From dff020c9db847ef1f054c2715be6ed87201f8fa4 Mon Sep 17 00:00:00 2001 From: agent-58ba63c88b4c9625 Date: Mon, 20 Apr 2026 15:21:45 +0200 Subject: [PATCH] build(agent): new-agents-4#58ba63 iteration --- README.md | 6 ++ blueprint/adapter_blueprint.py | 100 ++++++++++++++++++++++++++ blueprint/toy_cross_venue_pipeline.py | 91 +++++++++++++++++++++++ 3 files changed, 197 insertions(+) create mode 100644 blueprint/adapter_blueprint.py create mode 100644 blueprint/toy_cross_venue_pipeline.py diff --git a/README.md b/README.md index 6830685..2b27799 100644 --- a/README.md +++ b/README.md @@ -12,3 +12,9 @@ Getting started - The repository uses a minimal in-tree packaging setup (Python) and PyTest-based tests. This README intentionally documents the MVP scaffold added in this commit. + +Blueprints and Starter Interoperability +- This repository includes a minimal adapter blueprint and a toy cross-venue analytics pipeline to bootstrap MercuryMesh interoperability across ecosystems. +- blueprint/adapter_blueprint.py: A lean, copy-paste friendly adapter skeleton showing how to connect, extract signals, and emit MarketSignal-like payloads. +- blueprint/toy_cross_venue_pipeline.py: A tiny end-to-end example that simulates two venues and merges signals into an AggregatedSignal with a deterministic, offline-friendly merge strategy. +- You can adapt these templates to fit into your existing adapters and contract graph workflow. diff --git a/blueprint/adapter_blueprint.py b/blueprint/adapter_blueprint.py new file mode 100644 index 0000000..99f3a67 --- /dev/null +++ b/blueprint/adapter_blueprint.py @@ -0,0 +1,100 @@ +""" +Adapter Blueprint for MercuryMesh MVP +This module provides a minimal, well-documented skeleton that teams can copy +when implementing new venue adapters. It is intentionally simple and self-contained +so it can be dropped into new repos or integrated into the existing codebase with +minimal friction. + +The blueprint focuses on three responsibilities: +- Connect to a venue feed (simulated or real) +- Extract raw venue data and normalize it into a common signal format +- Emit a Signal contract compatible object that downstream components can consume + +Note: This is a blueprint, not a fully-featured adapter. It lacks networking, +security, and production-grade error handling which should be added in production use. +""" +from __future__ import annotations + +from dataclasses import dataclass +from typing import Dict, Any, Optional +import time + + +@dataclass +class LocalMarketContext: + venue_id: str + symbol: str + timeframe: str + + +@dataclass +class MarketSignal: + venue_id: str + symbol: str + timestamp: float + features: Dict[str, float] + + +class AdapterBlueprint: + """Minimal adapter blueprint. + + - venue_id: identifier for the venue this adapter connects to + - registry: optional contract/GoC registry payload (not required for the blueprint) + """ + + def __init__(self, venue_id: str, registry: Optional[Dict[str, Any]] = None) -> None: + self.venue_id = venue_id + self.registry = registry or {} + self.connected = False + + def connect(self) -> bool: + """Simulate a connection to the venue feed. + + In a real adapter this would establish a network connection, authenticate, etc. + For the blueprint, we simply mark as connected and return True. + """ + # In a real implementation, add try/except and reconnection logic + self.connected = True + return self.connected + + def fetch_raw(self) -> Any: + """Fetch a raw payload from the venue feed (simulated). + + Returns a simple dict that a concrete subclass would parse. + """ + if not self.connected: + raise RuntimeError("Adapter not connected to venue feed") + # Simulated raw payload; in practice this would be a socket/HTTP feed, etc. + now = time.time() + return { + "venue": self.venue_id, + "symbol": "XYZ", + "ts": now, + "raw_features": { + "liquidity_proxy": 0.9, + "order_flow_intensity": 0.6, + "volatility_proxy": 1.1, + }, + } + + def extract_signal(self, raw: Any) -> MarketSignal: + """Normalize and map raw payload to a MarketSignal contract.""" + venue = str(raw.get("venue", self.venue_id)) + symbol = str(raw.get("symbol", "UNKNOWN")) + timestamp = float(raw.get("ts", time.time())) + features = dict(raw.get("raw_features", {})) + return MarketSignal(venue_id=venue, symbol=symbol, timestamp=timestamp, features=features) + + def emit(self, signal: MarketSignal) -> MarketSignal: + """Hook for downstream consumers. In a real adapter this might publish to a bus.""" + # For blueprint purposes, simply return the signal to show it was produced + return signal + + +if __name__ == "__main__": + # Simple demonstration when run as a script + adapter = AdapterBlueprint(venue_id="venue_example") + adapter.connect() + raw = adapter.fetch_raw() + sig = adapter.extract_signal(raw) + print("Blueprint adapter produced signal:", sig) diff --git a/blueprint/toy_cross_venue_pipeline.py b/blueprint/toy_cross_venue_pipeline.py new file mode 100644 index 0000000..33964a4 --- /dev/null +++ b/blueprint/toy_cross_venue_pipeline.py @@ -0,0 +1,91 @@ +""" +Toy cross-venue analytics pipeline +This script demonstrates a very small, deterministic cross-venue merge +workflow that mirrors the MVP idea of aggregating signals from multiple venues +without sharing raw data. + +It is intentionally lightweight and self-contained to serve as a starter. +Run: python3 blueprint/toy_cross_venue_pipeline.py +""" +from __future__ import annotations + +from dataclasses import dataclass +from typing import Dict, List +import time + + +@dataclass +class LocalMarketContext: + venue_id: str + symbol: str + timeframe: str + + +@dataclass +class MarketSignal: + venue_id: str + symbol: str + timestamp: float + features: Dict[str, float] + + +@dataclass +class AggregatedSignal: + venue_set: List[str] + feature_vector: Dict[str, float] + privacy_budget_used: float + nonce: int + + +def simulate_two_venues() -> List[MarketSignal]: + now = time.time() + sigs = [ + MarketSignal( + venue_id="venue-A", + symbol="ABC", + timestamp=now, + features={"liquidity_proxy": 0.82, "order_flow_intensity": 0.55, "volatility_proxy": 1.15}, + ), + MarketSignal( + venue_id="venue-B", + symbol="ABC", + timestamp=now, + features={"liquidity_proxy": 0.78, "order_flow_intensity": 0.60, "volatility_proxy": 1.10}, + ), + ] + return sigs + + +def aggregate_signals(signals: List[MarketSignal]) -> AggregatedSignal: + if not signals: + return AggregatedSignal(venue_set=[], feature_vector={}, privacy_budget_used=0.0, nonce=0) + # Simple averaging across venues for each feature + keys = set().union(*(s.features.keys() for s in signals)) + avg = {k: 0.0 for k in keys} + for s in signals: + for k in keys: + avg[k] = avg[k] + s.features.get(k, 0.0) + n = float(len(signals)) + feature_vector = {k: (v / n) for k, v in avg.items()} + privacy_budget_used = min([s.features.get("privacy_budget", 0.0) for s in signals] or [0.0]) + return AggregatedSignal(venue_set=[s.venue_id for s in signals], feature_vector=feature_vector, privacy_budget_used=privacy_budget_used, nonce=int(now_epoch()) ) + + +def now_epoch() -> int: + return int(time.time()) + + +def main(): + signals = simulate_two_venues() + agg = aggregate_signals(signals) + print("Toy AggregatedSignal") + print(" venues:", agg.venue_set) + print(" features:") + for k, v in agg.feature_vector.items(): + print(f" {k}: {v:.4f}") + print(" privacy_budget_used:", agg.privacy_budget_used) + print(" nonce:", agg.nonce) + + +if __name__ == "__main__": + main()