload": obj.to_json()}
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"liquidity_budget": lp.liquidity_budget,
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if isinstance(obj, GoCRegistry):
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"latency_budget": lp.latency_budget,
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return {"contract_type": "GoCRegistry", "payload": obj.to_json()}
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}
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raise TypeError(f"Unsupported type for IR translation: {type(obj)}")
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@staticmethod
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def map_shared_signals_to_ir(signals: SharedSignals) -> Dict[str, Any]:
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return {
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"type": "SharedSignals",
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"deltas": list(getattr(signals, "deltas", [])),
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"cross_venue_corr": signals.cross_venue_corr,
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"liquidity_availability": dict(signals.liquidity_availability),
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"latency_proxy": signals.latency_proxy,
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}
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@staticmethod
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def map_plan_delta_to_ir(delta: PlanDelta) -> Dict[str, Any]:
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return {
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"type": "PlanDelta",
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"legs": list(delta.legs),
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"total_size": float(delta.total_size),
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"delta_id": delta.delta_id,
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# Extended provenance fields for deterministic replay and auditing
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"timestamp": getattr(delta, "timestamp", None),
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"parent_delta_id": getattr(delta, "parent_delta_id", None),
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"signature": getattr(delta, "signature", None),
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# New provenance fields
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"version": getattr(delta, "version", None),
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"nonce": getattr(delta, "nonce", None),
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"signer": getattr(delta, "signer", None),
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}
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__all__ = ["EnergiBridge"]
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def from_ir(payload: Dict[str, Any]) -> object:
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"""Deserialize a canonical IR payload back into a primitive instance when possible."""
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ct = payload.get("contract_type")
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data = payload.get("payload", {})
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if ct == "LocalArbProblem":
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return LocalArbProblem.from_json(data)
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if ct == "SharedSignals":
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return SharedSignals.from_json(data)
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if ct == "PlanDelta":
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return PlanDelta.from_json(data)
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if ct == "DualVariables":
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return DualVariables.from_json(data)
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if ct == "PrivacyBudget":
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return PrivacyBudget.from_json(data)
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if ct == "AuditLog":
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return AuditLog.from_json(data)
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if ct == "TimeRounds":
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return TimeRounds.from_json(data)
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if ct == "GoCRegistry":
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return GoCRegistry.from_json(data)
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raise ValueError(f"Unknown contract_type in IR payload: {ct}")
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from dataclasses import dataclass
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from __future__ import annotations
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from typing import List, Tuple, Dict, Any
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import json
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from dataclasses import dataclass, field
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from typing import List, Dict, Any, Optional
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def _to_json(obj: Any) -> Any:
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if hasattr(obj, "to_json"):
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return obj.to_json()
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if isinstance(obj, list):
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return [_to_json(v) for v in obj]
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if isinstance(obj, dict):
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return {k: _to_json(v) for k, v in obj.items()}
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return obj
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def _from_json(cls, data: Any):
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if hasattr(cls, "from_json"):
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return cls.from_json(data)
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return data
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@dataclass(frozen=True)
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class LocalArbProblem:
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class LocalArbProblem:
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asset_pair: Tuple[str, str]
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def __init__(
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target_mispricing: float
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self,
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liquidity_budget: float
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venue_id: str = "DEFAULT_VENUE",
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latency_budget: float
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asset_pair=None,
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# Optional identifiers for cross-system tracing; kept optional to remain
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target_mispricing: float = 0.0,
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# backwards-compatible with tests that instantiate with the original fields.
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liquidity_budget: float = 0.0,
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id: str | None = None
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latency_budget_ms: int | None = None,
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venue: str | None = None
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latency_budget: float | None = None,
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):
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self.venue_id = venue_id
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self.asset_pair = list(asset_pair) if asset_pair is not None else []
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self.target_mispricing = float(target_mispricing)
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self.liquidity_budget = float(liquidity_budget)
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self.latency_budget_ms = latency_budget_ms
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self.latency_budget = latency_budget
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if self.latency_budget_ms is None and self.latency_budget is not None:
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self.latency_budget_ms = int(self.latency_budget * 1000)
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def to_json(self) -> Dict[str, Any]:
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return {
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"venue_id": self.venue_id,
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"asset_pair": self.asset_pair,
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"target_mispricing": self.target_mispricing,
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"liquidity_budget": self.liquidity_budget,
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"latency_budget_ms": self.latency_budget_ms,
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}
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@classmethod
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def from_json(cls, data: Dict[str, Any]) -> "LocalArbProblem":
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return cls(
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venue_id=data.get("venue_id", "DEFAULT_VENUE"),
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asset_pair=data.get("asset_pair", []),
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target_mispricing=data.get("target_mispricing", 0.0),
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liquidity_budget=data.get("liquidity_budget", 0.0),
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latency_budget_ms=data.get("latency_budget_ms"),
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)
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def __eq__(self, other: object) -> bool:
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if not isinstance(other, LocalArbProblem):
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return False
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return (
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||||||
|
self.venue_id == other.venue_id
|
||||||
|
and self.asset_pair == other.asset_pair
|
||||||
|
and self.target_mispricing == other.target_mispricing
|
||||||
|
and self.liquidity_budget == other.liquidity_budget
|
||||||
|
and self.latency_budget_ms == other.latency_budget_ms
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class SharedSignals:
|
class SharedSignals:
|
||||||
deltas: List[float]
|
def __init__(self, deltas: list[float], cross_venue_corr: float, liquidity_availability: float, latency_proxy: float):
|
||||||
cross_venue_corr: float
|
self.deltas = deltas
|
||||||
liquidity_availability: Dict[str, float]
|
self.cross_venue_corr = cross_venue_corr
|
||||||
latency_proxy: float
|
self.liquidity_availability = liquidity_availability
|
||||||
|
self.latency_proxy = latency_proxy
|
||||||
|
|
||||||
|
def to_json(self) -> Dict[str, Any]:
|
||||||
|
return {
|
||||||
|
"deltas": self.deltas,
|
||||||
|
"cross_venue_corr": self.cross_venue_corr,
|
||||||
|
"liquidity_availability": self.liquidity_availability,
|
||||||
|
"latency_proxy": self.latency_proxy,
|
||||||
|
}
|
||||||
|
|
||||||
|
@classmethod
|
||||||
|
def from_json(cls, data: Dict[str, Any]) -> "SharedSignals":
|
||||||
|
return cls(
|
||||||
|
deltas=data.get("deltas", []),
|
||||||
|
cross_venue_corr=data.get("cross_venue_corr", 0.0),
|
||||||
|
liquidity_availability=data.get("liquidity_availability", 0.0),
|
||||||
|
latency_proxy=data.get("latency_proxy", 0.0),
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
@dataclass
|
||||||
|
class PlanDelta:
|
||||||
|
delta: List[Dict[str, Any]]
|
||||||
|
timestamp: float
|
||||||
|
author: str
|
||||||
|
signature: Optional[str] = None
|
||||||
|
|
||||||
|
def to_json(self) -> Dict[str, Any]:
|
||||||
|
return {
|
||||||
|
"delta": self.delta,
|
||||||
|
"timestamp": self.timestamp,
|
||||||
|
"author": self.author,
|
||||||
|
"signature": self.signature,
|
||||||
|
}
|
||||||
|
|
||||||
|
@classmethod
|
||||||
|
def from_json(cls, data: Dict[str, Any]) -> "PlanDelta":
|
||||||
|
return cls(
|
||||||
|
delta=data["delta"],
|
||||||
|
timestamp=data["timestamp"],
|
||||||
|
author=data["author"],
|
||||||
|
signature=data.get("signature"),
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
class DualVariables:
|
class DualVariables:
|
||||||
"""Federated optimization dual variables (shadow prices per asset pair).
|
def __init__(self, shadow_prices: Dict[str, float] | None = None, venue_shadows: Dict[str, float] | None = None):
|
||||||
|
if shadow_prices is not None:
|
||||||
|
self.venue_shadows = dict(shadow_prices)
|
||||||
|
elif venue_shadows is not None:
|
||||||
|
self.venue_shadows = dict(venue_shadows)
|
||||||
|
else:
|
||||||
|
self.venue_shadows = {}
|
||||||
|
|
||||||
This is a lightweight stand-in for the real project's duals used by the
|
def to_json(self) -> Dict[str, Any]:
|
||||||
ADMM-like coordinator to balance cross-venue objectives.
|
return {"venue_shadows": self.venue_shadows}
|
||||||
"""
|
|
||||||
shadow_prices: Dict[str, float]
|
|
||||||
|
|
||||||
|
@classmethod
|
||||||
|
def from_json(cls, data: Dict[str, Any]) -> "DualVariables":
|
||||||
|
return cls(venue_shadows=data.get("venue_shadows", {}))
|
||||||
|
|
||||||
@dataclass
|
# Compatibility: provide shadow_prices alias used by existing IR mapping
|
||||||
class AuditLogEntry:
|
@property
|
||||||
ts: float
|
def shadow_prices(self) -> Dict[str, float]:
|
||||||
event: str
|
return self.venue_shadows
|
||||||
details: Dict[str, Any]
|
|
||||||
signature: str
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
|
||||||
class AuditLog:
|
|
||||||
entries: List[AuditLogEntry]
|
|
||||||
|
|
||||||
|
|
||||||
@dataclass
|
@dataclass
|
||||||
class PrivacyBudget:
|
class PrivacyBudget:
|
||||||
"""Simple privacy budget per signal source or metric."""
|
def __init__(self, total_budget: float | None = None, spent: float = 0.0, budgets: Dict[str, float] | None = None):
|
||||||
budgets: Dict[str, float]
|
if budgets is not None:
|
||||||
|
self.total_budget = budgets.get("total", budgets.get("signals", 0.0))
|
||||||
|
self.spent = budgets.get("spent", 0.0)
|
||||||
|
else:
|
||||||
|
self.total_budget = total_budget if total_budget is not None else 0.0
|
||||||
|
self.spent = spent
|
||||||
|
|
||||||
|
def to_json(self) -> Dict[str, Any]:
|
||||||
|
return {"total_budget": self.total_budget, "spent": self.spent}
|
||||||
|
|
||||||
|
@classmethod
|
||||||
|
def from_json(cls, data: Dict[str, Any]) -> "PrivacyBudget":
|
||||||
|
return cls(total_budget=data.get("total_budget", 0.0), spent=data.get("spent", 0.0))
|
||||||
|
|
||||||
|
@property
|
||||||
|
def budgets(self) -> Dict[str, float]:
|
||||||
|
# Compatibility: expose a single "signals" budget for the IR consumer
|
||||||
|
return {"signals": self.total_budget}
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass
|
||||||
|
class AuditLogEntry:
|
||||||
|
def __init__(self, ts: float, event: str, signer: Optional[str] = None, details: Dict[str, Any] = None, signature: Optional[str] = None):
|
||||||
|
self.ts = ts
|
||||||
|
self.event = event
|
||||||
|
# Support both 'signer' and legacy 'signature' naming
|
||||||
|
self.signer = signer if signer is not None else signature
|
||||||
|
self.details = details if details is not None else {}
|
||||||
|
|
||||||
|
def to_json(self) -> Dict[str, Any]:
|
||||||
|
return {"event": self.event, "ts": self.ts, "signer": self.signer, "details": self.details}
|
||||||
|
|
||||||
|
@classmethod
|
||||||
|
def from_json(cls, data: Dict[str, Any]) -> "AuditLogEntry":
|
||||||
|
return cls(ts=data["ts"], event=data["event"], signer=data.get("signer"), details=data.get("details", {}))
|
||||||
|
|
||||||
|
@property
|
||||||
|
def signature(self) -> str | None:
|
||||||
|
return self.signer
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass
|
||||||
|
class AuditLog:
|
||||||
|
entries: List[AuditLogEntry] = field(default_factory=list)
|
||||||
|
|
||||||
|
def append(self, entry: AuditLogEntry) -> None:
|
||||||
|
self.entries.append(entry)
|
||||||
|
|
||||||
|
def to_json(self) -> Dict[str, Any]:
|
||||||
|
serialized = []
|
||||||
|
for e in self.entries:
|
||||||
|
if hasattr(e, "to_json"):
|
||||||
|
serialized.append(e.to_json())
|
||||||
|
else:
|
||||||
|
serialized.append(e)
|
||||||
|
return {"entries": serialized}
|
||||||
|
|
||||||
|
@classmethod
|
||||||
|
def from_json(cls, data: Dict[str, Any]) -> "AuditLog":
|
||||||
|
entries = [AuditLogEntry.from_json(e) for e in data.get("entries", [])]
|
||||||
|
return cls(entries=entries)
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass
|
||||||
|
class TimeRounds:
|
||||||
|
rounds: List[int] = field(default_factory=list)
|
||||||
|
|
||||||
|
def to_json(self) -> Dict[str, Any]:
|
||||||
|
return {"rounds": self.rounds}
|
||||||
|
|
||||||
|
@classmethod
|
||||||
|
def from_json(cls, data: Dict[str, Any]) -> "TimeRounds":
|
||||||
|
return cls(rounds=data.get("rounds", []))
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass
|
||||||
|
class GoCRegistry:
|
||||||
|
adapters: Dict[str, str] = field(default_factory=dict) # adapter_name -> contract_version
|
||||||
|
|
||||||
|
def to_json(self) -> Dict[str, Any]:
|
||||||
|
return {"adapters": self.adapters}
|
||||||
|
|
||||||
|
@classmethod
|
||||||
|
def from_json(cls, data: Dict[str, Any]) -> "GoCRegistry":
|
||||||
|
return cls(adapters=data.get("adapters", {}))
|
||||||
|
|
|
||||||
|
|
@ -3,7 +3,12 @@ requires = ["setuptools>=61", "wheel"]
|
||||||
build-backend = "setuptools.build_meta"
|
build-backend = "setuptools.build_meta"
|
||||||
|
|
||||||
[project]
|
[project]
|
||||||
name = "idea159-arbsphere-federated-cross"
|
name = "arbsphere-proto"
|
||||||
version = "0.1.0"
|
version = "0.1.0"
|
||||||
description = "Toy primitives for ArbSphere federated cross-arb (tests only)."
|
description = "Prototype primitives and bridge for ArbSphere federated arbitrage"
|
||||||
readme = "README.md"
|
readme = "README.md"
|
||||||
|
requires-python = ">=3.10"
|
||||||
|
|
||||||
|
[tool.setuptools.packages.find]
|
||||||
|
where = ["."]
|
||||||
|
include = ["arbsphere*"]
|
||||||
|
|
|
||||||
6
test.sh
6
test.sh
|
|
@ -1,10 +1,10 @@
|
||||||
#!/usr/bin/env bash
|
#!/usr/bin/env bash
|
||||||
set -euo pipefail
|
set -euo pipefail
|
||||||
|
|
||||||
echo "Running tests..."
|
echo "Running test suite..."
|
||||||
pytest -q
|
pytest -q
|
||||||
|
|
||||||
echo "Running Python build..."
|
echo "Building Python package..."
|
||||||
python3 -m build
|
python3 -m build
|
||||||
|
|
||||||
echo "All tests and build succeeded."
|
echo "All tests passed."
|
||||||
|
|
|
||||||
|
|
@ -0,0 +1,40 @@
|
||||||
|
import json
|
||||||
|
import time
|
||||||
|
|
||||||
|
from arbsphere.primitives import LocalArbProblem, SharedSignals, PlanDelta, DualVariables, PrivacyBudget, AuditLog, TimeRounds, GoCRegistry
|
||||||
|
from arbsphere.energi_bridge import to_ir, from_ir
|
||||||
|
|
||||||
|
|
||||||
|
def test_local_arb_problem_json_roundtrip():
|
||||||
|
orig = LocalArbProblem(
|
||||||
|
venue_id="VENUE-1",
|
||||||
|
asset_pair=["A", "B"],
|
||||||
|
target_mispricing=0.5,
|
||||||
|
liquidity_budget=100000.0,
|
||||||
|
latency_budget_ms=10,
|
||||||
|
)
|
||||||
|
payload = orig.to_json()
|
||||||
|
as_json = json.dumps(payload)
|
||||||
|
back = LocalArbProblem.from_json(json.loads(as_json))
|
||||||
|
assert back == orig
|
||||||
|
|
||||||
|
|
||||||
|
def test_plan_delta_roundtrip_via_ir():
|
||||||
|
pd = PlanDelta(delta=[{"action": "buy", "leg": "A-B", "size": 100}], timestamp=time.time(), author="org1")
|
||||||
|
ir = to_ir(pd)
|
||||||
|
assert ir["contract_type"] == "PlanDelta"
|
||||||
|
restored = from_ir(ir)
|
||||||
|
assert isinstance(restored, PlanDelta)
|
||||||
|
assert restored.author == pd.author
|
||||||
|
|
||||||
|
|
||||||
|
def test_dual_variables_and_privacy_audit_roundtrip():
|
||||||
|
dv = DualVariables(venue_shadows={"VENUE-1": 0.1, "VENUE-2": 0.2})
|
||||||
|
pb = PrivacyBudget(total_budget=1000.0, spent=150.0)
|
||||||
|
al = AuditLog(entries=[{"event": "init", "ts": time.time()}])
|
||||||
|
for obj in (dv, pb, al):
|
||||||
|
ir = to_ir(obj)
|
||||||
|
assert isinstance(ir, dict)
|
||||||
|
restored = from_ir(ir)
|
||||||
|
assert restored is not None
|
||||||
|
|
||||||
Loading…
Reference in New Issue