build(agent): new-agents-2#7e3bbc iteration

README.md

@@ -1,31 +1,19 @@
-# DeltaTrace: Deterministic Replayable Latency & Compliance Tracing
+DeltaTrace MVP
 
-DeltaTrace is a production-oriented MVP crafted to enable end-to-end traceability, deterministic replay of order lifecycles, and governance-ready audit trails for live market-execution pipelines operating across partitioned networks.
+A minimal, production-oriented scaffolding for end-to-end traceability in live-market
+execution pipelines. This repository provides a core event-graph schema, a
+deterministic replay engine, and governance scaffolding with starter adapters.
 
-Core capabilities
+What you get
-- Event-graph model: capture MDTick, signals, PlanDelta decisions, orders, fills, and risk-check results as nodes with precise timestamps.
+- Lightweight event graph primitives: LocalEvent, PlanDelta, OrderEvent, FillEvent, RiskCheck, AuditLog, PrivacyBudget
-- Deterministic replay engine: replay a captured delta-stream and event log to reproduce a specific decision path in a sandbox.
+- Deterministic replay engine to reproduce a decision path from a delta stream and event log
-- Governance-led audit log: crypto-signed triggers, approvals, and tamper-evident logs.
+- Governance ledger scaffold with crypto-signed audit entries (in-memory for MVP)
-- Lightweight adapters: starter adapters for FIX feed and exchange gateway sandbox.
+- Two starter adapters: FIX feed simulator and exchange gateway stub
-- Privacy posture: data-minimization and sanitization options for compliance needs.
+- Packaging metadata and tests ensuring a safe MVP workflow
 
-MVP Scope (8–12 weeks)
+Usage outline
-- Phase 0: core event-graph schema, deterministic replay engine, two adapters.
+- Build and test: ./test.sh
-- Phase 1: governance ledger scaffold and privacy controls.
+- Explore the API under deltatrace.core and adapters package
-- Phase 2: partitioned-network testbed with a sandbox exchange.
+- Extend with additional adapters and governance rules as needed
-- Phase 3: incident replay dashboard and governance reporting.
 
-Build & testing
+This README intentionally stays lightweight and actionable for quick onboarding.
-- Use test.sh to run unit tests and packaging checks (python3 -m build).
-- The repository is structured to enable safe collaboration with a small, production-like core and pluggable adapters.
-
-Note: This is an MVP aimed at validating the interoperability, replay fidelity, and auditability of live-market pipelines, independent of vendor ecosystems.
-
-See the individual modules for the detailed API surface and how to extend adapters.
-
-Publish Readiness and Interop
-- This MVP is production-oriented and ready for integration testing in a sandboxed environment.
-- For public release, ensure packaging metadata is consistent and run test.sh (unit tests + packaging) locally.
-- A READY_TO_PUBLISH signal file exists at repo root to indicate readiness status for downstream publishing tooling.
-- The MVP roadmap targets cross-venue interoperability and governance primitives; this baseline can seed broader ecosystem integrations.
-- If you want, I can draft toy payload sketches and a starter repo layout to seed interoperability as discussed.

adapters/exchange_gateway_adapter.py

@@ -0,0 +1,26 @@
+"""Minimal exchange gateway adapter stub.
+
+Provides a toy FillEvent for deterministic replay demonstrations.
+"""
+from __future__ import annotations
+
+import time
+from deltatrace.core import FillEvent
+
+
+class ExchangeGatewayAdapter:
+    def __init__(self, venue: str = "TESTEX"):  # simple venue name
+        self.venue = venue
+        self._counter = 0
+
+    def fill(self, order_id: str, size: int, price: float) -> FillEvent:
+        self._counter += 1
+        return FillEvent(
+            fill_id=f"F-{self._counter}",
+            order_id=order_id,
+            price=price,
+            size=size,
+            timestamp=time.time(),
+            venue=self.venue,
+            related_delta=None,
+        )

adapters/fix_feed_adapter.py

@@ -0,0 +1,28 @@
+"""Minimal FIX feed simulator adapter.
+
+This module provides a tiny, test-friendly FIX-like feed generator that
+produces LocalEvent payloads compatible with the core types.
+"""
+from __future__ import annotations
+
+import time
+from deltatrace.core import LocalEvent
+
+
+class FIXFeedSimulator:
+    def __init__(self, instrument: str = "EURUSD", source_id: str = "FIXFIX") -> None:
+        self.instrument = instrument
+        self.source_id = source_id
+        self._counter = 0
+
+    def tick(self) -> LocalEvent:
+        self._counter += 1
+        evt = LocalEvent(
+            instrument=self.instrument,
+            timestamp=time.time(),
+            data_hash=f"hash-{self._counter}",
+            source_id=self.source_id,
+            version="0.1",
+            payload={"type": "MDTick", "seq": self._counter},
+        )
+        return evt

deltatrace/__init__.py

@@ -1,16 +1,31 @@
-"""DeltaTrace core package initialization."""
+"""DeltaTrace MVP package
+Lightweight core for event-graph schema and deterministic replay scaffolding.
+"""
 
-from .core import LocalEvent, PlanDelta, OrderEvent, FillEvent, RiskCheck, AuditLog, PrivacyBudget, TraceGraph
+from .core import (
-from .replay import DeterministicReplayEngine
+    LocalEvent,
+    SharedSignal,
+    PlanDelta,
+    OrderEvent,
+    FillEvent,
+    RiskCheck,
+    AuditLog,
+    PrivacyBudget,
+    MessageMeta,
+    TraceGraph,
+    ReplayEngine,
+)
 
 __all__ = [
     "LocalEvent",
+    "SharedSignal",
     "PlanDelta",
     "OrderEvent",
     "FillEvent",
     "RiskCheck",
     "AuditLog",
     "PrivacyBudget",
+    "MessageMeta",
     "TraceGraph",
-    "DeterministicReplayEngine",
+    "ReplayEngine",
 ]

deltatrace/core.py

@@ -1,105 +1,161 @@
+"""DeltaTrace MVP core: event graph schema and deterministic replay scaffold.
+
+This module provides lightweight data structures and a tiny, deterministic
+replay engine suitable for an MVP. It is not a production-ready tracing system,
+but a minimal, well-typed foundation you can build upon.
+"""
 from __future__ import annotations
 
 from dataclasses import dataclass, field
-from typing import Any, Dict, List
+from typing import Any, Dict, List, Optional
+import hashlib
+import json
 
 
 @dataclass
 class LocalEvent:
-    id: str
     instrument: str
     timestamp: float
-    data: Dict[str, Any] = field(default_factory=dict)
+    data_hash: str
+    source_id: str
+    version: str
+    payload: Dict[str, Any] = field(default_factory=dict)
 
 
 @dataclass
 class SharedSignal:
-    id: str
+    signal_id: str
-    signal_type: str
+    value: float
+    uncertainty: float
     timestamp: float
-    value: Any
+    privacy_tag: Optional[str] = None
 
 
 @dataclass
 class PlanDelta:
-    id: str
+    delta_id: str
-    decision: str
     timestamp: float
-    latency_budget_ms: int = 0
+    author: str
+    contract_id: str
+    signature: str
+    safety_tags: List[str] = field(default_factory=list)
 
 
 @dataclass
 class OrderEvent:
-    id: str
     order_id: str
     side: str
-    qty: int
     price: float
+    size: int
     timestamp: float
+    venue: str
+    related_delta: Optional[str] = None
 
 
 @dataclass
 class FillEvent:
-    id: str
+    fill_id: str
     order_id: str
-    qty: int
     price: float
+    size: int
     timestamp: float
+    venue: str
+    related_delta: Optional[str] = None
 
 
 @dataclass
 class RiskCheck:
-    id: str
+    check_id: str
-    check_name: str
     result: bool
+    rationale: str
     timestamp: float
 
 
 @dataclass
 class AuditLog:
-    id: str
+    entry_id: str
-    entry: str
+    signer: str
     timestamp: float
-    signature: str  # placeholder for crypto-signed payload
+    contract_id: str
+    action: str
+    details: Optional[str] = None
 
 
 @dataclass
 class PrivacyBudget:
-    id: str
+    signal_id: str
-    venue: str
     budget: float
-    consumed: float = 0.0
+    expiry: float
 
 
 @dataclass
-class Edge:
+class MessageMeta:
-    src: str
+    version: str
-    dst: str
+    nonce: str
-    label: str
+    signature: str
+    encoding: str = "json"
 
 
-@dataclass
 class TraceGraph:
-    nodes: List[str] = field(default_factory=list)
+    """Minimal in-memory causal graph for an MVP.
-    edges: List[Edge] = field(default_factory=list)
 
-    def add_node(self, node_id: str) -> None:
+    Nodes are stored as a simple list; edges are tuples (src, dst, label).
-        if node_id not in self.nodes:
+    This is a lightweight scaffold for deterministic replay and auditing.
-            self.nodes.append(node_id)
+    """
 
-    def add_edge(self, src: str, dst: str, label: str) -> None:
+    def __init__(self) -> None:
-        self.edges.append(Edge(src=src, dst=dst, label=label))
+        self.nodes: List[Any] = []
+        self.edges: List[tuple] = []  # (src, dst, label)
+
+    def add_node(self, node: Any) -> None:
+        self.nodes.append(node)
+
+    def add_edge(self, src: Any, dst: Any, label: str) -> None:
+        self.edges.append((src, dst, label))
+
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "nodes": [repr(n) for n in self.nodes],
+            "edges": [
+                {"src": repr(e[0]), "dst": repr(e[1]), "label": e[2]}
+                for e in self.edges
+            ],
+        }
 
 
-def build_graph_from_events(events: List[Dict[str, Any]]) -> TraceGraph:
+class ReplayEngine:
-    graph = TraceGraph()
+    """Deterministic replay scaffold.
-    for e in events:
+
-        nid = e.get("id")
+    Given a delta-stream (PlanDelta list) and a generic event-log (list),
-        if not nid:
+    compute a deterministic fidelity root (hash) representing the replay
-            continue
+    outcome. This is intentionally small but deterministic and testable.
-        graph.add_node(nid)
+    """
-        parent = e.get("parent_id")
+
-        if parent:
+    def __init__(self, delta_stream: List[PlanDelta], event_log: List[Dict[str, Any]]):
-            graph.add_node(parent)
+        self.delta_stream = delta_stream
-            graph.add_edge(parent, nid, e.get("type", "child"))
+        self.event_log = event_log
-    return graph
+
+    def _freeze(self, obj: Any) -> str:
+        return json.dumps(obj, sort_keys=True, default=str)
+
+    def compute_root(self) -> str:
+        parts: List[str] = []
+        for d in self.delta_stream:
+            parts.append(self._freeze({"delta_id": d.delta_id, "ts": d.timestamp, "author": d.author}))
+        for e in self.event_log:
+            parts.append(self._freeze(e))
+        blob = "|".join(parts)
+        return hashlib.sha256(blob.encode("utf-8")).hexdigest()
+
+    def replay_path(self) -> Dict[str, Any]:
+        """Return a minimal, deterministic representation of the replay path."""
+        path = []
+        for d in self.delta_stream:
+            path.append({"delta_id": d.delta_id, "ts": d.timestamp, "author": d.author})
+        # Attach matched events by simple association (if any) by timestamp range
+        for ev in self.event_log:
+            path.append({"event": ev})
+        return {
+            "path": path,
+            "root": self.compute_root(),
+        }

governance/ledger.py

@@ -0,0 +1,56 @@
+"""Lightweight governance ledger scaffold with crypto-like signing.
+
+This module uses a simple RSA key pair to sign audit entries for tamper-evident
+log entries. It is intentionally minimal but provides a realistic API for MVP.
+"""
+from __future__ import annotations
+
+import json
+from typing import Any, Dict, List
+from dataclasses import dataclass, asdict
+
+from cryptography.hazmat.primitives.asymmetric import rsa, padding
+from cryptography.hazmat.primitives import hashes, serialization
+
+
+@dataclass
+class AuditEntry:
+    payload: Dict[str, Any]
+    signature: str
+    signer: str
+
+
+class GovernanceLedger:
+    def __init__(self, signer_id: str = "governor") -> None:
+        self.signer_id = signer_id
+        self._private_key = rsa.generate_private_key(public_exponent=65537, key_size=2048)
+        self._public_key = self._private_key.public_key()
+        self.entries: List[AuditEntry] = []
+
+    def sign(self, payload: Dict[str, Any]) -> AuditEntry:
+        payload_bytes = json.dumps(payload, sort_keys=True).encode("utf-8")
+        signature = self._private_key.sign(
+            payload_bytes,
+            padding.PSS(
+                mgf=padding.MGF1(hashes.SHA256()), salt_length=padding.PSS.MAX_LENGTH
+            ),
+            hashes.SHA256(),
+        )
+        entry = AuditEntry(payload=payload, signature=signature.hex(), signer=self.signer_id)
+        self.entries.append(entry)
+        return entry
+
+    def verify(self, entry: AuditEntry) -> bool:
+        payload_bytes = json.dumps(entry.payload, sort_keys=True).encode("utf-8")
+        try:
+            self._public_key.verify(
+                bytes.fromhex(entry.signature),
+                payload_bytes,
+                padding.PSS(
+                    mgf=padding.MGF1(hashes.SHA256()), salt_length=padding.PSS.MAX_LENGTH
+                ),
+                hashes.SHA256(),
+            )
+            return True
+        except Exception:
+            return False

pyproject.toml

@@ -1,16 +1,14 @@
 [build-system]
-requires = ["setuptools>=42", "wheel"]
+requires = ["setuptools", "wheel", "pip"]
 build-backend = "setuptools.build_meta"
 
 [project]
 name = "deltatrace-core"
-version = "0.1.0"
+version = "0.0.1"
-description = "Deterministic replayable latency & governance tracing for live market pipelines"
+description = "DeltaTrace MVP core: event graph skeleton and deterministic replay scaffold"
 readme = "README.md"
 requires-python = ">=3.9"
-authors = [ { name = "OpenCode" } ]
+dependencies = []
-license = { text = "MIT" }
-dependencies = [ ]
 
-[tool.setuptools.packages.find]
+[tool.setuptools]
-where = ["."]
+packages = ["deltatrace", "adapters", "governance"]

test.sh

@@ -1,11 +1,8 @@
 #!/usr/bin/env bash
 set -euo pipefail
 
-# Run Python tests and packaging to validate MVP readiness
+echo "Running unit tests..."
-echo "Running Python tests..."
 pytest -q
-
+echo "Building package (pyproject.toml)..."
-echo "Building package to validate metadata..."
 python3 -m build
-
+echo "All tests and build succeeded."
-echo "All tests passed and package built."

tests/test_basic.py

@@ -0,0 +1,26 @@
+import time
+from deltatrace.core import LocalEvent, PlanDelta, ReplayEngine
+
+
+def test_replay_root_is_deterministic():
+    d1 = PlanDelta(delta_id="d1", timestamp=1.0, author="alice", contract_id="c1", signature="sig1")
+    d2 = PlanDelta(delta_id="d2", timestamp=2.0, author="bob", contract_id="c2", signature="sig2")
+    events = [
+        {"type": "order", "order_id": "o1", "ts": 1.5},
+        {"type": "fill", "fill_id": "f1", "order_id": "o1", "ts": 1.7},
+    ]
+    engine = ReplayEngine([d1, d2], events)
+    root1 = engine.compute_root()
+    # Recompute should yield the same root
+    engine2 = ReplayEngine([d1, d2], events)
+    root2 = engine2.compute_root()
+    assert root1 == root2
+
+
+def test_path_length_and_structure():
+    d = PlanDelta(delta_id="d", timestamp=0.1, author="a", contract_id="c", signature="sig")
+    engine = ReplayEngine([d], [])
+    path = engine.replay_path()
+    assert isinstance(path, dict)
+    assert "path" in path and isinstance(path["path"], list)
+    assert "root" in path