build(agent): molt-z#db0ec5 iteration
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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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TradeCipher MVP - Agent Overview
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- Architecture: Python-based MVP with a clean separation between data contracts, a tamper-evident ledger, and a placeholder ZK proof generator.
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- Tech stack: Python 3.8+, dataclasses, in-memory ledger, JSON serialization. No external databases required for MVP.
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- Testing: PyTest test suite covering contracts, ledger, and ZK proof placeholder.
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- How to run tests: ./test.sh
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- Publishing: when ready, follow the publishing steps in the repo's instructions and ensure READY_TO_PUBLISH is created.
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Notes:
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- This is a minimal interoperable skeleton designed to be extended into a full cross-venue MVP.
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- Additional adapters and contract registries can be added under adapters/ and contracts/ respectively.
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18
README.md
18
README.md
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# tradecipher-blockchain-backed-privacy-pr
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# tradecipher-blockchain-backed-privacy-pr
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A modular, open-source platform enabling end-to-end trade lifecycle auditing across venues (options, equities) with cryptographic provenance, zero-knowledge privacy, and offline-first capabilities. The system anchors attestations of orders, fills, an
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A modular, open-source platform enabling end-to-end trade lifecycle auditing across venues (options, equities) with cryptographic provenance, zero-knowledge privacy, and offline-first capabilities. The system anchors attestations of orders, fills, and post-trade events to a tamper-evident ledger while keeping sensitive payloads off-chain.
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This repository provides a minimal MVP implementation in Python to satisfy tests and demonstrate the core concepts (contracts, a tamper-evident ledger, and placeholder ZK proofs). See AGENTS.md for contribution guidance and the READY_TO_PUBLISH signal when ready to publish.
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## How to run (local MVP)
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- Install Python 3.8+
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- Install build tooling: "python3 -m pip install build"
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- Run tests: ./test.sh
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- Build package: python3 -m build
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## Project layout
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- tradecipher_blockchain_backed_privacy_pr/: Python package with contracts, ledger, zk_proofs, and adapters
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- tests/: pytest test suite for core MVP
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- pyproject.toml: packaging metadata for the MVP package tradecipher_blockchain_backed_privacy_pr
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- AGENTS.md: architecture and contribution guidelines
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- test.sh: test runner that executes tests and packaging build
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- README.md: this file
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[build-system]
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requires = ["setuptools>=61.0", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "tradecipher_blockchain_backed_privacy_pr"
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version = "0.1.0"
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dependencies = []
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description = "MVP: blockchain-backed, privacy-preserving trade lifecycle auditing across venues"
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readme = "README.md"
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requires-python = ">=3.8"
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[tool.setuptools.packages.find]
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where = ["."]
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include = ["tradecipher_blockchain_backed_privacy_pr"]
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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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export PYTHONPATH="/workspace/repo:${PYTHONPATH:-}"
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pytest -q
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echo "Building package..."
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python3 -m build
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echo "ALL TESTS PASSED and BUILD SUCCEEDED"
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echo "READY_TO_PUBLISH_MARKER"
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import json
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from tradecipher_blockchain_backed_privacy_pr.contracts import LocalTrade, SharedSignals, PlanDelta
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def test_local_trade_json_roundtrip():
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lt = LocalTrade(
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trade_id="T1",
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product_id="P-XYZ",
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venue="VenueA",
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price=123.45,
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size=10,
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side="buy",
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timestamp=1620000000.0,
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signer_id="Signer1",
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signature="sig123",
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)
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j = lt.to_json()
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# Ensure it's valid JSON and contains expected fields
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obj = json.loads(j)
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assert isinstance(obj, dict)
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assert obj["trade_id"] == "T1"
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def test_shared_signals_and_plan_delta_structure():
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ss = SharedSignals(signals_version=1, aggregated_risk=0.5, margin_impact=0.1, liquidity_metric=0.9)
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pd = PlanDelta(delta_version=1, timestamp=1620000001.0, allocations={"T1": 0.5}, cryptographic_tag="tag")
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assert isinstance(ss.to_json(), str)
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assert isinstance(pd.to_json(), str)
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from tradecipher_blockchain_backed_privacy_pr.ledger import AttestationLedger
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import json
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def test_ledger_append_and_latest():
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ledger = AttestationLedger()
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payload = json.dumps({"event": "test"})
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block = ledger.append(payload)
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assert block.index == 0
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assert ledger.latest() is block
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from tradecipher_blockchain_backed_privacy_pr.zk_proofs import generate_zk_proof
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def test_generate_zk_proof_structure():
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data = {"trade_id": "T1"}
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constraints = {"price_band": [100, 200]}
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proof = generate_zk_proof(data, constraints)
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assert isinstance(proof, dict)
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assert proof.get("valid") is True
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assert "proof" in proof
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"""TradeCipher MVP package
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A lightweight reference implementation for LocalTrade / SharedSignals / PlanDelta
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contracts, a tamper-evident in-memory attestation ledger, and a placeholder
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Zero-Knowledge proof generator. This is intentionally minimal to satisfy the
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tests and provide a concrete starting point for further work.
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"""
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__all__ = [
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"contracts",
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"ledger",
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"zk_proofs",
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"adapters",
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]
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from __future__ import annotations
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"""Tiny adapters registry for two-venue MVP.
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This module is deliberately small; it provides a stub registry that could be
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extended to map LocalTrade -> canonical representation and to register
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simple venue adapters. It demonstrates the intended extension point.
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"""
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ADAPTER_REGISTRY = {}
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def register_adapter(name: str, adapter: object) -> None:
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ADAPTER_REGISTRY[name] = adapter
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def get_adapter(name: str):
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return ADAPTER_REGISTRY.get(name)
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from __future__ import annotations
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from dataclasses import dataclass, asdict
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from typing import Optional
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import json
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@dataclass
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class LocalTrade:
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trade_id: str
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product_id: str
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venue: str
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price: float
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size: int
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side: str # 'buy' or 'sell'
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timestamp: float
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signer_id: str
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signature: str
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def to_json(self) -> str:
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return json.dumps(asdict(self), sort_keys=True)
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@dataclass
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class SharedSignals:
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signals_version: int
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aggregated_risk: float # placeholder for aggregated risk metric
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margin_impact: float
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liquidity_metric: float
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def to_json(self) -> str:
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return json.dumps(asdict(self), sort_keys=True)
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@dataclass
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class PlanDelta:
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delta_version: int
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timestamp: float
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allocations: dict # mapping from trade_id to new allocation
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cryptographic_tag: str
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def to_json(self) -> str:
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return json.dumps(asdict(self), sort_keys=True)
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@dataclass
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class PrivacyBudget:
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budget_id: str
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max_privacy_leakage: float
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spent_privacy: float
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def to_json(self) -> str:
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return json.dumps(asdict(self), sort_keys=True)
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@dataclass
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class AuditLog:
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event_id: str
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timestamp: float
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actor: str
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action: str
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details: Optional[str] = None
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def to_json(self) -> str:
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return json.dumps(asdict(self), sort_keys=True)
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@dataclass
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class ComplianceEvent:
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event_id: str
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venue: str
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constraint: str
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violated: bool
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timestamp: float
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details: Optional[str] = None
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def to_json(self) -> str:
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return json.dumps(asdict(self), sort_keys=True)
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import List, Optional
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import hashlib
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import time
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import json
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def _hash(data: str) -> str:
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return hashlib.sha256(data.encode("utf-8")).hexdigest()
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@dataclass
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class Block:
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index: int
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timestamp: float
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payload: str # JSON-serialized contract data or attestation
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previous_hash: str
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hash: str = field(init=False)
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def __post_init__(self):
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self.hash = _hash(self._block_string())
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def _block_string(self) -> str:
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return f"{self.index}:{self.timestamp}:{self.payload}:{self.previous_hash}"
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class AttestationLedger:
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def __init__(self):
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self._chain: List[Block] = []
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self._current_previous_hash: str = "0" * 64
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def append(self, payload_json: str) -> Block:
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index = len(self._chain)
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block = Block(
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index=index,
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timestamp=time.time(),
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payload=payload_json,
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previous_hash=self._current_previous_hash,
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)
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self._chain.append(block)
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self._current_previous_hash = block.hash
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return block
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def latest(self) -> Optional[Block]:
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return self._chain[-1] if self._chain else None
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def to_json(self) -> str:
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return json.dumps([{
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"index": b.index,
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"timestamp": b.timestamp,
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"payload": b.payload,
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"previous_hash": b.previous_hash,
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"hash": b.hash,
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} for b in self._chain], sort_keys=True)
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from __future__ import annotations
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from typing import Dict
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def generate_zk_proof(data: dict, constraints: dict) -> Dict[str, object]:
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"""Placeholder ZK proof generator.
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This MVP uses a deterministic, non-secure stub that returns a structure
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compatible with a real ZK proof's interface. The real implementation should
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produce a succinct proof that the given data satisfies the constraints without
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revealing the underlying data.
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"""
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# Very naive: hash of inputs to simulate a proof id, and a dummy proof artifact
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probe = {
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"proof_id": hash(str(data) + str(constraints)),
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"proof": "dummy-zk-proof",
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"valid": True,
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"revealed": None,
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}
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return probe
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