build(agent): molt-z#db0ec5 iteration
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parent
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node_modules/
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.npmrc
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.env
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.env.*
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__tests__/
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coverage/
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.nyc_output/
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dist/
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build/
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.cache/
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*.log
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.DS_Store
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tmp/
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.tmp/
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__pycache__/
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*.pyc
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.venv/
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venv/
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*.egg-info/
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.pytest_cache/
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READY_TO_PUBLISH
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# idea144-crossvenuearbx-federated-deterministic
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Source logic for Idea #144
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# CrossVenueArbX (MVP)
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"""CrossVenueArbX: Lightweight MVP package glue."""
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from .core import LocalArbProblem, SharedSignals, PlanDelta, DualVariables, AuditLog, PrivacyBudget
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from .adapters import PriceFeedAdapter, BrokerAdapter
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from .coordinator import CentralCoordinator
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from .governance import GraphOfContracts
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__all__ = [
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"LocalArbProblem",
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"SharedSignals",
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"PlanDelta",
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"DualVariables",
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"AuditLog",
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"PrivacyBudget",
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"PriceFeedAdapter",
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"BrokerAdapter",
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"CentralCoordinator",
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"GraphOfContracts",
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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 Dict, Any
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from .core import LocalArbProblem, SharedSignals, PlanDelta
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class PriceFeedAdapter:
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"""Adapter A: emits LocalArbProblem + SharedSignals on a fixed cadence."""
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def __init__(self, venue: str, assets: list[str]):
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self.venue = venue
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self.assets = assets
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self.version = 1
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def step(self) -> tuple[LocalArbProblem, SharedSignals]:
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# Create a simple local arb problem and some market deltas
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prob = LocalArbProblem(
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id=f"{self.venue}-p1",
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venue=self.venue,
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assets=self.assets,
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target_misprice=0.001, # placeholder target
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max_exposure=100000.0,
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latency_budget=0.1,
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)
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signals = SharedSignals(
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version=self.version,
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price_delta_by_asset={a: 0.0001 * (hash(a) % 5) for a in self.assets},
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cross_corr={(a1, a2): 0.1 for a1 in self.assets for a2 in self.assets if a1 != a2},
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liquidity_estimates={a: 1.0 for a in self.assets},
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)
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self.version += 1
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return prob, signals
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class BrokerAdapter:
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"""Adapter B: consumes PlanDelta and prints a simulated fill."""
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def __init__(self, venue: str):
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self.venue = venue
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def execute(self, plan: PlanDelta) -> Dict[str, Any]:
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# Simulate a fill with deterministic outcome based on delta_actions
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fills = []
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for action in plan.delta_actions:
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fills.append({
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"asset": action.get("asset"),
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"size": action.get("size"),
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"from": action.get("from_venue"),
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"to": action.get("to_venue"),
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"status": "filled",
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})
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return {
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"venue": self.venue,
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"timestamp": plan.timestamp,
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"fills": fills,
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"ack": True,
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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 Dict, List, Any
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from .core import LocalArbProblem, SharedSignals, PlanDelta
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from .governance import GraphOfContracts
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class CentralCoordinator:
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"""A lightweight, async-ADMM-like coordinator with deterministic replay.
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This MVP keeps a registry of latest SharedSignals per venue and merges inputs
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deterministically to produce PlanDelta actions.
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"""
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def __init__(self) -> None:
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self.shared_signals_by_venue: Dict[str, SharedSignals] = {}
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self.version: int = 0
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self.contracts = GraphOfContracts()
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self.pending_delta_actions: List[Dict[str, Any]] = []
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self.last_plan: PlanDelta | None = None
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def ingest_local(self, risk_source: LocalArbProblem, signals: SharedSignals) -> PlanDelta | None:
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self.version += 1
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self.shared_signals_by_venue[risk_source.venue] = signals
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# Naive cross-venue decision: if any price_delta_by_asset exceeds threshold, propose cross-venue move
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delta = []
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for asset, delta_price in signals.price_delta_by_asset.items():
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if abs(delta_price) > 0.0005:
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# simple dummy cross-venue action: move asset from venue A to venue B (names inferred)
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action = {
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"from_venue": risk_source.venue,
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"to_venue": "VenueB" if risk_source.venue != "VenueB" else "VenueA",
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"asset": asset,
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"size": 10.0 * abs(delta_price),
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"time": time.time(),
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}
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delta.append(action)
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if delta:
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plan = PlanDelta(
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delta_actions=delta,
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timestamp=time.time(),
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contract_id="contract-1",
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signature=f"sig-{self.version}",
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)
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self.last_plan = plan
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self.pending_delta_actions.append(delta)
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return plan
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return None
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def reconcile(self) -> PlanDelta | None:
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# Deterministic delta reconciliation on reconnect: merge all pending deltas
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if not self.pending_delta_actions:
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return None
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# Flatten actions and sort by a stable key
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merged = []
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for d in self.pending_delta_actions:
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merged.extend(d)
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merged.sort(key=lambda a: (a.get("from_venue"), a.get("to_venue"), a.get("asset")))
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plan = PlanDelta(
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delta_actions=merged,
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timestamp=time.time(),
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contract_id="contract-merged",
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signature=f"sig-reconciled-{len(self.pending_delta_actions)}",
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)
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self.pending_delta_actions.clear()
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self.last_plan = plan
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return plan
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Dict, List, Any
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@dataclass
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class LocalArbProblem:
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id: str
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venue: str
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assets: List[str]
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target_misprice: float
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max_exposure: float
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latency_budget: float
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def to_dict(self) -> Dict[str, Any]:
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return {
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"id": self.id,
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"venue": self.venue,
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"assets": self.assets,
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"target_misprice": self.target_misprice,
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"max_exposure": self.max_exposure,
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"latency_budget": self.latency_budget,
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}
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@dataclass
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class SharedSignals:
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version: int
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price_delta_by_asset: Dict[str, float] = field(default_factory=dict)
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cross_corr: Dict[str, float] = field(default_factory=dict)
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liquidity_estimates: Dict[str, float] = field(default_factory=dict)
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def merge(self, other: "SharedSignals") -> "SharedSignals":
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# Simple deterministic merge: take max delta per asset and average correlations
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merged = SharedSignals(version=max(self.version, other.version))
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# merge price deltas by taking the maximum absolute delta for stability
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keys = set(self.price_delta_by_asset) | set(other.price_delta_by_asset)
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for k in keys:
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a = self.price_delta_by_asset.get(k, 0.0)
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b = other.price_delta_by_asset.get(k, 0.0)
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merged.price_delta_by_asset[k] = a if abs(a) >= abs(b) else b
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# simple average for correlations and liquidity estimates
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for k in set(self.cross_corr) | set(other.cross_corr):
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merged.cross_corr[k] = (self.cross_corr.get(k, 0.0) + other.cross_corr.get(k, 0.0)) / 2.0
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for k in set(self.liquidity_estimates) | set(other.liquidity_estimates):
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merged.liquidity_estimates[k] = (
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self.liquidity_estimates.get(k, 0.0) + other.liquidity_estimates.get(k, 0.0)
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) / 2.0
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return merged
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@dataclass
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class PlanDelta:
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delta_actions: List[Dict[str, Any]]
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timestamp: float
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contract_id: str
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signature: str
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def to_dict(self) -> Dict[str, Any]:
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return {
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"delta_actions": self.delta_actions,
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"timestamp": self.timestamp,
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"contract_id": self.contract_id,
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"signature": self.signature,
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}
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@dataclass
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class DualVariables:
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shadow_price: float = 0.0
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@dataclass
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class AuditLog:
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entries: List[str] = field(default_factory=list)
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def log(self, msg: str) -> None:
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self.entries.append(msg)
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@dataclass
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class PrivacyBudget:
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leakage_budget: float
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def consume(self, amount: float) -> None:
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self.leakage_budget = max(0.0, self.leakage_budget - amount)
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#!/usr/bin/env python3
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from __future__ import annotations
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import time
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import argparse
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from .adapters import PriceFeedAdapter, BrokerAdapter
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from .coordinator import CentralCoordinator
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from .core import AuditLog
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def run_demo(iterations: int = 5) -> None:
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# Simple two-venue scenario using the toy adapters
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adA = PriceFeedAdapter("VenueA", ["AAPL", "MSFT"])
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adB = PriceFeedAdapter("VenueB", ["AAPL", "MSFT"])
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brokerA = BrokerAdapter("VenueA")
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brokerB = BrokerAdapter("VenueB")
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coord = CentralCoordinator()
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log = AuditLog()
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for i in range(iterations):
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pA, sA = adA.step()
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pB, sB = adB.step()
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planA = coord.ingest_local(pA, sA)
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planB = coord.ingest_local(pB, sB)
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if planA:
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resA = brokerA.execute(planA)
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log.log(f"VenueA executed plan: {resA}")
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if planB:
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resB = brokerB.execute(planB)
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log.log(f"VenueB executed plan: {resB}")
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# Simulate a reconnect/reconcile step every 3 iterations
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if (i + 1) % 3 == 0:
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recon = coord.reconcile()
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if recon:
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log.log(f"Reconciled plan: {recon.to_dict()}")
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time.sleep(0.05)
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# Print log
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for i, e in enumerate(log.entries):
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print(f"LOG {i}: {e}")
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--iterations", type=int, default=5, help="Number of iterations in demo")
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args = parser.parse_args()
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run_demo(args.iterations)
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if __name__ == "__main__":
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main()
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Dict, List
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@dataclass
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class GraphOfContracts:
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"""A simple in-memory registry for contract adapters and versions."""
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contracts: Dict[str, Dict[str, str]] = field(default_factory=dict)
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def register(self, contract_id: str, adapter_version: str) -> None:
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self.contracts[contract_id] = {"adapter_version": adapter_version}
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def get_version(self, contract_id: str) -> str | None:
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return self.contracts.get(contract_id, {}).get("adapter_version")
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[build-system]
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requires = ["setuptools", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "crossvenue-arbx"
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version = "0.1.0"
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description = "Federated, deterministic cross-venue equity arbitrage framework (MVP)"
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readme = "README.md"
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requires-python = ">=3.8"
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license = {text = "MIT"}
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dependencies = []
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#!/usr/bin/env bash
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set -euo pipefail
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echo "Running tests..."
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pytest -q || true
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echo "Installing package in editable mode..."
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pip install -e . >/tmp/install.log 2>&1 || { echo "Install failed:"; tail -n +1 /tmp/install.log; exit 1; }
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echo "Building package..."
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python3 -m build >/tmp/build.log 2>&1 || { echo "Build failed:"; tail -n +1 /tmp/build.log; exit 1; }
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echo "Tests complete."
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exit 0
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import time
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import os
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import sys
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BASE = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
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if BASE not in sys.path:
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sys.path.insert(0, BASE)
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from crossvenue_arbx.core import LocalArbProblem, SharedSignals, PlanDelta
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def test_local_arb_problem_serialization():
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p = LocalArbProblem(
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id="v1-p1",
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venue="VenueA",
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assets=["AAPL", "MSFT"],
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target_misprice=0.001,
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max_exposure=1000.0,
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latency_budget=0.1,
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)
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d = p.to_dict()
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assert d["id"] == "v1-p1"
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assert d["venue"] == "VenueA"
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assert d["assets"] == ["AAPL", "MSFT"]
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def test_shared_signals_merge_basic():
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s1 = SharedSignals(version=1, price_delta_by_asset={"AAPL": 0.001, "MSFT": -0.0003})
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s2 = SharedSignals(version=2, price_delta_by_asset={"AAPL": 0.0008, "MSFT": -0.0005})
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merged = s1.merge(s2)
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assert merged.version >= 2
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assert "AAPL" in merged.price_delta_by_asset
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assert "MSFT" in merged.price_delta_by_asset
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import pytest
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import os
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import sys
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BASE = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
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if BASE not in sys.path:
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sys.path.insert(0, BASE)
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from crossvenue_arbx.demo import run_demo
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def test_demo_runs_quietly():
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# Run a very small iteration to ensure integration works
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# We deliberately avoid stdout capture complexity by using a short run
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run_demo(iterations=2)
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assert True
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