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Diffstat (limited to 'docs/superpowers')
8 files changed, 6355 insertions, 9082 deletions
diff --git a/docs/superpowers/plans/2026-04-01-crypto-trading-platform.md b/docs/superpowers/plans/2026-04-01-crypto-trading-platform.md deleted file mode 100644 index 08ff0f5..0000000 --- a/docs/superpowers/plans/2026-04-01-crypto-trading-platform.md +++ /dev/null @@ -1,4063 +0,0 @@ -# Crypto Trading Platform Implementation Plan - -> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. - -**Goal:** Binance 현물 암호화폐 자동매매 플랫폼을 마이크로서비스 아키텍처로 구축한다. - -**Architecture:** 6개 독립 서비스(data-collector, strategy-engine, order-executor, portfolio-manager, backtester)가 Redis Streams로 통신하고, PostgreSQL에 데이터를 저장한다. shared 라이브러리가 공통 모델/이벤트/DB 연결을 제공하며, Click 기반 CLI로 전체를 제어한다. - -**Tech Stack:** Python 3.12, ccxt, Redis Streams, PostgreSQL, asyncpg, pandas, pandas-ta, Click, pydantic-settings, Docker Compose, pytest - ---- - -## File Structure - -``` -trading/ -├── services/ -│ ├── data-collector/ -│ │ ├── src/data_collector/__init__.py -│ │ ├── src/data_collector/main.py -│ │ ├── src/data_collector/binance_ws.py -│ │ ├── src/data_collector/binance_rest.py -│ │ ├── src/data_collector/storage.py -│ │ ├── src/data_collector/config.py -│ │ ├── tests/test_binance_rest.py -│ │ ├── tests/test_storage.py -│ │ ├── tests/test_main.py -│ │ ├── Dockerfile -│ │ └── pyproject.toml -│ ├── strategy-engine/ -│ │ ├── src/strategy_engine/__init__.py -│ │ ├── src/strategy_engine/main.py -│ │ ├── src/strategy_engine/engine.py -│ │ ├── src/strategy_engine/plugin_loader.py -│ │ ├── src/strategy_engine/config.py -│ │ ├── strategies/base.py -│ │ ├── strategies/rsi_strategy.py -│ │ ├── strategies/grid_strategy.py -│ │ ├── tests/test_engine.py -│ │ ├── tests/test_plugin_loader.py -│ │ ├── tests/test_rsi_strategy.py -│ │ ├── tests/test_grid_strategy.py -│ │ ├── Dockerfile -│ │ └── pyproject.toml -│ ├── order-executor/ -│ │ ├── src/order_executor/__init__.py -│ │ ├── src/order_executor/main.py -│ │ ├── src/order_executor/executor.py -│ │ ├── src/order_executor/risk_manager.py -│ │ ├── src/order_executor/config.py -│ │ ├── tests/test_executor.py -│ │ ├── tests/test_risk_manager.py -│ │ ├── Dockerfile -│ │ └── pyproject.toml -│ ├── portfolio-manager/ -│ │ ├── src/portfolio_manager/__init__.py -│ │ ├── src/portfolio_manager/main.py -│ │ ├── src/portfolio_manager/portfolio.py -│ │ ├── src/portfolio_manager/pnl.py -│ │ ├── src/portfolio_manager/config.py -│ │ ├── tests/test_portfolio.py -│ │ ├── tests/test_pnl.py -│ │ ├── Dockerfile -│ │ └── pyproject.toml -│ └── backtester/ -│ ├── src/backtester/__init__.py -│ ├── src/backtester/main.py -│ ├── src/backtester/engine.py -│ ├── src/backtester/simulator.py -│ ├── src/backtester/reporter.py -│ ├── src/backtester/config.py -│ ├── tests/test_engine.py -│ ├── tests/test_simulator.py -│ ├── tests/test_reporter.py -│ ├── Dockerfile -│ └── pyproject.toml -├── shared/ -│ ├── src/shared/__init__.py -│ ├── src/shared/models.py -│ ├── src/shared/events.py -│ ├── src/shared/broker.py -│ ├── src/shared/db.py -│ ├── src/shared/config.py -│ ├── tests/test_models.py -│ ├── tests/test_events.py -│ ├── tests/test_broker.py -│ ├── tests/test_db.py -│ └── pyproject.toml -├── cli/ -│ ├── src/trading_cli/__init__.py -│ ├── src/trading_cli/main.py -│ ├── src/trading_cli/commands/data.py -│ ├── src/trading_cli/commands/trade.py -│ ├── src/trading_cli/commands/backtest.py -│ ├── src/trading_cli/commands/portfolio.py -│ ├── src/trading_cli/commands/strategy.py -│ ├── src/trading_cli/commands/service.py -│ ├── tests/test_cli_data.py -│ ├── tests/test_cli_trade.py -│ └── pyproject.toml -├── docker-compose.yml -├── .env.example -├── Makefile -└── pyproject.toml (workspace root) -``` - ---- - -## Task 1: Project Scaffolding - -**Files:** -- Create: `pyproject.toml` (workspace root) -- Create: `.env.example` -- Create: `docker-compose.yml` -- Create: `Makefile` -- Create: `.gitignore` -- Create: `shared/pyproject.toml` - -- [ ] **Step 1: Initialize git repo** - -```bash -cd /home/si/Private/repos/trading -git init -``` - -- [ ] **Step 2: Create .gitignore** - -Create `.gitignore`: - -```gitignore -__pycache__/ -*.py[cod] -*$py.class -*.egg-info/ -dist/ -build/ -.eggs/ -*.egg -.venv/ -venv/ -env/ -.env -.mypy_cache/ -.pytest_cache/ -.ruff_cache/ -*.log -.DS_Store -``` - -- [ ] **Step 3: Create workspace root pyproject.toml** - -Create `pyproject.toml`: - -```toml -[project] -name = "trading-platform" -version = "0.1.0" -description = "Binance spot crypto trading platform" -requires-python = ">=3.12" - -[tool.pytest.ini_options] -asyncio_mode = "auto" -testpaths = ["shared/tests", "services/*/tests", "cli/tests"] - -[tool.ruff] -target-version = "py312" -line-length = 100 -``` - -- [ ] **Step 4: Create .env.example** - -Create `.env.example`: - -```env -BINANCE_API_KEY= -BINANCE_API_SECRET= -REDIS_URL=redis://localhost:6379 -DATABASE_URL=postgresql://trading:trading@localhost:5432/trading -LOG_LEVEL=INFO -RISK_MAX_POSITION_SIZE=0.1 -RISK_STOP_LOSS_PCT=5 -RISK_DAILY_LOSS_LIMIT_PCT=10 -DRY_RUN=true -``` - -- [ ] **Step 5: Create docker-compose.yml** - -Create `docker-compose.yml`: - -```yaml -services: - redis: - image: redis:7-alpine - ports: - - "6379:6379" - volumes: - - redis_data:/data - healthcheck: - test: ["CMD", "redis-cli", "ping"] - interval: 5s - timeout: 3s - retries: 5 - - postgres: - image: postgres:16-alpine - ports: - - "5432:5432" - environment: - POSTGRES_USER: trading - POSTGRES_PASSWORD: trading - POSTGRES_DB: trading - volumes: - - postgres_data:/var/lib/postgresql/data - healthcheck: - test: ["CMD-LINE", "pg_isready", "-U", "trading"] - interval: 5s - timeout: 3s - retries: 5 - - data-collector: - build: - context: . - dockerfile: services/data-collector/Dockerfile - env_file: .env - depends_on: - redis: - condition: service_healthy - postgres: - condition: service_healthy - restart: unless-stopped - - strategy-engine: - build: - context: . - dockerfile: services/strategy-engine/Dockerfile - env_file: .env - depends_on: - redis: - condition: service_healthy - postgres: - condition: service_healthy - restart: unless-stopped - - order-executor: - build: - context: . - dockerfile: services/order-executor/Dockerfile - env_file: .env - depends_on: - redis: - condition: service_healthy - postgres: - condition: service_healthy - restart: unless-stopped - - portfolio-manager: - build: - context: . - dockerfile: services/portfolio-manager/Dockerfile - env_file: .env - depends_on: - redis: - condition: service_healthy - postgres: - condition: service_healthy - restart: unless-stopped - -volumes: - redis_data: - postgres_data: -``` - -- [ ] **Step 6: Create Makefile** - -Create `Makefile`: - -```makefile -.PHONY: infra up down logs test lint - -infra: - docker compose up -d redis postgres - -up: - docker compose up -d - -down: - docker compose down - -logs: - docker compose logs -f $(service) - -test: - pytest -v - -lint: - ruff check . - ruff format --check . - -format: - ruff check --fix . - ruff format . -``` - -- [ ] **Step 7: Create shared/pyproject.toml** - -Create `shared/pyproject.toml`: - -```toml -[project] -name = "trading-shared" -version = "0.1.0" -description = "Shared models, events, and utilities for trading platform" -requires-python = ">=3.12" -dependencies = [ - "pydantic>=2.0", - "pydantic-settings>=2.0", - "redis>=5.0", - "asyncpg>=0.29", -] - -[project.optional-dependencies] -dev = [ - "pytest>=8.0", - "pytest-asyncio>=0.23", - "ruff>=0.4", -] - -[build-system] -requires = ["hatchling"] -build-backend = "hatchling.build" - -[tool.hatch.build.targets.wheel] -packages = ["src/shared"] -``` - -- [ ] **Step 8: Commit scaffolding** - -```bash -git add . -git commit -m "chore: project scaffolding with docker-compose, makefile, shared package" -``` - ---- - -## Task 2: Shared — Config & Models - -**Files:** -- Create: `shared/src/shared/__init__.py` -- Create: `shared/src/shared/config.py` -- Create: `shared/src/shared/models.py` -- Create: `shared/tests/test_models.py` - -- [ ] **Step 1: Write failing test for config** - -Create `shared/tests/test_models.py`: - -```python -from shared.config import Settings - - -def test_settings_defaults(): - settings = Settings( - binance_api_key="test_key", - binance_api_secret="test_secret", - ) - assert settings.redis_url == "redis://localhost:6379" - assert settings.database_url == "postgresql://trading:trading@localhost:5432/trading" - assert settings.log_level == "INFO" - assert settings.dry_run is True -``` - -- [ ] **Step 2: Run test to verify it fails** - -```bash -cd /home/si/Private/repos/trading -pip install -e shared[dev] -pytest shared/tests/test_models.py::test_settings_defaults -v -``` - -Expected: FAIL — `ModuleNotFoundError: No module named 'shared'` - -- [ ] **Step 3: Implement config** - -Create `shared/src/shared/__init__.py`: - -```python -``` - -Create `shared/src/shared/config.py`: - -```python -from pydantic_settings import BaseSettings - - -class Settings(BaseSettings): - binance_api_key: str - binance_api_secret: str - redis_url: str = "redis://localhost:6379" - database_url: str = "postgresql://trading:trading@localhost:5432/trading" - log_level: str = "INFO" - risk_max_position_size: float = 0.1 - risk_stop_loss_pct: float = 5.0 - risk_daily_loss_limit_pct: float = 10.0 - dry_run: bool = True - - model_config = {"env_file": ".env", "env_file_encoding": "utf-8"} -``` - -- [ ] **Step 4: Run test to verify it passes** - -```bash -pytest shared/tests/test_models.py::test_settings_defaults -v -``` - -Expected: PASS - -- [ ] **Step 5: Write failing tests for models** - -Append to `shared/tests/test_models.py`: - -```python -from datetime import datetime, timezone -from decimal import Decimal - -from shared.models import Candle, Signal, Order, Position, OrderSide, OrderType, OrderStatus - - -def test_candle_creation(): - candle = Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2026, 1, 1, tzinfo=timezone.utc), - open=Decimal("50000"), - high=Decimal("50100"), - low=Decimal("49900"), - close=Decimal("50050"), - volume=Decimal("1.5"), - ) - assert candle.symbol == "BTCUSDT" - assert candle.close == Decimal("50050") - - -def test_signal_creation(): - signal = Signal( - strategy="rsi_strategy", - symbol="BTCUSDT", - side=OrderSide.BUY, - price=Decimal("50000"), - quantity=Decimal("0.01"), - reason="RSI below 30", - ) - assert signal.side == OrderSide.BUY - assert signal.reason == "RSI below 30" - - -def test_order_creation(): - order = Order( - symbol="BTCUSDT", - signal_id="sig_123", - side=OrderSide.BUY, - type=OrderType.MARKET, - price=Decimal("50000"), - quantity=Decimal("0.01"), - ) - assert order.status == OrderStatus.PENDING - assert order.filled_at is None - assert order.id is not None - - -def test_position_unrealized_pnl(): - pos = Position( - symbol="BTCUSDT", - quantity=Decimal("0.1"), - avg_entry_price=Decimal("50000"), - current_price=Decimal("51000"), - ) - assert pos.unrealized_pnl == Decimal("100") # 0.1 * (51000 - 50000) -``` - -- [ ] **Step 6: Run tests to verify they fail** - -```bash -pytest shared/tests/test_models.py -v -``` - -Expected: FAIL — `ModuleNotFoundError: No module named 'shared.models'` - -- [ ] **Step 7: Implement models** - -Create `shared/src/shared/models.py`: - -```python -from datetime import datetime, timezone -from decimal import Decimal -from enum import StrEnum -from uuid import uuid4 - -from pydantic import BaseModel, Field - - -class OrderSide(StrEnum): - BUY = "BUY" - SELL = "SELL" - - -class OrderType(StrEnum): - MARKET = "MARKET" - LIMIT = "LIMIT" - - -class OrderStatus(StrEnum): - PENDING = "PENDING" - FILLED = "FILLED" - CANCELLED = "CANCELLED" - FAILED = "FAILED" - - -class Candle(BaseModel): - symbol: str - timeframe: str - open_time: datetime - open: Decimal - high: Decimal - low: Decimal - close: Decimal - volume: Decimal - - -class Signal(BaseModel): - id: str = Field(default_factory=lambda: str(uuid4())) - strategy: str - symbol: str - side: OrderSide - price: Decimal - quantity: Decimal - reason: str - created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc)) - - -class Order(BaseModel): - id: str = Field(default_factory=lambda: str(uuid4())) - signal_id: str - symbol: str - side: OrderSide - type: OrderType - price: Decimal - quantity: Decimal - status: OrderStatus = OrderStatus.PENDING - created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc)) - filled_at: datetime | None = None - - -class Position(BaseModel): - symbol: str - quantity: Decimal - avg_entry_price: Decimal - current_price: Decimal - - @property - def unrealized_pnl(self) -> Decimal: - return self.quantity * (self.current_price - self.avg_entry_price) -``` - -- [ ] **Step 8: Run tests to verify they pass** - -```bash -pytest shared/tests/test_models.py -v -``` - -Expected: All PASS - -- [ ] **Step 9: Commit** - -```bash -git add shared/ -git commit -m "feat(shared): add config settings and core data models" -``` - ---- - -## Task 3: Shared — Events & Redis Broker - -**Files:** -- Create: `shared/src/shared/events.py` -- Create: `shared/src/shared/broker.py` -- Create: `shared/tests/test_events.py` -- Create: `shared/tests/test_broker.py` - -- [ ] **Step 1: Write failing tests for events** - -Create `shared/tests/test_events.py`: - -```python -import json -from decimal import Decimal -from datetime import datetime, timezone - -from shared.events import EventType, Event, CandleEvent, SignalEvent, OrderEvent -from shared.models import Candle, Signal, Order, OrderSide, OrderType - - -def test_candle_event_serialize(): - candle = Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2026, 1, 1, tzinfo=timezone.utc), - open=Decimal("50000"), - high=Decimal("50100"), - low=Decimal("49900"), - close=Decimal("50050"), - volume=Decimal("1.5"), - ) - event = CandleEvent(data=candle) - payload = event.to_dict() - assert payload["type"] == EventType.CANDLE - assert payload["data"]["symbol"] == "BTCUSDT" - - -def test_candle_event_deserialize(): - candle = Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2026, 1, 1, tzinfo=timezone.utc), - open=Decimal("50000"), - high=Decimal("50100"), - low=Decimal("49900"), - close=Decimal("50050"), - volume=Decimal("1.5"), - ) - event = CandleEvent(data=candle) - payload = event.to_dict() - restored = Event.from_dict(payload) - assert isinstance(restored, CandleEvent) - assert restored.data.symbol == "BTCUSDT" - - -def test_signal_event_serialize(): - signal = Signal( - strategy="rsi", - symbol="BTCUSDT", - side=OrderSide.BUY, - price=Decimal("50000"), - quantity=Decimal("0.01"), - reason="RSI < 30", - ) - event = SignalEvent(data=signal) - payload = event.to_dict() - assert payload["type"] == EventType.SIGNAL -``` - -- [ ] **Step 2: Run tests to verify they fail** - -```bash -pytest shared/tests/test_events.py -v -``` - -Expected: FAIL - -- [ ] **Step 3: Implement events** - -Create `shared/src/shared/events.py`: - -```python -from __future__ import annotations - -import json -from enum import StrEnum -from typing import Any - -from pydantic import BaseModel - -from shared.models import Candle, Signal, Order - - -class EventType(StrEnum): - CANDLE = "candle" - SIGNAL = "signal" - ORDER = "order" - - -class CandleEvent(BaseModel): - type: EventType = EventType.CANDLE - data: Candle - - def to_dict(self) -> dict[str, Any]: - return json.loads(self.model_dump_json()) - - @classmethod - def from_raw(cls, raw: dict[str, Any]) -> CandleEvent: - return cls.model_validate(raw) - - -class SignalEvent(BaseModel): - type: EventType = EventType.SIGNAL - data: Signal - - def to_dict(self) -> dict[str, Any]: - return json.loads(self.model_dump_json()) - - @classmethod - def from_raw(cls, raw: dict[str, Any]) -> SignalEvent: - return cls.model_validate(raw) - - -class OrderEvent(BaseModel): - type: EventType = EventType.ORDER - data: Order - - def to_dict(self) -> dict[str, Any]: - return json.loads(self.model_dump_json()) - - @classmethod - def from_raw(cls, raw: dict[str, Any]) -> OrderEvent: - return cls.model_validate(raw) - - -_EVENT_MAP = { - EventType.CANDLE: CandleEvent, - EventType.SIGNAL: SignalEvent, - EventType.ORDER: OrderEvent, -} - - -class Event: - @staticmethod - def from_dict(data: dict[str, Any]) -> CandleEvent | SignalEvent | OrderEvent: - event_type = EventType(data["type"]) - cls = _EVENT_MAP[event_type] - return cls.from_raw(data) -``` - -- [ ] **Step 4: Run tests to verify they pass** - -```bash -pytest shared/tests/test_events.py -v -``` - -Expected: All PASS - -- [ ] **Step 5: Write failing tests for broker** - -Create `shared/tests/test_broker.py`: - -```python -import asyncio -import pytest -from unittest.mock import AsyncMock, MagicMock, patch - -from shared.broker import RedisBroker - - -@pytest.fixture -def mock_redis(): - redis = AsyncMock() - redis.xadd = AsyncMock(return_value=b"1234-0") - redis.xread = AsyncMock(return_value=[]) - redis.close = AsyncMock() - return redis - - -@pytest.mark.asyncio -async def test_broker_publish(mock_redis): - broker = RedisBroker.__new__(RedisBroker) - broker._redis = mock_redis - - await broker.publish("candles.BTCUSDT", {"type": "candle", "data": "test"}) - - mock_redis.xadd.assert_called_once() - call_args = mock_redis.xadd.call_args - assert call_args[0][0] == "candles.BTCUSDT" - - -@pytest.mark.asyncio -async def test_broker_subscribe_returns_messages(mock_redis): - mock_redis.xread = AsyncMock(return_value=[ - ("candles.BTCUSDT", [ - (b"1234-0", {b"payload": b'{"type":"candle","data":"test"}'}), - ]) - ]) - broker = RedisBroker.__new__(RedisBroker) - broker._redis = mock_redis - - messages = await broker.read("candles.BTCUSDT", last_id="0-0", count=1) - assert len(messages) == 1 - assert messages[0]["type"] == "candle" -``` - -- [ ] **Step 6: Run tests to verify they fail** - -```bash -pytest shared/tests/test_broker.py -v -``` - -Expected: FAIL - -- [ ] **Step 7: Implement broker** - -Create `shared/src/shared/broker.py`: - -```python -from __future__ import annotations - -import json - -import redis.asyncio as redis - - -class RedisBroker: - def __init__(self, redis_url: str): - self._redis = redis.from_url(redis_url, decode_responses=False) - - async def publish(self, stream: str, data: dict) -> str: - payload = json.dumps(data) - msg_id = await self._redis.xadd(stream, {"payload": payload.encode()}) - return msg_id - - async def read( - self, stream: str, last_id: str = "$", count: int = 10, block: int = 0 - ) -> list[dict]: - results = await self._redis.xread({stream: last_id}, count=count, block=block) - messages = [] - for _stream_name, entries in results: - for _msg_id, fields in entries: - payload = fields[b"payload"] - messages.append(json.loads(payload)) - return messages - - async def close(self): - await self._redis.close() -``` - -- [ ] **Step 8: Run tests to verify they pass** - -```bash -pytest shared/tests/test_broker.py -v -``` - -Expected: All PASS - -- [ ] **Step 9: Commit** - -```bash -git add shared/ -git commit -m "feat(shared): add event system and Redis Streams broker" -``` - ---- - -## Task 4: Shared — Database Layer - -**Files:** -- Create: `shared/src/shared/db.py` -- Create: `shared/tests/test_db.py` - -- [ ] **Step 1: Write failing tests for DB** - -Create `shared/tests/test_db.py`: - -```python -import pytest -from unittest.mock import AsyncMock, patch, MagicMock - -from shared.db import Database - - -@pytest.mark.asyncio -async def test_db_init_sql_creates_tables(): - db = Database.__new__(Database) - db._pool = AsyncMock() - mock_conn = AsyncMock() - db._pool.acquire.return_value.__aenter__ = AsyncMock(return_value=mock_conn) - db._pool.acquire.return_value.__aexit__ = AsyncMock(return_value=False) - - await db.init_tables() - - mock_conn.execute.assert_called() - sql = mock_conn.execute.call_args[0][0] - assert "candles" in sql - assert "signals" in sql - assert "orders" in sql - assert "trades" in sql - assert "positions" in sql - assert "portfolio_snapshots" in sql - - -@pytest.mark.asyncio -async def test_db_insert_candle(): - db = Database.__new__(Database) - db._pool = AsyncMock() - mock_conn = AsyncMock() - db._pool.acquire.return_value.__aenter__ = AsyncMock(return_value=mock_conn) - db._pool.acquire.return_value.__aexit__ = AsyncMock(return_value=False) - - from datetime import datetime, timezone - from decimal import Decimal - from shared.models import Candle - - candle = Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2026, 1, 1, tzinfo=timezone.utc), - open=Decimal("50000"), - high=Decimal("50100"), - low=Decimal("49900"), - close=Decimal("50050"), - volume=Decimal("1.5"), - ) - - await db.insert_candle(candle) - mock_conn.execute.assert_called_once() - sql = mock_conn.execute.call_args[0][0] - assert "INSERT INTO candles" in sql -``` - -- [ ] **Step 2: Run tests to verify they fail** - -```bash -pytest shared/tests/test_db.py -v -``` - -Expected: FAIL - -- [ ] **Step 3: Implement database layer** - -Create `shared/src/shared/db.py`: - -```python -from __future__ import annotations - -import asyncpg - -from shared.models import Candle, Order, Signal - -_INIT_SQL = """ -CREATE TABLE IF NOT EXISTS candles ( - symbol TEXT NOT NULL, - timeframe TEXT NOT NULL, - open_time TIMESTAMPTZ NOT NULL, - open NUMERIC NOT NULL, - high NUMERIC NOT NULL, - low NUMERIC NOT NULL, - close NUMERIC NOT NULL, - volume NUMERIC NOT NULL, - PRIMARY KEY (symbol, timeframe, open_time) -); - -CREATE TABLE IF NOT EXISTS signals ( - id TEXT PRIMARY KEY, - strategy TEXT NOT NULL, - symbol TEXT NOT NULL, - side TEXT NOT NULL, - price NUMERIC NOT NULL, - quantity NUMERIC NOT NULL, - reason TEXT NOT NULL, - created_at TIMESTAMPTZ NOT NULL -); - -CREATE TABLE IF NOT EXISTS orders ( - id TEXT PRIMARY KEY, - signal_id TEXT REFERENCES signals(id), - symbol TEXT NOT NULL, - side TEXT NOT NULL, - type TEXT NOT NULL, - price NUMERIC NOT NULL, - quantity NUMERIC NOT NULL, - status TEXT NOT NULL DEFAULT 'PENDING', - created_at TIMESTAMPTZ NOT NULL, - filled_at TIMESTAMPTZ -); - -CREATE TABLE IF NOT EXISTS trades ( - id TEXT PRIMARY KEY, - order_id TEXT REFERENCES orders(id), - symbol TEXT NOT NULL, - side TEXT NOT NULL, - price NUMERIC NOT NULL, - quantity NUMERIC NOT NULL, - fee NUMERIC NOT NULL DEFAULT 0, - traded_at TIMESTAMPTZ NOT NULL -); - -CREATE TABLE IF NOT EXISTS positions ( - symbol TEXT PRIMARY KEY, - quantity NUMERIC NOT NULL, - avg_entry_price NUMERIC NOT NULL, - current_price NUMERIC NOT NULL, - updated_at TIMESTAMPTZ NOT NULL -); - -CREATE TABLE IF NOT EXISTS portfolio_snapshots ( - id SERIAL PRIMARY KEY, - total_value NUMERIC NOT NULL, - realized_pnl NUMERIC NOT NULL, - unrealized_pnl NUMERIC NOT NULL, - snapshot_at TIMESTAMPTZ NOT NULL -); -""" - - -class Database: - def __init__(self, dsn: str): - self._dsn = dsn - self._pool: asyncpg.Pool | None = None - - async def connect(self): - self._pool = await asyncpg.create_pool(self._dsn) - - async def close(self): - if self._pool: - await self._pool.close() - - async def init_tables(self): - async with self._pool.acquire() as conn: - await conn.execute(_INIT_SQL) - - async def insert_candle(self, candle: Candle): - sql = """ - INSERT INTO candles (symbol, timeframe, open_time, open, high, low, close, volume) - VALUES ($1, $2, $3, $4, $5, $6, $7, $8) - ON CONFLICT (symbol, timeframe, open_time) DO NOTHING - """ - async with self._pool.acquire() as conn: - await conn.execute( - sql, - candle.symbol, - candle.timeframe, - candle.open_time, - candle.open, - candle.high, - candle.low, - candle.close, - candle.volume, - ) - - async def insert_signal(self, signal: Signal): - sql = """ - INSERT INTO signals (id, strategy, symbol, side, price, quantity, reason, created_at) - VALUES ($1, $2, $3, $4, $5, $6, $7, $8) - """ - async with self._pool.acquire() as conn: - await conn.execute( - sql, - signal.id, - signal.strategy, - signal.symbol, - signal.side.value, - signal.price, - signal.quantity, - signal.reason, - signal.created_at, - ) - - async def insert_order(self, order: Order): - sql = """ - INSERT INTO orders (id, signal_id, symbol, side, type, price, quantity, status, created_at) - VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9) - """ - async with self._pool.acquire() as conn: - await conn.execute( - sql, - order.id, - order.signal_id, - order.symbol, - order.side.value, - order.type.value, - order.price, - order.quantity, - order.status.value, - order.created_at, - ) - - async def update_order_status(self, order_id: str, status: str, filled_at=None): - sql = "UPDATE orders SET status = $1, filled_at = $2 WHERE id = $3" - async with self._pool.acquire() as conn: - await conn.execute(sql, status, filled_at, order_id) - - async def get_candles(self, symbol: str, timeframe: str, limit: int = 500) -> list[dict]: - sql = """ - SELECT * FROM candles - WHERE symbol = $1 AND timeframe = $2 - ORDER BY open_time DESC - LIMIT $3 - """ - async with self._pool.acquire() as conn: - rows = await conn.fetch(sql, symbol, timeframe, limit) - return [dict(r) for r in rows] -``` - -- [ ] **Step 4: Run tests to verify they pass** - -```bash -pytest shared/tests/test_db.py -v -``` - -Expected: All PASS - -- [ ] **Step 5: Commit** - -```bash -git add shared/ -git commit -m "feat(shared): add database layer with table init and CRUD operations" -``` - ---- - -## Task 5: Data Collector Service - -**Files:** -- Create: `services/data-collector/pyproject.toml` -- Create: `services/data-collector/Dockerfile` -- Create: `services/data-collector/src/data_collector/__init__.py` -- Create: `services/data-collector/src/data_collector/config.py` -- Create: `services/data-collector/src/data_collector/binance_rest.py` -- Create: `services/data-collector/src/data_collector/binance_ws.py` -- Create: `services/data-collector/src/data_collector/storage.py` -- Create: `services/data-collector/src/data_collector/main.py` -- Create: `services/data-collector/tests/test_binance_rest.py` -- Create: `services/data-collector/tests/test_storage.py` - -- [ ] **Step 1: Create pyproject.toml** - -Create `services/data-collector/pyproject.toml`: - -```toml -[project] -name = "data-collector" -version = "0.1.0" -description = "Binance market data collector service" -requires-python = ">=3.12" -dependencies = [ - "ccxt>=4.0", - "websockets>=12.0", - "trading-shared", -] - -[project.optional-dependencies] -dev = [ - "pytest>=8.0", - "pytest-asyncio>=0.23", -] - -[build-system] -requires = ["hatchling"] -build-backend = "hatchling.build" - -[tool.hatch.build.targets.wheel] -packages = ["src/data_collector"] -``` - -- [ ] **Step 2: Write failing tests for binance_rest** - -Create `services/data-collector/tests/test_binance_rest.py`: - -```python -import pytest -from unittest.mock import AsyncMock, patch, MagicMock -from datetime import datetime, timezone -from decimal import Decimal - -from data_collector.binance_rest import fetch_historical_candles - - -@pytest.mark.asyncio -async def test_fetch_historical_candles_parses_response(): - mock_exchange = MagicMock() - mock_exchange.fetch_ohlcv = AsyncMock(return_value=[ - [1704067200000, 50000.0, 50100.0, 49900.0, 50050.0, 1.5], - [1704067260000, 50050.0, 50200.0, 50000.0, 50150.0, 2.0], - ]) - - candles = await fetch_historical_candles( - exchange=mock_exchange, - symbol="BTC/USDT", - timeframe="1m", - since=datetime(2026, 1, 1, tzinfo=timezone.utc), - limit=2, - ) - - assert len(candles) == 2 - assert candles[0].symbol == "BTCUSDT" - assert candles[0].close == Decimal("50050.0") - assert candles[1].volume == Decimal("2.0") - - -@pytest.mark.asyncio -async def test_fetch_historical_candles_empty_response(): - mock_exchange = MagicMock() - mock_exchange.fetch_ohlcv = AsyncMock(return_value=[]) - - candles = await fetch_historical_candles( - exchange=mock_exchange, - symbol="BTC/USDT", - timeframe="1m", - since=datetime(2026, 1, 1, tzinfo=timezone.utc), - limit=100, - ) - - assert candles == [] -``` - -- [ ] **Step 3: Run tests to verify they fail** - -```bash -cd /home/si/Private/repos/trading -pip install -e services/data-collector[dev] -pytest services/data-collector/tests/test_binance_rest.py -v -``` - -Expected: FAIL - -- [ ] **Step 4: Implement binance_rest** - -Create `services/data-collector/src/data_collector/__init__.py`: - -```python -``` - -Create `services/data-collector/src/data_collector/binance_rest.py`: - -```python -from __future__ import annotations - -from datetime import datetime, timezone -from decimal import Decimal - -from shared.models import Candle - - -async def fetch_historical_candles( - exchange, - symbol: str, - timeframe: str, - since: datetime, - limit: int = 500, -) -> list[Candle]: - since_ms = int(since.timestamp() * 1000) - ohlcv = await exchange.fetch_ohlcv(symbol, timeframe, since=since_ms, limit=limit) - - normalized_symbol = symbol.replace("/", "") - candles = [] - for row in ohlcv: - ts, o, h, l, c, v = row - candles.append( - Candle( - symbol=normalized_symbol, - timeframe=timeframe, - open_time=datetime.fromtimestamp(ts / 1000, tz=timezone.utc), - open=Decimal(str(o)), - high=Decimal(str(h)), - low=Decimal(str(l)), - close=Decimal(str(c)), - volume=Decimal(str(v)), - ) - ) - return candles -``` - -- [ ] **Step 5: Run tests to verify they pass** - -```bash -pytest services/data-collector/tests/test_binance_rest.py -v -``` - -Expected: All PASS - -- [ ] **Step 6: Write failing tests for storage** - -Create `services/data-collector/tests/test_storage.py`: - -```python -import pytest -from unittest.mock import AsyncMock -from datetime import datetime, timezone -from decimal import Decimal - -from shared.models import Candle -from data_collector.storage import CandleStorage - - -@pytest.fixture -def mock_db(): - db = AsyncMock() - db.insert_candle = AsyncMock() - return db - - -@pytest.fixture -def mock_broker(): - broker = AsyncMock() - broker.publish = AsyncMock() - return broker - - -@pytest.fixture -def sample_candle(): - return Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2026, 1, 1, tzinfo=timezone.utc), - open=Decimal("50000"), - high=Decimal("50100"), - low=Decimal("49900"), - close=Decimal("50050"), - volume=Decimal("1.5"), - ) - - -@pytest.mark.asyncio -async def test_storage_saves_to_db_and_publishes(mock_db, mock_broker, sample_candle): - storage = CandleStorage(db=mock_db, broker=mock_broker) - await storage.store(sample_candle) - - mock_db.insert_candle.assert_called_once_with(sample_candle) - mock_broker.publish.assert_called_once() - call_args = mock_broker.publish.call_args - assert call_args[0][0] == "candles.BTCUSDT" - - -@pytest.mark.asyncio -async def test_storage_batch_store(mock_db, mock_broker, sample_candle): - storage = CandleStorage(db=mock_db, broker=mock_broker) - candles = [sample_candle, sample_candle] - await storage.store_batch(candles) - - assert mock_db.insert_candle.call_count == 2 - assert mock_broker.publish.call_count == 2 -``` - -- [ ] **Step 7: Run tests to verify they fail** - -```bash -pytest services/data-collector/tests/test_storage.py -v -``` - -Expected: FAIL - -- [ ] **Step 8: Implement storage** - -Create `services/data-collector/src/data_collector/storage.py`: - -```python -from __future__ import annotations - -from shared.broker import RedisBroker -from shared.db import Database -from shared.events import CandleEvent -from shared.models import Candle - - -class CandleStorage: - def __init__(self, db: Database, broker: RedisBroker): - self._db = db - self._broker = broker - - async def store(self, candle: Candle): - await self._db.insert_candle(candle) - event = CandleEvent(data=candle) - await self._broker.publish(f"candles.{candle.symbol}", event.to_dict()) - - async def store_batch(self, candles: list[Candle]): - for candle in candles: - await self.store(candle) -``` - -- [ ] **Step 9: Run tests to verify they pass** - -```bash -pytest services/data-collector/tests/test_storage.py -v -``` - -Expected: All PASS - -- [ ] **Step 10: Implement config, binance_ws, and main** - -Create `services/data-collector/src/data_collector/config.py`: - -```python -from shared.config import Settings - - -class CollectorConfig(Settings): - symbols: list[str] = ["BTC/USDT"] - timeframes: list[str] = ["1m"] -``` - -Create `services/data-collector/src/data_collector/binance_ws.py`: - -```python -from __future__ import annotations - -import asyncio -import json -import logging -from datetime import datetime, timezone -from decimal import Decimal - -import websockets - -from shared.models import Candle - -logger = logging.getLogger(__name__) - -BINANCE_WS_URL = "wss://stream.binance.com:9443/ws" - - -class BinanceWebSocket: - def __init__(self, symbols: list[str], timeframe: str, on_candle): - self._symbols = symbols - self._timeframe = timeframe - self._on_candle = on_candle - self._running = False - - async def start(self): - streams = [ - f"{s.lower().replace('/', '')}@kline_{self._timeframe}" - for s in self._symbols - ] - url = f"{BINANCE_WS_URL}/{'/'.join(streams)}" - self._running = True - logger.info(f"Connecting to Binance WS: {streams}") - - while self._running: - try: - async with websockets.connect(url) as ws: - async for raw in ws: - if not self._running: - break - msg = json.loads(raw) - if "k" in msg: - candle = self._parse_kline(msg["k"]) - if candle: - await self._on_candle(candle) - except websockets.ConnectionClosed: - logger.warning("WebSocket disconnected, reconnecting in 5s...") - await asyncio.sleep(5) - except Exception as e: - logger.error(f"WebSocket error: {e}, reconnecting in 5s...") - await asyncio.sleep(5) - - def stop(self): - self._running = False - - def _parse_kline(self, k: dict) -> Candle | None: - if not k.get("x"): # only closed candles - return None - return Candle( - symbol=k["s"], - timeframe=k["i"], - open_time=datetime.fromtimestamp(k["t"] / 1000, tz=timezone.utc), - open=Decimal(k["o"]), - high=Decimal(k["h"]), - low=Decimal(k["l"]), - close=Decimal(k["c"]), - volume=Decimal(k["v"]), - ) -``` - -Create `services/data-collector/src/data_collector/main.py`: - -```python -from __future__ import annotations - -import asyncio -import logging - -import ccxt.async_support as ccxt - -from shared.broker import RedisBroker -from shared.db import Database -from data_collector.binance_ws import BinanceWebSocket -from data_collector.config import CollectorConfig -from data_collector.storage import CandleStorage - -logger = logging.getLogger(__name__) - - -async def run(): - config = CollectorConfig() - logging.basicConfig(level=config.log_level) - - db = Database(config.database_url) - await db.connect() - await db.init_tables() - - broker = RedisBroker(config.redis_url) - storage = CandleStorage(db=db, broker=broker) - - ws = BinanceWebSocket( - symbols=config.symbols, - timeframe=config.timeframes[0], - on_candle=storage.store, - ) - - logger.info(f"Starting data collector: symbols={config.symbols}") - try: - await ws.start() - finally: - ws.stop() - await broker.close() - await db.close() - - -def main(): - asyncio.run(run()) - - -if __name__ == "__main__": - main() -``` - -- [ ] **Step 11: Create Dockerfile** - -Create `services/data-collector/Dockerfile`: - -```dockerfile -FROM python:3.12-slim - -WORKDIR /app - -COPY shared/ shared/ -RUN pip install --no-cache-dir ./shared - -COPY services/data-collector/ services/data-collector/ -RUN pip install --no-cache-dir ./services/data-collector - -CMD ["python", "-m", "data_collector.main"] -``` - -- [ ] **Step 12: Commit** - -```bash -git add services/data-collector/ -git commit -m "feat(data-collector): add Binance REST/WS data collection with storage pipeline" -``` - ---- - -## Task 6: Strategy Engine Service - -**Files:** -- Create: `services/strategy-engine/pyproject.toml` -- Create: `services/strategy-engine/Dockerfile` -- Create: `services/strategy-engine/src/strategy_engine/__init__.py` -- Create: `services/strategy-engine/src/strategy_engine/config.py` -- Create: `services/strategy-engine/strategies/base.py` -- Create: `services/strategy-engine/strategies/rsi_strategy.py` -- Create: `services/strategy-engine/strategies/grid_strategy.py` -- Create: `services/strategy-engine/src/strategy_engine/plugin_loader.py` -- Create: `services/strategy-engine/src/strategy_engine/engine.py` -- Create: `services/strategy-engine/src/strategy_engine/main.py` -- Create: `services/strategy-engine/tests/test_rsi_strategy.py` -- Create: `services/strategy-engine/tests/test_grid_strategy.py` -- Create: `services/strategy-engine/tests/test_plugin_loader.py` -- Create: `services/strategy-engine/tests/test_engine.py` - -- [ ] **Step 1: Create pyproject.toml** - -Create `services/strategy-engine/pyproject.toml`: - -```toml -[project] -name = "strategy-engine" -version = "0.1.0" -description = "Plugin-based strategy execution engine" -requires-python = ">=3.12" -dependencies = [ - "pandas>=2.0", - "pandas-ta>=0.3", - "trading-shared", -] - -[project.optional-dependencies] -dev = [ - "pytest>=8.0", - "pytest-asyncio>=0.23", -] - -[build-system] -requires = ["hatchling"] -build-backend = "hatchling.build" - -[tool.hatch.build.targets.wheel] -packages = ["src/strategy_engine"] -``` - -- [ ] **Step 2: Implement base strategy** - -Create `services/strategy-engine/src/strategy_engine/__init__.py`: - -```python -``` - -Create `services/strategy-engine/strategies/base.py`: - -```python -from __future__ import annotations - -from abc import ABC, abstractmethod - -from shared.models import Candle, Signal - - -class BaseStrategy(ABC): - name: str = "base" - - @abstractmethod - def on_candle(self, candle: Candle) -> Signal | None: - pass - - @abstractmethod - def configure(self, params: dict) -> None: - pass - - def reset(self) -> None: - pass -``` - -- [ ] **Step 3: Write failing tests for RSI strategy** - -Create `services/strategy-engine/tests/test_rsi_strategy.py`: - -```python -from datetime import datetime, timezone -from decimal import Decimal - -from shared.models import Candle, OrderSide - - -def make_candle(close: float, idx: int = 0) -> Candle: - return Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2026, 1, 1, minute=idx, tzinfo=timezone.utc), - open=Decimal(str(close)), - high=Decimal(str(close + 10)), - low=Decimal(str(close - 10)), - close=Decimal(str(close)), - volume=Decimal("1.0"), - ) - - -def test_rsi_strategy_no_signal_insufficient_data(): - from strategy_engine.strategies.rsi_strategy import RsiStrategy - - strategy = RsiStrategy() - strategy.configure({"period": 14, "oversold": 30, "overbought": 70, "quantity": 0.01}) - - signal = strategy.on_candle(make_candle(50000)) - assert signal is None - - -def test_rsi_strategy_buy_signal_on_oversold(): - from strategy_engine.strategies.rsi_strategy import RsiStrategy - - strategy = RsiStrategy() - strategy.configure({"period": 14, "oversold": 30, "overbought": 70, "quantity": 0.01}) - - # Feed declining prices to push RSI below 30 - prices = [50000 - i * 100 for i in range(20)] - signal = None - for i, p in enumerate(prices): - signal = strategy.on_candle(make_candle(p, idx=i)) - - # After sustained drop, RSI should be oversold → BUY signal - if signal is not None: - assert signal.side == OrderSide.BUY - assert signal.strategy == "rsi" -``` - -- [ ] **Step 4: Run tests to verify they fail** - -```bash -pip install -e services/strategy-engine[dev] -pytest services/strategy-engine/tests/test_rsi_strategy.py -v -``` - -Expected: FAIL - -- [ ] **Step 5: Implement RSI strategy** - -Create `services/strategy-engine/strategies/rsi_strategy.py`: - -```python -from __future__ import annotations - -from collections import deque -from decimal import Decimal - -import pandas as pd -import pandas_ta as ta - -from shared.models import Candle, Signal, OrderSide -from strategies.base import BaseStrategy - - -class RsiStrategy(BaseStrategy): - name = "rsi" - - def __init__(self): - self._closes: deque[float] = deque(maxlen=200) - self._period: int = 14 - self._oversold: float = 30 - self._overbought: float = 70 - self._quantity: Decimal = Decimal("0.01") - - def configure(self, params: dict) -> None: - self._period = params.get("period", 14) - self._oversold = params.get("oversold", 30) - self._overbought = params.get("overbought", 70) - self._quantity = Decimal(str(params.get("quantity", 0.01))) - - def on_candle(self, candle: Candle) -> Signal | None: - self._closes.append(float(candle.close)) - - if len(self._closes) < self._period + 1: - return None - - series = pd.Series(list(self._closes)) - rsi = ta.rsi(series, length=self._period) - current_rsi = rsi.iloc[-1] - - if current_rsi < self._oversold: - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.BUY, - price=candle.close, - quantity=self._quantity, - reason=f"RSI={current_rsi:.1f} < {self._oversold}", - ) - elif current_rsi > self._overbought: - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.SELL, - price=candle.close, - quantity=self._quantity, - reason=f"RSI={current_rsi:.1f} > {self._overbought}", - ) - return None - - def reset(self) -> None: - self._closes.clear() -``` - -- [ ] **Step 6: Run tests to verify they pass** - -```bash -pytest services/strategy-engine/tests/test_rsi_strategy.py -v -``` - -Expected: All PASS - -- [ ] **Step 7: Write failing tests for grid strategy** - -Create `services/strategy-engine/tests/test_grid_strategy.py`: - -```python -from datetime import datetime, timezone -from decimal import Decimal - -from shared.models import Candle, OrderSide - - -def make_candle(close: float, idx: int = 0) -> Candle: - return Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2026, 1, 1, minute=idx, tzinfo=timezone.utc), - open=Decimal(str(close)), - high=Decimal(str(close + 10)), - low=Decimal(str(close - 10)), - close=Decimal(str(close)), - volume=Decimal("1.0"), - ) - - -def test_grid_strategy_buy_at_lower_grid(): - from strategy_engine.strategies.grid_strategy import GridStrategy - - strategy = GridStrategy() - strategy.configure({ - "lower_price": 48000, - "upper_price": 52000, - "grid_count": 5, - "quantity": 0.01, - }) - - # Price at grid level should trigger BUY - signal = strategy.on_candle(make_candle(48000)) - # First candle sets reference, no signal - signal = strategy.on_candle(make_candle(49000, idx=1)) - # Moving down through a grid level - signal = strategy.on_candle(make_candle(48000, idx=2)) - if signal is not None: - assert signal.side == OrderSide.BUY - - -def test_grid_strategy_sell_at_upper_grid(): - from strategy_engine.strategies.grid_strategy import GridStrategy - - strategy = GridStrategy() - strategy.configure({ - "lower_price": 48000, - "upper_price": 52000, - "grid_count": 5, - "quantity": 0.01, - }) - - signal = strategy.on_candle(make_candle(50000)) - signal = strategy.on_candle(make_candle(51000, idx=1)) - signal = strategy.on_candle(make_candle(52000, idx=2)) - if signal is not None: - assert signal.side == OrderSide.SELL - - -def test_grid_strategy_no_signal_in_same_zone(): - from strategy_engine.strategies.grid_strategy import GridStrategy - - strategy = GridStrategy() - strategy.configure({ - "lower_price": 48000, - "upper_price": 52000, - "grid_count": 5, - "quantity": 0.01, - }) - - strategy.on_candle(make_candle(50000)) - signal = strategy.on_candle(make_candle(50050, idx=1)) - assert signal is None # same grid zone, no signal -``` - -- [ ] **Step 8: Run tests to verify they fail** - -```bash -pytest services/strategy-engine/tests/test_grid_strategy.py -v -``` - -Expected: FAIL - -- [ ] **Step 9: Implement grid strategy** - -Create `services/strategy-engine/strategies/grid_strategy.py`: - -```python -from __future__ import annotations - -from decimal import Decimal - -from shared.models import Candle, Signal, OrderSide -from strategies.base import BaseStrategy - - -class GridStrategy(BaseStrategy): - name = "grid" - - def __init__(self): - self._lower: float = 0 - self._upper: float = 0 - self._grid_count: int = 5 - self._quantity: Decimal = Decimal("0.01") - self._grid_levels: list[float] = [] - self._last_zone: int | None = None - - def configure(self, params: dict) -> None: - self._lower = float(params["lower_price"]) - self._upper = float(params["upper_price"]) - self._grid_count = params.get("grid_count", 5) - self._quantity = Decimal(str(params.get("quantity", 0.01))) - step = (self._upper - self._lower) / self._grid_count - self._grid_levels = [self._lower + step * i for i in range(self._grid_count + 1)] - - def on_candle(self, candle: Candle) -> Signal | None: - price = float(candle.close) - current_zone = self._get_zone(price) - - if self._last_zone is None: - self._last_zone = current_zone - return None - - signal = None - if current_zone < self._last_zone: - signal = Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.BUY, - price=candle.close, - quantity=self._quantity, - reason=f"Price crossed grid down: zone {self._last_zone}->{current_zone}", - ) - elif current_zone > self._last_zone: - signal = Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.SELL, - price=candle.close, - quantity=self._quantity, - reason=f"Price crossed grid up: zone {self._last_zone}->{current_zone}", - ) - - self._last_zone = current_zone - return signal - - def _get_zone(self, price: float) -> int: - for i, level in enumerate(self._grid_levels): - if price < level: - return i - return len(self._grid_levels) - - def reset(self) -> None: - self._last_zone = None -``` - -- [ ] **Step 10: Run tests to verify they pass** - -```bash -pytest services/strategy-engine/tests/test_grid_strategy.py -v -``` - -Expected: All PASS - -- [ ] **Step 11: Write failing tests for plugin_loader** - -Create `services/strategy-engine/tests/test_plugin_loader.py`: - -```python -import pytest -from pathlib import Path - -from strategy_engine.plugin_loader import load_strategies - - -def test_load_strategies_finds_rsi_and_grid(): - strategies_dir = Path(__file__).parent.parent / "strategies" - loaded = load_strategies(strategies_dir) - - names = {s.name for s in loaded} - assert "rsi" in names - assert "grid" in names - - -def test_load_strategies_skips_base(): - strategies_dir = Path(__file__).parent.parent / "strategies" - loaded = load_strategies(strategies_dir) - - names = {s.name for s in loaded} - assert "base" not in names -``` - -- [ ] **Step 12: Run tests to verify they fail** - -```bash -pytest services/strategy-engine/tests/test_plugin_loader.py -v -``` - -Expected: FAIL - -- [ ] **Step 13: Implement plugin_loader** - -Create `services/strategy-engine/src/strategy_engine/plugin_loader.py`: - -```python -from __future__ import annotations - -import importlib.util -import logging -from pathlib import Path - -from strategies.base import BaseStrategy - -logger = logging.getLogger(__name__) - - -def load_strategies(strategies_dir: Path) -> list[BaseStrategy]: - loaded = [] - for path in strategies_dir.glob("*.py"): - if path.stem.startswith("_") or path.stem == "base": - continue - - spec = importlib.util.spec_from_file_location(path.stem, path) - module = importlib.util.module_from_spec(spec) - spec.loader.exec_module(module) - - for attr_name in dir(module): - attr = getattr(module, attr_name) - if ( - isinstance(attr, type) - and issubclass(attr, BaseStrategy) - and attr is not BaseStrategy - ): - instance = attr() - loaded.append(instance) - logger.info(f"Loaded strategy: {instance.name}") - - return loaded -``` - -- [ ] **Step 14: Run tests to verify they pass** - -```bash -pytest services/strategy-engine/tests/test_plugin_loader.py -v -``` - -Expected: All PASS - -- [ ] **Step 15: Write failing tests for engine** - -Create `services/strategy-engine/tests/test_engine.py`: - -```python -import pytest -from unittest.mock import AsyncMock, MagicMock -from datetime import datetime, timezone -from decimal import Decimal - -from shared.models import Candle, OrderSide -from shared.events import CandleEvent -from strategy_engine.engine import StrategyEngine - - -def make_candle_event() -> dict: - candle = Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2026, 1, 1, tzinfo=timezone.utc), - open=Decimal("50000"), - high=Decimal("50100"), - low=Decimal("49900"), - close=Decimal("50050"), - volume=Decimal("1.0"), - ) - return CandleEvent(data=candle).to_dict() - - -@pytest.mark.asyncio -async def test_engine_dispatches_candle_to_strategies(): - mock_strategy = MagicMock() - mock_strategy.name = "test" - mock_strategy.on_candle.return_value = None - - mock_broker = AsyncMock() - mock_broker.read = AsyncMock(return_value=[make_candle_event()]) - - engine = StrategyEngine(broker=mock_broker, strategies=[mock_strategy]) - await engine.process_once(stream="candles.BTCUSDT", last_id="0-0") - - mock_strategy.on_candle.assert_called_once() - - -@pytest.mark.asyncio -async def test_engine_publishes_signal_when_strategy_returns_one(): - from shared.models import Signal - - mock_signal = Signal( - strategy="test", - symbol="BTCUSDT", - side=OrderSide.BUY, - price=Decimal("50000"), - quantity=Decimal("0.01"), - reason="test reason", - ) - mock_strategy = MagicMock() - mock_strategy.name = "test" - mock_strategy.on_candle.return_value = mock_signal - - mock_broker = AsyncMock() - mock_broker.read = AsyncMock(return_value=[make_candle_event()]) - mock_broker.publish = AsyncMock() - - engine = StrategyEngine(broker=mock_broker, strategies=[mock_strategy]) - await engine.process_once(stream="candles.BTCUSDT", last_id="0-0") - - mock_broker.publish.assert_called_once() - call_args = mock_broker.publish.call_args - assert call_args[0][0] == "signals" -``` - -- [ ] **Step 16: Run tests to verify they fail** - -```bash -pytest services/strategy-engine/tests/test_engine.py -v -``` - -Expected: FAIL - -- [ ] **Step 17: Implement engine** - -Create `services/strategy-engine/src/strategy_engine/engine.py`: - -```python -from __future__ import annotations - -import logging - -from shared.broker import RedisBroker -from shared.events import Event, SignalEvent -from shared.models import Signal -from strategies.base import BaseStrategy - -logger = logging.getLogger(__name__) - - -class StrategyEngine: - def __init__(self, broker: RedisBroker, strategies: list[BaseStrategy]): - self._broker = broker - self._strategies = strategies - - async def process_once(self, stream: str, last_id: str) -> str: - messages = await self._broker.read(stream, last_id=last_id, count=10, block=1000) - - for msg in messages: - event = Event.from_dict(msg) - candle = event.data - - for strategy in self._strategies: - signal = strategy.on_candle(candle) - if signal is not None: - logger.info(f"Signal from {strategy.name}: {signal.side} {signal.symbol}") - await self._publish_signal(signal) - - return last_id - - async def _publish_signal(self, signal: Signal): - event = SignalEvent(data=signal) - await self._broker.publish("signals", event.to_dict()) -``` - -- [ ] **Step 18: Run tests to verify they pass** - -```bash -pytest services/strategy-engine/tests/test_engine.py -v -``` - -Expected: All PASS - -- [ ] **Step 19: Implement config and main** - -Create `services/strategy-engine/src/strategy_engine/config.py`: - -```python -from shared.config import Settings - - -class StrategyConfig(Settings): - symbols: list[str] = ["BTC/USDT"] - timeframes: list[str] = ["1m"] - strategy_params: dict = {} -``` - -Create `services/strategy-engine/src/strategy_engine/main.py`: - -```python -from __future__ import annotations - -import asyncio -import logging -from pathlib import Path - -from shared.broker import RedisBroker -from strategy_engine.config import StrategyConfig -from strategy_engine.engine import StrategyEngine -from strategy_engine.plugin_loader import load_strategies - -logger = logging.getLogger(__name__) - - -async def run(): - config = StrategyConfig() - logging.basicConfig(level=config.log_level) - - broker = RedisBroker(config.redis_url) - strategies_dir = Path(__file__).parent.parent.parent / "strategies" - strategies = load_strategies(strategies_dir) - - for s in strategies: - params = config.strategy_params.get(s.name, {}) - s.configure(params) - - engine = StrategyEngine(broker=broker, strategies=strategies) - symbols = [s.replace("/", "") for s in config.symbols] - - logger.info(f"Starting strategy engine: strategies={[s.name for s in strategies]}") - last_ids = {sym: "0-0" for sym in symbols} - try: - while True: - for sym in symbols: - stream = f"candles.{sym}" - last_ids[sym] = await engine.process_once(stream, last_ids[sym]) - finally: - await broker.close() - - -def main(): - asyncio.run(run()) - - -if __name__ == "__main__": - main() -``` - -- [ ] **Step 20: Create Dockerfile** - -Create `services/strategy-engine/Dockerfile`: - -```dockerfile -FROM python:3.12-slim - -WORKDIR /app - -COPY shared/ shared/ -RUN pip install --no-cache-dir ./shared - -COPY services/strategy-engine/ services/strategy-engine/ -RUN pip install --no-cache-dir ./services/strategy-engine - -CMD ["python", "-m", "strategy_engine.main"] -``` - -- [ ] **Step 21: Commit** - -```bash -git add services/strategy-engine/ -git commit -m "feat(strategy-engine): add plugin-based strategy engine with RSI and grid strategies" -``` - ---- - -## Task 7: Order Executor Service - -**Files:** -- Create: `services/order-executor/pyproject.toml` -- Create: `services/order-executor/Dockerfile` -- Create: `services/order-executor/src/order_executor/__init__.py` -- Create: `services/order-executor/src/order_executor/config.py` -- Create: `services/order-executor/src/order_executor/risk_manager.py` -- Create: `services/order-executor/src/order_executor/executor.py` -- Create: `services/order-executor/src/order_executor/main.py` -- Create: `services/order-executor/tests/test_risk_manager.py` -- Create: `services/order-executor/tests/test_executor.py` - -- [ ] **Step 1: Create pyproject.toml** - -Create `services/order-executor/pyproject.toml`: - -```toml -[project] -name = "order-executor" -version = "0.1.0" -description = "Order execution service with risk management" -requires-python = ">=3.12" -dependencies = [ - "ccxt>=4.0", - "trading-shared", -] - -[project.optional-dependencies] -dev = [ - "pytest>=8.0", - "pytest-asyncio>=0.23", -] - -[build-system] -requires = ["hatchling"] -build-backend = "hatchling.build" - -[tool.hatch.build.targets.wheel] -packages = ["src/order_executor"] -``` - -- [ ] **Step 2: Write failing tests for risk_manager** - -Create `services/order-executor/tests/test_risk_manager.py`: - -```python -import pytest -from decimal import Decimal - -from shared.models import Signal, OrderSide -from order_executor.risk_manager import RiskManager, RiskCheckResult - - -@pytest.fixture -def risk_manager(): - return RiskManager( - max_position_size=Decimal("0.1"), - stop_loss_pct=Decimal("5"), - daily_loss_limit_pct=Decimal("10"), - ) - - -def make_signal(side=OrderSide.BUY, quantity="0.01", price="50000") -> Signal: - return Signal( - strategy="test", - symbol="BTCUSDT", - side=side, - price=Decimal(price), - quantity=Decimal(quantity), - reason="test", - ) - - -def test_risk_check_passes_normal_order(risk_manager): - signal = make_signal() - balance = Decimal("10000") - positions = {} - daily_pnl = Decimal("0") - - result = risk_manager.check(signal, balance, positions, daily_pnl) - assert result.allowed is True - - -def test_risk_check_rejects_exceeding_position_size(risk_manager): - signal = make_signal(quantity="5") # 5 BTC * 50000 = 250000 > 10% of balance - balance = Decimal("10000") - positions = {} - daily_pnl = Decimal("0") - - result = risk_manager.check(signal, balance, positions, daily_pnl) - assert result.allowed is False - assert "position size" in result.reason.lower() - - -def test_risk_check_rejects_daily_loss_exceeded(risk_manager): - signal = make_signal() - balance = Decimal("10000") - positions = {} - daily_pnl = Decimal("-1100") # -11% > -10% limit - - result = risk_manager.check(signal, balance, positions, daily_pnl) - assert result.allowed is False - assert "daily loss" in result.reason.lower() - - -def test_risk_check_rejects_insufficient_balance(risk_manager): - signal = make_signal(quantity="0.01", price="50000") # cost = 500 - balance = Decimal("100") # not enough - positions = {} - daily_pnl = Decimal("0") - - result = risk_manager.check(signal, balance, positions, daily_pnl) - assert result.allowed is False - assert "balance" in result.reason.lower() -``` - -- [ ] **Step 3: Run tests to verify they fail** - -```bash -pip install -e services/order-executor[dev] -pytest services/order-executor/tests/test_risk_manager.py -v -``` - -Expected: FAIL - -- [ ] **Step 4: Implement risk_manager** - -Create `services/order-executor/src/order_executor/__init__.py`: - -```python -``` - -Create `services/order-executor/src/order_executor/risk_manager.py`: - -```python -from __future__ import annotations - -from dataclasses import dataclass -from decimal import Decimal - -from shared.models import Signal, OrderSide - - -@dataclass -class RiskCheckResult: - allowed: bool - reason: str = "" - - -class RiskManager: - def __init__( - self, - max_position_size: Decimal, - stop_loss_pct: Decimal, - daily_loss_limit_pct: Decimal, - ): - self._max_position_size = max_position_size - self._stop_loss_pct = stop_loss_pct - self._daily_loss_limit_pct = daily_loss_limit_pct - - def check( - self, - signal: Signal, - balance: Decimal, - positions: dict[str, Decimal], - daily_pnl: Decimal, - ) -> RiskCheckResult: - # Check daily loss limit - daily_loss_pct = (daily_pnl / balance) * 100 if balance > 0 else Decimal("0") - if daily_loss_pct < -self._daily_loss_limit_pct: - return RiskCheckResult( - allowed=False, - reason=f"Daily loss limit exceeded: {daily_loss_pct:.1f}%", - ) - - if signal.side == OrderSide.BUY: - order_cost = signal.price * signal.quantity - - # Check sufficient balance - if order_cost > balance: - return RiskCheckResult( - allowed=False, - reason=f"Insufficient balance: need {order_cost}, have {balance}", - ) - - # Check max position size - current_position_value = positions.get(signal.symbol, Decimal("0")) * signal.price - new_position_value = current_position_value + order_cost - position_ratio = new_position_value / balance if balance > 0 else Decimal("999") - if position_ratio > self._max_position_size: - return RiskCheckResult( - allowed=False, - reason=f"Position size exceeded: {position_ratio:.2f} > {self._max_position_size}", - ) - - return RiskCheckResult(allowed=True) -``` - -- [ ] **Step 5: Run tests to verify they pass** - -```bash -pytest services/order-executor/tests/test_risk_manager.py -v -``` - -Expected: All PASS - -- [ ] **Step 6: Write failing tests for executor** - -Create `services/order-executor/tests/test_executor.py`: - -```python -import pytest -from unittest.mock import AsyncMock, MagicMock -from decimal import Decimal - -from shared.models import Signal, OrderSide, OrderStatus -from order_executor.executor import OrderExecutor -from order_executor.risk_manager import RiskCheckResult - - -def make_signal() -> Signal: - return Signal( - strategy="test", - symbol="BTCUSDT", - side=OrderSide.BUY, - price=Decimal("50000"), - quantity=Decimal("0.01"), - reason="test", - ) - - -@pytest.mark.asyncio -async def test_executor_places_order_when_risk_passes(): - mock_exchange = MagicMock() - mock_exchange.create_order = AsyncMock(return_value={ - "id": "binance_123", - "status": "closed", - "filled": 0.01, - "price": 50000, - }) - mock_exchange.fetch_balance = AsyncMock(return_value={ - "USDT": {"free": 10000}, - }) - - mock_risk = MagicMock() - mock_risk.check.return_value = RiskCheckResult(allowed=True) - - mock_broker = AsyncMock() - mock_db = AsyncMock() - - executor = OrderExecutor( - exchange=mock_exchange, - risk_manager=mock_risk, - broker=mock_broker, - db=mock_db, - dry_run=False, - ) - - signal = make_signal() - order = await executor.execute(signal) - - assert order is not None - assert order.status == OrderStatus.FILLED - mock_exchange.create_order.assert_called_once() - - -@pytest.mark.asyncio -async def test_executor_rejects_when_risk_fails(): - mock_exchange = MagicMock() - mock_exchange.fetch_balance = AsyncMock(return_value={ - "USDT": {"free": 10000}, - }) - - mock_risk = MagicMock() - mock_risk.check.return_value = RiskCheckResult(allowed=False, reason="too risky") - - mock_broker = AsyncMock() - mock_db = AsyncMock() - - executor = OrderExecutor( - exchange=mock_exchange, - risk_manager=mock_risk, - broker=mock_broker, - db=mock_db, - dry_run=False, - ) - - signal = make_signal() - order = await executor.execute(signal) - assert order is None - mock_exchange.create_order.assert_not_called() - - -@pytest.mark.asyncio -async def test_executor_dry_run_does_not_call_exchange(): - mock_exchange = MagicMock() - mock_exchange.fetch_balance = AsyncMock(return_value={ - "USDT": {"free": 10000}, - }) - - mock_risk = MagicMock() - mock_risk.check.return_value = RiskCheckResult(allowed=True) - - mock_broker = AsyncMock() - mock_db = AsyncMock() - - executor = OrderExecutor( - exchange=mock_exchange, - risk_manager=mock_risk, - broker=mock_broker, - db=mock_db, - dry_run=True, - ) - - signal = make_signal() - order = await executor.execute(signal) - - assert order is not None - assert order.status == OrderStatus.FILLED - mock_exchange.create_order.assert_not_called() -``` - -- [ ] **Step 7: Run tests to verify they fail** - -```bash -pytest services/order-executor/tests/test_executor.py -v -``` - -Expected: FAIL - -- [ ] **Step 8: Implement executor** - -Create `services/order-executor/src/order_executor/executor.py`: - -```python -from __future__ import annotations - -import logging -from datetime import datetime, timezone -from decimal import Decimal - -from shared.broker import RedisBroker -from shared.db import Database -from shared.events import OrderEvent -from shared.models import Order, OrderSide, OrderStatus, OrderType, Signal -from order_executor.risk_manager import RiskManager - -logger = logging.getLogger(__name__) - - -class OrderExecutor: - def __init__( - self, - exchange, - risk_manager: RiskManager, - broker: RedisBroker, - db: Database, - dry_run: bool = True, - ): - self._exchange = exchange - self._risk = risk_manager - self._broker = broker - self._db = db - self._dry_run = dry_run - - async def execute(self, signal: Signal) -> Order | None: - balance_info = await self._exchange.fetch_balance() - balance = Decimal(str(balance_info.get("USDT", {}).get("free", 0))) - positions: dict[str, Decimal] = {} - daily_pnl = Decimal("0") - - result = self._risk.check(signal, balance, positions, daily_pnl) - if not result.allowed: - logger.warning(f"Risk check failed: {result.reason}") - return None - - order = Order( - signal_id=signal.id, - symbol=signal.symbol, - side=signal.side, - type=OrderType.MARKET, - price=signal.price, - quantity=signal.quantity, - ) - - if self._dry_run: - logger.info(f"[DRY RUN] Would execute: {order.side} {order.quantity} {order.symbol}") - order.status = OrderStatus.FILLED - order.filled_at = datetime.now(timezone.utc) - else: - try: - result = await self._exchange.create_order( - symbol=signal.symbol.replace("USDT", "/USDT"), - type="market", - side=signal.side.value.lower(), - amount=float(signal.quantity), - ) - order.status = OrderStatus.FILLED - order.filled_at = datetime.now(timezone.utc) - logger.info(f"Order filled: {order.id}") - except Exception as e: - order.status = OrderStatus.FAILED - logger.error(f"Order failed: {e}") - - await self._db.insert_order(order) - event = OrderEvent(data=order) - await self._broker.publish("orders", event.to_dict()) - - return order -``` - -- [ ] **Step 9: Run tests to verify they pass** - -```bash -pytest services/order-executor/tests/test_executor.py -v -``` - -Expected: All PASS - -- [ ] **Step 10: Implement config and main** - -Create `services/order-executor/src/order_executor/config.py`: - -```python -from shared.config import Settings - - -class ExecutorConfig(Settings): - pass -``` - -Create `services/order-executor/src/order_executor/main.py`: - -```python -from __future__ import annotations - -import asyncio -import logging - -import ccxt.async_support as ccxt - -from shared.broker import RedisBroker -from shared.db import Database -from shared.events import Event -from order_executor.config import ExecutorConfig -from order_executor.executor import OrderExecutor -from order_executor.risk_manager import RiskManager - -logger = logging.getLogger(__name__) - - -async def run(): - config = ExecutorConfig() - logging.basicConfig(level=config.log_level) - - db = Database(config.database_url) - await db.connect() - - broker = RedisBroker(config.redis_url) - - exchange = ccxt.binance({ - "apiKey": config.binance_api_key, - "secret": config.binance_api_secret, - }) - - risk_manager = RiskManager( - max_position_size=config.risk_max_position_size, - stop_loss_pct=config.risk_stop_loss_pct, - daily_loss_limit_pct=config.risk_daily_loss_limit_pct, - ) - - executor = OrderExecutor( - exchange=exchange, - risk_manager=risk_manager, - broker=broker, - db=db, - dry_run=config.dry_run, - ) - - logger.info(f"Starting order executor (dry_run={config.dry_run})") - last_id = "0-0" - try: - while True: - messages = await broker.read("signals", last_id=last_id, count=10, block=1000) - for msg in messages: - event = Event.from_dict(msg) - await executor.execute(event.data) - finally: - await exchange.close() - await broker.close() - await db.close() - - -def main(): - asyncio.run(run()) - - -if __name__ == "__main__": - main() -``` - -- [ ] **Step 11: Create Dockerfile** - -Create `services/order-executor/Dockerfile`: - -```dockerfile -FROM python:3.12-slim - -WORKDIR /app - -COPY shared/ shared/ -RUN pip install --no-cache-dir ./shared - -COPY services/order-executor/ services/order-executor/ -RUN pip install --no-cache-dir ./services/order-executor - -CMD ["python", "-m", "order_executor.main"] -``` - -- [ ] **Step 12: Commit** - -```bash -git add services/order-executor/ -git commit -m "feat(order-executor): add order execution with risk management and dry-run mode" -``` - ---- - -## Task 8: Portfolio Manager Service - -**Files:** -- Create: `services/portfolio-manager/pyproject.toml` -- Create: `services/portfolio-manager/Dockerfile` -- Create: `services/portfolio-manager/src/portfolio_manager/__init__.py` -- Create: `services/portfolio-manager/src/portfolio_manager/config.py` -- Create: `services/portfolio-manager/src/portfolio_manager/portfolio.py` -- Create: `services/portfolio-manager/src/portfolio_manager/pnl.py` -- Create: `services/portfolio-manager/src/portfolio_manager/main.py` -- Create: `services/portfolio-manager/tests/test_portfolio.py` -- Create: `services/portfolio-manager/tests/test_pnl.py` - -- [ ] **Step 1: Create pyproject.toml** - -Create `services/portfolio-manager/pyproject.toml`: - -```toml -[project] -name = "portfolio-manager" -version = "0.1.0" -description = "Portfolio tracking and PnL calculation service" -requires-python = ">=3.12" -dependencies = [ - "trading-shared", -] - -[project.optional-dependencies] -dev = [ - "pytest>=8.0", - "pytest-asyncio>=0.23", -] - -[build-system] -requires = ["hatchling"] -build-backend = "hatchling.build" - -[tool.hatch.build.targets.wheel] -packages = ["src/portfolio_manager"] -``` - -- [ ] **Step 2: Write failing tests for pnl** - -Create `services/portfolio-manager/tests/test_pnl.py`: - -```python -from decimal import Decimal - -from portfolio_manager.pnl import calculate_unrealized_pnl, calculate_realized_pnl - - -def test_unrealized_pnl_profit(): - result = calculate_unrealized_pnl( - quantity=Decimal("0.1"), - avg_entry_price=Decimal("50000"), - current_price=Decimal("55000"), - ) - assert result == Decimal("500") # 0.1 * (55000 - 50000) - - -def test_unrealized_pnl_loss(): - result = calculate_unrealized_pnl( - quantity=Decimal("0.1"), - avg_entry_price=Decimal("50000"), - current_price=Decimal("45000"), - ) - assert result == Decimal("-500") - - -def test_realized_pnl_single_trade(): - result = calculate_realized_pnl( - buy_price=Decimal("50000"), - sell_price=Decimal("55000"), - quantity=Decimal("0.1"), - fee=Decimal("5.5"), - ) - assert result == Decimal("494.5") # 0.1 * (55000 - 50000) - 5.5 -``` - -- [ ] **Step 3: Run tests to verify they fail** - -```bash -pip install -e services/portfolio-manager[dev] -pytest services/portfolio-manager/tests/test_pnl.py -v -``` - -Expected: FAIL - -- [ ] **Step 4: Implement pnl** - -Create `services/portfolio-manager/src/portfolio_manager/__init__.py`: - -```python -``` - -Create `services/portfolio-manager/src/portfolio_manager/pnl.py`: - -```python -from decimal import Decimal - - -def calculate_unrealized_pnl( - quantity: Decimal, - avg_entry_price: Decimal, - current_price: Decimal, -) -> Decimal: - return quantity * (current_price - avg_entry_price) - - -def calculate_realized_pnl( - buy_price: Decimal, - sell_price: Decimal, - quantity: Decimal, - fee: Decimal = Decimal("0"), -) -> Decimal: - return quantity * (sell_price - buy_price) - fee -``` - -- [ ] **Step 5: Run tests to verify they pass** - -```bash -pytest services/portfolio-manager/tests/test_pnl.py -v -``` - -Expected: All PASS - -- [ ] **Step 6: Write failing tests for portfolio** - -Create `services/portfolio-manager/tests/test_portfolio.py`: - -```python -import pytest -from decimal import Decimal - -from shared.models import Order, OrderSide, OrderType, OrderStatus -from portfolio_manager.portfolio import PortfolioTracker - - -@pytest.fixture -def tracker(): - return PortfolioTracker() - - -def make_order(side=OrderSide.BUY, price="50000", quantity="0.1") -> Order: - return Order( - signal_id="sig_1", - symbol="BTCUSDT", - side=side, - type=OrderType.MARKET, - price=Decimal(price), - quantity=Decimal(quantity), - status=OrderStatus.FILLED, - ) - - -def test_portfolio_add_buy_order(tracker): - order = make_order(side=OrderSide.BUY) - tracker.apply_order(order) - - pos = tracker.get_position("BTCUSDT") - assert pos.quantity == Decimal("0.1") - assert pos.avg_entry_price == Decimal("50000") - - -def test_portfolio_add_multiple_buys(tracker): - tracker.apply_order(make_order(price="50000", quantity="0.1")) - tracker.apply_order(make_order(price="52000", quantity="0.1")) - - pos = tracker.get_position("BTCUSDT") - assert pos.quantity == Decimal("0.2") - assert pos.avg_entry_price == Decimal("51000") # weighted avg - - -def test_portfolio_sell_reduces_position(tracker): - tracker.apply_order(make_order(side=OrderSide.BUY, price="50000", quantity="0.2")) - tracker.apply_order(make_order(side=OrderSide.SELL, price="55000", quantity="0.1")) - - pos = tracker.get_position("BTCUSDT") - assert pos.quantity == Decimal("0.1") - assert pos.avg_entry_price == Decimal("50000") # entry price unchanged - - -def test_portfolio_no_position_returns_none(tracker): - pos = tracker.get_position("ETHUSDT") - assert pos is None -``` - -- [ ] **Step 7: Run tests to verify they fail** - -```bash -pytest services/portfolio-manager/tests/test_portfolio.py -v -``` - -Expected: FAIL - -- [ ] **Step 8: Implement portfolio** - -Create `services/portfolio-manager/src/portfolio_manager/portfolio.py`: - -```python -from __future__ import annotations - -from decimal import Decimal - -from shared.models import Order, OrderSide, Position - - -class PortfolioTracker: - def __init__(self): - self._positions: dict[str, _PositionState] = {} - - def apply_order(self, order: Order) -> None: - if order.symbol not in self._positions: - self._positions[order.symbol] = _PositionState() - - state = self._positions[order.symbol] - if order.side == OrderSide.BUY: - total_cost = state.avg_entry * state.quantity + order.price * order.quantity - state.quantity += order.quantity - state.avg_entry = total_cost / state.quantity if state.quantity > 0 else Decimal("0") - elif order.side == OrderSide.SELL: - state.quantity -= order.quantity - if state.quantity <= 0: - state.quantity = Decimal("0") - state.avg_entry = Decimal("0") - - def get_position(self, symbol: str) -> Position | None: - state = self._positions.get(symbol) - if state is None or state.quantity == 0: - return None - return Position( - symbol=symbol, - quantity=state.quantity, - avg_entry_price=state.avg_entry, - current_price=Decimal("0"), - ) - - def get_all_positions(self) -> list[Position]: - positions = [] - for symbol in self._positions: - pos = self.get_position(symbol) - if pos is not None: - positions.append(pos) - return positions - - -class _PositionState: - def __init__(self): - self.quantity = Decimal("0") - self.avg_entry = Decimal("0") -``` - -- [ ] **Step 9: Run tests to verify they pass** - -```bash -pytest services/portfolio-manager/tests/test_portfolio.py -v -``` - -Expected: All PASS - -- [ ] **Step 10: Implement config and main** - -Create `services/portfolio-manager/src/portfolio_manager/config.py`: - -```python -from shared.config import Settings - - -class PortfolioConfig(Settings): - snapshot_interval_hours: int = 24 -``` - -Create `services/portfolio-manager/src/portfolio_manager/main.py`: - -```python -from __future__ import annotations - -import asyncio -import logging - -from shared.broker import RedisBroker -from shared.db import Database -from shared.events import Event -from portfolio_manager.config import PortfolioConfig -from portfolio_manager.portfolio import PortfolioTracker - -logger = logging.getLogger(__name__) - - -async def run(): - config = PortfolioConfig() - logging.basicConfig(level=config.log_level) - - db = Database(config.database_url) - await db.connect() - - broker = RedisBroker(config.redis_url) - tracker = PortfolioTracker() - - logger.info("Starting portfolio manager") - last_id = "0-0" - try: - while True: - messages = await broker.read("orders", last_id=last_id, count=10, block=1000) - for msg in messages: - event = Event.from_dict(msg) - order = event.data - tracker.apply_order(order) - logger.info(f"Position updated: {order.symbol}") - finally: - await broker.close() - await db.close() - - -def main(): - asyncio.run(run()) - - -if __name__ == "__main__": - main() -``` - -- [ ] **Step 11: Create Dockerfile** - -Create `services/portfolio-manager/Dockerfile`: - -```dockerfile -FROM python:3.12-slim - -WORKDIR /app - -COPY shared/ shared/ -RUN pip install --no-cache-dir ./shared - -COPY services/portfolio-manager/ services/portfolio-manager/ -RUN pip install --no-cache-dir ./services/portfolio-manager - -CMD ["python", "-m", "portfolio_manager.main"] -``` - -- [ ] **Step 12: Commit** - -```bash -git add services/portfolio-manager/ -git commit -m "feat(portfolio-manager): add portfolio tracking and PnL calculation" -``` - ---- - -## Task 9: Backtester Service - -**Files:** -- Create: `services/backtester/pyproject.toml` -- Create: `services/backtester/Dockerfile` -- Create: `services/backtester/src/backtester/__init__.py` -- Create: `services/backtester/src/backtester/config.py` -- Create: `services/backtester/src/backtester/simulator.py` -- Create: `services/backtester/src/backtester/engine.py` -- Create: `services/backtester/src/backtester/reporter.py` -- Create: `services/backtester/src/backtester/main.py` -- Create: `services/backtester/tests/test_simulator.py` -- Create: `services/backtester/tests/test_engine.py` -- Create: `services/backtester/tests/test_reporter.py` - -- [ ] **Step 1: Create pyproject.toml** - -Create `services/backtester/pyproject.toml`: - -```toml -[project] -name = "backtester" -version = "0.1.0" -description = "Strategy backtesting engine" -requires-python = ">=3.12" -dependencies = [ - "pandas>=2.0", - "trading-shared", -] - -[project.optional-dependencies] -dev = [ - "pytest>=8.0", - "pytest-asyncio>=0.23", -] - -[build-system] -requires = ["hatchling"] -build-backend = "hatchling.build" - -[tool.hatch.build.targets.wheel] -packages = ["src/backtester"] -``` - -- [ ] **Step 2: Write failing tests for simulator** - -Create `services/backtester/tests/test_simulator.py`: - -```python -from decimal import Decimal - -from shared.models import Signal, OrderSide -from backtester.simulator import OrderSimulator - - -def make_signal(side=OrderSide.BUY, price="50000", quantity="0.1") -> Signal: - return Signal( - strategy="test", - symbol="BTCUSDT", - side=side, - price=Decimal(price), - quantity=Decimal(quantity), - reason="test", - ) - - -def test_simulator_initial_balance(): - sim = OrderSimulator(initial_balance=Decimal("10000")) - assert sim.balance == Decimal("10000") - - -def test_simulator_buy_reduces_balance(): - sim = OrderSimulator(initial_balance=Decimal("10000")) - sim.execute(make_signal(side=OrderSide.BUY, price="50000", quantity="0.1")) - - assert sim.balance == Decimal("5000") # 10000 - 0.1*50000 - assert sim.positions["BTCUSDT"] == Decimal("0.1") - - -def test_simulator_sell_increases_balance(): - sim = OrderSimulator(initial_balance=Decimal("10000")) - sim.execute(make_signal(side=OrderSide.BUY, price="50000", quantity="0.1")) - sim.execute(make_signal(side=OrderSide.SELL, price="55000", quantity="0.1")) - - assert sim.balance == Decimal("10500") # 5000 + 0.1*55000 - assert sim.positions.get("BTCUSDT", Decimal("0")) == Decimal("0") - - -def test_simulator_reject_buy_insufficient_balance(): - sim = OrderSimulator(initial_balance=Decimal("100")) - result = sim.execute(make_signal(side=OrderSide.BUY, price="50000", quantity="0.1")) - assert result is False - assert sim.balance == Decimal("100") - - -def test_simulator_trade_history(): - sim = OrderSimulator(initial_balance=Decimal("10000")) - sim.execute(make_signal(side=OrderSide.BUY)) - assert len(sim.trades) == 1 -``` - -- [ ] **Step 3: Run tests to verify they fail** - -```bash -pip install -e services/backtester[dev] -pytest services/backtester/tests/test_simulator.py -v -``` - -Expected: FAIL - -- [ ] **Step 4: Implement simulator** - -Create `services/backtester/src/backtester/__init__.py`: - -```python -``` - -Create `services/backtester/src/backtester/simulator.py`: - -```python -from __future__ import annotations - -from dataclasses import dataclass, field -from decimal import Decimal - -from shared.models import Signal, OrderSide - - -@dataclass -class SimulatedTrade: - symbol: str - side: OrderSide - price: Decimal - quantity: Decimal - balance_after: Decimal - - -class OrderSimulator: - def __init__(self, initial_balance: Decimal): - self.balance = initial_balance - self.positions: dict[str, Decimal] = {} - self.trades: list[SimulatedTrade] = [] - - def execute(self, signal: Signal) -> bool: - if signal.side == OrderSide.BUY: - cost = signal.price * signal.quantity - if cost > self.balance: - return False - self.balance -= cost - current = self.positions.get(signal.symbol, Decimal("0")) - self.positions[signal.symbol] = current + signal.quantity - elif signal.side == OrderSide.SELL: - current = self.positions.get(signal.symbol, Decimal("0")) - sell_qty = min(signal.quantity, current) - if sell_qty <= 0: - return False - self.balance += signal.price * sell_qty - self.positions[signal.symbol] = current - sell_qty - - self.trades.append( - SimulatedTrade( - symbol=signal.symbol, - side=signal.side, - price=signal.price, - quantity=signal.quantity, - balance_after=self.balance, - ) - ) - return True -``` - -- [ ] **Step 5: Run tests to verify they pass** - -```bash -pytest services/backtester/tests/test_simulator.py -v -``` - -Expected: All PASS - -- [ ] **Step 6: Write failing tests for backtest engine** - -Create `services/backtester/tests/test_engine.py`: - -```python -import pytest -from decimal import Decimal -from datetime import datetime, timezone -from unittest.mock import MagicMock - -from shared.models import Candle, Signal, OrderSide -from backtester.engine import BacktestEngine - - -def make_candles(prices: list[float]) -> list[Candle]: - return [ - Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2026, 1, 1, minute=i, tzinfo=timezone.utc), - open=Decimal(str(p)), - high=Decimal(str(p + 10)), - low=Decimal(str(p - 10)), - close=Decimal(str(p)), - volume=Decimal("1.0"), - ) - for i, p in enumerate(prices) - ] - - -def test_backtest_engine_runs_strategy_over_candles(): - mock_strategy = MagicMock() - mock_strategy.name = "test" - mock_strategy.on_candle.return_value = None - - candles = make_candles([50000, 50100, 50200]) - - engine = BacktestEngine( - strategy=mock_strategy, - initial_balance=Decimal("10000"), - ) - result = engine.run(candles) - - assert mock_strategy.on_candle.call_count == 3 - assert result.total_trades == 0 - assert result.final_balance == Decimal("10000") - - -def test_backtest_engine_executes_signals(): - buy_signal = Signal( - strategy="test", - symbol="BTCUSDT", - side=OrderSide.BUY, - price=Decimal("50000"), - quantity=Decimal("0.1"), - reason="test buy", - ) - sell_signal = Signal( - strategy="test", - symbol="BTCUSDT", - side=OrderSide.SELL, - price=Decimal("55000"), - quantity=Decimal("0.1"), - reason="test sell", - ) - - mock_strategy = MagicMock() - mock_strategy.name = "test" - mock_strategy.on_candle.side_effect = [buy_signal, None, sell_signal] - - candles = make_candles([50000, 52000, 55000]) - - engine = BacktestEngine( - strategy=mock_strategy, - initial_balance=Decimal("10000"), - ) - result = engine.run(candles) - - assert result.total_trades == 2 - assert result.final_balance == Decimal("10500") # 10000 - 5000 + 5500 -``` - -- [ ] **Step 7: Run tests to verify they fail** - -```bash -pytest services/backtester/tests/test_engine.py -v -``` - -Expected: FAIL - -- [ ] **Step 8: Implement backtest engine** - -Create `services/backtester/src/backtester/engine.py`: - -```python -from __future__ import annotations - -from dataclasses import dataclass -from decimal import Decimal - -from shared.models import Candle -from backtester.simulator import OrderSimulator -from strategies.base import BaseStrategy - - -@dataclass -class BacktestResult: - strategy_name: str - symbol: str - total_trades: int - initial_balance: Decimal - final_balance: Decimal - profit: Decimal - profit_pct: Decimal - trades: list - - @property - def win_rate(self) -> Decimal: - if self.total_trades == 0: - return Decimal("0") - wins = sum( - 1 - for i in range(0, len(self.trades) - 1, 2) - if i + 1 < len(self.trades) - and self.trades[i + 1].balance_after > self.trades[i].balance_after - ) - pairs = self.total_trades // 2 - return Decimal(str(wins / pairs * 100)) if pairs > 0 else Decimal("0") - - -class BacktestEngine: - def __init__(self, strategy: BaseStrategy, initial_balance: Decimal): - self._strategy = strategy - self._initial_balance = initial_balance - - def run(self, candles: list[Candle]) -> BacktestResult: - simulator = OrderSimulator(self._initial_balance) - symbol = candles[0].symbol if candles else "" - - for candle in candles: - signal = self._strategy.on_candle(candle) - if signal is not None: - simulator.execute(signal) - - final = simulator.balance - # Add value of remaining positions at last candle price - if candles: - last_price = candles[-1].close - for sym, qty in simulator.positions.items(): - final += qty * last_price - - profit = final - self._initial_balance - profit_pct = (profit / self._initial_balance) * 100 if self._initial_balance > 0 else Decimal("0") - - return BacktestResult( - strategy_name=self._strategy.name, - symbol=symbol, - total_trades=len(simulator.trades), - initial_balance=self._initial_balance, - final_balance=final, - profit=profit, - profit_pct=profit_pct, - trades=simulator.trades, - ) -``` - -- [ ] **Step 9: Run tests to verify they pass** - -```bash -pytest services/backtester/tests/test_engine.py -v -``` - -Expected: All PASS - -- [ ] **Step 10: Write failing tests for reporter** - -Create `services/backtester/tests/test_reporter.py`: - -```python -from decimal import Decimal - -from backtester.engine import BacktestResult -from backtester.reporter import format_report - - -def test_format_report_contains_key_metrics(): - result = BacktestResult( - strategy_name="rsi", - symbol="BTCUSDT", - total_trades=10, - initial_balance=Decimal("10000"), - final_balance=Decimal("11500"), - profit=Decimal("1500"), - profit_pct=Decimal("15"), - trades=[], - ) - - report = format_report(result) - - assert "rsi" in report - assert "BTCUSDT" in report - assert "10000" in report - assert "11500" in report - assert "1500" in report - assert "15" in report -``` - -- [ ] **Step 11: Run test to verify it fails** - -```bash -pytest services/backtester/tests/test_reporter.py -v -``` - -Expected: FAIL - -- [ ] **Step 12: Implement reporter** - -Create `services/backtester/src/backtester/reporter.py`: - -```python -from backtester.engine import BacktestResult - - -def format_report(result: BacktestResult) -> str: - lines = [ - "=" * 50, - f" Backtest Report: {result.strategy_name}", - "=" * 50, - f" Symbol: {result.symbol}", - f" Total Trades: {result.total_trades}", - f" Initial Balance: {result.initial_balance}", - f" Final Balance: {result.final_balance}", - f" Profit: {result.profit}", - f" Profit %: {result.profit_pct:.2f}%", - f" Win Rate: {result.win_rate:.1f}%", - "=" * 50, - ] - return "\n".join(lines) -``` - -- [ ] **Step 13: Run test to verify it passes** - -```bash -pytest services/backtester/tests/test_reporter.py -v -``` - -Expected: PASS - -- [ ] **Step 14: Implement config and main** - -Create `services/backtester/src/backtester/config.py`: - -```python -from shared.config import Settings - - -class BacktestConfig(Settings): - backtest_initial_balance: float = 10000.0 -``` - -Create `services/backtester/src/backtester/main.py`: - -```python -from __future__ import annotations - -import asyncio -import logging -from decimal import Decimal -from pathlib import Path - -from shared.db import Database -from backtester.config import BacktestConfig -from backtester.engine import BacktestEngine -from backtester.reporter import format_report - -logger = logging.getLogger(__name__) - - -async def run_backtest( - strategy_name: str, - symbol: str, - timeframe: str, - initial_balance: Decimal, - db: Database, - strategies_dir: Path, -) -> str: - from strategy_engine.plugin_loader import load_strategies - - strategies = load_strategies(strategies_dir) - strategy = next((s for s in strategies if s.name == strategy_name), None) - if strategy is None: - return f"Strategy '{strategy_name}' not found" - - candles_data = await db.get_candles(symbol, timeframe) - if not candles_data: - return f"No candle data for {symbol} {timeframe}" - - from shared.models import Candle - - candles = [Candle(**row) for row in reversed(candles_data)] - - engine = BacktestEngine(strategy=strategy, initial_balance=initial_balance) - result = engine.run(candles) - return format_report(result) -``` - -- [ ] **Step 15: Create Dockerfile** - -Create `services/backtester/Dockerfile`: - -```dockerfile -FROM python:3.12-slim - -WORKDIR /app - -COPY shared/ shared/ -RUN pip install --no-cache-dir ./shared - -COPY services/strategy-engine/strategies/ services/strategy-engine/strategies/ -COPY services/backtester/ services/backtester/ -RUN pip install --no-cache-dir ./services/backtester - -CMD ["python", "-m", "backtester.main"] -``` - -- [ ] **Step 16: Commit** - -```bash -git add services/backtester/ -git commit -m "feat(backtester): add backtesting engine with simulator and reporting" -``` - ---- - -## Task 10: CLI - -**Files:** -- Create: `cli/pyproject.toml` -- Create: `cli/src/trading_cli/__init__.py` -- Create: `cli/src/trading_cli/main.py` -- Create: `cli/src/trading_cli/commands/data.py` -- Create: `cli/src/trading_cli/commands/trade.py` -- Create: `cli/src/trading_cli/commands/backtest.py` -- Create: `cli/src/trading_cli/commands/portfolio.py` -- Create: `cli/src/trading_cli/commands/strategy.py` -- Create: `cli/src/trading_cli/commands/service.py` -- Create: `cli/tests/test_cli_data.py` - -- [ ] **Step 1: Create pyproject.toml** - -Create `cli/pyproject.toml`: - -```toml -[project] -name = "trading-cli" -version = "0.1.0" -description = "CLI interface for the trading platform" -requires-python = ">=3.12" -dependencies = [ - "click>=8.0", - "rich>=13.0", - "trading-shared", -] - -[project.scripts] -trading = "trading_cli.main:cli" - -[project.optional-dependencies] -dev = [ - "pytest>=8.0", - "pytest-asyncio>=0.23", -] - -[build-system] -requires = ["hatchling"] -build-backend = "hatchling.build" - -[tool.hatch.build.targets.wheel] -packages = ["src/trading_cli"] -``` - -- [ ] **Step 2: Write failing tests for CLI data commands** - -Create `cli/tests/test_cli_data.py`: - -```python -from click.testing import CliRunner -from trading_cli.main import cli - - -def test_cli_help(): - runner = CliRunner() - result = runner.invoke(cli, ["--help"]) - assert result.exit_code == 0 - assert "trading" in result.output.lower() or "Usage" in result.output - - -def test_cli_data_group(): - runner = CliRunner() - result = runner.invoke(cli, ["data", "--help"]) - assert result.exit_code == 0 - assert "collect" in result.output - assert "history" in result.output -``` - -- [ ] **Step 3: Run tests to verify they fail** - -```bash -pip install -e cli[dev] -pytest cli/tests/test_cli_data.py -v -``` - -Expected: FAIL - -- [ ] **Step 4: Implement CLI main and data commands** - -Create `cli/src/trading_cli/__init__.py`: - -```python -``` - -Create `cli/src/trading_cli/main.py`: - -```python -import click - -from trading_cli.commands.data import data -from trading_cli.commands.trade import trade -from trading_cli.commands.backtest import backtest -from trading_cli.commands.portfolio import portfolio -from trading_cli.commands.strategy import strategy -from trading_cli.commands.service import service - - -@click.group() -@click.version_option(version="0.1.0") -def cli(): - """Trading Platform CLI — Binance spot crypto trading""" - pass - - -cli.add_command(data) -cli.add_command(trade) -cli.add_command(backtest) -cli.add_command(portfolio) -cli.add_command(strategy) -cli.add_command(service) -``` - -Create `cli/src/trading_cli/commands/data.py`: - -```python -import asyncio - -import click - - -@click.group() -def data(): - """Data collection commands""" - pass - - -@data.command() -@click.option("--symbol", required=True, help="Trading pair (e.g. BTCUSDT)") -@click.option("--timeframe", default="1m", help="Candle timeframe") -def collect(symbol: str, timeframe: str): - """Start real-time data collection""" - click.echo(f"Starting data collection: {symbol} {timeframe}") - - from data_collector.config import CollectorConfig - from data_collector.main import run - - asyncio.run(run()) - - -@data.command() -@click.option("--symbol", required=True, help="Trading pair (e.g. BTCUSDT)") -@click.option("--timeframe", default="1m", help="Candle timeframe") -@click.option("--from", "since", required=True, help="Start date (YYYY-MM-DD)") -@click.option("--limit", default=1000, help="Number of candles") -def history(symbol: str, timeframe: str, since: str, limit: int): - """Download historical candle data""" - click.echo(f"Downloading history: {symbol} {timeframe} from {since} (limit={limit})") - - async def _run(): - import ccxt.async_support as ccxt - from datetime import datetime, timezone - from shared.broker import RedisBroker - from shared.config import Settings - from shared.db import Database - from data_collector.binance_rest import fetch_historical_candles - from data_collector.storage import CandleStorage - - settings = Settings() - db = Database(settings.database_url) - await db.connect() - await db.init_tables() - broker = RedisBroker(settings.redis_url) - storage = CandleStorage(db=db, broker=broker) - - exchange = ccxt.binance() - since_dt = datetime.strptime(since, "%Y-%m-%d").replace(tzinfo=timezone.utc) - candles = await fetch_historical_candles( - exchange=exchange, - symbol=symbol.replace("USDT", "/USDT"), - timeframe=timeframe, - since=since_dt, - limit=limit, - ) - await storage.store_batch(candles) - await exchange.close() - await broker.close() - await db.close() - click.echo(f"Downloaded {len(candles)} candles") - - asyncio.run(_run()) - - -@data.command("list") -def list_data(): - """List currently collecting symbols""" - click.echo("Collecting symbols:") - click.echo(" (Check docker-compose service status)") -``` - -- [ ] **Step 5: Implement remaining CLI command stubs** - -Create `cli/src/trading_cli/commands/trade.py`: - -```python -import click - - -@click.group() -def trade(): - """Trading bot commands""" - pass - - -@trade.command() -@click.option("--strategy", required=True, help="Strategy name") -@click.option("--symbol", required=True, help="Trading pair") -def start(strategy: str, symbol: str): - """Start a trading bot""" - click.echo(f"Starting bot: strategy={strategy} symbol={symbol}") - - -@trade.command() -@click.option("--strategy", required=True, help="Strategy name") -def stop(strategy: str): - """Stop a trading bot""" - click.echo(f"Stopping bot: strategy={strategy}") - - -@trade.command() -def status(): - """Show running bot status""" - click.echo("Running bots:") - - -@trade.command("stop-all") -def stop_all(): - """Emergency stop: stop all bots and cancel all orders""" - click.confirm("Are you sure you want to stop ALL bots?", abort=True) - click.echo("Stopping all bots and cancelling open orders...") -``` - -Create `cli/src/trading_cli/commands/backtest.py`: - -```python -import asyncio -from decimal import Decimal - -import click - - -@click.group() -def backtest(): - """Backtesting commands""" - pass - - -@backtest.command("run") -@click.option("--strategy", required=True, help="Strategy name") -@click.option("--symbol", required=True, help="Trading pair") -@click.option("--from", "since", required=True, help="Start date") -@click.option("--to", "until", required=True, help="End date") -@click.option("--balance", default=10000.0, help="Initial balance") -def run_backtest(strategy: str, symbol: str, since: str, until: str, balance: float): - """Run a backtest""" - click.echo(f"Running backtest: {strategy} on {symbol} ({since} ~ {until})") - - async def _run(): - from pathlib import Path - from shared.config import Settings - from shared.db import Database - from backtester.main import run_backtest as bt_run - - settings = Settings() - db = Database(settings.database_url) - await db.connect() - - strategies_dir = Path(__file__).parent.parent.parent.parent.parent / "services" / "strategy-engine" / "strategies" - report = await bt_run( - strategy_name=strategy, - symbol=symbol, - timeframe="1m", - initial_balance=Decimal(str(balance)), - db=db, - strategies_dir=strategies_dir, - ) - click.echo(report) - await db.close() - - asyncio.run(_run()) - - -@backtest.command() -@click.option("--id", "report_id", default="latest", help="Report ID") -def report(report_id: str): - """Show backtest report""" - click.echo(f"Showing report: {report_id}") -``` - -Create `cli/src/trading_cli/commands/portfolio.py`: - -```python -import click - - -@click.group() -def portfolio(): - """Portfolio commands""" - pass - - -@portfolio.command() -def show(): - """Show current portfolio""" - click.echo("Current Portfolio:") - click.echo(" (Connect to portfolio-manager service)") - - -@portfolio.command() -@click.option("--days", default=30, help="Number of days") -def history(days: int): - """Show PnL history""" - click.echo(f"PnL history (last {days} days):") -``` - -Create `cli/src/trading_cli/commands/strategy.py`: - -```python -from pathlib import Path - -import click - - -@click.group() -def strategy(): - """Strategy management commands""" - pass - - -@strategy.command("list") -def list_strategies(): - """List available strategies""" - from strategy_engine.plugin_loader import load_strategies - - strategies_dir = Path(__file__).parent.parent.parent.parent.parent / "services" / "strategy-engine" / "strategies" - strategies = load_strategies(strategies_dir) - click.echo("Available strategies:") - for s in strategies: - click.echo(f" - {s.name}") - - -@strategy.command() -@click.option("--name", required=True, help="Strategy name") -def info(name: str): - """Show strategy details""" - click.echo(f"Strategy: {name}") -``` - -Create `cli/src/trading_cli/commands/service.py`: - -```python -import subprocess - -import click - - -@click.group() -def service(): - """Service management commands""" - pass - - -@service.command() -def up(): - """Start all services""" - click.echo("Starting all services...") - subprocess.run(["docker", "compose", "up", "-d"], check=True) - - -@service.command() -def down(): - """Stop all services""" - click.echo("Stopping all services...") - subprocess.run(["docker", "compose", "down"], check=True) - - -@service.command() -@click.option("--name", required=True, help="Service name") -def logs(name: str): - """Show service logs""" - subprocess.run(["docker", "compose", "logs", "-f", name]) -``` - -- [ ] **Step 6: Run tests to verify they pass** - -```bash -pytest cli/tests/test_cli_data.py -v -``` - -Expected: All PASS - -- [ ] **Step 7: Commit** - -```bash -git add cli/ -git commit -m "feat(cli): add Click-based CLI with data, trade, backtest, portfolio, strategy, and service commands" -``` - ---- - -## Task 11: Integration Verification - -- [ ] **Step 1: Run all tests** - -```bash -cd /home/si/Private/repos/trading -pytest -v -``` - -Expected: All tests pass - -- [ ] **Step 2: Lint check** - -```bash -ruff check . -``` - -Fix any issues found. - -- [ ] **Step 3: Verify Docker builds** - -```bash -docker compose build -``` - -Expected: All services build successfully - -- [ ] **Step 4: Start infrastructure and verify** - -```bash -make infra -# Wait for healthy status -docker compose ps -``` - -Expected: redis and postgres running and healthy - -- [ ] **Step 5: Final commit** - -```bash -git add . -git commit -m "chore: integration verification — all tests pass, docker builds succeed" -``` diff --git a/docs/superpowers/plans/2026-04-01-operations-and-strategy-expansion.md b/docs/superpowers/plans/2026-04-01-operations-and-strategy-expansion.md deleted file mode 100644 index 761a49a..0000000 --- a/docs/superpowers/plans/2026-04-01-operations-and-strategy-expansion.md +++ /dev/null @@ -1,4187 +0,0 @@ -# Operations Infrastructure & Strategy Expansion — Implementation Plan - -> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. - -**Goal:** Add production-grade operations infrastructure (SQLAlchemy ORM, Alembic migrations, structlog, Telegram alerts, resilience, Prometheus) and expand the strategy library (MACD, Bollinger, EMA Crossover, VWAP, Volume Profile) with enhanced backtesting metrics. - -**Architecture:** Operations-first approach. Migrate the DB layer to SQLAlchemy 2.0 async, add structured logging and Telegram notifications as shared infrastructure, then build resilience and metrics on top. Strategy expansion builds on the stabilized platform with new BaseStrategy.warmup_period contract and YAML config loading. - -**Tech Stack:** SQLAlchemy 2.0 async (asyncpg driver), Alembic, structlog, aiohttp (Telegram), prometheus-client, pyyaml, rich, pandas, numpy - ---- - -## File Structure - -### New Files - -| File | Responsibility | -|------|---------------| -| `shared/src/shared/sa_models.py` | SQLAlchemy ORM table definitions | -| `shared/src/shared/logging.py` | structlog setup and Telegram error processor | -| `shared/src/shared/notifier.py` | TelegramNotifier class | -| `shared/src/shared/resilience.py` | retry_with_backoff decorator + CircuitBreaker | -| `shared/src/shared/healthcheck.py` | aiohttp-based /health + /metrics server | -| `shared/src/shared/metrics.py` | Prometheus metric definitions | -| `shared/alembic.ini` | Alembic config | -| `shared/alembic/env.py` | Alembic async environment | -| `shared/alembic/script.py.mako` | Alembic migration template | -| `shared/alembic/versions/` | Migration files (auto-generated) | -| `shared/tests/test_sa_models.py` | SA model tests | -| `shared/tests/test_logging.py` | structlog setup tests | -| `shared/tests/test_notifier.py` | TelegramNotifier tests | -| `shared/tests/test_resilience.py` | retry + circuit breaker tests | -| `shared/tests/test_healthcheck.py` | Healthcheck server tests | -| `shared/tests/test_metrics.py` | Prometheus metrics tests | -| `services/strategy-engine/strategies/config/rsi_strategy.yaml` | RSI params | -| `services/strategy-engine/strategies/config/grid_strategy.yaml` | Grid params | -| `services/strategy-engine/strategies/config/macd_strategy.yaml` | MACD params | -| `services/strategy-engine/strategies/config/bollinger_strategy.yaml` | Bollinger params | -| `services/strategy-engine/strategies/config/ema_crossover_strategy.yaml` | EMA params | -| `services/strategy-engine/strategies/config/vwap_strategy.yaml` | VWAP params | -| `services/strategy-engine/strategies/config/volume_profile_strategy.yaml` | Volume Profile params | -| `services/strategy-engine/strategies/macd_strategy.py` | MACD strategy | -| `services/strategy-engine/strategies/bollinger_strategy.py` | Bollinger Bands strategy | -| `services/strategy-engine/strategies/ema_crossover_strategy.py` | EMA Crossover strategy | -| `services/strategy-engine/strategies/vwap_strategy.py` | VWAP strategy | -| `services/strategy-engine/strategies/volume_profile_strategy.py` | Volume Profile strategy | -| `services/strategy-engine/tests/test_macd_strategy.py` | MACD tests | -| `services/strategy-engine/tests/test_bollinger_strategy.py` | Bollinger tests | -| `services/strategy-engine/tests/test_ema_crossover_strategy.py` | EMA Crossover tests | -| `services/strategy-engine/tests/test_vwap_strategy.py` | VWAP tests | -| `services/strategy-engine/tests/test_volume_profile_strategy.py` | Volume Profile tests | -| `services/backtester/src/backtester/metrics.py` | DetailedMetrics + TradeRecord | -| `services/backtester/tests/test_metrics.py` | Detailed metrics tests | -| `monitoring/prometheus.yml` | Prometheus scrape config | - -### Modified Files - -| File | Changes | -|------|---------| -| `shared/pyproject.toml` | Add sqlalchemy, alembic, structlog, prometheus-client, pyyaml | -| `shared/src/shared/config.py` | Add Telegram, health, circuit breaker settings | -| `shared/src/shared/db.py` | Rewrite to SQLAlchemy async session | -| `shared/src/shared/__init__.py` | Export new modules | -| `shared/tests/test_db.py` | Update for SQLAlchemy API | -| `services/strategy-engine/strategies/base.py` | Add warmup_period abstract property | -| `services/strategy-engine/strategies/rsi_strategy.py` | Add warmup_period, update for YAML config | -| `services/strategy-engine/strategies/grid_strategy.py` | Add warmup_period, update for YAML config | -| `services/strategy-engine/src/strategy_engine/plugin_loader.py` | Add YAML config loading | -| `services/strategy-engine/src/strategy_engine/main.py` | Use YAML config loader | -| `services/data-collector/src/data_collector/storage.py` | Use AsyncSession | -| `services/data-collector/src/data_collector/main.py` | Use structlog, healthcheck, resilience | -| `services/order-executor/src/order_executor/executor.py` | Use AsyncSession, notifier | -| `services/order-executor/src/order_executor/main.py` | Use structlog, healthcheck, resilience | -| `services/portfolio-manager/src/portfolio_manager/main.py` | Use structlog, healthcheck, daily summary | -| `services/backtester/src/backtester/engine.py` | Compute DetailedMetrics | -| `services/backtester/src/backtester/simulator.py` | Track entry/exit for TradeRecord | -| `services/backtester/src/backtester/reporter.py` | Rich table output, CSV/JSON export | -| `docker-compose.yml` | Add healthcheck endpoints, monitoring profile | -| `Makefile` | Add migrate, migrate-down, migrate-new targets | -| `.env.example` | Add Telegram, health, log format vars | - ---- - -## Task 1: SQLAlchemy ORM Models + Alembic Setup - -**Files:** -- Create: `shared/src/shared/sa_models.py` -- Create: `shared/alembic.ini` -- Create: `shared/alembic/env.py` -- Create: `shared/alembic/script.py.mako` -- Modify: `shared/pyproject.toml` -- Test: `shared/tests/test_sa_models.py` - -- [ ] **Step 1: Add dependencies to shared/pyproject.toml** - -```toml -[project] -name = "trading-shared" -version = "0.1.0" -description = "Shared models, events, and utilities for trading platform" -requires-python = ">=3.12" -dependencies = [ - "pydantic>=2.0", - "pydantic-settings>=2.0", - "redis>=5.0", - "sqlalchemy[asyncio]>=2.0", - "asyncpg>=0.29", - "alembic>=1.13", - "structlog>=24.0", - "prometheus-client>=0.20", - "pyyaml>=6.0", - "aiohttp>=3.9", - "rich>=13.0", -] -``` - -- [ ] **Step 2: Write the failing test for SA models** - -Create `shared/tests/test_sa_models.py`: - -```python -"""Tests for SQLAlchemy ORM models.""" -from datetime import datetime, timezone -from decimal import Decimal - -from shared.sa_models import ( - Base, - CandleRow, - SignalRow, - OrderRow, - TradeRow, - PositionRow, - PortfolioSnapshotRow, -) - - -def test_candle_row_table_name(): - assert CandleRow.__tablename__ == "candles" - - -def test_candle_row_columns(): - cols = {c.name for c in CandleRow.__table__.columns} - assert cols == {"symbol", "timeframe", "open_time", "open", "high", "low", "close", "volume"} - - -def test_signal_row_table_name(): - assert SignalRow.__tablename__ == "signals" - - -def test_signal_row_columns(): - cols = {c.name for c in SignalRow.__table__.columns} - assert cols == {"id", "strategy", "symbol", "side", "price", "quantity", "reason", "created_at"} - - -def test_order_row_table_name(): - assert OrderRow.__tablename__ == "orders" - - -def test_order_row_columns(): - cols = {c.name for c in OrderRow.__table__.columns} - assert cols == { - "id", "signal_id", "symbol", "side", "type", "price", - "quantity", "status", "created_at", "filled_at", - } - - -def test_trade_row_table_name(): - assert TradeRow.__tablename__ == "trades" - - -def test_position_row_table_name(): - assert PositionRow.__tablename__ == "positions" - - -def test_portfolio_snapshot_row_table_name(): - assert PortfolioSnapshotRow.__tablename__ == "portfolio_snapshots" - - -def test_base_metadata_has_all_tables(): - table_names = set(Base.metadata.tables.keys()) - assert table_names == { - "candles", "signals", "orders", "trades", "positions", "portfolio_snapshots", - } -``` - -- [ ] **Step 3: Run test to verify it fails** - -Run: `pytest shared/tests/test_sa_models.py -v` -Expected: FAIL with `ModuleNotFoundError: No module named 'shared.sa_models'` - -- [ ] **Step 4: Implement SA models** - -Create `shared/src/shared/sa_models.py`: - -```python -"""SQLAlchemy ORM models for the trading platform.""" -from datetime import datetime - -from sqlalchemy import ( - DateTime, - ForeignKey, - Integer, - Numeric, - String, - Text, -) -from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column - - -class Base(DeclarativeBase): - pass - - -class CandleRow(Base): - __tablename__ = "candles" - - symbol: Mapped[str] = mapped_column(String, primary_key=True) - timeframe: Mapped[str] = mapped_column(String, primary_key=True) - open_time: Mapped[datetime] = mapped_column(DateTime(timezone=True), primary_key=True) - open: Mapped[float] = mapped_column(Numeric, nullable=False) - high: Mapped[float] = mapped_column(Numeric, nullable=False) - low: Mapped[float] = mapped_column(Numeric, nullable=False) - close: Mapped[float] = mapped_column(Numeric, nullable=False) - volume: Mapped[float] = mapped_column(Numeric, nullable=False) - - -class SignalRow(Base): - __tablename__ = "signals" - - id: Mapped[str] = mapped_column(String, primary_key=True) - strategy: Mapped[str] = mapped_column(String, nullable=False) - symbol: Mapped[str] = mapped_column(String, nullable=False) - side: Mapped[str] = mapped_column(String, nullable=False) - price: Mapped[float] = mapped_column(Numeric, nullable=False) - quantity: Mapped[float] = mapped_column(Numeric, nullable=False) - reason: Mapped[str | None] = mapped_column(Text) - created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False) - - -class OrderRow(Base): - __tablename__ = "orders" - - id: Mapped[str] = mapped_column(String, primary_key=True) - signal_id: Mapped[str | None] = mapped_column(String, ForeignKey("signals.id")) - symbol: Mapped[str] = mapped_column(String, nullable=False) - side: Mapped[str] = mapped_column(String, nullable=False) - type: Mapped[str] = mapped_column(String, nullable=False) - price: Mapped[float] = mapped_column(Numeric, nullable=False) - quantity: Mapped[float] = mapped_column(Numeric, nullable=False) - status: Mapped[str] = mapped_column(String, nullable=False, default="PENDING") - created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False) - filled_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True)) - - -class TradeRow(Base): - __tablename__ = "trades" - - id: Mapped[str] = mapped_column(String, primary_key=True) - order_id: Mapped[str | None] = mapped_column(String, ForeignKey("orders.id")) - symbol: Mapped[str] = mapped_column(String, nullable=False) - side: Mapped[str] = mapped_column(String, nullable=False) - price: Mapped[float] = mapped_column(Numeric, nullable=False) - quantity: Mapped[float] = mapped_column(Numeric, nullable=False) - fee: Mapped[float] = mapped_column(Numeric, nullable=False, default=0) - traded_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False) - - -class PositionRow(Base): - __tablename__ = "positions" - - symbol: Mapped[str] = mapped_column(String, primary_key=True) - quantity: Mapped[float] = mapped_column(Numeric, nullable=False) - avg_entry_price: Mapped[float] = mapped_column(Numeric, nullable=False) - current_price: Mapped[float] = mapped_column(Numeric, nullable=False) - updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False) - - -class PortfolioSnapshotRow(Base): - __tablename__ = "portfolio_snapshots" - - id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True) - total_value: Mapped[float] = mapped_column(Numeric, nullable=False) - realized_pnl: Mapped[float] = mapped_column(Numeric, nullable=False) - unrealized_pnl: Mapped[float] = mapped_column(Numeric, nullable=False) - snapshot_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False) -``` - -- [ ] **Step 5: Run test to verify it passes** - -Run: `pytest shared/tests/test_sa_models.py -v` -Expected: All 8 tests PASS - -- [ ] **Step 6: Set up Alembic** - -Create `shared/alembic.ini`: - -```ini -[alembic] -script_location = alembic -sqlalchemy.url = postgresql+asyncpg://trading:trading@localhost:5432/trading - -[loggers] -keys = root,sqlalchemy,alembic - -[handlers] -keys = console - -[formatters] -keys = generic - -[logger_root] -level = WARN -handlers = console - -[logger_sqlalchemy] -level = WARN -handlers = -qualname = sqlalchemy.engine - -[logger_alembic] -level = INFO -handlers = -qualname = alembic - -[handler_console] -class = StreamHandler -args = (sys.stderr,) -level = NOTSET -formatter = generic - -[formatter_generic] -format = %(levelname)-5.5s [%(name)s] %(message)s -datefmt = %H:%M:%S -``` - -Create `shared/alembic/script.py.mako`: - -```mako -"""${message} - -Revision ID: ${up_revision} -Revises: ${down_revision | comma,n} -Create Date: ${create_date} -""" -from typing import Sequence, Union - -from alembic import op -import sqlalchemy as sa -${imports if imports else ""} - -# revision identifiers, used by Alembic. -revision: str = ${repr(up_revision)} -down_revision: Union[str, None] = ${repr(down_revision)} -branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)} -depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)} - - -def upgrade() -> None: - ${upgrades if upgrades else "pass"} - - -def downgrade() -> None: - ${downgrades if downgrades else "pass"} -``` - -Create `shared/alembic/env.py`: - -```python -"""Alembic environment configuration for async SQLAlchemy.""" -import asyncio -import os -from logging.config import fileConfig - -from alembic import context -from sqlalchemy import pool -from sqlalchemy.ext.asyncio import async_engine_from_config - -from shared.sa_models import Base - -config = context.config - -if config.config_file_name is not None: - fileConfig(config.config_file_name) - -target_metadata = Base.metadata - -# Override URL from environment if available -database_url = os.environ.get("DATABASE_URL") -if database_url: - # Ensure async driver prefix - if database_url.startswith("postgresql://"): - database_url = database_url.replace("postgresql://", "postgresql+asyncpg://", 1) - config.set_main_option("sqlalchemy.url", database_url) - - -def run_migrations_offline() -> None: - url = config.get_main_option("sqlalchemy.url") - context.configure(url=url, target_metadata=target_metadata, literal_binds=True) - with context.begin_transaction(): - context.run_migrations() - - -def do_run_migrations(connection): - context.configure(connection=connection, target_metadata=target_metadata) - with context.begin_transaction(): - context.run_migrations() - - -async def run_async_migrations() -> None: - connectable = async_engine_from_config( - config.get_section(config.config_ini_section, {}), - prefix="sqlalchemy.", - poolclass=pool.NullPool, - ) - async with connectable.connect() as connection: - await connection.run_sync(do_run_migrations) - await connectable.dispose() - - -def run_migrations_online() -> None: - asyncio.run(run_async_migrations()) - - -if context.is_offline_mode(): - run_migrations_offline() -else: - run_migrations_online() -``` - -Create empty `shared/alembic/versions/` directory (with `.gitkeep`). - -- [ ] **Step 7: Add Makefile targets** - -Append to `Makefile`: - -```makefile -migrate: - cd shared && alembic upgrade head - -migrate-down: - cd shared && alembic downgrade -1 - -migrate-new: - cd shared && alembic revision --autogenerate -m "$(MSG)" -``` - -- [ ] **Step 8: Commit** - -```bash -git add shared/src/shared/sa_models.py shared/alembic.ini shared/alembic/ \ - shared/tests/test_sa_models.py shared/pyproject.toml Makefile -git commit -m "feat(shared): add SQLAlchemy ORM models and Alembic setup" -``` - ---- - -## Task 2: Rewrite Database Layer to SQLAlchemy Async - -**Files:** -- Modify: `shared/src/shared/db.py` -- Modify: `shared/tests/test_db.py` - -- [ ] **Step 1: Write the failing test for the new DB layer** - -Replace `shared/tests/test_db.py`: - -```python -"""Tests for the SQLAlchemy async database layer.""" -from datetime import datetime, timezone -from decimal import Decimal -from unittest.mock import AsyncMock, MagicMock, patch - -import pytest - -from shared.db import Database -from shared.models import Candle, Signal, OrderSide, Order, OrderType, OrderStatus - - -@pytest.fixture -def db(): - return Database("postgresql+asyncpg://trading:trading@localhost:5432/trading") - - -def test_database_stores_url(db): - assert db._database_url == "postgresql+asyncpg://trading:trading@localhost:5432/trading" - - -@pytest.mark.asyncio -async def test_get_session_returns_async_session(db): - """Verify get_session is an async context manager (structural test).""" - # We can't connect without a real DB, but we verify the method exists - assert hasattr(db, "get_session") - assert callable(db.get_session) - - -@pytest.mark.asyncio -async def test_insert_candle_creates_candle_row(): - """Verify insert_candle adds a CandleRow to the session.""" - db = Database("postgresql+asyncpg://test:test@localhost/test") - - candle = Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2025, 1, 1, tzinfo=timezone.utc), - open=Decimal("50000"), - high=Decimal("51000"), - low=Decimal("49000"), - close=Decimal("50500"), - volume=Decimal("100"), - ) - - mock_session = AsyncMock() - mock_session.__aenter__ = AsyncMock(return_value=mock_session) - mock_session.__aexit__ = AsyncMock(return_value=False) - - with patch.object(db, "get_session", return_value=mock_session): - await db.insert_candle(candle) - - mock_session.merge.assert_called_once() - mock_session.commit.assert_called_once() - - -@pytest.mark.asyncio -async def test_insert_signal_creates_signal_row(): - db = Database("postgresql+asyncpg://test:test@localhost/test") - - signal = Signal( - strategy="rsi", - symbol="BTCUSDT", - side=OrderSide.BUY, - price=Decimal("50000"), - quantity=Decimal("0.01"), - reason="test signal", - ) - - mock_session = AsyncMock() - mock_session.__aenter__ = AsyncMock(return_value=mock_session) - mock_session.__aexit__ = AsyncMock(return_value=False) - - with patch.object(db, "get_session", return_value=mock_session): - await db.insert_signal(signal) - - mock_session.add.assert_called_once() - mock_session.commit.assert_called_once() - - -@pytest.mark.asyncio -async def test_insert_order_creates_order_row(): - db = Database("postgresql+asyncpg://test:test@localhost/test") - - order = Order( - signal_id="sig-1", - symbol="BTCUSDT", - side=OrderSide.BUY, - type=OrderType.MARKET, - price=Decimal("50000"), - quantity=Decimal("0.01"), - ) - - mock_session = AsyncMock() - mock_session.__aenter__ = AsyncMock(return_value=mock_session) - mock_session.__aexit__ = AsyncMock(return_value=False) - - with patch.object(db, "get_session", return_value=mock_session): - await db.insert_order(order) - - mock_session.add.assert_called_once() - mock_session.commit.assert_called_once() -``` - -- [ ] **Step 2: Run test to verify it fails** - -Run: `pytest shared/tests/test_db.py -v` -Expected: FAIL — old Database class doesn't have `get_session` - -- [ ] **Step 3: Rewrite db.py with SQLAlchemy async** - -Replace `shared/src/shared/db.py`: - -```python -"""Database layer using SQLAlchemy async for the trading platform.""" -from datetime import datetime, timezone -from decimal import Decimal -from typing import Optional - -from sqlalchemy import select, update -from sqlalchemy.ext.asyncio import ( - AsyncSession, - async_sessionmaker, - create_async_engine, -) - -from shared.models import Candle, Order, OrderStatus, Signal -from shared.sa_models import ( - Base, - CandleRow, - OrderRow, - SignalRow, -) - - -class Database: - """Async database access layer backed by SQLAlchemy.""" - - def __init__(self, database_url: str) -> None: - self._database_url = database_url - # Ensure async driver prefix - if self._database_url.startswith("postgresql://"): - self._database_url = self._database_url.replace( - "postgresql://", "postgresql+asyncpg://", 1 - ) - self._engine = create_async_engine(self._database_url) - self._session_factory = async_sessionmaker(self._engine, expire_on_commit=False) - - def get_session(self) -> AsyncSession: - """Return a new AsyncSession.""" - return self._session_factory() - - async def connect(self) -> None: - """Create all tables (for dev/test — prefer Alembic in production).""" - async with self._engine.begin() as conn: - await conn.run_sync(Base.metadata.create_all) - - async def close(self) -> None: - """Dispose of the engine.""" - await self._engine.dispose() - - # Alias for backward compatibility - async def init_tables(self) -> None: - await self.connect() - - async def insert_candle(self, candle: Candle) -> None: - """Upsert a candle row using merge.""" - async with self.get_session() as session: - row = CandleRow( - symbol=candle.symbol, - timeframe=candle.timeframe, - open_time=candle.open_time, - open=candle.open, - high=candle.high, - low=candle.low, - close=candle.close, - volume=candle.volume, - ) - await session.merge(row) - await session.commit() - - async def insert_signal(self, signal: Signal) -> None: - """Insert a signal row.""" - async with self.get_session() as session: - row = SignalRow( - id=signal.id, - strategy=signal.strategy, - symbol=signal.symbol, - side=signal.side.value, - price=signal.price, - quantity=signal.quantity, - reason=signal.reason, - created_at=signal.created_at, - ) - session.add(row) - await session.commit() - - async def insert_order(self, order: Order) -> None: - """Insert an order row.""" - async with self.get_session() as session: - row = OrderRow( - id=order.id, - signal_id=order.signal_id, - symbol=order.symbol, - side=order.side.value, - type=order.type.value, - price=order.price, - quantity=order.quantity, - status=order.status.value, - created_at=order.created_at, - filled_at=order.filled_at, - ) - session.add(row) - await session.commit() - - async def update_order_status( - self, - order_id: str, - status: OrderStatus, - filled_at: Optional[datetime] = None, - ) -> None: - """Update the status of an order.""" - async with self.get_session() as session: - stmt = ( - update(OrderRow) - .where(OrderRow.id == order_id) - .values(status=status.value, filled_at=filled_at) - ) - await session.execute(stmt) - await session.commit() - - async def get_candles( - self, symbol: str, timeframe: str, limit: int = 500 - ) -> list[dict]: - """Retrieve candles ordered by open_time descending.""" - async with self.get_session() as session: - stmt = ( - select(CandleRow) - .where(CandleRow.symbol == symbol, CandleRow.timeframe == timeframe) - .order_by(CandleRow.open_time.desc()) - .limit(limit) - ) - result = await session.execute(stmt) - rows = result.scalars().all() - return [ - { - "symbol": r.symbol, - "timeframe": r.timeframe, - "open_time": r.open_time, - "open": r.open, - "high": r.high, - "low": r.low, - "close": r.close, - "volume": r.volume, - } - for r in rows - ] -``` - -- [ ] **Step 4: Run test to verify it passes** - -Run: `pytest shared/tests/test_db.py -v` -Expected: All tests PASS - -- [ ] **Step 5: Commit** - -```bash -git add shared/src/shared/db.py shared/tests/test_db.py -git commit -m "refactor(shared): rewrite db layer to SQLAlchemy 2.0 async" -``` - ---- - -## Task 3: Structured Logging with structlog - -**Files:** -- Create: `shared/src/shared/logging.py` -- Test: `shared/tests/test_logging.py` - -- [ ] **Step 1: Write the failing test** - -Create `shared/tests/test_logging.py`: - -```python -"""Tests for structured logging setup.""" -import logging - -import structlog - -from shared.logging import setup_logging - - -def test_setup_logging_returns_logger(): - logger = setup_logging("test-service", "INFO") - assert logger is not None - - -def test_setup_logging_binds_service_name(): - logger = setup_logging("data-collector", "INFO") - # structlog loggers have _context with bound values - assert logger._context.get("service") == "data-collector" - - -def test_setup_logging_sets_log_level(): - setup_logging("test-service", "DEBUG") - root = logging.getLogger() - assert root.level == logging.DEBUG - - -def test_setup_logging_json_format(capsys): - logger = setup_logging("test-service", "INFO", log_format="json") - logger.info("test_event", key="value") - captured = capsys.readouterr() - assert "test_event" in captured.out or "test_event" in captured.err - - -def test_setup_logging_console_format(capsys): - logger = setup_logging("test-service", "INFO", log_format="console") - logger.info("test_event", key="value") - captured = capsys.readouterr() - assert "test_event" in captured.out or "test_event" in captured.err -``` - -- [ ] **Step 2: Run test to verify it fails** - -Run: `pytest shared/tests/test_logging.py -v` -Expected: FAIL with `ModuleNotFoundError: No module named 'shared.logging'` - -- [ ] **Step 3: Implement structured logging** - -Create `shared/src/shared/logging.py`: - -```python -"""Structured logging setup using structlog.""" -import logging -import sys - -import structlog - - -def setup_logging( - service_name: str, - log_level: str = "INFO", - log_format: str = "json", -) -> structlog.stdlib.BoundLogger: - """Configure structlog for the given service. - - Args: - service_name: Bound to every log entry as 'service'. - log_level: Python log level string (DEBUG, INFO, WARNING, ERROR). - log_format: 'json' for production, 'console' for development. - - Returns: - A bound structlog logger with service context. - """ - # Set stdlib root logger level - logging.basicConfig( - format="%(message)s", - stream=sys.stdout, - level=getattr(logging, log_level.upper(), logging.INFO), - force=True, - ) - - shared_processors: list[structlog.types.Processor] = [ - structlog.contextvars.merge_contextvars, - structlog.stdlib.add_log_level, - structlog.stdlib.add_logger_name, - structlog.processors.TimeStamper(fmt="iso"), - structlog.processors.StackInfoRenderer(), - structlog.processors.UnicodeDecoder(), - ] - - if log_format == "console": - renderer = structlog.dev.ConsoleRenderer() - else: - renderer = structlog.processors.JSONRenderer() - - structlog.configure( - processors=[ - *shared_processors, - structlog.stdlib.ProcessorFormatter.wrap_for_formatter, - ], - logger_factory=structlog.stdlib.LoggerFactory(), - wrapper_class=structlog.stdlib.BoundLogger, - cache_logger_on_first_use=True, - ) - - # Also configure the formatter for stdlib loggers - formatter = structlog.stdlib.ProcessorFormatter( - processors=[ - structlog.stdlib.ProcessorFormatter.remove_processors_meta, - renderer, - ], - ) - - root = logging.getLogger() - for handler in root.handlers: - handler.setFormatter(formatter) - - return structlog.get_logger().bind(service=service_name) -``` - -- [ ] **Step 4: Run test to verify it passes** - -Run: `pytest shared/tests/test_logging.py -v` -Expected: All 5 tests PASS - -- [ ] **Step 5: Commit** - -```bash -git add shared/src/shared/logging.py shared/tests/test_logging.py -git commit -m "feat(shared): add structlog-based structured logging" -``` - ---- - -## Task 4: Telegram Notification Service - -**Files:** -- Create: `shared/src/shared/notifier.py` -- Modify: `shared/src/shared/config.py` -- Modify: `.env.example` -- Test: `shared/tests/test_notifier.py` - -- [ ] **Step 1: Update config.py with Telegram settings** - -Add to `shared/src/shared/config.py` after `dry_run`: - -```python - # Telegram - telegram_bot_token: str = "" - telegram_chat_id: str = "" - telegram_enabled: bool = False - # Logging - log_format: str = "json" - # Health - health_port: int = 8080 - # Circuit Breaker - circuit_breaker_threshold: int = 5 - circuit_breaker_timeout: int = 60 -``` - -- [ ] **Step 2: Update .env.example** - -Replace `.env.example`: - -```env -# Exchange -BINANCE_API_KEY= -BINANCE_API_SECRET= - -# Infrastructure -REDIS_URL=redis://localhost:6379 -DATABASE_URL=postgresql+asyncpg://trading:trading@localhost:5432/trading - -# Logging -LOG_LEVEL=INFO -LOG_FORMAT=json - -# Telegram -TELEGRAM_BOT_TOKEN= -TELEGRAM_CHAT_ID= -TELEGRAM_ENABLED=false - -# Risk Management -RISK_MAX_POSITION_SIZE=0.1 -RISK_STOP_LOSS_PCT=5 -RISK_DAILY_LOSS_LIMIT_PCT=10 -DRY_RUN=true - -# Health & Metrics -HEALTH_PORT=8080 -CIRCUIT_BREAKER_THRESHOLD=5 -CIRCUIT_BREAKER_TIMEOUT=60 -``` - -- [ ] **Step 3: Write the failing test for TelegramNotifier** - -Create `shared/tests/test_notifier.py`: - -```python -"""Tests for Telegram notification service.""" -from decimal import Decimal -from unittest.mock import AsyncMock, patch, MagicMock - -import pytest - -from shared.models import Signal, OrderSide, Order, OrderType, OrderStatus -from shared.notifier import TelegramNotifier - - -@pytest.fixture -def notifier(): - return TelegramNotifier(bot_token="test-token", chat_id="12345") - - -def test_notifier_disabled_when_no_token(): - n = TelegramNotifier(bot_token="", chat_id="12345") - assert n.enabled is False - - -def test_notifier_enabled_with_token(): - n = TelegramNotifier(bot_token="abc", chat_id="12345") - assert n.enabled is True - - -@pytest.mark.asyncio -async def test_send_does_nothing_when_disabled(): - n = TelegramNotifier(bot_token="", chat_id="12345") - # Should not raise - await n.send("test message") - - -@pytest.mark.asyncio -async def test_send_posts_to_telegram_api(notifier): - mock_response = AsyncMock() - mock_response.status = 200 - mock_response.__aenter__ = AsyncMock(return_value=mock_response) - mock_response.__aexit__ = AsyncMock(return_value=False) - - mock_session = AsyncMock() - mock_session.post = MagicMock(return_value=mock_response) - - notifier._session = mock_session - - await notifier.send("Hello") - - mock_session.post.assert_called_once() - call_kwargs = mock_session.post.call_args - assert "12345" in str(call_kwargs) or "Hello" in str(call_kwargs) - - -@pytest.mark.asyncio -async def test_send_signal_formats_message(notifier): - signal = Signal( - strategy="rsi", - symbol="BTCUSDT", - side=OrderSide.BUY, - price=Decimal("50000"), - quantity=Decimal("0.01"), - reason="RSI oversold", - ) - - with patch.object(notifier, "send", new_callable=AsyncMock) as mock_send: - await notifier.send_signal(signal) - mock_send.assert_called_once() - msg = mock_send.call_args[0][0] - assert "BUY" in msg - assert "BTCUSDT" in msg - assert "rsi" in msg - - -@pytest.mark.asyncio -async def test_send_order_formats_message(notifier): - order = Order( - signal_id="sig-1", - symbol="BTCUSDT", - side=OrderSide.BUY, - type=OrderType.MARKET, - price=Decimal("50000"), - quantity=Decimal("0.01"), - status=OrderStatus.FILLED, - ) - - with patch.object(notifier, "send", new_callable=AsyncMock) as mock_send: - await notifier.send_order(order) - mock_send.assert_called_once() - msg = mock_send.call_args[0][0] - assert "FILLED" in msg - assert "BTCUSDT" in msg - - -@pytest.mark.asyncio -async def test_send_error_formats_message(notifier): - with patch.object(notifier, "send", new_callable=AsyncMock) as mock_send: - await notifier.send_error("Connection lost", "data-collector") - mock_send.assert_called_once() - msg = mock_send.call_args[0][0] - assert "Connection lost" in msg - assert "data-collector" in msg -``` - -- [ ] **Step 4: Run test to verify it fails** - -Run: `pytest shared/tests/test_notifier.py -v` -Expected: FAIL with `ModuleNotFoundError: No module named 'shared.notifier'` - -- [ ] **Step 5: Implement TelegramNotifier** - -Create `shared/src/shared/notifier.py`: - -```python -"""Telegram notification service for trading alerts.""" -import asyncio -import logging -from decimal import Decimal - -import aiohttp - -from shared.models import Order, Signal - -logger = logging.getLogger(__name__) - -TELEGRAM_API = "https://api.telegram.org/bot{token}/sendMessage" - - -class TelegramNotifier: - """Sends notifications via Telegram Bot API.""" - - def __init__(self, bot_token: str, chat_id: str) -> None: - self._bot_token = bot_token - self._chat_id = chat_id - self._session: aiohttp.ClientSession | None = None - self._semaphore = asyncio.Semaphore(1) # Rate limit: 1 msg at a time - - @property - def enabled(self) -> bool: - return bool(self._bot_token) - - async def _ensure_session(self) -> aiohttp.ClientSession: - if self._session is None or self._session.closed: - self._session = aiohttp.ClientSession() - return self._session - - async def send(self, message: str, parse_mode: str = "HTML") -> None: - """Send a message to the configured Telegram chat.""" - if not self.enabled: - return - - async with self._semaphore: - url = TELEGRAM_API.format(token=self._bot_token) - payload = { - "chat_id": self._chat_id, - "text": message, - "parse_mode": parse_mode, - } - - retries = 3 - for attempt in range(retries): - try: - session = await self._ensure_session() - async with session.post(url, json=payload) as resp: - if resp.status == 200: - return - logger.warning( - "Telegram API returned %d on attempt %d", - resp.status, - attempt + 1, - ) - except Exception as exc: - logger.warning( - "Telegram send failed attempt %d: %s", attempt + 1, exc - ) - if attempt < retries - 1: - await asyncio.sleep(1) - - logger.error("Failed to send Telegram message after %d attempts", retries) - - async def send_signal(self, signal: Signal) -> None: - """Format and send a trading signal notification.""" - msg = ( - f"<b>Signal: {signal.side.value}</b>\n" - f"Strategy: {signal.strategy}\n" - f"Symbol: {signal.symbol}\n" - f"Price: {signal.price}\n" - f"Quantity: {signal.quantity}\n" - f"Reason: {signal.reason}" - ) - await self.send(msg) - - async def send_order(self, order: Order) -> None: - """Format and send an order execution notification.""" - msg = ( - f"<b>Order: {order.status.value}</b>\n" - f"Symbol: {order.symbol}\n" - f"Side: {order.side.value}\n" - f"Price: {order.price}\n" - f"Quantity: {order.quantity}" - ) - await self.send(msg) - - async def send_error(self, error: str, service: str) -> None: - """Send an error alert.""" - msg = f"<b>Error in {service}</b>\n{error}" - await self.send(msg) - - async def send_daily_summary( - self, positions: list, total_value: Decimal, daily_pnl: Decimal - ) -> None: - """Send daily portfolio summary.""" - lines = [f"<b>Daily Summary</b>"] - lines.append(f"Total Value: {total_value:.2f}") - lines.append(f"Daily PnL: {daily_pnl:.2f}") - lines.append(f"Open Positions: {len(positions)}") - for pos in positions: - lines.append(f" {pos.symbol}: {pos.quantity} @ {pos.avg_entry_price}") - await self.send("\n".join(lines)) - - async def close(self) -> None: - """Close the HTTP session.""" - if self._session and not self._session.closed: - await self._session.close() -``` - -- [ ] **Step 6: Run test to verify it passes** - -Run: `pytest shared/tests/test_notifier.py -v` -Expected: All 7 tests PASS - -- [ ] **Step 7: Commit** - -```bash -git add shared/src/shared/notifier.py shared/src/shared/config.py \ - shared/tests/test_notifier.py .env.example -git commit -m "feat(shared): add Telegram notification service" -``` - ---- - -## Task 5: Error Recovery — Retry + Circuit Breaker - -**Files:** -- Create: `shared/src/shared/resilience.py` -- Test: `shared/tests/test_resilience.py` - -- [ ] **Step 1: Write the failing test** - -Create `shared/tests/test_resilience.py`: - -```python -"""Tests for retry and circuit breaker.""" -import asyncio - -import pytest - -from shared.resilience import retry_with_backoff, CircuitBreaker, CircuitState - - -# --- retry_with_backoff tests --- - -@pytest.mark.asyncio -async def test_retry_succeeds_on_first_attempt(): - call_count = 0 - - @retry_with_backoff(max_retries=3, base_delay=0.01) - async def succeed(): - nonlocal call_count - call_count += 1 - return "ok" - - result = await succeed() - assert result == "ok" - assert call_count == 1 - - -@pytest.mark.asyncio -async def test_retry_succeeds_after_failures(): - call_count = 0 - - @retry_with_backoff(max_retries=3, base_delay=0.01) - async def fail_then_succeed(): - nonlocal call_count - call_count += 1 - if call_count < 3: - raise ConnectionError("down") - return "recovered" - - result = await fail_then_succeed() - assert result == "recovered" - assert call_count == 3 - - -@pytest.mark.asyncio -async def test_retry_raises_after_max_retries(): - @retry_with_backoff(max_retries=2, base_delay=0.01) - async def always_fail(): - raise ConnectionError("always down") - - with pytest.raises(ConnectionError, match="always down"): - await always_fail() - - -# --- CircuitBreaker tests --- - -@pytest.mark.asyncio -async def test_circuit_breaker_starts_closed(): - cb = CircuitBreaker(failure_threshold=3, recovery_timeout=0.1) - assert cb.state == CircuitState.CLOSED - - -@pytest.mark.asyncio -async def test_circuit_breaker_opens_after_threshold(): - cb = CircuitBreaker(failure_threshold=2, recovery_timeout=0.1) - cb.record_failure() - assert cb.state == CircuitState.CLOSED - cb.record_failure() - assert cb.state == CircuitState.OPEN - - -@pytest.mark.asyncio -async def test_circuit_breaker_rejects_when_open(): - cb = CircuitBreaker(failure_threshold=1, recovery_timeout=60) - cb.record_failure() - assert cb.state == CircuitState.OPEN - assert cb.allow_request() is False - - -@pytest.mark.asyncio -async def test_circuit_breaker_half_open_after_timeout(): - cb = CircuitBreaker(failure_threshold=1, recovery_timeout=0.05) - cb.record_failure() - assert cb.state == CircuitState.OPEN - await asyncio.sleep(0.06) - assert cb.allow_request() is True - assert cb.state == CircuitState.HALF_OPEN - - -@pytest.mark.asyncio -async def test_circuit_breaker_closes_on_success(): - cb = CircuitBreaker(failure_threshold=1, recovery_timeout=0.05) - cb.record_failure() - await asyncio.sleep(0.06) - cb.allow_request() # transitions to HALF_OPEN - cb.record_success() - assert cb.state == CircuitState.CLOSED -``` - -- [ ] **Step 2: Run test to verify it fails** - -Run: `pytest shared/tests/test_resilience.py -v` -Expected: FAIL with `ModuleNotFoundError: No module named 'shared.resilience'` - -- [ ] **Step 3: Implement resilience module** - -Create `shared/src/shared/resilience.py`: - -```python -"""Retry with backoff and circuit breaker patterns.""" -import asyncio -import functools -import logging -import random -import time -from enum import Enum -from typing import Callable - -logger = logging.getLogger(__name__) - - -def retry_with_backoff( - max_retries: int = 3, - base_delay: float = 1.0, - max_delay: float = 60.0, -) -> Callable: - """Decorator for async functions that retries with exponential backoff + jitter.""" - - def decorator(func: Callable) -> Callable: - @functools.wraps(func) - async def wrapper(*args, **kwargs): - last_exc = None - for attempt in range(max_retries): - try: - return await func(*args, **kwargs) - except Exception as exc: - last_exc = exc - if attempt < max_retries - 1: - delay = min(base_delay * (2**attempt), max_delay) - jitter = delay * random.uniform(0, 0.5) - wait = delay + jitter - logger.warning( - "Retry %d/%d for %s after %.2fs: %s", - attempt + 1, - max_retries, - func.__name__, - wait, - exc, - ) - await asyncio.sleep(wait) - raise last_exc - - return wrapper - - return decorator - - -class CircuitState(Enum): - CLOSED = "closed" - OPEN = "open" - HALF_OPEN = "half_open" - - -class CircuitBreaker: - """Circuit breaker that opens after consecutive failures.""" - - def __init__( - self, - failure_threshold: int = 5, - recovery_timeout: float = 60.0, - ) -> None: - self._failure_threshold = failure_threshold - self._recovery_timeout = recovery_timeout - self._failure_count = 0 - self._state = CircuitState.CLOSED - self._opened_at: float | None = None - - @property - def state(self) -> CircuitState: - return self._state - - def allow_request(self) -> bool: - """Check if a request should be allowed.""" - if self._state == CircuitState.CLOSED: - return True - - if self._state == CircuitState.OPEN: - if self._opened_at and (time.monotonic() - self._opened_at) >= self._recovery_timeout: - self._state = CircuitState.HALF_OPEN - return True - return False - - # HALF_OPEN — allow one probe request - return True - - def record_success(self) -> None: - """Record a successful call.""" - self._failure_count = 0 - self._state = CircuitState.CLOSED - self._opened_at = None - - def record_failure(self) -> None: - """Record a failed call.""" - self._failure_count += 1 - if self._failure_count >= self._failure_threshold: - self._state = CircuitState.OPEN - self._opened_at = time.monotonic() - logger.error( - "Circuit breaker OPEN after %d failures", self._failure_count - ) -``` - -- [ ] **Step 4: Run test to verify it passes** - -Run: `pytest shared/tests/test_resilience.py -v` -Expected: All 8 tests PASS - -- [ ] **Step 5: Commit** - -```bash -git add shared/src/shared/resilience.py shared/tests/test_resilience.py -git commit -m "feat(shared): add retry with backoff and circuit breaker" -``` - ---- - -## Task 6: Health Check + Prometheus Metrics - -**Files:** -- Create: `shared/src/shared/healthcheck.py` -- Create: `shared/src/shared/metrics.py` -- Create: `monitoring/prometheus.yml` -- Modify: `docker-compose.yml` -- Test: `shared/tests/test_healthcheck.py` -- Test: `shared/tests/test_metrics.py` - -- [ ] **Step 1: Write the failing test for metrics** - -Create `shared/tests/test_metrics.py`: - -```python -"""Tests for Prometheus metrics definitions.""" -from shared.metrics import ServiceMetrics - - -def test_service_metrics_creates_counters(): - m = ServiceMetrics("test-service") - assert m.errors_total is not None - assert m.events_processed is not None - - -def test_service_metrics_increment_errors(): - m = ServiceMetrics("test-service-2") - m.errors_total.labels(service="test-service-2", error_type="connection").inc() - # No assertion needed — prometheus_client raises on invalid labels - - -def test_service_metrics_observe_processing_time(): - m = ServiceMetrics("test-service-3") - m.processing_seconds.labels(service="test-service-3").observe(0.5) -``` - -- [ ] **Step 2: Run test to verify it fails** - -Run: `pytest shared/tests/test_metrics.py -v` -Expected: FAIL with `ModuleNotFoundError: No module named 'shared.metrics'` - -- [ ] **Step 3: Implement metrics module** - -Create `shared/src/shared/metrics.py`: - -```python -"""Prometheus metric definitions for trading services.""" -from prometheus_client import Counter, Gauge, Histogram - - -class ServiceMetrics: - """Common Prometheus metrics for any trading service.""" - - def __init__(self, service_name: str) -> None: - prefix = service_name.replace("-", "_") - - self.errors_total = Counter( - f"{prefix}_errors_total", - "Total error count", - ["service", "error_type"], - ) - - self.events_processed = Counter( - f"{prefix}_events_processed_total", - "Total events processed", - ["service", "event_type"], - ) - - self.processing_seconds = Histogram( - f"{prefix}_processing_seconds", - "Event processing duration in seconds", - ["service"], - ) - - self.service_up = Gauge( - f"{prefix}_up", - "Service health status (1=up, 0=down)", - ["service"], - ) -``` - -- [ ] **Step 4: Run test to verify it passes** - -Run: `pytest shared/tests/test_metrics.py -v` -Expected: All 3 tests PASS - -- [ ] **Step 5: Write the failing test for healthcheck** - -Create `shared/tests/test_healthcheck.py`: - -```python -"""Tests for health check server.""" -import pytest -from unittest.mock import AsyncMock - -from shared.healthcheck import HealthCheckServer - - -def test_healthcheck_server_init(): - server = HealthCheckServer(service_name="test", port=9090) - assert server._service_name == "test" - assert server._port == 9090 - - -def test_healthcheck_register_check(): - server = HealthCheckServer(service_name="test", port=9090) - check_fn = AsyncMock(return_value=True) - server.register_check("redis", check_fn) - assert "redis" in server._checks - - -@pytest.mark.asyncio -async def test_healthcheck_run_checks_all_pass(): - server = HealthCheckServer(service_name="test", port=9090) - server.register_check("redis", AsyncMock(return_value=True)) - server.register_check("postgres", AsyncMock(return_value=True)) - result = await server.run_checks() - assert result["status"] == "ok" - assert result["checks"]["redis"] is True - assert result["checks"]["postgres"] is True - - -@pytest.mark.asyncio -async def test_healthcheck_run_checks_one_fails(): - server = HealthCheckServer(service_name="test", port=9090) - server.register_check("redis", AsyncMock(return_value=True)) - server.register_check("postgres", AsyncMock(return_value=False)) - result = await server.run_checks() - assert result["status"] == "degraded" - assert result["checks"]["postgres"] is False -``` - -- [ ] **Step 6: Run test to verify it fails** - -Run: `pytest shared/tests/test_healthcheck.py -v` -Expected: FAIL with `ModuleNotFoundError: No module named 'shared.healthcheck'` - -- [ ] **Step 7: Implement healthcheck server** - -Create `shared/src/shared/healthcheck.py`: - -```python -"""Lightweight HTTP server for health checks and Prometheus metrics.""" -import time -from typing import Any, Callable, Coroutine - -from aiohttp import web -from prometheus_client import generate_latest, CONTENT_TYPE_LATEST - - -class HealthCheckServer: - """Serves /health and /metrics endpoints.""" - - def __init__(self, service_name: str, port: int = 8080) -> None: - self._service_name = service_name - self._port = port - self._checks: dict[str, Callable[[], Coroutine[Any, Any, bool]]] = {} - self._start_time = time.monotonic() - - def register_check( - self, name: str, check_fn: Callable[[], Coroutine[Any, Any, bool]] - ) -> None: - """Register a named async health check function.""" - self._checks[name] = check_fn - - async def run_checks(self) -> dict[str, Any]: - """Run all registered checks and return aggregated result.""" - results = {} - all_ok = True - for name, fn in self._checks.items(): - try: - results[name] = await fn() - except Exception: - results[name] = False - if not results[name]: - all_ok = False - - return { - "status": "ok" if all_ok else "degraded", - "service": self._service_name, - "uptime_seconds": round(time.monotonic() - self._start_time, 1), - "checks": results, - } - - async def _handle_health(self, request: web.Request) -> web.Response: - result = await self.run_checks() - status = 200 if result["status"] == "ok" else 503 - return web.json_response(result, status=status) - - async def _handle_metrics(self, request: web.Request) -> web.Response: - return web.Response( - body=generate_latest(), - content_type=CONTENT_TYPE_LATEST, - ) - - async def start(self) -> web.AppRunner: - """Start the HTTP server in the background.""" - app = web.Application() - app.router.add_get("/health", self._handle_health) - app.router.add_get("/metrics", self._handle_metrics) - - runner = web.AppRunner(app) - await runner.setup() - site = web.TCPSite(runner, "0.0.0.0", self._port) - await site.start() - return runner -``` - -- [ ] **Step 8: Run test to verify it passes** - -Run: `pytest shared/tests/test_healthcheck.py -v` -Expected: All 4 tests PASS - -- [ ] **Step 9: Create Prometheus config and update docker-compose** - -Create `monitoring/prometheus.yml`: - -```yaml -global: - scrape_interval: 15s - -scrape_configs: - - job_name: "trading-services" - static_configs: - - targets: - - "data-collector:8080" - - "strategy-engine:8081" - - "order-executor:8082" - - "portfolio-manager:8083" -``` - -Add to `docker-compose.yml` — append these services before the `volumes:` section: - -```yaml - prometheus: - image: prom/prometheus:latest - profiles: ["monitoring"] - ports: - - "9090:9090" - volumes: - - ./monitoring/prometheus.yml:/etc/prometheus/prometheus.yml - depends_on: - - data-collector - - strategy-engine - - order-executor - - portfolio-manager - - grafana: - image: grafana/grafana:latest - profiles: ["monitoring"] - ports: - - "3000:3000" - depends_on: - - prometheus -``` - -- [ ] **Step 10: Commit** - -```bash -git add shared/src/shared/metrics.py shared/src/shared/healthcheck.py \ - shared/tests/test_metrics.py shared/tests/test_healthcheck.py \ - monitoring/prometheus.yml docker-compose.yml -git commit -m "feat(shared): add health checks and Prometheus metrics" -``` - ---- - -## Task 7: Integrate Operations Infrastructure into Services - -**Files:** -- Modify: `services/data-collector/src/data_collector/main.py` -- Modify: `services/data-collector/src/data_collector/storage.py` -- Modify: `services/order-executor/src/order_executor/main.py` -- Modify: `services/order-executor/src/order_executor/executor.py` -- Modify: `services/portfolio-manager/src/portfolio_manager/main.py` -- Modify: `services/strategy-engine/src/strategy_engine/main.py` - -This task integrates structlog, healthcheck, metrics, Telegram, and resilience into each service's entry point. Each service follows the same pattern. - -- [ ] **Step 1: Update data-collector/main.py** - -Replace `services/data-collector/src/data_collector/main.py`: - -```python -"""Data Collector Service entry point.""" -import asyncio - -from shared.broker import RedisBroker -from shared.config import Settings -from shared.db import Database -from shared.healthcheck import HealthCheckServer -from shared.logging import setup_logging -from shared.metrics import ServiceMetrics -from shared.notifier import TelegramNotifier -from shared.resilience import retry_with_backoff - -from data_collector.binance_ws import BinanceWebSocket -from data_collector.config import CollectorConfig -from data_collector.storage import CandleStorage - - -async def run() -> None: - config = CollectorConfig() - log = setup_logging("data-collector", config.log_level, config.log_format) - metrics = ServiceMetrics("data_collector") - - notifier = TelegramNotifier( - bot_token=config.telegram_bot_token, - chat_id=config.telegram_chat_id, - ) - - db = Database(config.database_url) - await db.connect() - - broker = RedisBroker(config.redis_url) - storage = CandleStorage(db=db, broker=broker) - - # Health checks - health = HealthCheckServer("data-collector", port=config.health_port) - - async def check_redis(): - try: - await broker._redis.ping() - return True - except Exception: - return False - - health.register_check("redis", check_redis) - await health.start() - - metrics.service_up.labels(service="data-collector").set(1) - - async def on_candle(candle): - log.info("candle_received", symbol=candle.symbol, timeframe=candle.timeframe) - await storage.store(candle) - metrics.events_processed.labels( - service="data-collector", event_type="candle" - ).inc() - - timeframe = config.timeframes[0] if config.timeframes else "1m" - - ws = BinanceWebSocket( - symbols=config.symbols, - timeframe=timeframe, - on_candle=on_candle, - ) - - log.info("starting", symbols=config.symbols, timeframe=timeframe) - - try: - await ws.start() - except Exception as exc: - log.error("fatal_error", error=str(exc)) - metrics.errors_total.labels( - service="data-collector", error_type="fatal" - ).inc() - await notifier.send_error(str(exc), "data-collector") - raise - finally: - metrics.service_up.labels(service="data-collector").set(0) - await notifier.close() - await broker.close() - await db.close() - - -def main() -> None: - asyncio.run(run()) - - -if __name__ == "__main__": - main() -``` - -- [ ] **Step 2: Update order-executor/executor.py to use notifier** - -Add notifier parameter to `OrderExecutor.__init__` and call it on order events. Replace `services/order-executor/src/order_executor/executor.py`: - -```python -"""Order execution logic.""" -import logging -from datetime import datetime, timezone -from decimal import Decimal -from typing import Any, Optional - -from shared.broker import RedisBroker -from shared.db import Database -from shared.events import OrderEvent -from shared.models import Order, OrderSide, OrderStatus, OrderType, Signal -from shared.notifier import TelegramNotifier - -from order_executor.risk_manager import RiskManager - -logger = logging.getLogger(__name__) - - -class OrderExecutor: - """Executes orders on an exchange with risk gating.""" - - def __init__( - self, - exchange: Any, - risk_manager: RiskManager, - broker: RedisBroker, - db: Database, - notifier: TelegramNotifier, - dry_run: bool = True, - ) -> None: - self.exchange = exchange - self.risk_manager = risk_manager - self.broker = broker - self.db = db - self.notifier = notifier - self.dry_run = dry_run - - async def execute(self, signal: Signal) -> Optional[Order]: - """Run risk checks and place an order for the given signal.""" - balance_data = await self.exchange.fetch_balance() - free_balances = balance_data.get("free", {}) - quote_currency = signal.symbol.split("/")[-1] if "/" in signal.symbol else "USDT" - balance = Decimal(str(free_balances.get(quote_currency, 0))) - - positions = {} - daily_pnl = Decimal(0) - - result = self.risk_manager.check( - signal=signal, - balance=balance, - positions=positions, - daily_pnl=daily_pnl, - ) - - if not result.allowed: - logger.warning( - "Risk check rejected signal %s: %s", signal.id, result.reason - ) - return None - - order = Order( - signal_id=signal.id, - symbol=signal.symbol, - side=signal.side, - type=OrderType.MARKET, - price=signal.price, - quantity=signal.quantity, - status=OrderStatus.PENDING, - ) - - if self.dry_run: - order.status = OrderStatus.FILLED - order.filled_at = datetime.now(timezone.utc) - logger.info("[DRY RUN] Order filled: %s %s %s", order.side, order.quantity, order.symbol) - else: - try: - await self.exchange.create_order( - symbol=signal.symbol, - type="market", - side=signal.side.value.lower(), - amount=float(signal.quantity), - ) - order.status = OrderStatus.FILLED - order.filled_at = datetime.now(timezone.utc) - logger.info("Order filled: %s %s %s", order.side, order.quantity, order.symbol) - except Exception as exc: - order.status = OrderStatus.FAILED - logger.error("Order failed for signal %s: %s", signal.id, exc) - - await self.db.insert_order(order) - await self.broker.publish("orders", OrderEvent(data=order).to_dict()) - await self.notifier.send_order(order) - - return order -``` - -- [ ] **Step 3: Update order-executor/main.py** - -Replace `services/order-executor/src/order_executor/main.py`: - -```python -"""Order Executor Service entry point.""" -import asyncio -from decimal import Decimal - -import ccxt.async_support as ccxt - -from shared.broker import RedisBroker -from shared.db import Database -from shared.events import Event, EventType -from shared.healthcheck import HealthCheckServer -from shared.logging import setup_logging -from shared.metrics import ServiceMetrics -from shared.notifier import TelegramNotifier - -from order_executor.config import ExecutorConfig -from order_executor.executor import OrderExecutor -from order_executor.risk_manager import RiskManager - - -async def run() -> None: - config = ExecutorConfig() - log = setup_logging("order-executor", config.log_level, config.log_format) - metrics = ServiceMetrics("order_executor") - - notifier = TelegramNotifier( - bot_token=config.telegram_bot_token, - chat_id=config.telegram_chat_id, - ) - - db = Database(config.database_url) - await db.connect() - - broker = RedisBroker(config.redis_url) - - exchange = ccxt.binance( - {"apiKey": config.binance_api_key, "secret": config.binance_api_secret} - ) - - risk_manager = RiskManager( - max_position_size=Decimal(str(config.risk_max_position_size)), - stop_loss_pct=Decimal(str(config.risk_stop_loss_pct)), - daily_loss_limit_pct=Decimal(str(config.risk_daily_loss_limit_pct)), - ) - - executor = OrderExecutor( - exchange=exchange, - risk_manager=risk_manager, - broker=broker, - db=db, - notifier=notifier, - dry_run=config.dry_run, - ) - - health = HealthCheckServer("order-executor", port=config.health_port + 2) - await health.start() - metrics.service_up.labels(service="order-executor").set(1) - - last_id = "$" - stream = "signals" - log.info("started", stream=stream, dry_run=config.dry_run) - - try: - while True: - messages = await broker.read(stream, last_id=last_id, count=10, block=5000) - for msg in messages: - try: - event = Event.from_dict(msg) - if event.type == EventType.SIGNAL: - signal = event.data - log.info("processing_signal", signal_id=signal.id, symbol=signal.symbol) - await executor.execute(signal) - metrics.events_processed.labels( - service="order-executor", event_type="signal" - ).inc() - except Exception as exc: - log.error("process_failed", error=str(exc)) - metrics.errors_total.labels( - service="order-executor", error_type="processing" - ).inc() - finally: - metrics.service_up.labels(service="order-executor").set(0) - await notifier.close() - await broker.close() - await db.close() - await exchange.close() - - -def main() -> None: - asyncio.run(run()) - - -if __name__ == "__main__": - main() -``` - -- [ ] **Step 4: Update strategy-engine/main.py** - -Replace `services/strategy-engine/src/strategy_engine/main.py`: - -```python -"""Strategy Engine Service entry point.""" -import asyncio -from pathlib import Path - -from shared.broker import RedisBroker -from shared.healthcheck import HealthCheckServer -from shared.logging import setup_logging -from shared.metrics import ServiceMetrics -from shared.notifier import TelegramNotifier - -from strategy_engine.config import StrategyConfig -from strategy_engine.engine import StrategyEngine -from strategy_engine.plugin_loader import load_strategies - -STRATEGIES_DIR = Path(__file__).parent.parent.parent.parent / "strategies" - - -async def run() -> None: - config = StrategyConfig() - log = setup_logging("strategy-engine", config.log_level, config.log_format) - metrics = ServiceMetrics("strategy_engine") - - notifier = TelegramNotifier( - bot_token=config.telegram_bot_token, - chat_id=config.telegram_chat_id, - ) - - broker = RedisBroker(config.redis_url) - strategies = load_strategies(STRATEGIES_DIR) - - for strategy in strategies: - params = config.strategy_params.get(strategy.name, {}) - strategy.configure(params) - - log.info("loaded_strategies", count=len(strategies), names=[s.name for s in strategies]) - - engine = StrategyEngine(broker=broker, strategies=strategies) - - health = HealthCheckServer("strategy-engine", port=config.health_port + 1) - await health.start() - metrics.service_up.labels(service="strategy-engine").set(1) - - try: - for symbol in config.symbols: - stream = f"candles.{symbol.replace('/', '_')}" - last_id = "$" - log.info("engine_loop_start", stream=stream) - while True: - last_id = await engine.process_once(stream, last_id) - except Exception as exc: - log.error("fatal_error", error=str(exc)) - await notifier.send_error(str(exc), "strategy-engine") - raise - finally: - metrics.service_up.labels(service="strategy-engine").set(0) - await notifier.close() - await broker.close() - - -def main() -> None: - asyncio.run(run()) - - -if __name__ == "__main__": - main() -``` - -- [ ] **Step 5: Update portfolio-manager/main.py** - -Replace `services/portfolio-manager/src/portfolio_manager/main.py`: - -```python -"""Portfolio Manager Service entry point.""" -import asyncio - -from shared.broker import RedisBroker -from shared.events import Event, OrderEvent -from shared.healthcheck import HealthCheckServer -from shared.logging import setup_logging -from shared.metrics import ServiceMetrics -from shared.notifier import TelegramNotifier - -from portfolio_manager.config import PortfolioConfig -from portfolio_manager.portfolio import PortfolioTracker - -ORDERS_STREAM = "orders" - - -async def run() -> None: - config = PortfolioConfig() - log = setup_logging("portfolio-manager", config.log_level, config.log_format) - metrics = ServiceMetrics("portfolio_manager") - - notifier = TelegramNotifier( - bot_token=config.telegram_bot_token, - chat_id=config.telegram_chat_id, - ) - - broker = RedisBroker(config.redis_url) - tracker = PortfolioTracker() - - health = HealthCheckServer("portfolio-manager", port=config.health_port + 3) - await health.start() - metrics.service_up.labels(service="portfolio-manager").set(1) - - last_id = "$" - log.info("started", stream=ORDERS_STREAM) - - try: - while True: - messages = await broker.read(ORDERS_STREAM, last_id=last_id, block=1000) - for msg in messages: - try: - event = Event.from_dict(msg) - if isinstance(event, OrderEvent): - order = event.data - tracker.apply_order(order) - log.info( - "order_applied", - symbol=order.symbol, - side=order.side.value, - qty=str(order.quantity), - ) - metrics.events_processed.labels( - service="portfolio-manager", event_type="order" - ).inc() - except Exception as exc: - log.error("process_failed", error=str(exc)) - metrics.errors_total.labels( - service="portfolio-manager", error_type="processing" - ).inc() - finally: - metrics.service_up.labels(service="portfolio-manager").set(0) - await notifier.close() - await broker.close() - - -def main() -> None: - asyncio.run(run()) - - -if __name__ == "__main__": - main() -``` - -- [ ] **Step 6: Run all tests to verify nothing is broken** - -Run: `pytest -v` -Expected: All existing tests PASS (some executor tests may need mock updates for `notifier` param) - -- [ ] **Step 7: Fix any broken executor tests** - -The `OrderExecutor` now requires a `notifier` parameter. Update `services/order-executor/tests/test_executor.py` — add `notifier=AsyncMock()` to every `OrderExecutor(...)` call. For example, wherever the test creates: - -```python -executor = OrderExecutor( - exchange=mock_exchange, - risk_manager=mock_risk, - broker=mock_broker, - db=mock_db, - dry_run=True, -) -``` - -Change to: - -```python -executor = OrderExecutor( - exchange=mock_exchange, - risk_manager=mock_risk, - broker=mock_broker, - db=mock_db, - notifier=AsyncMock(), - dry_run=True, -) -``` - -- [ ] **Step 8: Run all tests again** - -Run: `pytest -v` -Expected: All tests PASS - -- [ ] **Step 9: Commit** - -```bash -git add services/data-collector/src/data_collector/main.py \ - services/order-executor/src/order_executor/executor.py \ - services/order-executor/src/order_executor/main.py \ - services/order-executor/tests/test_executor.py \ - services/strategy-engine/src/strategy_engine/main.py \ - services/portfolio-manager/src/portfolio_manager/main.py -git commit -m "feat(services): integrate structlog, healthcheck, metrics, and Telegram" -``` - ---- - -## Task 8: BaseStrategy warmup_period + YAML Config Loading - -**Files:** -- Modify: `services/strategy-engine/strategies/base.py` -- Modify: `services/strategy-engine/strategies/rsi_strategy.py` -- Modify: `services/strategy-engine/strategies/grid_strategy.py` -- Modify: `services/strategy-engine/src/strategy_engine/plugin_loader.py` -- Create: `services/strategy-engine/strategies/config/rsi_strategy.yaml` -- Create: `services/strategy-engine/strategies/config/grid_strategy.yaml` - -- [ ] **Step 1: Update BaseStrategy with warmup_period** - -Replace `services/strategy-engine/strategies/base.py`: - -```python -from abc import ABC, abstractmethod -from shared.models import Candle, Signal - - -class BaseStrategy(ABC): - name: str = "base" - - @property - @abstractmethod - def warmup_period(self) -> int: - """Minimum number of candles needed before generating signals.""" - pass - - @abstractmethod - def on_candle(self, candle: Candle) -> Signal | None: - pass - - @abstractmethod - def configure(self, params: dict) -> None: - pass - - def reset(self) -> None: - pass -``` - -- [ ] **Step 2: Update RsiStrategy with warmup_period** - -Add this property to `RsiStrategy` in `rsi_strategy.py`, after `__init__`: - -```python - @property - def warmup_period(self) -> int: - return self._period + 1 -``` - -- [ ] **Step 3: Update GridStrategy with warmup_period** - -Add this property to `GridStrategy` in `grid_strategy.py`, after `__init__`: - -```python - @property - def warmup_period(self) -> int: - return 2 # Needs at least 2 candles to detect zone crossing -``` - -- [ ] **Step 4: Create YAML config files** - -Create `services/strategy-engine/strategies/config/rsi_strategy.yaml`: - -```yaml -period: 14 -oversold: 30 -overbought: 70 -quantity: "0.01" -``` - -Create `services/strategy-engine/strategies/config/grid_strategy.yaml`: - -```yaml -lower_price: 60000 -upper_price: 70000 -grid_count: 5 -quantity: "0.01" -``` - -- [ ] **Step 5: Update plugin_loader.py with YAML config loading** - -Replace `services/strategy-engine/src/strategy_engine/plugin_loader.py`: - -```python -"""Dynamic plugin loader for strategy modules with YAML config support.""" -import importlib.util -import sys -from pathlib import Path - -import yaml - -from strategies.base import BaseStrategy - - -def load_strategies(strategies_dir: Path) -> list[BaseStrategy]: - """Scan strategies_dir for *.py files and load all BaseStrategy subclasses. - - Automatically loads matching YAML config from strategies_dir/config/. - """ - loaded: list[BaseStrategy] = [] - config_dir = strategies_dir / "config" - - for path in sorted(strategies_dir.glob("*.py")): - if path.name.startswith("__") or path.name == "base.py": - continue - - module_name = f"_strategy_plugin_{path.stem}" - spec = importlib.util.spec_from_file_location(module_name, path) - if spec is None or spec.loader is None: - continue - - module = importlib.util.module_from_spec(spec) - sys.modules[module_name] = module - spec.loader.exec_module(module) - - for attr_name in dir(module): - obj = getattr(module, attr_name) - if ( - isinstance(obj, type) - and issubclass(obj, BaseStrategy) - and obj is not BaseStrategy - ): - instance = obj() - - # Load YAML config if it exists - yaml_path = config_dir / f"{path.stem}.yaml" - if yaml_path.exists(): - with open(yaml_path) as f: - params = yaml.safe_load(f) or {} - instance.configure(params) - - loaded.append(instance) - - return loaded -``` - -- [ ] **Step 6: Run existing strategy tests** - -Run: `pytest services/strategy-engine/tests/ -v` -Expected: All tests PASS - -- [ ] **Step 7: Commit** - -```bash -git add services/strategy-engine/strategies/base.py \ - services/strategy-engine/strategies/rsi_strategy.py \ - services/strategy-engine/strategies/grid_strategy.py \ - services/strategy-engine/src/strategy_engine/plugin_loader.py \ - services/strategy-engine/strategies/config/ -git commit -m "feat(strategy): add warmup_period to BaseStrategy and YAML config loading" -``` - ---- - -## Task 9: MACD Strategy - -**Files:** -- Create: `services/strategy-engine/strategies/macd_strategy.py` -- Create: `services/strategy-engine/strategies/config/macd_strategy.yaml` -- Test: `services/strategy-engine/tests/test_macd_strategy.py` - -- [ ] **Step 1: Write the failing test** - -Create `services/strategy-engine/tests/test_macd_strategy.py`: - -```python -"""Tests for MACD strategy.""" -from decimal import Decimal - -import pytest - -from shared.models import Candle, OrderSide -from strategies.macd_strategy import MacdStrategy - - -@pytest.fixture -def strategy(): - s = MacdStrategy() - s.configure({"fast_period": 3, "slow_period": 6, "signal_period": 3, "quantity": "0.01"}) - return s - - -def _candle(price: float) -> Candle: - from datetime import datetime, timezone - return Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2025, 1, 1, tzinfo=timezone.utc), - open=Decimal(str(price)), - high=Decimal(str(price + 100)), - low=Decimal(str(price - 100)), - close=Decimal(str(price)), - volume=Decimal("10"), - ) - - -def test_macd_warmup_period(strategy): - assert strategy.warmup_period == 9 # slow_period + signal_period = 6 + 3 - - -def test_macd_no_signal_insufficient_data(strategy): - for price in [100, 101, 102, 103, 104]: - result = strategy.on_candle(_candle(price)) - assert result is None - - -def test_macd_buy_signal_on_bullish_crossover(strategy): - # Feed declining prices to push MACD below signal, then rising to cross above - prices = [100, 98, 96, 94, 92, 90, 88, 90, 93, 97, 102, 108, 115, 123, 132] - signals = [] - for p in prices: - sig = strategy.on_candle(_candle(p)) - if sig is not None: - signals.append(sig) - buy_signals = [s for s in signals if s.side == OrderSide.BUY] - assert len(buy_signals) > 0 - assert buy_signals[0].strategy == "macd" - - -def test_macd_sell_signal_on_bearish_crossover(strategy): - # Feed rising prices to push MACD above signal, then declining to cross below - prices = [100, 105, 110, 116, 122, 128, 125, 120, 114, 107, 99, 90, 80, 70, 60] - signals = [] - for p in prices: - sig = strategy.on_candle(_candle(p)) - if sig is not None: - signals.append(sig) - sell_signals = [s for s in signals if s.side == OrderSide.SELL] - assert len(sell_signals) > 0 - - -def test_macd_reset_clears_state(strategy): - for p in [100, 101, 102]: - strategy.on_candle(_candle(p)) - strategy.reset() - assert len(strategy._closes) == 0 -``` - -- [ ] **Step 2: Run test to verify it fails** - -Run: `pytest services/strategy-engine/tests/test_macd_strategy.py -v` -Expected: FAIL with `ModuleNotFoundError: No module named 'strategies.macd_strategy'` - -- [ ] **Step 3: Implement MACD strategy** - -Create `services/strategy-engine/strategies/macd_strategy.py`: - -```python -"""MACD (Moving Average Convergence Divergence) strategy.""" -from collections import deque -from decimal import Decimal - -import pandas as pd - -from shared.models import Candle, Signal, OrderSide -from strategies.base import BaseStrategy - - -class MacdStrategy(BaseStrategy): - name: str = "macd" - - def __init__(self) -> None: - self._fast_period: int = 12 - self._slow_period: int = 26 - self._signal_period: int = 9 - self._quantity: Decimal = Decimal("0.01") - self._closes: deque[float] = deque(maxlen=500) - self._prev_histogram: float | None = None - - @property - def warmup_period(self) -> int: - return self._slow_period + self._signal_period - - def configure(self, params: dict) -> None: - self._fast_period = int(params.get("fast_period", 12)) - self._slow_period = int(params.get("slow_period", 26)) - self._signal_period = int(params.get("signal_period", 9)) - self._quantity = Decimal(str(params.get("quantity", "0.01"))) - - def reset(self) -> None: - self._closes.clear() - self._prev_histogram = None - - def on_candle(self, candle: Candle) -> Signal | None: - self._closes.append(float(candle.close)) - - if len(self._closes) < self.warmup_period: - return None - - series = pd.Series(list(self._closes)) - fast_ema = series.ewm(span=self._fast_period, adjust=False).mean() - slow_ema = series.ewm(span=self._slow_period, adjust=False).mean() - macd_line = fast_ema - slow_ema - signal_line = macd_line.ewm(span=self._signal_period, adjust=False).mean() - histogram = macd_line - signal_line - - current_hist = histogram.iloc[-1] - - if self._prev_histogram is None: - self._prev_histogram = current_hist - return None - - prev = self._prev_histogram - self._prev_histogram = current_hist - - # Bullish crossover: histogram crosses from negative to positive - if prev < 0 and current_hist > 0: - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.BUY, - price=candle.close, - quantity=self._quantity, - reason=f"MACD bullish crossover (histogram {prev:.4f} -> {current_hist:.4f})", - ) - - # Bearish crossover: histogram crosses from positive to negative - if prev > 0 and current_hist < 0: - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.SELL, - price=candle.close, - quantity=self._quantity, - reason=f"MACD bearish crossover (histogram {prev:.4f} -> {current_hist:.4f})", - ) - - return None -``` - -Create `services/strategy-engine/strategies/config/macd_strategy.yaml`: - -```yaml -fast_period: 12 -slow_period: 26 -signal_period: 9 -quantity: "0.01" -``` - -- [ ] **Step 4: Run test to verify it passes** - -Run: `pytest services/strategy-engine/tests/test_macd_strategy.py -v` -Expected: All 5 tests PASS - -- [ ] **Step 5: Commit** - -```bash -git add services/strategy-engine/strategies/macd_strategy.py \ - services/strategy-engine/strategies/config/macd_strategy.yaml \ - services/strategy-engine/tests/test_macd_strategy.py -git commit -m "feat(strategy): add MACD strategy" -``` - ---- - -## Task 10: Bollinger Bands Strategy - -**Files:** -- Create: `services/strategy-engine/strategies/bollinger_strategy.py` -- Create: `services/strategy-engine/strategies/config/bollinger_strategy.yaml` -- Test: `services/strategy-engine/tests/test_bollinger_strategy.py` - -- [ ] **Step 1: Write the failing test** - -Create `services/strategy-engine/tests/test_bollinger_strategy.py`: - -```python -"""Tests for Bollinger Bands strategy.""" -from decimal import Decimal -from datetime import datetime, timezone - -import pytest - -from shared.models import Candle, OrderSide -from strategies.bollinger_strategy import BollingerStrategy - - -@pytest.fixture -def strategy(): - s = BollingerStrategy() - s.configure({"period": 5, "num_std": 2.0, "min_bandwidth": 0.0, "quantity": "0.01"}) - return s - - -def _candle(price: float) -> Candle: - return Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2025, 1, 1, tzinfo=timezone.utc), - open=Decimal(str(price)), - high=Decimal(str(price + 10)), - low=Decimal(str(price - 10)), - close=Decimal(str(price)), - volume=Decimal("10"), - ) - - -def test_bollinger_warmup_period(strategy): - assert strategy.warmup_period == 5 - - -def test_bollinger_no_signal_insufficient_data(strategy): - for p in [100, 101, 102]: - result = strategy.on_candle(_candle(p)) - assert result is None - - -def test_bollinger_buy_on_lower_band_recovery(strategy): - # Stable prices to build bands, then drop below and recover - prices = [100, 100, 100, 100, 100, 80, 80, 95] - signals = [] - for p in prices: - sig = strategy.on_candle(_candle(p)) - if sig is not None: - signals.append(sig) - buy_signals = [s for s in signals if s.side == OrderSide.BUY] - assert len(buy_signals) > 0 - assert buy_signals[0].strategy == "bollinger" - - -def test_bollinger_sell_on_upper_band_recovery(strategy): - prices = [100, 100, 100, 100, 100, 120, 120, 105] - signals = [] - for p in prices: - sig = strategy.on_candle(_candle(p)) - if sig is not None: - signals.append(sig) - sell_signals = [s for s in signals if s.side == OrderSide.SELL] - assert len(sell_signals) > 0 - - -def test_bollinger_reset_clears_state(strategy): - for p in [100, 101]: - strategy.on_candle(_candle(p)) - strategy.reset() - assert len(strategy._closes) == 0 -``` - -- [ ] **Step 2: Run test to verify it fails** - -Run: `pytest services/strategy-engine/tests/test_bollinger_strategy.py -v` -Expected: FAIL with `ModuleNotFoundError` - -- [ ] **Step 3: Implement Bollinger Bands strategy** - -Create `services/strategy-engine/strategies/bollinger_strategy.py`: - -```python -"""Bollinger Bands strategy.""" -from collections import deque -from decimal import Decimal - -import pandas as pd - -from shared.models import Candle, Signal, OrderSide -from strategies.base import BaseStrategy - - -class BollingerStrategy(BaseStrategy): - name: str = "bollinger" - - def __init__(self) -> None: - self._period: int = 20 - self._num_std: float = 2.0 - self._min_bandwidth: float = 0.02 - self._quantity: Decimal = Decimal("0.01") - self._closes: deque[float] = deque(maxlen=500) - self._was_below_lower: bool = False - self._was_above_upper: bool = False - - @property - def warmup_period(self) -> int: - return self._period - - def configure(self, params: dict) -> None: - self._period = int(params.get("period", 20)) - self._num_std = float(params.get("num_std", 2.0)) - self._min_bandwidth = float(params.get("min_bandwidth", 0.02)) - self._quantity = Decimal(str(params.get("quantity", "0.01"))) - - def reset(self) -> None: - self._closes.clear() - self._was_below_lower = False - self._was_above_upper = False - - def on_candle(self, candle: Candle) -> Signal | None: - self._closes.append(float(candle.close)) - - if len(self._closes) < self._period: - return None - - series = pd.Series(list(self._closes)) - sma = series.rolling(self._period).mean().iloc[-1] - std = series.rolling(self._period).std().iloc[-1] - - upper = sma + self._num_std * std - lower = sma - self._num_std * std - - # Bandwidth filter - if sma > 0: - bandwidth = (upper - lower) / sma - if bandwidth < self._min_bandwidth: - return None - - price = float(candle.close) - - # Track band penetration - if price < lower: - self._was_below_lower = True - if price > upper: - self._was_above_upper = True - - # BUY: price was below lower band and recovered back inside - if self._was_below_lower and price >= lower: - self._was_below_lower = False - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.BUY, - price=candle.close, - quantity=self._quantity, - reason=f"Bollinger: price recovered above lower band ({lower:.2f})", - ) - - # SELL: price was above upper band and recovered back inside - if self._was_above_upper and price <= upper: - self._was_above_upper = False - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.SELL, - price=candle.close, - quantity=self._quantity, - reason=f"Bollinger: price recovered below upper band ({upper:.2f})", - ) - - return None -``` - -Create `services/strategy-engine/strategies/config/bollinger_strategy.yaml`: - -```yaml -period: 20 -num_std: 2.0 -min_bandwidth: 0.02 -quantity: "0.01" -``` - -- [ ] **Step 4: Run test to verify it passes** - -Run: `pytest services/strategy-engine/tests/test_bollinger_strategy.py -v` -Expected: All 5 tests PASS - -- [ ] **Step 5: Commit** - -```bash -git add services/strategy-engine/strategies/bollinger_strategy.py \ - services/strategy-engine/strategies/config/bollinger_strategy.yaml \ - services/strategy-engine/tests/test_bollinger_strategy.py -git commit -m "feat(strategy): add Bollinger Bands strategy" -``` - ---- - -## Task 11: EMA Crossover Strategy - -**Files:** -- Create: `services/strategy-engine/strategies/ema_crossover_strategy.py` -- Create: `services/strategy-engine/strategies/config/ema_crossover_strategy.yaml` -- Test: `services/strategy-engine/tests/test_ema_crossover_strategy.py` - -- [ ] **Step 1: Write the failing test** - -Create `services/strategy-engine/tests/test_ema_crossover_strategy.py`: - -```python -"""Tests for EMA Crossover strategy.""" -from decimal import Decimal -from datetime import datetime, timezone - -import pytest - -from shared.models import Candle, OrderSide -from strategies.ema_crossover_strategy import EmaCrossoverStrategy - - -@pytest.fixture -def strategy(): - s = EmaCrossoverStrategy() - s.configure({"short_period": 3, "long_period": 6, "quantity": "0.01"}) - return s - - -def _candle(price: float) -> Candle: - return Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2025, 1, 1, tzinfo=timezone.utc), - open=Decimal(str(price)), - high=Decimal(str(price + 10)), - low=Decimal(str(price - 10)), - close=Decimal(str(price)), - volume=Decimal("10"), - ) - - -def test_ema_warmup_period(strategy): - assert strategy.warmup_period == 6 - - -def test_ema_no_signal_insufficient_data(strategy): - for p in [100, 101, 102]: - result = strategy.on_candle(_candle(p)) - assert result is None - - -def test_ema_buy_signal_golden_cross(strategy): - # Declining then sharp rise: short EMA crosses above long EMA - prices = [100, 98, 96, 94, 92, 90, 95, 100, 108, 117, 127] - signals = [] - for p in prices: - sig = strategy.on_candle(_candle(p)) - if sig is not None: - signals.append(sig) - buy_signals = [s for s in signals if s.side == OrderSide.BUY] - assert len(buy_signals) > 0 - assert buy_signals[0].strategy == "ema_crossover" - - -def test_ema_sell_signal_death_cross(strategy): - # Rising then sharp decline: short EMA crosses below long EMA - prices = [100, 105, 110, 115, 120, 125, 118, 110, 100, 88, 75] - signals = [] - for p in prices: - sig = strategy.on_candle(_candle(p)) - if sig is not None: - signals.append(sig) - sell_signals = [s for s in signals if s.side == OrderSide.SELL] - assert len(sell_signals) > 0 - - -def test_ema_reset_clears_state(strategy): - for p in [100, 101]: - strategy.on_candle(_candle(p)) - strategy.reset() - assert len(strategy._closes) == 0 -``` - -- [ ] **Step 2: Run test to verify it fails** - -Run: `pytest services/strategy-engine/tests/test_ema_crossover_strategy.py -v` -Expected: FAIL with `ModuleNotFoundError` - -- [ ] **Step 3: Implement EMA Crossover strategy** - -Create `services/strategy-engine/strategies/ema_crossover_strategy.py`: - -```python -"""EMA Crossover (Golden Cross / Death Cross) strategy.""" -from collections import deque -from decimal import Decimal - -import pandas as pd - -from shared.models import Candle, Signal, OrderSide -from strategies.base import BaseStrategy - - -class EmaCrossoverStrategy(BaseStrategy): - name: str = "ema_crossover" - - def __init__(self) -> None: - self._short_period: int = 9 - self._long_period: int = 21 - self._quantity: Decimal = Decimal("0.01") - self._closes: deque[float] = deque(maxlen=500) - self._prev_short_above: bool | None = None - - @property - def warmup_period(self) -> int: - return self._long_period - - def configure(self, params: dict) -> None: - self._short_period = int(params.get("short_period", 9)) - self._long_period = int(params.get("long_period", 21)) - self._quantity = Decimal(str(params.get("quantity", "0.01"))) - - def reset(self) -> None: - self._closes.clear() - self._prev_short_above = None - - def on_candle(self, candle: Candle) -> Signal | None: - self._closes.append(float(candle.close)) - - if len(self._closes) < self._long_period: - return None - - series = pd.Series(list(self._closes)) - short_ema = series.ewm(span=self._short_period, adjust=False).mean().iloc[-1] - long_ema = series.ewm(span=self._long_period, adjust=False).mean().iloc[-1] - - short_above = short_ema > long_ema - - if self._prev_short_above is None: - self._prev_short_above = short_above - return None - - prev = self._prev_short_above - self._prev_short_above = short_above - - # Golden Cross: short EMA crosses above long EMA - if not prev and short_above: - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.BUY, - price=candle.close, - quantity=self._quantity, - reason=f"EMA Golden Cross (short={short_ema:.2f} > long={long_ema:.2f})", - ) - - # Death Cross: short EMA crosses below long EMA - if prev and not short_above: - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.SELL, - price=candle.close, - quantity=self._quantity, - reason=f"EMA Death Cross (short={short_ema:.2f} < long={long_ema:.2f})", - ) - - return None -``` - -Create `services/strategy-engine/strategies/config/ema_crossover_strategy.yaml`: - -```yaml -short_period: 9 -long_period: 21 -quantity: "0.01" -``` - -- [ ] **Step 4: Run test to verify it passes** - -Run: `pytest services/strategy-engine/tests/test_ema_crossover_strategy.py -v` -Expected: All 5 tests PASS - -- [ ] **Step 5: Commit** - -```bash -git add services/strategy-engine/strategies/ema_crossover_strategy.py \ - services/strategy-engine/strategies/config/ema_crossover_strategy.yaml \ - services/strategy-engine/tests/test_ema_crossover_strategy.py -git commit -m "feat(strategy): add EMA Crossover strategy" -``` - ---- - -## Task 12: VWAP Strategy - -**Files:** -- Create: `services/strategy-engine/strategies/vwap_strategy.py` -- Create: `services/strategy-engine/strategies/config/vwap_strategy.yaml` -- Test: `services/strategy-engine/tests/test_vwap_strategy.py` - -- [ ] **Step 1: Write the failing test** - -Create `services/strategy-engine/tests/test_vwap_strategy.py`: - -```python -"""Tests for VWAP strategy.""" -from decimal import Decimal -from datetime import datetime, timezone - -import pytest - -from shared.models import Candle, OrderSide -from strategies.vwap_strategy import VwapStrategy - - -@pytest.fixture -def strategy(): - s = VwapStrategy() - s.configure({"deviation_threshold": 0.01, "quantity": "0.01"}) - return s - - -def _candle(price: float, volume: float = 10.0) -> Candle: - return Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2025, 1, 1, tzinfo=timezone.utc), - open=Decimal(str(price)), - high=Decimal(str(price + 10)), - low=Decimal(str(price - 10)), - close=Decimal(str(price)), - volume=Decimal(str(volume)), - ) - - -def test_vwap_warmup_period(strategy): - assert strategy.warmup_period == 30 - - -def test_vwap_no_signal_insufficient_data(strategy): - for i in range(10): - result = strategy.on_candle(_candle(100)) - assert result is None - - -def test_vwap_buy_signal_below_vwap_recovery(strategy): - # Build VWAP at ~100, then go below, then recover - signals = [] - for _ in range(30): - strategy.on_candle(_candle(100, 100)) - # Drop below VWAP - for _ in range(5): - strategy.on_candle(_candle(95, 10)) - # Recover to VWAP - sig = strategy.on_candle(_candle(100, 10)) - if sig is not None: - signals.append(sig) - buy_signals = [s for s in signals if s.side == OrderSide.BUY] - assert len(buy_signals) > 0 - - -def test_vwap_sell_signal_above_vwap_recovery(strategy): - signals = [] - for _ in range(30): - strategy.on_candle(_candle(100, 100)) - for _ in range(5): - strategy.on_candle(_candle(105, 10)) - sig = strategy.on_candle(_candle(100, 10)) - if sig is not None: - signals.append(sig) - sell_signals = [s for s in signals if s.side == OrderSide.SELL] - assert len(sell_signals) > 0 - - -def test_vwap_reset_clears_state(strategy): - strategy.on_candle(_candle(100)) - strategy.reset() - assert strategy._cumulative_tp_vol == 0.0 - assert strategy._cumulative_vol == 0.0 -``` - -- [ ] **Step 2: Run test to verify it fails** - -Run: `pytest services/strategy-engine/tests/test_vwap_strategy.py -v` -Expected: FAIL with `ModuleNotFoundError` - -- [ ] **Step 3: Implement VWAP strategy** - -Create `services/strategy-engine/strategies/vwap_strategy.py`: - -```python -"""VWAP (Volume Weighted Average Price) strategy.""" -from decimal import Decimal - -from shared.models import Candle, Signal, OrderSide -from strategies.base import BaseStrategy - - -class VwapStrategy(BaseStrategy): - name: str = "vwap" - - def __init__(self) -> None: - self._deviation_threshold: float = 0.002 - self._quantity: Decimal = Decimal("0.01") - self._cumulative_tp_vol: float = 0.0 - self._cumulative_vol: float = 0.0 - self._candle_count: int = 0 - self._was_below_vwap: bool = False - self._was_above_vwap: bool = False - - @property - def warmup_period(self) -> int: - return 30 - - def configure(self, params: dict) -> None: - self._deviation_threshold = float(params.get("deviation_threshold", 0.002)) - self._quantity = Decimal(str(params.get("quantity", "0.01"))) - - def reset(self) -> None: - self._cumulative_tp_vol = 0.0 - self._cumulative_vol = 0.0 - self._candle_count = 0 - self._was_below_vwap = False - self._was_above_vwap = False - - def on_candle(self, candle: Candle) -> Signal | None: - high = float(candle.high) - low = float(candle.low) - close = float(candle.close) - volume = float(candle.volume) - - typical_price = (high + low + close) / 3.0 - self._cumulative_tp_vol += typical_price * volume - self._cumulative_vol += volume - self._candle_count += 1 - - if self._candle_count < self.warmup_period: - return None - - if self._cumulative_vol == 0: - return None - - vwap = self._cumulative_tp_vol / self._cumulative_vol - deviation = (close - vwap) / vwap if vwap != 0 else 0 - - # Track VWAP deviations - if deviation < -self._deviation_threshold: - self._was_below_vwap = True - self._was_above_vwap = False - elif deviation > self._deviation_threshold: - self._was_above_vwap = True - self._was_below_vwap = False - - # BUY: price was below VWAP and recovered to VWAP (mean reversion) - if self._was_below_vwap and abs(deviation) <= self._deviation_threshold: - self._was_below_vwap = False - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.BUY, - price=candle.close, - quantity=self._quantity, - reason=f"VWAP mean reversion from below (VWAP={vwap:.2f}, deviation={deviation:.4f})", - ) - - # SELL: price was above VWAP and recovered to VWAP - if self._was_above_vwap and abs(deviation) <= self._deviation_threshold: - self._was_above_vwap = False - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.SELL, - price=candle.close, - quantity=self._quantity, - reason=f"VWAP mean reversion from above (VWAP={vwap:.2f}, deviation={deviation:.4f})", - ) - - return None -``` - -Create `services/strategy-engine/strategies/config/vwap_strategy.yaml`: - -```yaml -deviation_threshold: 0.002 -quantity: "0.01" -``` - -- [ ] **Step 4: Run test to verify it passes** - -Run: `pytest services/strategy-engine/tests/test_vwap_strategy.py -v` -Expected: All 5 tests PASS - -- [ ] **Step 5: Commit** - -```bash -git add services/strategy-engine/strategies/vwap_strategy.py \ - services/strategy-engine/strategies/config/vwap_strategy.yaml \ - services/strategy-engine/tests/test_vwap_strategy.py -git commit -m "feat(strategy): add VWAP strategy" -``` - ---- - -## Task 13: Volume Profile Strategy - -**Files:** -- Create: `services/strategy-engine/strategies/volume_profile_strategy.py` -- Create: `services/strategy-engine/strategies/config/volume_profile_strategy.yaml` -- Test: `services/strategy-engine/tests/test_volume_profile_strategy.py` - -- [ ] **Step 1: Write the failing test** - -Create `services/strategy-engine/tests/test_volume_profile_strategy.py`: - -```python -"""Tests for Volume Profile strategy.""" -from decimal import Decimal -from datetime import datetime, timezone - -import pytest - -from shared.models import Candle, OrderSide -from strategies.volume_profile_strategy import VolumeProfileStrategy - - -@pytest.fixture -def strategy(): - s = VolumeProfileStrategy() - s.configure({ - "lookback_period": 10, - "num_bins": 5, - "value_area_pct": 0.7, - "quantity": "0.01", - }) - return s - - -def _candle(price: float, volume: float = 10.0) -> Candle: - return Candle( - symbol="BTCUSDT", - timeframe="1m", - open_time=datetime(2025, 1, 1, tzinfo=timezone.utc), - open=Decimal(str(price)), - high=Decimal(str(price + 5)), - low=Decimal(str(price - 5)), - close=Decimal(str(price)), - volume=Decimal(str(volume)), - ) - - -def test_volume_profile_warmup_period(strategy): - assert strategy.warmup_period == 10 - - -def test_volume_profile_no_signal_insufficient_data(strategy): - for p in [100, 101, 102]: - result = strategy.on_candle(_candle(p)) - assert result is None - - -def test_volume_profile_buy_at_value_area_low(strategy): - # Concentrate volume at 100, then price drops to bottom of value area - signals = [] - for _ in range(10): - strategy.on_candle(_candle(100, 100)) - # Price drops to lower edge - sig = strategy.on_candle(_candle(90, 10)) - if sig is not None: - signals.append(sig) - # Multiple attempts — may need several candles for the signal - for p in [89, 88, 90]: - sig = strategy.on_candle(_candle(p, 10)) - if sig is not None: - signals.append(sig) - buy_signals = [s for s in signals if s.side == OrderSide.BUY] - assert len(buy_signals) > 0 - - -def test_volume_profile_sell_at_value_area_high(strategy): - signals = [] - for _ in range(10): - strategy.on_candle(_candle(100, 100)) - sig = strategy.on_candle(_candle(110, 10)) - if sig is not None: - signals.append(sig) - for p in [111, 112, 110]: - sig = strategy.on_candle(_candle(p, 10)) - if sig is not None: - signals.append(sig) - sell_signals = [s for s in signals if s.side == OrderSide.SELL] - assert len(sell_signals) > 0 - - -def test_volume_profile_reset_clears_state(strategy): - strategy.on_candle(_candle(100)) - strategy.reset() - assert len(strategy._candles) == 0 -``` - -- [ ] **Step 2: Run test to verify it fails** - -Run: `pytest services/strategy-engine/tests/test_volume_profile_strategy.py -v` -Expected: FAIL with `ModuleNotFoundError` - -- [ ] **Step 3: Implement Volume Profile strategy** - -Create `services/strategy-engine/strategies/volume_profile_strategy.py`: - -```python -"""Volume Profile strategy based on Point of Control and Value Area.""" -from collections import deque -from decimal import Decimal - -import numpy as np - -from shared.models import Candle, Signal, OrderSide -from strategies.base import BaseStrategy - - -class VolumeProfileStrategy(BaseStrategy): - name: str = "volume_profile" - - def __init__(self) -> None: - self._lookback_period: int = 100 - self._num_bins: int = 50 - self._value_area_pct: float = 0.7 - self._quantity: Decimal = Decimal("0.01") - self._candles: deque[tuple[float, float]] = deque(maxlen=500) # (close, volume) - self._was_below_va: bool = False - self._was_above_va: bool = False - - @property - def warmup_period(self) -> int: - return self._lookback_period - - def configure(self, params: dict) -> None: - self._lookback_period = int(params.get("lookback_period", 100)) - self._num_bins = int(params.get("num_bins", 50)) - self._value_area_pct = float(params.get("value_area_pct", 0.7)) - self._quantity = Decimal(str(params.get("quantity", "0.01"))) - - def reset(self) -> None: - self._candles.clear() - self._was_below_va = False - self._was_above_va = False - - def _compute_value_area(self) -> tuple[float, float, float] | None: - """Compute POC, value area low, and value area high. - - Returns (poc, va_low, va_high) or None if insufficient data. - """ - if len(self._candles) < self._lookback_period: - return None - - recent = list(self._candles)[-self._lookback_period :] - prices = [c[0] for c in recent] - volumes = [c[1] for c in recent] - - min_price = min(prices) - max_price = max(prices) - if min_price == max_price: - return None - - bin_edges = np.linspace(min_price, max_price, self._num_bins + 1) - volume_profile = np.zeros(self._num_bins) - - for price, vol in zip(prices, volumes): - bin_idx = int((price - min_price) / (max_price - min_price) * (self._num_bins - 1)) - bin_idx = min(bin_idx, self._num_bins - 1) - volume_profile[bin_idx] += vol - - poc_idx = int(np.argmax(volume_profile)) - poc = (bin_edges[poc_idx] + bin_edges[poc_idx + 1]) / 2 - - # Expand from POC to capture value_area_pct of total volume - total_vol = volume_profile.sum() - if total_vol == 0: - return None - - target_vol = total_vol * self._value_area_pct - accumulated = volume_profile[poc_idx] - low_idx = poc_idx - high_idx = poc_idx - - while accumulated < target_vol: - expand_low = low_idx > 0 - expand_high = high_idx < self._num_bins - 1 - - if not expand_low and not expand_high: - break - - low_vol = volume_profile[low_idx - 1] if expand_low else 0 - high_vol = volume_profile[high_idx + 1] if expand_high else 0 - - if low_vol >= high_vol and expand_low: - low_idx -= 1 - accumulated += volume_profile[low_idx] - elif expand_high: - high_idx += 1 - accumulated += volume_profile[high_idx] - else: - low_idx -= 1 - accumulated += volume_profile[low_idx] - - va_low = bin_edges[low_idx] - va_high = bin_edges[high_idx + 1] - - return poc, va_low, va_high - - def on_candle(self, candle: Candle) -> Signal | None: - self._candles.append((float(candle.close), float(candle.volume))) - - result = self._compute_value_area() - if result is None: - return None - - poc, va_low, va_high = result - price = float(candle.close) - - # Track value area penetration - if price < va_low: - self._was_below_va = True - self._was_above_va = False - elif price > va_high: - self._was_above_va = True - self._was_below_va = False - - # BUY: price was below VA and bounced back to VA low (support) - if self._was_below_va and price >= va_low and price <= poc: - self._was_below_va = False - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.BUY, - price=candle.close, - quantity=self._quantity, - reason=f"Volume Profile: bounce at VA low ({va_low:.2f}), POC={poc:.2f}", - ) - - # SELL: price was above VA and pulled back to VA high (resistance) - if self._was_above_va and price <= va_high and price >= poc: - self._was_above_va = False - return Signal( - strategy=self.name, - symbol=candle.symbol, - side=OrderSide.SELL, - price=candle.close, - quantity=self._quantity, - reason=f"Volume Profile: rejection at VA high ({va_high:.2f}), POC={poc:.2f}", - ) - - return None -``` - -Create `services/strategy-engine/strategies/config/volume_profile_strategy.yaml`: - -```yaml -lookback_period: 100 -num_bins: 50 -value_area_pct: 0.7 -quantity: "0.01" -``` - -- [ ] **Step 4: Run test to verify it passes** - -Run: `pytest services/strategy-engine/tests/test_volume_profile_strategy.py -v` -Expected: All 5 tests PASS - -- [ ] **Step 5: Commit** - -```bash -git add services/strategy-engine/strategies/volume_profile_strategy.py \ - services/strategy-engine/strategies/config/volume_profile_strategy.yaml \ - services/strategy-engine/tests/test_volume_profile_strategy.py -git commit -m "feat(strategy): add Volume Profile strategy" -``` - ---- - -## Task 14: Backtest Detailed Metrics - -**Files:** -- Create: `services/backtester/src/backtester/metrics.py` -- Test: `services/backtester/tests/test_metrics.py` - -- [ ] **Step 1: Write the failing test** - -Create `services/backtester/tests/test_metrics.py`: - -```python -"""Tests for detailed backtest metrics.""" -from datetime import datetime, timedelta, timezone -from decimal import Decimal - -import pytest - -from backtester.metrics import TradeRecord, compute_detailed_metrics - - -def _trade(entry_price: float, exit_price: float, qty: float = 1.0, days: int = 1) -> tuple[TradeRecord, TradeRecord]: - entry_time = datetime(2025, 1, 1, tzinfo=timezone.utc) - exit_time = entry_time + timedelta(days=days) - entry = TradeRecord( - time=entry_time, - symbol="BTCUSDT", - side="BUY", - price=Decimal(str(entry_price)), - quantity=Decimal(str(qty)), - ) - exit_rec = TradeRecord( - time=exit_time, - symbol="BTCUSDT", - side="SELL", - price=Decimal(str(exit_price)), - quantity=Decimal(str(qty)), - ) - return entry, exit_rec - - -def test_compute_metrics_basic(): - trades = [] - e1, x1 = _trade(100, 110) # +10 profit - e2, x2 = _trade(100, 95) # -5 loss - trades = [e1, x1, e2, x2] - - metrics = compute_detailed_metrics( - trades=trades, - initial_balance=Decimal("1000"), - final_balance=Decimal("1005"), - ) - - assert metrics.total_trades == 4 - assert metrics.winning_trades == 1 - assert metrics.losing_trades == 1 - assert metrics.win_rate == pytest.approx(50.0, rel=0.01) - assert metrics.total_return == pytest.approx(0.5, rel=0.01) - - -def test_compute_metrics_profit_factor(): - e1, x1 = _trade(100, 120) # +20 - e2, x2 = _trade(100, 90) # -10 - trades = [e1, x1, e2, x2] - - metrics = compute_detailed_metrics( - trades=trades, - initial_balance=Decimal("1000"), - final_balance=Decimal("1010"), - ) - - assert metrics.profit_factor == pytest.approx(2.0, rel=0.01) - - -def test_compute_metrics_max_drawdown(): - # Three trades: +10, -20, +5 => peak 1010, trough 990 - e1, x1 = _trade(100, 110) - e2, x2 = _trade(100, 80) - e3, x3 = _trade(100, 105) - trades = [e1, x1, e2, x2, e3, x3] - - metrics = compute_detailed_metrics( - trades=trades, - initial_balance=Decimal("1000"), - final_balance=Decimal("995"), - ) - - assert metrics.max_drawdown > 0 - - -def test_compute_metrics_sharpe_ratio(): - e1, x1 = _trade(100, 110, days=1) - e2, x2 = _trade(100, 105, days=1) - trades = [e1, x1, e2, x2] - - metrics = compute_detailed_metrics( - trades=trades, - initial_balance=Decimal("1000"), - final_balance=Decimal("1015"), - ) - - # Sharpe should be a finite number - assert metrics.sharpe_ratio != 0 or metrics.sharpe_ratio == 0 - - -def test_compute_metrics_empty_trades(): - metrics = compute_detailed_metrics( - trades=[], - initial_balance=Decimal("1000"), - final_balance=Decimal("1000"), - ) - assert metrics.total_trades == 0 - assert metrics.win_rate == 0.0 - assert metrics.sharpe_ratio == 0.0 -``` - -- [ ] **Step 2: Run test to verify it fails** - -Run: `pytest services/backtester/tests/test_metrics.py -v` -Expected: FAIL with `ModuleNotFoundError: No module named 'backtester.metrics'` - -- [ ] **Step 3: Implement detailed metrics** - -Create `services/backtester/src/backtester/metrics.py`: - -```python -"""Detailed backtest metrics: Sharpe, Sortino, Calmar, drawdown, trade analysis.""" -import math -from dataclasses import dataclass, field -from datetime import datetime, timedelta -from decimal import Decimal - - -@dataclass -class TradeRecord: - time: datetime - symbol: str - side: str - price: Decimal - quantity: Decimal - - -@dataclass -class DetailedMetrics: - # Basic - total_return: float - total_trades: int - winning_trades: int - losing_trades: int - win_rate: float - profit_factor: float - - # Risk - sharpe_ratio: float - sortino_ratio: float - calmar_ratio: float - max_drawdown: float - max_drawdown_duration: timedelta - - # Returns - monthly_returns: dict[str, float] - avg_win: float - avg_loss: float - largest_win: float - largest_loss: float - avg_holding_period: timedelta - - # Individual trades - trade_pairs: list[dict] = field(default_factory=list) - - -def compute_detailed_metrics( - trades: list[TradeRecord], - initial_balance: Decimal, - final_balance: Decimal, -) -> DetailedMetrics: - """Compute detailed metrics from a list of trade records.""" - initial = float(initial_balance) - final = float(final_balance) - - total_return = ((final - initial) / initial * 100) if initial > 0 else 0.0 - - if not trades: - return DetailedMetrics( - total_return=total_return, - total_trades=0, - winning_trades=0, - losing_trades=0, - win_rate=0.0, - profit_factor=0.0, - sharpe_ratio=0.0, - sortino_ratio=0.0, - calmar_ratio=0.0, - max_drawdown=0.0, - max_drawdown_duration=timedelta(0), - monthly_returns={}, - avg_win=0.0, - avg_loss=0.0, - largest_win=0.0, - largest_loss=0.0, - avg_holding_period=timedelta(0), - trade_pairs=[], - ) - - # Pair up BUY/SELL trades - buys: list[TradeRecord] = [] - pairs: list[dict] = [] - pnls: list[float] = [] - holding_periods: list[timedelta] = [] - - for trade in trades: - if trade.side == "BUY": - buys.append(trade) - elif trade.side == "SELL" and buys: - buy = buys.pop(0) - pnl = float(trade.price - buy.price) * float(trade.quantity) - pnls.append(pnl) - holding = trade.time - buy.time - holding_periods.append(holding) - pairs.append({ - "entry_time": buy.time.isoformat(), - "exit_time": trade.time.isoformat(), - "entry_price": float(buy.price), - "exit_price": float(trade.price), - "quantity": float(trade.quantity), - "pnl": pnl, - "pnl_pct": (pnl / (float(buy.price) * float(trade.quantity))) * 100 if float(buy.price) > 0 else 0, - "holding_period": str(holding), - }) - - wins = [p for p in pnls if p > 0] - losses = [p for p in pnls if p < 0] - - winning_trades = len(wins) - losing_trades = len(losses) - win_rate = (winning_trades / len(pnls) * 100) if pnls else 0.0 - - gross_profit = sum(wins) if wins else 0.0 - gross_loss = abs(sum(losses)) if losses else 0.0 - profit_factor = (gross_profit / gross_loss) if gross_loss > 0 else 0.0 - - avg_win = (sum(wins) / len(wins)) if wins else 0.0 - avg_loss = (sum(losses) / len(losses)) if losses else 0.0 - largest_win = max(wins) if wins else 0.0 - largest_loss = min(losses) if losses else 0.0 - avg_holding = ( - sum(holding_periods, timedelta(0)) / len(holding_periods) - if holding_periods - else timedelta(0) - ) - - # Equity curve for drawdown and ratios - equity = [initial] - for pnl in pnls: - equity.append(equity[-1] + pnl) - - # Max drawdown - peak = equity[0] - max_dd = 0.0 - dd_start = 0 - max_dd_duration = timedelta(0) - current_dd_start = 0 - - for i, val in enumerate(equity): - if val > peak: - peak = val - current_dd_start = i - dd = (peak - val) / peak if peak > 0 else 0 - if dd > max_dd: - max_dd = dd - - # Daily returns approximation (per-trade returns) - returns = [] - for i in range(1, len(equity)): - if equity[i - 1] > 0: - returns.append((equity[i] - equity[i - 1]) / equity[i - 1]) - - # Sharpe ratio (annualized for crypto: 365 days) - if returns and len(returns) > 1: - mean_ret = sum(returns) / len(returns) - std_ret = math.sqrt(sum((r - mean_ret) ** 2 for r in returns) / (len(returns) - 1)) - sharpe = (mean_ret / std_ret * math.sqrt(365)) if std_ret > 0 else 0.0 - - # Sortino ratio (downside deviation only) - downside = [r for r in returns if r < 0] - if downside: - downside_std = math.sqrt(sum(r**2 for r in downside) / len(downside)) - sortino = (mean_ret / downside_std * math.sqrt(365)) if downside_std > 0 else 0.0 - else: - sortino = 0.0 - else: - sharpe = 0.0 - sortino = 0.0 - - # Calmar ratio - annualized_return = total_return / 100 # as fraction - calmar = (annualized_return / max_dd) if max_dd > 0 else 0.0 - - # Monthly returns - monthly: dict[str, float] = {} - for pair in pairs: - month_key = pair["exit_time"][:7] # YYYY-MM - monthly[month_key] = monthly.get(month_key, 0.0) + pair["pnl"] - - return DetailedMetrics( - total_return=total_return, - total_trades=len(trades), - winning_trades=winning_trades, - losing_trades=losing_trades, - win_rate=win_rate, - profit_factor=profit_factor, - sharpe_ratio=sharpe, - sortino_ratio=sortino, - calmar_ratio=calmar, - max_drawdown=max_dd * 100, # as percentage - max_drawdown_duration=max_dd_duration, - monthly_returns=monthly, - avg_win=avg_win, - avg_loss=avg_loss, - largest_win=largest_win, - largest_loss=largest_loss, - avg_holding_period=avg_holding, - trade_pairs=pairs, - ) -``` - -- [ ] **Step 4: Run test to verify it passes** - -Run: `pytest services/backtester/tests/test_metrics.py -v` -Expected: All 5 tests PASS - -- [ ] **Step 5: Commit** - -```bash -git add services/backtester/src/backtester/metrics.py \ - services/backtester/tests/test_metrics.py -git commit -m "feat(backtester): add detailed metrics (Sharpe, Sortino, drawdown)" -``` - ---- - -## Task 15: Integrate Metrics into BacktestEngine + Enhanced Reporter - -**Files:** -- Modify: `services/backtester/src/backtester/simulator.py` -- Modify: `services/backtester/src/backtester/engine.py` -- Modify: `services/backtester/src/backtester/reporter.py` -- Modify: `services/backtester/tests/test_engine.py` -- Modify: `services/backtester/tests/test_reporter.py` - -- [ ] **Step 1: Update simulator to produce TradeRecords** - -Add timestamp to `SimulatedTrade` in `services/backtester/src/backtester/simulator.py`. Replace file: - -```python -"""Simulated order executor for backtesting.""" -from dataclasses import dataclass, field -from datetime import datetime, timezone -from decimal import Decimal - -from shared.models import OrderSide, Signal - - -@dataclass -class SimulatedTrade: - symbol: str - side: OrderSide - price: Decimal - quantity: Decimal - balance_after: Decimal - timestamp: datetime = field(default_factory=lambda: datetime.now(timezone.utc)) - - -class OrderSimulator: - """Simulates order execution against a paper balance.""" - - def __init__(self, initial_balance: Decimal) -> None: - self.balance: Decimal = initial_balance - self.positions: dict[str, Decimal] = {} - self.trades: list[SimulatedTrade] = [] - - def execute(self, signal: Signal, timestamp: datetime | None = None) -> bool: - """Execute a signal. Returns True if the trade was accepted.""" - ts = timestamp or datetime.now(timezone.utc) - - if signal.side == OrderSide.BUY: - cost = signal.price * signal.quantity - if cost > self.balance: - return False - self.balance -= cost - self.positions[signal.symbol] = ( - self.positions.get(signal.symbol, Decimal("0")) + signal.quantity - ) - trade_quantity = signal.quantity - else: # SELL - current_position = self.positions.get(signal.symbol, Decimal("0")) - if current_position <= Decimal("0"): - return False - trade_quantity = min(signal.quantity, current_position) - proceeds = signal.price * trade_quantity - self.balance += proceeds - self.positions[signal.symbol] = current_position - trade_quantity - - self.trades.append( - SimulatedTrade( - symbol=signal.symbol, - side=signal.side, - price=signal.price, - quantity=trade_quantity, - balance_after=self.balance, - timestamp=ts, - ) - ) - return True -``` - -- [ ] **Step 2: Update engine to compute DetailedMetrics** - -Replace `services/backtester/src/backtester/engine.py`: - -```python -"""Backtesting engine that runs strategies against historical candle data.""" -from dataclasses import dataclass, field -from decimal import Decimal -from typing import Protocol - -from shared.models import Candle, Signal - -from backtester.metrics import DetailedMetrics, TradeRecord, compute_detailed_metrics -from backtester.simulator import OrderSimulator, SimulatedTrade - - -class StrategyProtocol(Protocol): - name: str - - def on_candle(self, candle: Candle) -> Signal | None: ... - def configure(self, params: dict) -> None: ... - def reset(self) -> None: ... - - -@dataclass -class BacktestResult: - strategy_name: str - symbol: str - total_trades: int - initial_balance: Decimal - final_balance: Decimal - profit: Decimal - profit_pct: Decimal - trades: list[SimulatedTrade] = field(default_factory=list) - detailed: DetailedMetrics | None = None - - @property - def win_rate(self) -> float: - buy_prices: list[Decimal] = [] - wins = 0 - total_pairs = 0 - - for trade in self.trades: - if trade.side.value == "BUY": - buy_prices.append(trade.price) - else: - if buy_prices: - buy_price = buy_prices.pop(0) - total_pairs += 1 - if trade.price > buy_price: - wins += 1 - - if total_pairs == 0: - return 0.0 - return wins / total_pairs * 100 - - -class BacktestEngine: - """Runs a strategy against historical candles using a simulated order executor.""" - - def __init__(self, strategy: StrategyProtocol, initial_balance: Decimal) -> None: - self._strategy = strategy - self._initial_balance = initial_balance - - def run(self, candles: list[Candle]) -> BacktestResult: - """Run the backtest over a list of candles and return a result.""" - simulator = OrderSimulator(self._initial_balance) - - for candle in candles: - signal = self._strategy.on_candle(candle) - if signal is not None: - simulator.execute(signal, timestamp=candle.open_time) - - final_balance = simulator.balance - if candles: - last_price = candles[-1].close - for symbol, qty in simulator.positions.items(): - if qty > Decimal("0"): - final_balance += qty * last_price - - profit = final_balance - self._initial_balance - if self._initial_balance != Decimal("0"): - profit_pct = (profit / self._initial_balance) * Decimal("100") - else: - profit_pct = Decimal("0") - - # Build TradeRecords for detailed metrics - trade_records = [ - TradeRecord( - time=t.timestamp, - symbol=t.symbol, - side=t.side.value, - price=t.price, - quantity=t.quantity, - ) - for t in simulator.trades - ] - - detailed = compute_detailed_metrics( - trades=trade_records, - initial_balance=self._initial_balance, - final_balance=final_balance, - ) - - return BacktestResult( - strategy_name=self._strategy.name, - symbol=candles[0].symbol if candles else "", - total_trades=len(simulator.trades), - initial_balance=self._initial_balance, - final_balance=final_balance, - profit=profit, - profit_pct=profit_pct, - trades=simulator.trades, - detailed=detailed, - ) -``` - -- [ ] **Step 3: Update reporter with rich tables and export** - -Replace `services/backtester/src/backtester/reporter.py`: - -```python -"""Report formatting for backtest results using rich tables.""" -import csv -import io -import json - -from rich.console import Console -from rich.table import Table - -from backtester.engine import BacktestResult - - -def format_report(result: BacktestResult) -> str: - """Format a backtest result into a rich text report.""" - console = Console(file=io.StringIO(), force_terminal=True) - - # Summary table - summary = Table(title="BACKTEST REPORT", show_lines=True) - summary.add_column("Metric", style="bold") - summary.add_column("Value", justify="right") - - summary.add_row("Strategy", result.strategy_name) - summary.add_row("Symbol", result.symbol) - summary.add_row("Initial Balance", f"{result.initial_balance:.2f}") - summary.add_row("Final Balance", f"{result.final_balance:.2f}") - summary.add_row("Profit/Loss", f"{result.profit:.2f}") - summary.add_row("Profit %", f"{result.profit_pct:.2f}%") - summary.add_row("Total Trades", str(result.total_trades)) - summary.add_row("Win Rate", f"{result.win_rate:.2f}%") - - if result.detailed: - d = result.detailed - summary.add_row("Sharpe Ratio", f"{d.sharpe_ratio:.3f}") - summary.add_row("Sortino Ratio", f"{d.sortino_ratio:.3f}") - summary.add_row("Calmar Ratio", f"{d.calmar_ratio:.3f}") - summary.add_row("Max Drawdown", f"{d.max_drawdown:.2f}%") - summary.add_row("Profit Factor", f"{d.profit_factor:.2f}") - summary.add_row("Avg Win", f"{d.avg_win:.2f}") - summary.add_row("Avg Loss", f"{d.avg_loss:.2f}") - summary.add_row("Largest Win", f"{d.largest_win:.2f}") - summary.add_row("Largest Loss", f"{d.largest_loss:.2f}") - summary.add_row("Avg Holding Period", str(d.avg_holding_period)) - - console.print(summary) - - # Monthly returns table - if result.detailed and result.detailed.monthly_returns: - monthly = Table(title="MONTHLY RETURNS") - monthly.add_column("Month") - monthly.add_column("PnL", justify="right") - for month, pnl in sorted(result.detailed.monthly_returns.items()): - style = "green" if pnl >= 0 else "red" - monthly.add_row(month, f"{pnl:.2f}", style=style) - console.print(monthly) - - output = console.file.getvalue() - return output - - -def export_csv(result: BacktestResult) -> str: - """Export trade pairs as CSV.""" - if not result.detailed or not result.detailed.trade_pairs: - return "" - - output = io.StringIO() - writer = csv.DictWriter( - output, - fieldnames=["entry_time", "exit_time", "entry_price", "exit_price", "quantity", "pnl", "pnl_pct", "holding_period"], - ) - writer.writeheader() - for pair in result.detailed.trade_pairs: - writer.writerow(pair) - return output.getvalue() - - -def export_json(result: BacktestResult) -> str: - """Export detailed metrics as JSON.""" - if not result.detailed: - return "{}" - - d = result.detailed - data = { - "total_return": d.total_return, - "total_trades": d.total_trades, - "winning_trades": d.winning_trades, - "losing_trades": d.losing_trades, - "win_rate": d.win_rate, - "profit_factor": d.profit_factor, - "sharpe_ratio": d.sharpe_ratio, - "sortino_ratio": d.sortino_ratio, - "calmar_ratio": d.calmar_ratio, - "max_drawdown": d.max_drawdown, - "monthly_returns": d.monthly_returns, - "avg_win": d.avg_win, - "avg_loss": d.avg_loss, - "largest_win": d.largest_win, - "largest_loss": d.largest_loss, - "trade_pairs": d.trade_pairs, - } - return json.dumps(data, indent=2, default=str) -``` - -- [ ] **Step 4: Run all backtester tests** - -Run: `pytest services/backtester/tests/ -v` -Expected: All tests PASS (existing tests may need minor updates for `timestamp` parameter) - -- [ ] **Step 5: Fix any broken tests** - -If `test_simulator.py` fails due to `timestamp` parameter, the existing tests should still work since `timestamp` defaults to `datetime.now()`. If `test_reporter.py` fails, update it to check for rich output: - -Update `services/backtester/tests/test_reporter.py`: - -```python -"""Tests for backtest report formatter.""" -from decimal import Decimal - -from backtester.engine import BacktestResult -from backtester.reporter import format_report, export_csv, export_json - - -def test_format_report_contains_key_metrics(): - result = BacktestResult( - strategy_name="rsi", - symbol="BTCUSDT", - total_trades=10, - initial_balance=Decimal("10000"), - final_balance=Decimal("10500"), - profit=Decimal("500"), - profit_pct=Decimal("5"), - ) - report = format_report(result) - assert "rsi" in report - assert "BTCUSDT" in report - assert "10000" in report or "10,000" in report - - -def test_export_csv_empty_when_no_detailed(): - result = BacktestResult( - strategy_name="rsi", - symbol="BTCUSDT", - total_trades=0, - initial_balance=Decimal("10000"), - final_balance=Decimal("10000"), - profit=Decimal("0"), - profit_pct=Decimal("0"), - ) - assert export_csv(result) == "" - - -def test_export_json_empty_when_no_detailed(): - result = BacktestResult( - strategy_name="rsi", - symbol="BTCUSDT", - total_trades=0, - initial_balance=Decimal("10000"), - final_balance=Decimal("10000"), - profit=Decimal("0"), - profit_pct=Decimal("0"), - ) - assert export_json(result) == "{}" -``` - -- [ ] **Step 6: Run all backtester tests again** - -Run: `pytest services/backtester/tests/ -v` -Expected: All tests PASS - -- [ ] **Step 7: Commit** - -```bash -git add services/backtester/src/backtester/simulator.py \ - services/backtester/src/backtester/engine.py \ - services/backtester/src/backtester/reporter.py \ - services/backtester/tests/test_engine.py \ - services/backtester/tests/test_reporter.py -git commit -m "feat(backtester): integrate detailed metrics and rich reporter" -``` - ---- - -## Task 16: Final Integration Test - -**Files:** -- All - -- [ ] **Step 1: Run the full test suite** - -Run: `pytest -v` -Expected: All tests PASS - -- [ ] **Step 2: Run linting** - -Run: `make lint` -Expected: No errors - -- [ ] **Step 3: Fix any lint issues** - -Run: `make format` if needed, then `make lint` again. - -- [ ] **Step 4: Verify plugin loader finds all 7 strategies** - -Run: `python -c "from pathlib import Path; from strategy_engine.plugin_loader import load_strategies; s = load_strategies(Path('services/strategy-engine/strategies')); print([x.name for x in s])"` -Expected: `['bollinger', 'ema_crossover', 'grid', 'macd', 'rsi', 'volume_profile', 'vwap']` - -- [ ] **Step 5: Final commit if any fixes were made** - -```bash -git add -A -git commit -m "fix: resolve lint issues and final integration fixes" -``` diff --git a/docs/superpowers/plans/2026-04-02-news-driven-stock-selector.md b/docs/superpowers/plans/2026-04-02-news-driven-stock-selector.md new file mode 100644 index 0000000..0964f21 --- /dev/null +++ b/docs/superpowers/plans/2026-04-02-news-driven-stock-selector.md @@ -0,0 +1,3689 @@ +# News-Driven Stock Selector Implementation Plan + +> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. + +**Goal:** Replace the MOC strategy's fixed symbol list with a dynamic, news-driven stock selection system that continuously collects news/sentiment data and selects 2-3 optimal stocks daily before market close. + +**Architecture:** A new `news-collector` service runs 7 data source collectors on individual poll intervals, storing `NewsItem` records in PostgreSQL and publishing to Redis. A sentiment aggregator computes per-symbol composite scores every 15 minutes. Before market close, a 3-stage stock selector (sentiment candidates → technical filter → LLM final pick) chooses 2-3 stocks and feeds them to the existing MOC strategy. + +**Tech Stack:** Python 3.12+, asyncio, aiohttp, Pydantic, SQLAlchemy 2.0 async, Redis Streams, VADER (nltk), feedparser (RSS), Anthropic SDK (Claude API), Alembic + +--- + +## Phase 1: Shared Foundation (Models, DB, Events) + +### Task 1: Add NewsItem and sentiment models to shared + +**Files:** +- Modify: `shared/src/shared/models.py` +- Create: `shared/src/shared/sentiment_models.py` +- Create: `shared/tests/test_sentiment_models.py` + +- [ ] **Step 1: Write tests for new models** + +Create `shared/tests/test_sentiment_models.py`: + +```python +"""Tests for news and sentiment models.""" + +import pytest +from datetime import datetime, timezone + +from shared.models import NewsCategory, NewsItem, OrderSide +from shared.sentiment_models import SymbolScore, MarketSentiment, SelectedStock, Candidate + + +def test_news_item_defaults(): + item = NewsItem( + source="finnhub", + headline="Test headline", + published_at=datetime(2026, 4, 2, tzinfo=timezone.utc), + sentiment=0.5, + category=NewsCategory.MACRO, + ) + assert item.id # UUID generated + assert item.symbols == [] + assert item.summary is None + assert item.raw_data == {} + assert item.created_at is not None + + +def test_news_item_with_symbols(): + item = NewsItem( + source="rss", + headline="AAPL earnings beat", + published_at=datetime(2026, 4, 2, tzinfo=timezone.utc), + sentiment=0.8, + category=NewsCategory.EARNINGS, + symbols=["AAPL"], + ) + assert item.symbols == ["AAPL"] + assert item.category == NewsCategory.EARNINGS + + +def test_news_category_values(): + assert NewsCategory.POLICY == "policy" + assert NewsCategory.EARNINGS == "earnings" + assert NewsCategory.MACRO == "macro" + assert NewsCategory.SOCIAL == "social" + assert NewsCategory.FILING == "filing" + assert NewsCategory.FED == "fed" + + +def test_symbol_score(): + score = SymbolScore( + symbol="AAPL", + news_score=0.5, + news_count=10, + social_score=0.3, + policy_score=0.0, + filing_score=0.2, + composite=0.3, + updated_at=datetime(2026, 4, 2, tzinfo=timezone.utc), + ) + assert score.symbol == "AAPL" + assert score.composite == 0.3 + + +def test_market_sentiment(): + ms = MarketSentiment( + fear_greed=25, + fear_greed_label="Extreme Fear", + vix=32.5, + fed_stance="hawkish", + market_regime="risk_off", + updated_at=datetime(2026, 4, 2, tzinfo=timezone.utc), + ) + assert ms.market_regime == "risk_off" + assert ms.vix == 32.5 + + +def test_market_sentiment_no_vix(): + ms = MarketSentiment( + fear_greed=50, + fear_greed_label="Neutral", + fed_stance="neutral", + market_regime="neutral", + updated_at=datetime(2026, 4, 2, tzinfo=timezone.utc), + ) + assert ms.vix is None + + +def test_selected_stock(): + ss = SelectedStock( + symbol="NVDA", + side=OrderSide.BUY, + conviction=0.85, + reason="CHIPS Act expansion", + key_news=["Trump signs CHIPS Act expansion"], + ) + assert ss.conviction == 0.85 + assert len(ss.key_news) == 1 + + +def test_candidate(): + c = Candidate( + symbol="TSLA", + source="sentiment", + direction=OrderSide.BUY, + score=0.75, + reason="High social buzz", + ) + assert c.direction == OrderSide.BUY + + c2 = Candidate( + symbol="XOM", + source="llm", + score=0.6, + reason="Oil price surge", + ) + assert c2.direction is None +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest shared/tests/test_sentiment_models.py -v` +Expected: FAIL — `NewsCategory`, `NewsItem` not found in `shared.models`, `shared.sentiment_models` does not exist + +- [ ] **Step 3: Add NewsCategory and NewsItem to shared/models.py** + +Add to the end of `shared/src/shared/models.py`: + +```python +class NewsCategory(str, Enum): + POLICY = "policy" + EARNINGS = "earnings" + MACRO = "macro" + SOCIAL = "social" + FILING = "filing" + FED = "fed" + + +class NewsItem(BaseModel): + id: str = Field(default_factory=lambda: str(uuid.uuid4())) + source: str + headline: str + summary: Optional[str] = None + url: Optional[str] = None + published_at: datetime + symbols: list[str] = [] + sentiment: float + category: NewsCategory + raw_data: dict = {} + created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc)) +``` + +- [ ] **Step 4: Create shared/src/shared/sentiment_models.py** + +```python +"""Sentiment scoring and stock selection models.""" + +from datetime import datetime +from typing import Optional + +from pydantic import BaseModel + +from shared.models import OrderSide + + +class SymbolScore(BaseModel): + symbol: str + news_score: float + news_count: int + social_score: float + policy_score: float + filing_score: float + composite: float + updated_at: datetime + + +class MarketSentiment(BaseModel): + fear_greed: int + fear_greed_label: str + vix: Optional[float] = None + fed_stance: str + market_regime: str + updated_at: datetime + + +class SelectedStock(BaseModel): + symbol: str + side: OrderSide + conviction: float + reason: str + key_news: list[str] + + +class Candidate(BaseModel): + symbol: str + source: str + direction: Optional[OrderSide] = None + score: float + reason: str +``` + +- [ ] **Step 5: Run tests to verify they pass** + +Run: `pytest shared/tests/test_sentiment_models.py -v` +Expected: All 9 tests PASS + +- [ ] **Step 6: Commit** + +```bash +git add shared/src/shared/models.py shared/src/shared/sentiment_models.py shared/tests/test_sentiment_models.py +git commit -m "feat: add NewsItem, sentiment scoring, and stock selection models" +``` + +--- + +### Task 2: Add SQLAlchemy ORM models for news tables + +**Files:** +- Modify: `shared/src/shared/sa_models.py` +- Create: `shared/tests/test_sa_news_models.py` + +- [ ] **Step 1: Write tests for new SA models** + +Create `shared/tests/test_sa_news_models.py`: + +```python +"""Tests for news-related SQLAlchemy models.""" + +from shared.sa_models import NewsItemRow, SymbolScoreRow, MarketSentimentRow, StockSelectionRow + + +def test_news_item_row_tablename(): + assert NewsItemRow.__tablename__ == "news_items" + + +def test_symbol_score_row_tablename(): + assert SymbolScoreRow.__tablename__ == "symbol_scores" + + +def test_market_sentiment_row_tablename(): + assert MarketSentimentRow.__tablename__ == "market_sentiment" + + +def test_stock_selection_row_tablename(): + assert StockSelectionRow.__tablename__ == "stock_selections" + + +def test_news_item_row_columns(): + cols = {c.name for c in NewsItemRow.__table__.columns} + assert cols >= {"id", "source", "headline", "published_at", "sentiment", "category"} + + +def test_symbol_score_row_columns(): + cols = {c.name for c in SymbolScoreRow.__table__.columns} + assert cols >= {"id", "symbol", "news_score", "composite", "updated_at"} +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest shared/tests/test_sa_news_models.py -v` +Expected: FAIL — import errors + +- [ ] **Step 3: Add ORM models to sa_models.py** + +Add to the end of `shared/src/shared/sa_models.py`: + +```python +class NewsItemRow(Base): + __tablename__ = "news_items" + + id: Mapped[str] = mapped_column(Text, primary_key=True) + source: Mapped[str] = mapped_column(Text, nullable=False) + headline: Mapped[str] = mapped_column(Text, nullable=False) + summary: Mapped[str | None] = mapped_column(Text) + url: Mapped[str | None] = mapped_column(Text) + published_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False) + symbols: Mapped[str | None] = mapped_column(Text) # JSON-encoded list + sentiment: Mapped[float] = mapped_column(sa.Float, nullable=False) + category: Mapped[str] = mapped_column(Text, nullable=False) + raw_data: Mapped[str | None] = mapped_column(Text) # JSON string + created_at: Mapped[datetime] = mapped_column( + DateTime(timezone=True), nullable=False, server_default=sa.func.now() + ) + + +class SymbolScoreRow(Base): + __tablename__ = "symbol_scores" + + id: Mapped[str] = mapped_column(Text, primary_key=True) + symbol: Mapped[str] = mapped_column(Text, nullable=False, unique=True) + news_score: Mapped[float] = mapped_column(sa.Float, nullable=False, server_default="0") + news_count: Mapped[int] = mapped_column(sa.Integer, nullable=False, server_default="0") + social_score: Mapped[float] = mapped_column(sa.Float, nullable=False, server_default="0") + policy_score: Mapped[float] = mapped_column(sa.Float, nullable=False, server_default="0") + filing_score: Mapped[float] = mapped_column(sa.Float, nullable=False, server_default="0") + composite: Mapped[float] = mapped_column(sa.Float, nullable=False, server_default="0") + updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False) + + +class MarketSentimentRow(Base): + __tablename__ = "market_sentiment" + + id: Mapped[str] = mapped_column(Text, primary_key=True) + fear_greed: Mapped[int] = mapped_column(sa.Integer, nullable=False) + fear_greed_label: Mapped[str] = mapped_column(Text, nullable=False) + vix: Mapped[float | None] = mapped_column(sa.Float) + fed_stance: Mapped[str] = mapped_column(Text, nullable=False, server_default="neutral") + market_regime: Mapped[str] = mapped_column(Text, nullable=False, server_default="neutral") + updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False) + + +class StockSelectionRow(Base): + __tablename__ = "stock_selections" + + id: Mapped[str] = mapped_column(Text, primary_key=True) + trade_date: Mapped[datetime] = mapped_column(sa.Date, nullable=False) + symbol: Mapped[str] = mapped_column(Text, nullable=False) + side: Mapped[str] = mapped_column(Text, nullable=False) + conviction: Mapped[float] = mapped_column(sa.Float, nullable=False) + reason: Mapped[str] = mapped_column(Text, nullable=False) + key_news: Mapped[str | None] = mapped_column(Text) # JSON string + sentiment_snapshot: Mapped[str | None] = mapped_column(Text) # JSON string + created_at: Mapped[datetime] = mapped_column( + DateTime(timezone=True), nullable=False, server_default=sa.func.now() + ) +``` + +Also add `import sqlalchemy as sa` to the imports at the top of `sa_models.py`. + +- [ ] **Step 4: Run tests to verify they pass** + +Run: `pytest shared/tests/test_sa_news_models.py -v` +Expected: All 6 tests PASS + +- [ ] **Step 5: Commit** + +```bash +git add shared/src/shared/sa_models.py shared/tests/test_sa_news_models.py +git commit -m "feat: add SQLAlchemy ORM models for news, scores, selections" +``` + +--- + +### Task 3: Create Alembic migration for news tables + +**Files:** +- Create: `shared/alembic/versions/002_news_sentiment_tables.py` + +- [ ] **Step 1: Create migration file** + +Create `shared/alembic/versions/002_news_sentiment_tables.py`: + +```python +"""Add news, sentiment, and stock selection tables + +Revision ID: 002 +Revises: 001 +Create Date: 2026-04-02 +""" + +from typing import Sequence, Union + +from alembic import op +import sqlalchemy as sa + +revision: str = "002" +down_revision: Union[str, None] = "001" +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + + +def upgrade() -> None: + op.create_table( + "news_items", + sa.Column("id", sa.Text, primary_key=True), + sa.Column("source", sa.Text, nullable=False), + sa.Column("headline", sa.Text, nullable=False), + sa.Column("summary", sa.Text), + sa.Column("url", sa.Text), + sa.Column("published_at", sa.DateTime(timezone=True), nullable=False), + sa.Column("symbols", sa.Text), + sa.Column("sentiment", sa.Float, nullable=False), + sa.Column("category", sa.Text, nullable=False), + sa.Column("raw_data", sa.Text), + sa.Column("created_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.func.now()), + ) + op.create_index("idx_news_items_published", "news_items", ["published_at"]) + op.create_index("idx_news_items_source", "news_items", ["source"]) + + op.create_table( + "symbol_scores", + sa.Column("id", sa.Text, primary_key=True), + sa.Column("symbol", sa.Text, nullable=False, unique=True), + sa.Column("news_score", sa.Float, nullable=False, server_default="0"), + sa.Column("news_count", sa.Integer, nullable=False, server_default="0"), + sa.Column("social_score", sa.Float, nullable=False, server_default="0"), + sa.Column("policy_score", sa.Float, nullable=False, server_default="0"), + sa.Column("filing_score", sa.Float, nullable=False, server_default="0"), + sa.Column("composite", sa.Float, nullable=False, server_default="0"), + sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False), + ) + + op.create_table( + "market_sentiment", + sa.Column("id", sa.Text, primary_key=True), + sa.Column("fear_greed", sa.Integer, nullable=False), + sa.Column("fear_greed_label", sa.Text, nullable=False), + sa.Column("vix", sa.Float), + sa.Column("fed_stance", sa.Text, nullable=False, server_default="neutral"), + sa.Column("market_regime", sa.Text, nullable=False, server_default="neutral"), + sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False), + ) + + op.create_table( + "stock_selections", + sa.Column("id", sa.Text, primary_key=True), + sa.Column("trade_date", sa.Date, nullable=False), + sa.Column("symbol", sa.Text, nullable=False), + sa.Column("side", sa.Text, nullable=False), + sa.Column("conviction", sa.Float, nullable=False), + sa.Column("reason", sa.Text, nullable=False), + sa.Column("key_news", sa.Text), + sa.Column("sentiment_snapshot", sa.Text), + sa.Column("created_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.func.now()), + ) + op.create_index("idx_stock_selections_date", "stock_selections", ["trade_date"]) + + +def downgrade() -> None: + op.drop_table("stock_selections") + op.drop_table("market_sentiment") + op.drop_table("symbol_scores") + op.drop_table("news_items") +``` + +- [ ] **Step 2: Verify migration imports correctly** + +Run: `cd shared && python -c "from alembic.versions import *; print('OK')" && cd ..` +Or simply: `python -c "import importlib.util; s=importlib.util.spec_from_file_location('m','shared/alembic/versions/002_news_sentiment_tables.py'); m=importlib.util.module_from_spec(s); s.loader.exec_module(m); print('OK')"` +Expected: OK (no import errors) + +- [ ] **Step 3: Commit** + +```bash +git add shared/alembic/versions/002_news_sentiment_tables.py +git commit -m "feat: add Alembic migration for news and sentiment tables" +``` + +--- + +### Task 4: Add NewsEvent to shared events and DB methods for news + +**Files:** +- Modify: `shared/src/shared/events.py` +- Modify: `shared/src/shared/db.py` +- Create: `shared/tests/test_news_events.py` +- Create: `shared/tests/test_db_news.py` + +- [ ] **Step 1: Write tests for NewsEvent** + +Create `shared/tests/test_news_events.py`: + +```python +"""Tests for NewsEvent.""" + +from datetime import datetime, timezone + +from shared.models import NewsCategory, NewsItem +from shared.events import NewsEvent, EventType, Event + + +def test_news_event_to_dict(): + item = NewsItem( + source="finnhub", + headline="Test", + published_at=datetime(2026, 4, 2, tzinfo=timezone.utc), + sentiment=0.5, + category=NewsCategory.MACRO, + ) + event = NewsEvent(data=item) + d = event.to_dict() + assert d["type"] == EventType.NEWS + assert d["data"]["source"] == "finnhub" + + +def test_news_event_from_raw(): + raw = { + "type": "NEWS", + "data": { + "id": "abc", + "source": "rss", + "headline": "Test headline", + "published_at": "2026-04-02T00:00:00+00:00", + "sentiment": 0.3, + "category": "earnings", + "symbols": ["AAPL"], + "raw_data": {}, + }, + } + event = NewsEvent.from_raw(raw) + assert event.data.source == "rss" + assert event.data.symbols == ["AAPL"] + + +def test_event_dispatcher_news(): + raw = { + "type": "NEWS", + "data": { + "id": "abc", + "source": "finnhub", + "headline": "Test", + "published_at": "2026-04-02T00:00:00+00:00", + "sentiment": 0.0, + "category": "macro", + "raw_data": {}, + }, + } + event = Event.from_dict(raw) + assert isinstance(event, NewsEvent) +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest shared/tests/test_news_events.py -v` +Expected: FAIL — `NewsEvent` not in events.py, `EventType.NEWS` missing + +- [ ] **Step 3: Add NewsEvent to events.py** + +Add `NEWS = "NEWS"` to `EventType` enum. + +Add `NewsEvent` class and register it in `_EVENT_TYPE_MAP`: + +```python +from shared.models import Candle, Signal, Order, NewsItem + +class NewsEvent(BaseModel): + type: EventType = EventType.NEWS + data: NewsItem + + def to_dict(self) -> dict: + return { + "type": self.type, + "data": self.data.model_dump(mode="json"), + } + + @classmethod + def from_raw(cls, raw: dict) -> "NewsEvent": + return cls(type=raw["type"], data=NewsItem(**raw["data"])) +``` + +Add to `_EVENT_TYPE_MAP`: +```python +EventType.NEWS: NewsEvent, +``` + +- [ ] **Step 4: Run event tests to verify they pass** + +Run: `pytest shared/tests/test_news_events.py -v` +Expected: All 3 tests PASS + +- [ ] **Step 5: Run all existing event tests to check no regressions** + +Run: `pytest shared/tests/test_events.py -v` +Expected: All existing tests PASS + +- [ ] **Step 6: Write tests for DB news methods** + +Create `shared/tests/test_db_news.py`: + +```python +"""Tests for database news/sentiment methods. + +These tests use an in-memory SQLite database. +""" + +import json +import uuid +import pytest +from datetime import datetime, date, timezone + +from shared.db import Database +from shared.models import NewsItem, NewsCategory +from shared.sentiment_models import SymbolScore, MarketSentiment + + +@pytest.fixture +async def db(): + database = Database("sqlite+aiosqlite://") + await database.connect() + yield database + await database.close() + + +async def test_insert_and_get_news_items(db): + item = NewsItem( + source="finnhub", + headline="AAPL earnings beat", + published_at=datetime(2026, 4, 2, 12, 0, tzinfo=timezone.utc), + sentiment=0.8, + category=NewsCategory.EARNINGS, + symbols=["AAPL"], + ) + await db.insert_news_item(item) + items = await db.get_recent_news(hours=24) + assert len(items) == 1 + assert items[0]["headline"] == "AAPL earnings beat" + + +async def test_upsert_symbol_score(db): + score = SymbolScore( + symbol="AAPL", + news_score=0.5, + news_count=10, + social_score=0.3, + policy_score=0.0, + filing_score=0.2, + composite=0.3, + updated_at=datetime(2026, 4, 2, tzinfo=timezone.utc), + ) + await db.upsert_symbol_score(score) + scores = await db.get_top_symbol_scores(limit=5) + assert len(scores) == 1 + assert scores[0]["symbol"] == "AAPL" + + +async def test_upsert_market_sentiment(db): + ms = MarketSentiment( + fear_greed=55, + fear_greed_label="Neutral", + vix=18.2, + fed_stance="neutral", + market_regime="neutral", + updated_at=datetime(2026, 4, 2, tzinfo=timezone.utc), + ) + await db.upsert_market_sentiment(ms) + result = await db.get_latest_market_sentiment() + assert result is not None + assert result["fear_greed"] == 55 + + +async def test_insert_stock_selection(db): + await db.insert_stock_selection( + trade_date=date(2026, 4, 2), + symbol="NVDA", + side="BUY", + conviction=0.85, + reason="CHIPS Act", + key_news=["Trump signs CHIPS expansion"], + sentiment_snapshot={"composite": 0.8}, + ) + selections = await db.get_stock_selections(date(2026, 4, 2)) + assert len(selections) == 1 + assert selections[0]["symbol"] == "NVDA" +``` + +- [ ] **Step 7: Run DB news tests to verify they fail** + +Run: `pytest shared/tests/test_db_news.py -v` +Expected: FAIL — methods not yet on Database class + +- [ ] **Step 8: Add news/sentiment DB methods to db.py** + +Add to `shared/src/shared/db.py` — new import at top: + +```python +import json +import uuid +from datetime import date +from shared.models import NewsItem +from shared.sentiment_models import SymbolScore, MarketSentiment +from shared.sa_models import NewsItemRow, SymbolScoreRow, MarketSentimentRow, StockSelectionRow +``` + +Add these methods to the `Database` class: + +```python + async def insert_news_item(self, item: NewsItem) -> None: + """Insert a news item.""" + row = NewsItemRow( + id=item.id, + source=item.source, + headline=item.headline, + summary=item.summary, + url=item.url, + published_at=item.published_at, + symbols=json.dumps(item.symbols), + sentiment=item.sentiment, + category=item.category.value, + raw_data=json.dumps(item.raw_data), + created_at=item.created_at, + ) + async with self._session_factory() as session: + try: + session.add(row) + await session.commit() + except Exception: + await session.rollback() + raise + + async def get_recent_news(self, hours: int = 24) -> list[dict]: + """Retrieve news items from the last N hours.""" + since = datetime.now(timezone.utc) - timedelta(hours=hours) + stmt = ( + select(NewsItemRow) + .where(NewsItemRow.published_at >= since) + .order_by(NewsItemRow.published_at.desc()) + ) + async with self._session_factory() as session: + result = await session.execute(stmt) + rows = result.scalars().all() + return [ + { + "id": r.id, + "source": r.source, + "headline": r.headline, + "summary": r.summary, + "url": r.url, + "published_at": r.published_at, + "symbols": json.loads(r.symbols) if r.symbols else [], + "sentiment": r.sentiment, + "category": r.category, + "created_at": r.created_at, + } + for r in rows + ] + + async def upsert_symbol_score(self, score: SymbolScore) -> None: + """Insert or update a symbol score.""" + async with self._session_factory() as session: + try: + existing = await session.execute( + select(SymbolScoreRow).where(SymbolScoreRow.symbol == score.symbol) + ) + row = existing.scalar_one_or_none() + if row: + row.news_score = score.news_score + row.news_count = score.news_count + row.social_score = score.social_score + row.policy_score = score.policy_score + row.filing_score = score.filing_score + row.composite = score.composite + row.updated_at = score.updated_at + else: + row = SymbolScoreRow( + id=str(uuid.uuid4()), + symbol=score.symbol, + news_score=score.news_score, + news_count=score.news_count, + social_score=score.social_score, + policy_score=score.policy_score, + filing_score=score.filing_score, + composite=score.composite, + updated_at=score.updated_at, + ) + session.add(row) + await session.commit() + except Exception: + await session.rollback() + raise + + async def get_top_symbol_scores(self, limit: int = 20) -> list[dict]: + """Get top symbol scores ordered by composite descending.""" + stmt = ( + select(SymbolScoreRow) + .order_by(SymbolScoreRow.composite.desc()) + .limit(limit) + ) + async with self._session_factory() as session: + result = await session.execute(stmt) + rows = result.scalars().all() + return [ + { + "symbol": r.symbol, + "news_score": r.news_score, + "news_count": r.news_count, + "social_score": r.social_score, + "policy_score": r.policy_score, + "filing_score": r.filing_score, + "composite": r.composite, + "updated_at": r.updated_at, + } + for r in rows + ] + + async def upsert_market_sentiment(self, ms: MarketSentiment) -> None: + """Insert or update the latest market sentiment (single row, id='latest').""" + async with self._session_factory() as session: + try: + existing = await session.execute( + select(MarketSentimentRow).where(MarketSentimentRow.id == "latest") + ) + row = existing.scalar_one_or_none() + if row: + row.fear_greed = ms.fear_greed + row.fear_greed_label = ms.fear_greed_label + row.vix = ms.vix + row.fed_stance = ms.fed_stance + row.market_regime = ms.market_regime + row.updated_at = ms.updated_at + else: + row = MarketSentimentRow( + id="latest", + fear_greed=ms.fear_greed, + fear_greed_label=ms.fear_greed_label, + vix=ms.vix, + fed_stance=ms.fed_stance, + market_regime=ms.market_regime, + updated_at=ms.updated_at, + ) + session.add(row) + await session.commit() + except Exception: + await session.rollback() + raise + + async def get_latest_market_sentiment(self) -> dict | None: + """Get the latest market sentiment.""" + stmt = select(MarketSentimentRow).where(MarketSentimentRow.id == "latest") + async with self._session_factory() as session: + result = await session.execute(stmt) + r = result.scalar_one_or_none() + if r is None: + return None + return { + "fear_greed": r.fear_greed, + "fear_greed_label": r.fear_greed_label, + "vix": r.vix, + "fed_stance": r.fed_stance, + "market_regime": r.market_regime, + "updated_at": r.updated_at, + } + + async def insert_stock_selection( + self, + trade_date: date, + symbol: str, + side: str, + conviction: float, + reason: str, + key_news: list[str], + sentiment_snapshot: dict, + ) -> None: + """Insert a stock selection record.""" + row = StockSelectionRow( + id=str(uuid.uuid4()), + trade_date=trade_date, + symbol=symbol, + side=side, + conviction=conviction, + reason=reason, + key_news=json.dumps(key_news), + sentiment_snapshot=json.dumps(sentiment_snapshot), + ) + async with self._session_factory() as session: + try: + session.add(row) + await session.commit() + except Exception: + await session.rollback() + raise + + async def get_stock_selections(self, trade_date: date) -> list[dict]: + """Get stock selections for a specific date.""" + stmt = ( + select(StockSelectionRow) + .where(StockSelectionRow.trade_date == trade_date) + .order_by(StockSelectionRow.conviction.desc()) + ) + async with self._session_factory() as session: + result = await session.execute(stmt) + rows = result.scalars().all() + return [ + { + "symbol": r.symbol, + "side": r.side, + "conviction": r.conviction, + "reason": r.reason, + "key_news": json.loads(r.key_news) if r.key_news else [], + "sentiment_snapshot": json.loads(r.sentiment_snapshot) if r.sentiment_snapshot else {}, + } + for r in rows + ] +``` + +- [ ] **Step 9: Run DB news tests to verify they pass** + +Run: `pytest shared/tests/test_db_news.py -v` +Expected: All 4 tests PASS + +Note: These tests require `aiosqlite` package. If not installed: `pip install aiosqlite` + +- [ ] **Step 10: Run all shared tests to check no regressions** + +Run: `pytest shared/tests/ -v` +Expected: All tests PASS + +- [ ] **Step 11: Commit** + +```bash +git add shared/src/shared/events.py shared/src/shared/db.py shared/tests/test_news_events.py shared/tests/test_db_news.py +git commit -m "feat: add NewsEvent, DB methods for news/sentiment/selections" +``` + +--- + +### Task 5: Update Settings with new env vars + +**Files:** +- Modify: `shared/src/shared/config.py` +- Modify: `.env.example` + +- [ ] **Step 1: Add new settings to config.py** + +Add these fields to the `Settings` class in `shared/src/shared/config.py`: + +```python + # News collector + finnhub_api_key: str = "" + news_poll_interval: int = 300 + sentiment_aggregate_interval: int = 900 + # Stock selector + selector_candidates_time: str = "15:00" + selector_filter_time: str = "15:15" + selector_final_time: str = "15:30" + selector_max_picks: int = 3 + # LLM + anthropic_api_key: str = "" + anthropic_model: str = "claude-sonnet-4-20250514" +``` + +- [ ] **Step 2: Add to .env.example** + +Append to `.env.example`: + +```bash + +# News Collector +FINNHUB_API_KEY= +NEWS_POLL_INTERVAL=300 +SENTIMENT_AGGREGATE_INTERVAL=900 + +# Stock Selector +SELECTOR_CANDIDATES_TIME=15:00 +SELECTOR_FILTER_TIME=15:15 +SELECTOR_FINAL_TIME=15:30 +SELECTOR_MAX_PICKS=3 + +# LLM (for stock selector) +ANTHROPIC_API_KEY= +ANTHROPIC_MODEL=claude-sonnet-4-20250514 +``` + +- [ ] **Step 3: Commit** + +```bash +git add shared/src/shared/config.py .env.example +git commit -m "feat: add news collector and stock selector config settings" +``` + +--- + +## Phase 2: News Collector Service + +### Task 6: Scaffold news-collector service + +**Files:** +- Create: `services/news-collector/pyproject.toml` +- Create: `services/news-collector/Dockerfile` +- Create: `services/news-collector/src/news_collector/__init__.py` +- Create: `services/news-collector/src/news_collector/config.py` +- Create: `services/news-collector/src/news_collector/collectors/__init__.py` +- Create: `services/news-collector/src/news_collector/collectors/base.py` +- Create: `services/news-collector/tests/__init__.py` + +- [ ] **Step 1: Create pyproject.toml** + +Create `services/news-collector/pyproject.toml`: + +```toml +[project] +name = "news-collector" +version = "0.1.0" +description = "News and sentiment data collector service" +requires-python = ">=3.12" +dependencies = [ + "trading-shared", + "feedparser>=6.0", + "nltk>=3.8", + "aiohttp>=3.9", +] + +[project.optional-dependencies] +dev = [ + "pytest>=8.0", + "pytest-asyncio>=0.23", + "aioresponses>=0.7", +] + +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[tool.hatch.build.targets.wheel] +packages = ["src/news_collector"] +``` + +- [ ] **Step 2: Create Dockerfile** + +Create `services/news-collector/Dockerfile`: + +```dockerfile +FROM python:3.12-slim +WORKDIR /app +COPY shared/ shared/ +RUN pip install --no-cache-dir ./shared +COPY services/news-collector/ services/news-collector/ +RUN pip install --no-cache-dir ./services/news-collector +RUN python -c "import nltk; nltk.download('vader_lexicon', quiet=True)" +ENV PYTHONPATH=/app +CMD ["python", "-m", "news_collector.main"] +``` + +- [ ] **Step 3: Create config.py** + +Create `services/news-collector/src/news_collector/config.py`: + +```python +"""News Collector configuration.""" + +from shared.config import Settings + + +class NewsCollectorConfig(Settings): + health_port: int = 8084 + finnhub_api_key: str = "" + news_poll_interval: int = 300 + sentiment_aggregate_interval: int = 900 +``` + +- [ ] **Step 4: Create BaseCollector** + +Create `services/news-collector/src/news_collector/collectors/base.py`: + +```python +"""Base class for all news collectors.""" + +from abc import ABC, abstractmethod + +from shared.models import NewsItem + + +class BaseCollector(ABC): + name: str = "base" + poll_interval: int = 300 # seconds + + @abstractmethod + async def collect(self) -> list[NewsItem]: + """Collect news items from the source.""" + + @abstractmethod + async def is_available(self) -> bool: + """Check if this data source is accessible.""" +``` + +- [ ] **Step 5: Create __init__.py files** + +Create `services/news-collector/src/news_collector/__init__.py`: +```python +"""News collector service.""" +``` + +Create `services/news-collector/src/news_collector/collectors/__init__.py`: +```python +"""News collectors.""" +``` + +Create `services/news-collector/tests/__init__.py`: +```python +``` + +- [ ] **Step 6: Commit** + +```bash +git add services/news-collector/ +git commit -m "feat: scaffold news-collector service with BaseCollector" +``` + +--- + +### Task 7: Implement Finnhub news collector + +**Files:** +- Create: `services/news-collector/src/news_collector/collectors/finnhub.py` +- Create: `services/news-collector/tests/test_finnhub.py` + +- [ ] **Step 1: Write tests** + +Create `services/news-collector/tests/test_finnhub.py`: + +```python +"""Tests for Finnhub news collector.""" + +import pytest +from unittest.mock import AsyncMock, patch +from datetime import datetime, timezone + +from news_collector.collectors.finnhub import FinnhubCollector + + +@pytest.fixture +def collector(): + return FinnhubCollector(api_key="test_key") + + +def test_collector_name(collector): + assert collector.name == "finnhub" + assert collector.poll_interval == 300 + + +async def test_is_available_with_key(collector): + assert await collector.is_available() is True + + +async def test_is_available_without_key(): + c = FinnhubCollector(api_key="") + assert await c.is_available() is False + + +async def test_collect_parses_response(collector): + mock_response = [ + { + "category": "top news", + "datetime": 1711929600, + "headline": "AAPL beats earnings", + "id": 12345, + "related": "AAPL", + "source": "MarketWatch", + "summary": "Apple reported better than expected...", + "url": "https://example.com/article", + }, + { + "category": "top news", + "datetime": 1711929000, + "headline": "Fed holds rates steady", + "id": 12346, + "related": "", + "source": "Reuters", + "summary": "The Federal Reserve...", + "url": "https://example.com/fed", + }, + ] + + with patch.object(collector, "_fetch_news", new_callable=AsyncMock, return_value=mock_response): + items = await collector.collect() + + assert len(items) == 2 + assert items[0].source == "finnhub" + assert items[0].headline == "AAPL beats earnings" + assert items[0].symbols == ["AAPL"] + assert items[0].url == "https://example.com/article" + assert isinstance(items[0].sentiment, float) + # Second item has no related ticker + assert items[1].symbols == [] + + +async def test_collect_handles_empty_response(collector): + with patch.object(collector, "_fetch_news", new_callable=AsyncMock, return_value=[]): + items = await collector.collect() + assert items == [] +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest services/news-collector/tests/test_finnhub.py -v` +Expected: FAIL — module not found + +- [ ] **Step 3: Implement FinnhubCollector** + +Create `services/news-collector/src/news_collector/collectors/finnhub.py`: + +```python +"""Finnhub market news collector (free tier: 60 req/min).""" + +import logging +from datetime import datetime, timezone + +import aiohttp +from nltk.sentiment.vader import SentimentIntensityAnalyzer + +from shared.models import NewsCategory, NewsItem +from news_collector.collectors.base import BaseCollector + +logger = logging.getLogger(__name__) + +FINNHUB_NEWS_URL = "https://finnhub.io/api/v1/news" + + +class FinnhubCollector(BaseCollector): + name = "finnhub" + poll_interval = 300 # 5 minutes + + def __init__(self, api_key: str) -> None: + self._api_key = api_key + self._vader = SentimentIntensityAnalyzer() + + async def is_available(self) -> bool: + return bool(self._api_key) + + async def _fetch_news(self) -> list[dict]: + """Fetch general news from Finnhub API.""" + params = {"category": "general", "token": self._api_key} + async with aiohttp.ClientSession() as session: + async with session.get(FINNHUB_NEWS_URL, params=params) as resp: + if resp.status != 200: + logger.warning("finnhub_fetch_failed", status=resp.status) + return [] + return await resp.json() + + def _analyze_sentiment(self, text: str) -> float: + """Return VADER compound score (-1.0 to 1.0).""" + scores = self._vader.polarity_scores(text) + return scores["compound"] + + def _extract_symbols(self, related: str) -> list[str]: + """Parse Finnhub 'related' field into symbol list.""" + if not related or not related.strip(): + return [] + return [s.strip() for s in related.split(",") if s.strip()] + + def _categorize(self, article: dict) -> NewsCategory: + """Determine category from article content.""" + headline = article.get("headline", "").lower() + if any(w in headline for w in ["fed", "fomc", "rate", "inflation"]): + return NewsCategory.FED + if any(w in headline for w in ["tariff", "sanction", "regulation", "trump", "biden", "congress"]): + return NewsCategory.POLICY + if any(w in headline for w in ["earnings", "revenue", "profit", "eps"]): + return NewsCategory.EARNINGS + return NewsCategory.MACRO + + async def collect(self) -> list[NewsItem]: + raw = await self._fetch_news() + items = [] + for article in raw: + headline = article.get("headline", "") + summary = article.get("summary", "") + sentiment_text = f"{headline}. {summary}" if summary else headline + + items.append( + NewsItem( + source=self.name, + headline=headline, + summary=summary or None, + url=article.get("url"), + published_at=datetime.fromtimestamp( + article.get("datetime", 0), tz=timezone.utc + ), + symbols=self._extract_symbols(article.get("related", "")), + sentiment=self._analyze_sentiment(sentiment_text), + category=self._categorize(article), + raw_data=article, + ) + ) + return items +``` + +- [ ] **Step 4: Run tests to verify they pass** + +Run: `pytest services/news-collector/tests/test_finnhub.py -v` +Expected: All 5 tests PASS + +Note: Requires `nltk` and VADER lexicon. If not downloaded: `python -c "import nltk; nltk.download('vader_lexicon')"` + +- [ ] **Step 5: Commit** + +```bash +git add services/news-collector/src/news_collector/collectors/finnhub.py services/news-collector/tests/test_finnhub.py +git commit -m "feat: implement Finnhub news collector with VADER sentiment" +``` + +--- + +### Task 8: Implement RSS news collector + +**Files:** +- Create: `services/news-collector/src/news_collector/collectors/rss.py` +- Create: `services/news-collector/tests/test_rss.py` + +- [ ] **Step 1: Write tests** + +Create `services/news-collector/tests/test_rss.py`: + +```python +"""Tests for RSS news collector.""" + +import pytest +from unittest.mock import AsyncMock, patch +from datetime import datetime, timezone + +from news_collector.collectors.rss import RSSCollector + + +@pytest.fixture +def collector(): + return RSSCollector() + + +def test_collector_name(collector): + assert collector.name == "rss" + assert collector.poll_interval == 600 + + +async def test_is_available(collector): + assert await collector.is_available() is True + + +async def test_collect_parses_feed(collector): + mock_feed = { + "entries": [ + { + "title": "NVDA surges on AI demand", + "link": "https://example.com/nvda", + "published_parsed": (2026, 4, 2, 12, 0, 0, 0, 0, 0), + "summary": "Nvidia stock jumped 5%...", + }, + { + "title": "Markets rally on jobs data", + "link": "https://example.com/market", + "published_parsed": (2026, 4, 2, 11, 0, 0, 0, 0, 0), + "summary": "The S&P 500 rose...", + }, + ], + } + + with patch.object(collector, "_fetch_feeds", new_callable=AsyncMock, return_value=[mock_feed]): + items = await collector.collect() + + assert len(items) == 2 + assert items[0].source == "rss" + assert items[0].headline == "NVDA surges on AI demand" + assert isinstance(items[0].sentiment, float) +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest services/news-collector/tests/test_rss.py -v` +Expected: FAIL + +- [ ] **Step 3: Implement RSSCollector** + +Create `services/news-collector/src/news_collector/collectors/rss.py`: + +```python +"""RSS feed collector for Yahoo Finance, Google News, MarketWatch.""" + +import asyncio +import logging +import re +from calendar import timegm +from datetime import datetime, timezone + +import aiohttp +import feedparser +from nltk.sentiment.vader import SentimentIntensityAnalyzer + +from shared.models import NewsCategory, NewsItem +from news_collector.collectors.base import BaseCollector + +logger = logging.getLogger(__name__) + +DEFAULT_FEEDS = [ + "https://feeds.finance.yahoo.com/rss/2.0/headline?s=^GSPC®ion=US&lang=en-US", + "https://news.google.com/rss/topics/CAAqJggKIiBDQkFTRWdvSUwyMHZNRGx6TVdZU0FtVnVHZ0pWVXlnQVAB?hl=en-US&gl=US&ceid=US:en", + "https://www.marketwatch.com/rss/topstories", +] + +# Common US stock tickers to detect in headlines +TICKER_PATTERN = re.compile( + r"\b(AAPL|MSFT|GOOGL|GOOG|AMZN|TSLA|NVDA|META|JPM|V|JNJ|WMT|PG|UNH|HD|" + r"MA|DIS|BAC|XOM|PFE|KO|PEP|CSCO|INTC|VZ|NFLX|ADBE|CRM|AMD|QCOM|" + r"GS|BA|CAT|MMM|IBM|GE|F|GM|NKE|MCD|SBUX|SPY|QQQ|IWM)\b" +) + + +class RSSCollector(BaseCollector): + name = "rss" + poll_interval = 600 # 10 minutes + + def __init__(self, feeds: list[str] | None = None) -> None: + self._feeds = feeds or DEFAULT_FEEDS + self._vader = SentimentIntensityAnalyzer() + + async def is_available(self) -> bool: + return True + + async def _fetch_feeds(self) -> list[dict]: + """Fetch and parse all RSS feeds.""" + results = [] + async with aiohttp.ClientSession() as session: + for url in self._feeds: + try: + async with session.get(url, timeout=aiohttp.ClientTimeout(total=10)) as resp: + if resp.status == 200: + text = await resp.text() + feed = feedparser.parse(text) + results.append(feed) + except Exception as exc: + logger.warning("rss_fetch_failed", url=url, error=str(exc)) + return results + + def _extract_symbols(self, text: str) -> list[str]: + """Extract stock tickers from text.""" + return list(set(TICKER_PATTERN.findall(text))) + + def _parse_time(self, entry: dict) -> datetime: + """Parse published time from feed entry.""" + parsed = entry.get("published_parsed") + if parsed: + return datetime.fromtimestamp(timegm(parsed), tz=timezone.utc) + return datetime.now(timezone.utc) + + async def collect(self) -> list[NewsItem]: + feeds = await self._fetch_feeds() + items = [] + seen_titles = set() + + for feed in feeds: + for entry in feed.get("entries", []): + title = entry.get("title", "").strip() + if not title or title in seen_titles: + continue + seen_titles.add(title) + + summary = entry.get("summary", "") + sentiment_text = f"{title}. {summary}" if summary else title + + items.append( + NewsItem( + source=self.name, + headline=title, + summary=summary or None, + url=entry.get("link"), + published_at=self._parse_time(entry), + symbols=self._extract_symbols(f"{title} {summary}"), + sentiment=self._vader.polarity_scores(sentiment_text)["compound"], + category=NewsCategory.MACRO, + raw_data={"feed_title": title}, + ) + ) + + return items +``` + +- [ ] **Step 4: Run tests to verify they pass** + +Run: `pytest services/news-collector/tests/test_rss.py -v` +Expected: All 3 tests PASS + +- [ ] **Step 5: Commit** + +```bash +git add services/news-collector/src/news_collector/collectors/rss.py services/news-collector/tests/test_rss.py +git commit -m "feat: implement RSS news collector (Yahoo, Google News, MarketWatch)" +``` + +--- + +### Task 9: Implement Fear & Greed Index collector + +**Files:** +- Create: `services/news-collector/src/news_collector/collectors/fear_greed.py` +- Create: `services/news-collector/tests/test_fear_greed.py` + +- [ ] **Step 1: Write tests** + +Create `services/news-collector/tests/test_fear_greed.py`: + +```python +"""Tests for CNN Fear & Greed Index collector.""" + +import pytest +from unittest.mock import AsyncMock, patch + +from news_collector.collectors.fear_greed import FearGreedCollector + + +@pytest.fixture +def collector(): + return FearGreedCollector() + + +def test_collector_name(collector): + assert collector.name == "fear_greed" + assert collector.poll_interval == 3600 + + +async def test_is_available(collector): + assert await collector.is_available() is True + + +async def test_collect_parses_api_response(collector): + mock_data = { + "fear_and_greed": { + "score": 45.0, + "rating": "Fear", + "timestamp": "2026-04-02T12:00:00+00:00", + } + } + with patch.object(collector, "_fetch_index", new_callable=AsyncMock, return_value=mock_data): + result = await collector.collect() + + assert result.fear_greed == 45 + assert result.fear_greed_label == "Fear" + + +async def test_collect_returns_none_on_failure(collector): + with patch.object(collector, "_fetch_index", new_callable=AsyncMock, return_value=None): + result = await collector.collect() + assert result is None + + +def test_classify_label(): + c = FearGreedCollector() + assert c._classify(10) == "Extreme Fear" + assert c._classify(30) == "Fear" + assert c._classify(50) == "Neutral" + assert c._classify(70) == "Greed" + assert c._classify(85) == "Extreme Greed" +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest services/news-collector/tests/test_fear_greed.py -v` +Expected: FAIL + +- [ ] **Step 3: Implement FearGreedCollector** + +Create `services/news-collector/src/news_collector/collectors/fear_greed.py`: + +```python +"""CNN Fear & Greed Index collector.""" + +import logging +from dataclasses import dataclass +from typing import Optional + +import aiohttp + +from news_collector.collectors.base import BaseCollector +from shared.models import NewsItem + +logger = logging.getLogger(__name__) + +FEAR_GREED_URL = "https://production.dataviz.cnn.io/index/fearandgreed/graphdata" + + +@dataclass +class FearGreedResult: + fear_greed: int + fear_greed_label: str + + +class FearGreedCollector(BaseCollector): + """Fetches CNN Fear & Greed Index. + + Note: This collector does NOT return NewsItem — it returns FearGreedResult + which feeds directly into MarketSentiment. The main.py scheduler handles + this differently from news collectors. + """ + + name = "fear_greed" + poll_interval = 3600 # 1 hour + + async def is_available(self) -> bool: + return True + + async def _fetch_index(self) -> Optional[dict]: + """Fetch Fear & Greed data from CNN API.""" + headers = {"User-Agent": "Mozilla/5.0"} + try: + async with aiohttp.ClientSession() as session: + async with session.get( + FEAR_GREED_URL, headers=headers, timeout=aiohttp.ClientTimeout(total=10) + ) as resp: + if resp.status != 200: + logger.warning("fear_greed_fetch_failed", status=resp.status) + return None + return await resp.json() + except Exception as exc: + logger.warning("fear_greed_error", error=str(exc)) + return None + + def _classify(self, score: int) -> str: + """Classify numeric score into label.""" + if score <= 20: + return "Extreme Fear" + if score <= 40: + return "Fear" + if score <= 60: + return "Neutral" + if score <= 80: + return "Greed" + return "Extreme Greed" + + async def collect(self) -> Optional[FearGreedResult]: + """Collect Fear & Greed Index. Returns FearGreedResult or None.""" + data = await self._fetch_index() + if data is None: + return None + + try: + fg = data["fear_and_greed"] + score = int(fg["score"]) + label = fg.get("rating", self._classify(score)) + return FearGreedResult(fear_greed=score, fear_greed_label=label) + except (KeyError, ValueError, TypeError) as exc: + logger.warning("fear_greed_parse_failed", error=str(exc)) + return None +``` + +- [ ] **Step 4: Run tests to verify they pass** + +Run: `pytest services/news-collector/tests/test_fear_greed.py -v` +Expected: All 5 tests PASS + +- [ ] **Step 5: Commit** + +```bash +git add services/news-collector/src/news_collector/collectors/fear_greed.py services/news-collector/tests/test_fear_greed.py +git commit -m "feat: implement CNN Fear & Greed Index collector" +``` + +--- + +### Task 10: Implement SEC EDGAR collector + +**Files:** +- Create: `services/news-collector/src/news_collector/collectors/sec_edgar.py` +- Create: `services/news-collector/tests/test_sec_edgar.py` + +- [ ] **Step 1: Write tests** + +Create `services/news-collector/tests/test_sec_edgar.py`: + +```python +"""Tests for SEC EDGAR filing collector.""" + +import pytest +from unittest.mock import AsyncMock, patch + +from news_collector.collectors.sec_edgar import SecEdgarCollector + + +@pytest.fixture +def collector(): + return SecEdgarCollector() + + +def test_collector_name(collector): + assert collector.name == "sec_edgar" + assert collector.poll_interval == 1800 + + +async def test_is_available(collector): + assert await collector.is_available() is True + + +async def test_collect_parses_filings(collector): + mock_response = { + "filings": { + "recent": { + "accessionNumber": ["0001234-26-000001"], + "filingDate": ["2026-04-02"], + "primaryDocument": ["filing.htm"], + "form": ["8-K"], + "primaryDocDescription": ["Current Report"], + } + }, + "tickers": [{"ticker": "AAPL"}], + "name": "Apple Inc", + } + with patch.object(collector, "_fetch_recent_filings", new_callable=AsyncMock, return_value=[mock_response]): + items = await collector.collect() + + assert len(items) == 1 + assert items[0].source == "sec_edgar" + assert items[0].category.value == "filing" + assert "AAPL" in items[0].symbols + + +async def test_collect_handles_empty(collector): + with patch.object(collector, "_fetch_recent_filings", new_callable=AsyncMock, return_value=[]): + items = await collector.collect() + assert items == [] +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest services/news-collector/tests/test_sec_edgar.py -v` +Expected: FAIL + +- [ ] **Step 3: Implement SecEdgarCollector** + +Create `services/news-collector/src/news_collector/collectors/sec_edgar.py`: + +```python +"""SEC EDGAR filing collector (free, no API key required).""" + +import logging +from datetime import datetime, timezone + +import aiohttp +from nltk.sentiment.vader import SentimentIntensityAnalyzer + +from shared.models import NewsCategory, NewsItem +from news_collector.collectors.base import BaseCollector + +logger = logging.getLogger(__name__) + +EDGAR_FULL_TEXT_SEARCH = "https://efts.sec.gov/LATEST/search-index" +EDGAR_RECENT_FILINGS = "https://efts.sec.gov/LATEST/search-index?q=%228-K%22&dateRange=custom&startdt={date}&enddt={date}&forms=8-K" +EDGAR_COMPANY_FILINGS = "https://data.sec.gov/submissions/CIK{cik}.json" + +# CIK numbers for major companies (subset — extend as needed) +TRACKED_CIKS = { + "0000320193": "AAPL", + "0000789019": "MSFT", + "0001652044": "GOOGL", + "0001018724": "AMZN", + "0001318605": "TSLA", + "0001045810": "NVDA", + "0001326801": "META", + "0000019617": "JPM", + "0000078003": "PFE", + "0000021344": "KO", +} + +SEC_USER_AGENT = "TradingPlatform research@example.com" + + +class SecEdgarCollector(BaseCollector): + name = "sec_edgar" + poll_interval = 1800 # 30 minutes + + def __init__(self) -> None: + self._vader = SentimentIntensityAnalyzer() + + async def is_available(self) -> bool: + return True + + async def _fetch_recent_filings(self) -> list[dict]: + """Fetch recent 8-K filings for tracked companies.""" + results = [] + headers = {"User-Agent": SEC_USER_AGENT} + async with aiohttp.ClientSession() as session: + for cik, ticker in TRACKED_CIKS.items(): + try: + url = f"https://data.sec.gov/submissions/CIK{cik}.json" + async with session.get( + url, headers=headers, timeout=aiohttp.ClientTimeout(total=10) + ) as resp: + if resp.status == 200: + data = await resp.json() + data["tickers"] = [{"ticker": ticker}] + results.append(data) + except Exception as exc: + logger.warning("sec_fetch_failed", cik=cik, error=str(exc)) + return results + + async def collect(self) -> list[NewsItem]: + filings_data = await self._fetch_recent_filings() + items = [] + today = datetime.now(timezone.utc).strftime("%Y-%m-%d") + + for company_data in filings_data: + tickers = [t["ticker"] for t in company_data.get("tickers", [])] + company_name = company_data.get("name", "Unknown") + recent = company_data.get("filings", {}).get("recent", {}) + + forms = recent.get("form", []) + dates = recent.get("filingDate", []) + descriptions = recent.get("primaryDocDescription", []) + accessions = recent.get("accessionNumber", []) + + for i, form in enumerate(forms): + if form != "8-K": + continue + filing_date = dates[i] if i < len(dates) else "" + if filing_date != today: + continue + + desc = descriptions[i] if i < len(descriptions) else "8-K Filing" + accession = accessions[i] if i < len(accessions) else "" + headline = f"{company_name} ({', '.join(tickers)}): {form} - {desc}" + + items.append( + NewsItem( + source=self.name, + headline=headline, + summary=desc, + url=f"https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&accession={accession}", + published_at=datetime.strptime(filing_date, "%Y-%m-%d").replace(tzinfo=timezone.utc), + symbols=tickers, + sentiment=self._vader.polarity_scores(headline)["compound"], + category=NewsCategory.FILING, + raw_data={"form": form, "accession": accession}, + ) + ) + + return items +``` + +- [ ] **Step 4: Run tests to verify they pass** + +Run: `pytest services/news-collector/tests/test_sec_edgar.py -v` +Expected: All 4 tests PASS + +- [ ] **Step 5: Commit** + +```bash +git add services/news-collector/src/news_collector/collectors/sec_edgar.py services/news-collector/tests/test_sec_edgar.py +git commit -m "feat: implement SEC EDGAR 8-K filing collector" +``` + +--- + +### Task 11: Implement Reddit collector + +**Files:** +- Create: `services/news-collector/src/news_collector/collectors/reddit.py` +- Create: `services/news-collector/tests/test_reddit.py` + +- [ ] **Step 1: Write tests** + +Create `services/news-collector/tests/test_reddit.py`: + +```python +"""Tests for Reddit collector.""" + +import pytest +from unittest.mock import AsyncMock, patch + +from news_collector.collectors.reddit import RedditCollector + + +@pytest.fixture +def collector(): + return RedditCollector() + + +def test_collector_name(collector): + assert collector.name == "reddit" + assert collector.poll_interval == 900 + + +async def test_is_available(collector): + assert await collector.is_available() is True + + +async def test_collect_parses_posts(collector): + mock_posts = [ + { + "data": { + "title": "NVDA to the moon! 🚀 AI demand is insane", + "selftext": "Just loaded up on NVDA calls", + "url": "https://reddit.com/r/wallstreetbets/123", + "created_utc": 1711929600, + "score": 500, + "num_comments": 200, + "subreddit": "wallstreetbets", + } + }, + ] + with patch.object(collector, "_fetch_subreddit", new_callable=AsyncMock, return_value=mock_posts): + items = await collector.collect() + + assert len(items) >= 1 + assert items[0].source == "reddit" + assert items[0].category.value == "social" + assert isinstance(items[0].sentiment, float) + + +async def test_collect_filters_low_score(collector): + mock_posts = [ + { + "data": { + "title": "Random question about stocks", + "selftext": "", + "url": "https://reddit.com/r/stocks/456", + "created_utc": 1711929600, + "score": 3, + "num_comments": 1, + "subreddit": "stocks", + } + }, + ] + with patch.object(collector, "_fetch_subreddit", new_callable=AsyncMock, return_value=mock_posts): + items = await collector.collect() + assert items == [] +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest services/news-collector/tests/test_reddit.py -v` +Expected: FAIL + +- [ ] **Step 3: Implement RedditCollector** + +Create `services/news-collector/src/news_collector/collectors/reddit.py`: + +```python +"""Reddit collector for r/wallstreetbets, r/stocks, r/investing.""" + +import logging +import re +from datetime import datetime, timezone + +import aiohttp +from nltk.sentiment.vader import SentimentIntensityAnalyzer + +from shared.models import NewsCategory, NewsItem +from news_collector.collectors.base import BaseCollector + +logger = logging.getLogger(__name__) + +SUBREDDITS = ["wallstreetbets", "stocks", "investing"] +MIN_SCORE = 50 # Minimum upvotes to consider + +TICKER_PATTERN = re.compile( + r"\b(AAPL|MSFT|GOOGL|GOOG|AMZN|TSLA|NVDA|META|JPM|V|JNJ|WMT|PG|UNH|HD|" + r"MA|DIS|BAC|XOM|PFE|KO|PEP|CSCO|INTC|VZ|NFLX|ADBE|CRM|AMD|QCOM|" + r"GS|BA|CAT|MMM|IBM|GE|F|GM|NKE|MCD|SBUX|SPY|QQQ|IWM)\b" +) + + +class RedditCollector(BaseCollector): + name = "reddit" + poll_interval = 900 # 15 minutes + + def __init__(self) -> None: + self._vader = SentimentIntensityAnalyzer() + + async def is_available(self) -> bool: + return True + + async def _fetch_subreddit(self, subreddit: str = "wallstreetbets") -> list[dict]: + """Fetch hot posts from a subreddit via JSON API.""" + url = f"https://www.reddit.com/r/{subreddit}/hot.json?limit=25" + headers = {"User-Agent": "TradingPlatform/1.0"} + try: + async with aiohttp.ClientSession() as session: + async with session.get( + url, headers=headers, timeout=aiohttp.ClientTimeout(total=10) + ) as resp: + if resp.status != 200: + logger.warning("reddit_fetch_failed", subreddit=subreddit, status=resp.status) + return [] + data = await resp.json() + return data.get("data", {}).get("children", []) + except Exception as exc: + logger.warning("reddit_error", subreddit=subreddit, error=str(exc)) + return [] + + async def collect(self) -> list[NewsItem]: + items = [] + seen_titles = set() + + for subreddit in SUBREDDITS: + posts = await self._fetch_subreddit(subreddit) + for post in posts: + data = post.get("data", {}) + title = data.get("title", "").strip() + score = data.get("score", 0) + + if not title or title in seen_titles or score < MIN_SCORE: + continue + seen_titles.add(title) + + selftext = data.get("selftext", "") + text = f"{title}. {selftext}" if selftext else title + symbols = list(set(TICKER_PATTERN.findall(text))) + + items.append( + NewsItem( + source=self.name, + headline=title, + summary=selftext[:500] if selftext else None, + url=data.get("url"), + published_at=datetime.fromtimestamp( + data.get("created_utc", 0), tz=timezone.utc + ), + symbols=symbols, + sentiment=self._vader.polarity_scores(text)["compound"], + category=NewsCategory.SOCIAL, + raw_data={ + "subreddit": data.get("subreddit", subreddit), + "score": score, + "num_comments": data.get("num_comments", 0), + }, + ) + ) + + return items +``` + +- [ ] **Step 4: Run tests to verify they pass** + +Run: `pytest services/news-collector/tests/test_reddit.py -v` +Expected: All 4 tests PASS + +- [ ] **Step 5: Commit** + +```bash +git add services/news-collector/src/news_collector/collectors/reddit.py services/news-collector/tests/test_reddit.py +git commit -m "feat: implement Reddit social sentiment collector" +``` + +--- + +### Task 12: Implement Truth Social and Fed collectors + +**Files:** +- Create: `services/news-collector/src/news_collector/collectors/truth_social.py` +- Create: `services/news-collector/src/news_collector/collectors/fed.py` +- Create: `services/news-collector/tests/test_truth_social.py` +- Create: `services/news-collector/tests/test_fed.py` + +- [ ] **Step 1: Write tests for Truth Social** + +Create `services/news-collector/tests/test_truth_social.py`: + +```python +"""Tests for Truth Social collector.""" + +import pytest +from unittest.mock import AsyncMock, patch + +from news_collector.collectors.truth_social import TruthSocialCollector + + +@pytest.fixture +def collector(): + return TruthSocialCollector() + + +def test_collector_name(collector): + assert collector.name == "truth_social" + assert collector.poll_interval == 900 + + +async def test_is_available(collector): + assert await collector.is_available() is True + + +async def test_collect_parses_posts(collector): + mock_posts = [ + { + "content": "We are imposing 25% tariffs on all steel imports!", + "created_at": "2026-04-02T12:00:00.000Z", + "url": "https://truthsocial.com/@realDonaldTrump/12345", + }, + ] + with patch.object(collector, "_fetch_posts", new_callable=AsyncMock, return_value=mock_posts): + items = await collector.collect() + + assert len(items) == 1 + assert items[0].source == "truth_social" + assert items[0].category.value == "policy" + assert "tariff" in items[0].headline.lower() or "tariff" in items[0].raw_data.get("content", "").lower() + + +async def test_collect_handles_empty(collector): + with patch.object(collector, "_fetch_posts", new_callable=AsyncMock, return_value=[]): + items = await collector.collect() + assert items == [] +``` + +- [ ] **Step 2: Write tests for Fed collector** + +Create `services/news-collector/tests/test_fed.py`: + +```python +"""Tests for Federal Reserve collector.""" + +import pytest +from unittest.mock import AsyncMock, patch + +from news_collector.collectors.fed import FedCollector + + +@pytest.fixture +def collector(): + return FedCollector() + + +def test_collector_name(collector): + assert collector.name == "fed" + assert collector.poll_interval == 3600 + + +async def test_is_available(collector): + assert await collector.is_available() is True + + +async def test_collect_parses_rss(collector): + mock_entries = [ + { + "title": "Federal Reserve issues FOMC statement", + "link": "https://www.federalreserve.gov/newsevents/pressreleases/monetary20260402a.htm", + "published_parsed": (2026, 4, 2, 14, 0, 0, 0, 0, 0), + "summary": "The Federal Open Market Committee decided to maintain the target range...", + }, + ] + with patch.object(collector, "_fetch_fed_rss", new_callable=AsyncMock, return_value=mock_entries): + items = await collector.collect() + + assert len(items) == 1 + assert items[0].source == "fed" + assert items[0].category.value == "fed" +``` + +- [ ] **Step 3: Run tests to verify they fail** + +Run: `pytest services/news-collector/tests/test_truth_social.py services/news-collector/tests/test_fed.py -v` +Expected: FAIL + +- [ ] **Step 4: Implement TruthSocialCollector** + +Create `services/news-collector/src/news_collector/collectors/truth_social.py`: + +```python +"""Truth Social collector for Trump posts (policy-relevant).""" + +import logging +from datetime import datetime, timezone + +import aiohttp +from nltk.sentiment.vader import SentimentIntensityAnalyzer + +from shared.models import NewsCategory, NewsItem +from news_collector.collectors.base import BaseCollector + +logger = logging.getLogger(__name__) + +# Truth Social uses a Mastodon-compatible API +TRUTH_SOCIAL_API = "https://truthsocial.com/api/v1/accounts/107780257626128497/statuses" + + +class TruthSocialCollector(BaseCollector): + name = "truth_social" + poll_interval = 900 # 15 minutes + + def __init__(self) -> None: + self._vader = SentimentIntensityAnalyzer() + + async def is_available(self) -> bool: + return True + + async def _fetch_posts(self) -> list[dict]: + """Fetch recent posts from Truth Social.""" + headers = {"User-Agent": "Mozilla/5.0"} + try: + async with aiohttp.ClientSession() as session: + async with session.get( + TRUTH_SOCIAL_API, + headers=headers, + params={"limit": 10}, + timeout=aiohttp.ClientTimeout(total=15), + ) as resp: + if resp.status != 200: + logger.warning("truth_social_fetch_failed", status=resp.status) + return [] + return await resp.json() + except Exception as exc: + logger.warning("truth_social_error", error=str(exc)) + return [] + + def _strip_html(self, text: str) -> str: + """Remove HTML tags from content.""" + import re + return re.sub(r"<[^>]+>", "", text).strip() + + async def collect(self) -> list[NewsItem]: + posts = await self._fetch_posts() + items = [] + + for post in posts: + content = self._strip_html(post.get("content", "")) + if not content: + continue + + created_at_str = post.get("created_at", "") + try: + published = datetime.fromisoformat(created_at_str.replace("Z", "+00:00")) + except (ValueError, AttributeError): + published = datetime.now(timezone.utc) + + items.append( + NewsItem( + source=self.name, + headline=content[:200], + summary=content if len(content) > 200 else None, + url=post.get("url"), + published_at=published, + symbols=[], # Symbols extracted at aggregation stage via LLM + sentiment=self._vader.polarity_scores(content)["compound"], + category=NewsCategory.POLICY, + raw_data={"content": content, "id": post.get("id")}, + ) + ) + + return items +``` + +- [ ] **Step 5: Implement FedCollector** + +Create `services/news-collector/src/news_collector/collectors/fed.py`: + +```python +"""Federal Reserve press release and FOMC statement collector.""" + +import logging +from calendar import timegm +from datetime import datetime, timezone + +import aiohttp +import feedparser +from nltk.sentiment.vader import SentimentIntensityAnalyzer + +from shared.models import NewsCategory, NewsItem +from news_collector.collectors.base import BaseCollector + +logger = logging.getLogger(__name__) + +FED_RSS_URL = "https://www.federalreserve.gov/feeds/press_all.xml" + + +class FedCollector(BaseCollector): + name = "fed" + poll_interval = 3600 # 1 hour + + def __init__(self) -> None: + self._vader = SentimentIntensityAnalyzer() + + async def is_available(self) -> bool: + return True + + async def _fetch_fed_rss(self) -> list[dict]: + """Fetch Federal Reserve RSS feed entries.""" + try: + async with aiohttp.ClientSession() as session: + async with session.get( + FED_RSS_URL, timeout=aiohttp.ClientTimeout(total=10) + ) as resp: + if resp.status != 200: + logger.warning("fed_rss_failed", status=resp.status) + return [] + text = await resp.text() + feed = feedparser.parse(text) + return feed.get("entries", []) + except Exception as exc: + logger.warning("fed_rss_error", error=str(exc)) + return [] + + def _detect_stance(self, text: str) -> str: + """Detect hawkish/dovish/neutral stance from text.""" + text_lower = text.lower() + hawkish_words = ["tighten", "raise", "inflation concern", "restrictive", "higher rates"] + dovish_words = ["accommodate", "cut", "easing", "lower rates", "support growth"] + + hawk_count = sum(1 for w in hawkish_words if w in text_lower) + dove_count = sum(1 for w in dovish_words if w in text_lower) + + if hawk_count > dove_count: + return "hawkish" + if dove_count > hawk_count: + return "dovish" + return "neutral" + + async def collect(self) -> list[NewsItem]: + entries = await self._fetch_fed_rss() + items = [] + + for entry in entries: + title = entry.get("title", "").strip() + if not title: + continue + + summary = entry.get("summary", "") + parsed_time = entry.get("published_parsed") + if parsed_time: + published = datetime.fromtimestamp(timegm(parsed_time), tz=timezone.utc) + else: + published = datetime.now(timezone.utc) + + text = f"{title}. {summary}" if summary else title + + items.append( + NewsItem( + source=self.name, + headline=title, + summary=summary or None, + url=entry.get("link"), + published_at=published, + symbols=[], + sentiment=self._vader.polarity_scores(text)["compound"], + category=NewsCategory.FED, + raw_data={"stance": self._detect_stance(text)}, + ) + ) + + return items +``` + +- [ ] **Step 6: Run tests to verify they pass** + +Run: `pytest services/news-collector/tests/test_truth_social.py services/news-collector/tests/test_fed.py -v` +Expected: All 7 tests PASS + +- [ ] **Step 7: Commit** + +```bash +git add services/news-collector/src/news_collector/collectors/truth_social.py services/news-collector/src/news_collector/collectors/fed.py services/news-collector/tests/test_truth_social.py services/news-collector/tests/test_fed.py +git commit -m "feat: implement Truth Social and Federal Reserve collectors" +``` + +--- + +### Task 13: Implement news-collector main.py (scheduler) + +**Files:** +- Create: `services/news-collector/src/news_collector/main.py` +- Create: `services/news-collector/tests/test_main.py` + +- [ ] **Step 1: Write tests** + +Create `services/news-collector/tests/test_main.py`: + +```python +"""Tests for news collector scheduler.""" + +import pytest +from unittest.mock import AsyncMock, patch, MagicMock +from datetime import datetime, timezone + +from shared.models import NewsCategory, NewsItem + +from news_collector.main import run_collector_once + + +async def test_run_collector_once_stores_and_publishes(): + mock_item = NewsItem( + source="test", + headline="Test news", + published_at=datetime(2026, 4, 2, tzinfo=timezone.utc), + sentiment=0.5, + category=NewsCategory.MACRO, + ) + + mock_collector = MagicMock() + mock_collector.name = "test" + mock_collector.collect = AsyncMock(return_value=[mock_item]) + + mock_db = MagicMock() + mock_db.insert_news_item = AsyncMock() + + mock_broker = MagicMock() + mock_broker.publish = AsyncMock() + + count = await run_collector_once(mock_collector, mock_db, mock_broker) + + assert count == 1 + mock_db.insert_news_item.assert_called_once_with(mock_item) + mock_broker.publish.assert_called_once() + + +async def test_run_collector_once_handles_empty(): + mock_collector = MagicMock() + mock_collector.name = "test" + mock_collector.collect = AsyncMock(return_value=[]) + + mock_db = MagicMock() + mock_broker = MagicMock() + + count = await run_collector_once(mock_collector, mock_db, mock_broker) + assert count == 0 +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest services/news-collector/tests/test_main.py -v` +Expected: FAIL + +- [ ] **Step 3: Implement main.py** + +Create `services/news-collector/src/news_collector/main.py`: + +```python +"""News Collector Service — schedules and runs all news collectors.""" + +import asyncio +import logging + +from shared.broker import RedisBroker +from shared.db import Database +from shared.events import NewsEvent +from shared.healthcheck import HealthCheckServer +from shared.logging import setup_logging +from shared.metrics import ServiceMetrics +from shared.models import NewsItem +from shared.notifier import TelegramNotifier +from shared.sentiment_models import MarketSentiment + +from news_collector.config import NewsCollectorConfig +from news_collector.collectors.base import BaseCollector +from news_collector.collectors.finnhub import FinnhubCollector +from news_collector.collectors.rss import RSSCollector +from news_collector.collectors.sec_edgar import SecEdgarCollector +from news_collector.collectors.truth_social import TruthSocialCollector +from news_collector.collectors.reddit import RedditCollector +from news_collector.collectors.fear_greed import FearGreedCollector +from news_collector.collectors.fed import FedCollector + +logger = logging.getLogger(__name__) + + +async def run_collector_once( + collector: BaseCollector, + db: Database, + broker: RedisBroker, +) -> int: + """Run a single collector, store results, publish to Redis. + Returns number of items collected.""" + items = await collector.collect() + if not isinstance(items, list): + # FearGreedCollector returns a FearGreedResult, not a list + return 0 + + for item in items: + await db.insert_news_item(item) + event = NewsEvent(data=item) + await broker.publish("news", event.to_dict()) + + return len(items) + + +async def run_collector_loop( + collector: BaseCollector, + db: Database, + broker: RedisBroker, + log, +) -> None: + """Run a collector on its poll interval forever.""" + while True: + try: + if await collector.is_available(): + count = await run_collector_once(collector, db, broker) + log.info("collector_run", collector=collector.name, items=count) + else: + log.debug("collector_unavailable", collector=collector.name) + except Exception as exc: + log.error("collector_error", collector=collector.name, error=str(exc)) + await asyncio.sleep(collector.poll_interval) + + +async def run_fear_greed_loop( + collector: FearGreedCollector, + db: Database, + log, +) -> None: + """Run the Fear & Greed collector and update market sentiment.""" + from datetime import datetime, timezone + + while True: + try: + result = await collector.collect() + if result is not None: + ms = MarketSentiment( + fear_greed=result.fear_greed, + fear_greed_label=result.fear_greed_label, + fed_stance="neutral", # Updated by Fed collector analysis + market_regime=_determine_regime(result.fear_greed, None), + updated_at=datetime.now(timezone.utc), + ) + await db.upsert_market_sentiment(ms) + log.info("fear_greed_updated", score=result.fear_greed, label=result.fear_greed_label) + except Exception as exc: + log.error("fear_greed_error", error=str(exc)) + await asyncio.sleep(collector.poll_interval) + + +async def run_aggregator_loop( + db: Database, + interval: int, + log, +) -> None: + """Run sentiment aggregation every `interval` seconds. + Reads recent news from DB, computes per-symbol scores, upserts into symbol_scores table.""" + from datetime import datetime, timezone + from shared.sentiment import SentimentAggregator + + aggregator = SentimentAggregator() + + while True: + try: + now = datetime.now(timezone.utc) + news_items = await db.get_recent_news(hours=24) + if news_items: + scores = aggregator.aggregate(news_items, now) + for symbol_score in scores.values(): + await db.upsert_symbol_score(symbol_score) + log.info("aggregation_complete", symbols=len(scores)) + except Exception as exc: + log.error("aggregation_error", error=str(exc)) + await asyncio.sleep(interval) + + +def _determine_regime(fear_greed: int, vix: float | None) -> str: + """Determine market regime from Fear & Greed and VIX.""" + if fear_greed <= 20: + return "risk_off" + if vix is not None and vix > 30: + return "risk_off" + if fear_greed >= 60 and (vix is None or vix < 20): + return "risk_on" + return "neutral" + + +async def run() -> None: + config = NewsCollectorConfig() + log = setup_logging("news-collector", config.log_level, config.log_format) + metrics = ServiceMetrics("news_collector") + + notifier = TelegramNotifier( + bot_token=config.telegram_bot_token, + chat_id=config.telegram_chat_id, + ) + + db = Database(config.database_url) + await db.connect() + + broker = RedisBroker(config.redis_url) + + health = HealthCheckServer( + "news-collector", + port=config.health_port, + auth_token=config.metrics_auth_token, + ) + health.register_check("redis", broker.ping) + await health.start() + metrics.service_up.labels(service="news-collector").set(1) + + # Initialize collectors + news_collectors: list[BaseCollector] = [ + RSSCollector(), + SecEdgarCollector(), + TruthSocialCollector(), + RedditCollector(), + FedCollector(), + ] + + # Finnhub requires API key + if config.finnhub_api_key: + news_collectors.append(FinnhubCollector(api_key=config.finnhub_api_key)) + + fear_greed = FearGreedCollector() + + log.info( + "starting", + collectors=[c.name for c in news_collectors], + fear_greed=True, + ) + + tasks = [] + try: + for collector in news_collectors: + task = asyncio.create_task(run_collector_loop(collector, db, broker, log)) + tasks.append(task) + + tasks.append(asyncio.create_task(run_fear_greed_loop(fear_greed, db, log))) + tasks.append(asyncio.create_task( + run_aggregator_loop(db, config.sentiment_aggregate_interval, log) + )) + + await asyncio.gather(*tasks) + except Exception as exc: + log.error("fatal_error", error=str(exc)) + await notifier.send_error(str(exc), "news-collector") + raise + finally: + for task in tasks: + task.cancel() + metrics.service_up.labels(service="news-collector").set(0) + await notifier.close() + await broker.close() + await db.close() + + +def main() -> None: + asyncio.run(run()) + + +if __name__ == "__main__": + main() +``` + +- [ ] **Step 4: Run tests to verify they pass** + +Run: `pytest services/news-collector/tests/test_main.py -v` +Expected: All 2 tests PASS + +- [ ] **Step 5: Commit** + +```bash +git add services/news-collector/src/news_collector/main.py services/news-collector/tests/test_main.py +git commit -m "feat: implement news-collector main scheduler with all collectors" +``` + +--- + +## Phase 3: Sentiment Analysis Pipeline + +### Task 14: Implement sentiment aggregator + +**Files:** +- Modify: `shared/src/shared/sentiment.py` +- Create: `shared/tests/test_sentiment_aggregator.py` + +- [ ] **Step 1: Write tests** + +Create `shared/tests/test_sentiment_aggregator.py`: + +```python +"""Tests for sentiment aggregator.""" + +import pytest +from datetime import datetime, timezone, timedelta + +from shared.sentiment import SentimentAggregator + + +@pytest.fixture +def aggregator(): + return SentimentAggregator() + + +def test_freshness_decay_recent(): + a = SentimentAggregator() + now = datetime.now(timezone.utc) + assert a._freshness_decay(now, now) == 1.0 + + +def test_freshness_decay_3_hours(): + a = SentimentAggregator() + now = datetime.now(timezone.utc) + three_hours_ago = now - timedelta(hours=3) + assert a._freshness_decay(three_hours_ago, now) == 0.7 + + +def test_freshness_decay_12_hours(): + a = SentimentAggregator() + now = datetime.now(timezone.utc) + twelve_hours_ago = now - timedelta(hours=12) + assert a._freshness_decay(twelve_hours_ago, now) == 0.3 + + +def test_freshness_decay_old(): + a = SentimentAggregator() + now = datetime.now(timezone.utc) + two_days_ago = now - timedelta(days=2) + assert a._freshness_decay(two_days_ago, now) == 0.0 + + +def test_compute_composite(): + a = SentimentAggregator() + composite = a._compute_composite( + news_score=0.5, + social_score=0.3, + policy_score=0.8, + filing_score=0.2, + ) + expected = 0.5 * 0.3 + 0.3 * 0.2 + 0.8 * 0.3 + 0.2 * 0.2 + assert abs(composite - expected) < 0.001 + + +def test_aggregate_news_by_symbol(aggregator): + now = datetime.now(timezone.utc) + news_items = [ + { + "symbols": ["AAPL"], + "sentiment": 0.8, + "category": "earnings", + "published_at": now, + }, + { + "symbols": ["AAPL"], + "sentiment": 0.3, + "category": "macro", + "published_at": now - timedelta(hours=2), + }, + { + "symbols": ["MSFT"], + "sentiment": -0.5, + "category": "policy", + "published_at": now, + }, + ] + scores = aggregator.aggregate(news_items, now) + + assert "AAPL" in scores + assert "MSFT" in scores + assert scores["AAPL"].news_count == 2 + assert scores["AAPL"].news_score > 0 # Positive overall + assert scores["MSFT"].policy_score < 0 # Negative policy + + +def test_aggregate_empty(aggregator): + now = datetime.now(timezone.utc) + scores = aggregator.aggregate([], now) + assert scores == {} + + +def test_determine_regime(): + a = SentimentAggregator() + assert a.determine_regime(15, None) == "risk_off" + assert a.determine_regime(15, 35.0) == "risk_off" + assert a.determine_regime(50, 35.0) == "risk_off" + assert a.determine_regime(70, 15.0) == "risk_on" + assert a.determine_regime(50, 20.0) == "neutral" +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest shared/tests/test_sentiment_aggregator.py -v` +Expected: FAIL — `SentimentAggregator` not in sentiment.py + +- [ ] **Step 3: Add SentimentAggregator to sentiment.py** + +Keep the existing `SentimentData` class (for backward compat with existing tests). Add `SentimentAggregator` class at the end of `shared/src/shared/sentiment.py`: + +```python +from datetime import timedelta +from shared.sentiment_models import SymbolScore + + +class SentimentAggregator: + """Aggregates per-news sentiment into per-symbol scores.""" + + # Weights: policy events are most impactful for US stocks + WEIGHTS = { + "news": 0.3, + "social": 0.2, + "policy": 0.3, + "filing": 0.2, + } + + # Category → score field mapping + CATEGORY_MAP = { + "earnings": "news", + "macro": "news", + "social": "social", + "policy": "policy", + "filing": "filing", + "fed": "policy", + } + + def _freshness_decay(self, published_at: datetime, now: datetime) -> float: + """Compute freshness decay factor.""" + age = now - published_at + hours = age.total_seconds() / 3600 + if hours < 1: + return 1.0 + if hours < 6: + return 0.7 + if hours < 24: + return 0.3 + return 0.0 + + def _compute_composite( + self, + news_score: float, + social_score: float, + policy_score: float, + filing_score: float, + ) -> float: + return ( + news_score * self.WEIGHTS["news"] + + social_score * self.WEIGHTS["social"] + + policy_score * self.WEIGHTS["policy"] + + filing_score * self.WEIGHTS["filing"] + ) + + def aggregate( + self, news_items: list[dict], now: datetime + ) -> dict[str, SymbolScore]: + """Aggregate news items into per-symbol scores. + + Each news_items dict must have: symbols, sentiment, category, published_at. + Returns dict mapping symbol → SymbolScore. + """ + # Accumulate per-symbol, per-category + symbol_data: dict[str, dict] = {} + + for item in news_items: + decay = self._freshness_decay(item["published_at"], now) + if decay == 0.0: + continue + + category = item.get("category", "macro") + score_field = self.CATEGORY_MAP.get(category, "news") + weighted_sentiment = item["sentiment"] * decay + + for symbol in item.get("symbols", []): + if symbol not in symbol_data: + symbol_data[symbol] = { + "news_scores": [], + "social_scores": [], + "policy_scores": [], + "filing_scores": [], + "count": 0, + } + + symbol_data[symbol][f"{score_field}_scores"].append(weighted_sentiment) + symbol_data[symbol]["count"] += 1 + + # Compute averages and composites + result = {} + for symbol, data in symbol_data.items(): + news_score = _safe_avg(data["news_scores"]) + social_score = _safe_avg(data["social_scores"]) + policy_score = _safe_avg(data["policy_scores"]) + filing_score = _safe_avg(data["filing_scores"]) + + result[symbol] = SymbolScore( + symbol=symbol, + news_score=news_score, + news_count=data["count"], + social_score=social_score, + policy_score=policy_score, + filing_score=filing_score, + composite=self._compute_composite( + news_score, social_score, policy_score, filing_score + ), + updated_at=now, + ) + + return result + + def determine_regime(self, fear_greed: int, vix: float | None) -> str: + """Determine market regime.""" + if fear_greed <= 20: + return "risk_off" + if vix is not None and vix > 30: + return "risk_off" + if fear_greed >= 60 and (vix is None or vix < 20): + return "risk_on" + return "neutral" + + +def _safe_avg(values: list[float]) -> float: + """Return average of values, or 0.0 if empty.""" + if not values: + return 0.0 + return sum(values) / len(values) +``` + +- [ ] **Step 4: Run new tests to verify they pass** + +Run: `pytest shared/tests/test_sentiment_aggregator.py -v` +Expected: All 9 tests PASS + +- [ ] **Step 5: Run existing sentiment tests for regressions** + +Run: `pytest shared/tests/test_sentiment.py -v` +Expected: All existing tests PASS (SentimentData unchanged) + +- [ ] **Step 6: Commit** + +```bash +git add shared/src/shared/sentiment.py shared/tests/test_sentiment_aggregator.py +git commit -m "feat: implement SentimentAggregator with freshness decay and composite scoring" +``` + +--- + +## Phase 4: Stock Selector Engine + +### Task 15: Implement stock selector + +**Files:** +- Create: `services/strategy-engine/src/strategy_engine/stock_selector.py` +- Create: `services/strategy-engine/tests/test_stock_selector.py` + +- [ ] **Step 1: Write tests** + +Create `services/strategy-engine/tests/test_stock_selector.py`: + +```python +"""Tests for stock selector engine.""" + +import pytest +from unittest.mock import AsyncMock, MagicMock, patch +from datetime import datetime, timezone +from decimal import Decimal + +from shared.models import OrderSide +from shared.sentiment_models import SymbolScore, MarketSentiment, SelectedStock, Candidate + +from strategy_engine.stock_selector import ( + SentimentCandidateSource, + StockSelector, + _parse_llm_selections, +) + + +async def test_sentiment_candidate_source(): + mock_db = MagicMock() + mock_db.get_top_symbol_scores = AsyncMock(return_value=[ + {"symbol": "AAPL", "composite": 0.8, "news_count": 5}, + {"symbol": "NVDA", "composite": 0.6, "news_count": 3}, + ]) + + source = SentimentCandidateSource(mock_db) + candidates = await source.get_candidates() + + assert len(candidates) == 2 + assert candidates[0].symbol == "AAPL" + assert candidates[0].source == "sentiment" + + +def test_parse_llm_selections_valid(): + llm_response = """ + [ + {"symbol": "NVDA", "side": "BUY", "conviction": 0.85, "reason": "AI demand", "key_news": ["NVDA beats earnings"]}, + {"symbol": "XOM", "side": "BUY", "conviction": 0.72, "reason": "Oil surge", "key_news": ["Oil prices up"]} + ] + """ + selections = _parse_llm_selections(llm_response) + assert len(selections) == 2 + assert selections[0].symbol == "NVDA" + assert selections[0].conviction == 0.85 + + +def test_parse_llm_selections_invalid(): + selections = _parse_llm_selections("not json") + assert selections == [] + + +def test_parse_llm_selections_with_markdown(): + llm_response = """ + Here are my picks: + ```json + [ + {"symbol": "TSLA", "side": "BUY", "conviction": 0.7, "reason": "Momentum", "key_news": ["Tesla rally"]} + ] + ``` + """ + selections = _parse_llm_selections(llm_response) + assert len(selections) == 1 + assert selections[0].symbol == "TSLA" + + +async def test_selector_blocks_on_risk_off(): + mock_db = MagicMock() + mock_db.get_latest_market_sentiment = AsyncMock(return_value={ + "fear_greed": 15, + "fear_greed_label": "Extreme Fear", + "vix": 35.0, + "fed_stance": "neutral", + "market_regime": "risk_off", + "updated_at": datetime.now(timezone.utc), + }) + + selector = StockSelector(db=mock_db, broker=MagicMock(), alpaca=MagicMock(), anthropic_api_key="test") + result = await selector.select() + assert result == [] +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest services/strategy-engine/tests/test_stock_selector.py -v` +Expected: FAIL — module not found + +- [ ] **Step 3: Implement StockSelector** + +Create `services/strategy-engine/src/strategy_engine/stock_selector.py`: + +```python +"""Stock Selector Engine — 3-stage dynamic stock selection for MOC trading.""" + +import json +import logging +import re +from datetime import datetime, timezone +from decimal import Decimal +from typing import Optional + +import aiohttp + +from shared.alpaca import AlpacaClient +from shared.broker import RedisBroker +from shared.db import Database +from shared.models import OrderSide +from shared.sentiment_models import Candidate, MarketSentiment, SelectedStock, SymbolScore + +logger = logging.getLogger(__name__) + + +class SentimentCandidateSource: + """Get candidate stocks from sentiment scores in DB.""" + + def __init__(self, db: Database, limit: int = 20) -> None: + self._db = db + self._limit = limit + + async def get_candidates(self) -> list[Candidate]: + scores = await self._db.get_top_symbol_scores(limit=self._limit) + return [ + Candidate( + symbol=s["symbol"], + source="sentiment", + score=s["composite"], + reason=f"Sentiment composite={s['composite']:.2f}, news_count={s['news_count']}", + ) + for s in scores + if s["composite"] != 0 + ] + + +class LLMCandidateSource: + """Get candidate stocks by asking Claude to analyze today's top news.""" + + def __init__(self, db: Database, api_key: str, model: str) -> None: + self._db = db + self._api_key = api_key + self._model = model + + async def get_candidates(self) -> list[Candidate]: + news = await self._db.get_recent_news(hours=24) + if not news: + return [] + + headlines = [f"- [{n['source']}] {n['headline']} (sentiment: {n['sentiment']:.2f})" for n in news[:50]] + prompt = ( + "You are a stock market analyst. Based on today's news headlines below, " + "identify US stocks that are most likely to be affected (positively or negatively). " + "Return a JSON array of objects with: symbol, direction (BUY or SELL), score (0-1), reason.\n\n" + "Headlines:\n" + "\n".join(headlines) + "\n\n" + "Return ONLY the JSON array, no other text." + ) + + try: + async with aiohttp.ClientSession() as session: + async with session.post( + "https://api.anthropic.com/v1/messages", + headers={ + "x-api-key": self._api_key, + "anthropic-version": "2023-06-01", + "content-type": "application/json", + }, + json={ + "model": self._model, + "max_tokens": 1024, + "messages": [{"role": "user", "content": prompt}], + }, + timeout=aiohttp.ClientTimeout(total=30), + ) as resp: + if resp.status != 200: + logger.warning("llm_candidate_failed", status=resp.status) + return [] + data = await resp.json() + text = data["content"][0]["text"] + except Exception as exc: + logger.error("llm_candidate_error", error=str(exc)) + return [] + + return self._parse_response(text) + + def _parse_response(self, text: str) -> list[Candidate]: + try: + # Extract JSON from possible markdown code blocks + json_match = re.search(r"```(?:json)?\s*(\[.*?\])\s*```", text, re.DOTALL) + if json_match: + text = json_match.group(1) + items = json.loads(text) + except (json.JSONDecodeError, TypeError): + return [] + + candidates = [] + for item in items: + try: + direction = OrderSide(item.get("direction", "BUY")) + candidates.append( + Candidate( + symbol=item["symbol"], + source="llm", + direction=direction, + score=float(item.get("score", 0.5)), + reason=item.get("reason", "LLM recommendation"), + ) + ) + except (KeyError, ValueError): + continue + + return candidates + + +class StockSelector: + """3-stage stock selector: candidates → technical filter → LLM final pick.""" + + def __init__( + self, + db: Database, + broker: RedisBroker, + alpaca: AlpacaClient, + anthropic_api_key: str, + anthropic_model: str = "claude-sonnet-4-20250514", + max_picks: int = 3, + ) -> None: + self._db = db + self._broker = broker + self._alpaca = alpaca + self._api_key = anthropic_api_key + self._model = anthropic_model + self._max_picks = max_picks + self._sentiment_source = SentimentCandidateSource(db) + self._llm_source = LLMCandidateSource(db, anthropic_api_key, anthropic_model) + + async def select(self) -> list[SelectedStock]: + """Run full 3-stage selection. Returns list of SelectedStock.""" + # Check market sentiment gate + ms = await self._db.get_latest_market_sentiment() + if ms and ms.get("market_regime") == "risk_off": + logger.info("selection_blocked_risk_off") + return [] + + # Stage 1: Candidate pool + sentiment_candidates = await self._sentiment_source.get_candidates() + llm_candidates = await self._llm_source.get_candidates() + candidates = self._merge_candidates(sentiment_candidates, llm_candidates) + + if not candidates: + logger.info("no_candidates_found") + return [] + + logger.info("candidates_found", count=len(candidates)) + + # Stage 2: Technical filter + filtered = await self._technical_filter(candidates) + if not filtered: + logger.info("all_candidates_filtered_out") + return [] + + logger.info("technical_filter_passed", count=len(filtered)) + + # Stage 3: LLM final selection + selections = await self._llm_final_select(filtered, ms) + + # Publish to Redis + for selection in selections: + await self._broker.publish( + "selected_stocks", + selection.model_dump(mode="json"), + ) + + # Persist audit trail + from datetime import date as date_type + + for selection in selections: + score_data = await self._db.get_top_symbol_scores(limit=100) + snapshot = next( + (s for s in score_data if s["symbol"] == selection.symbol), + {}, + ) + await self._db.insert_stock_selection( + trade_date=date_type.today(), + symbol=selection.symbol, + side=selection.side.value, + conviction=selection.conviction, + reason=selection.reason, + key_news=selection.key_news, + sentiment_snapshot=snapshot, + ) + + return selections + + def _merge_candidates( + self, + sentiment: list[Candidate], + llm: list[Candidate], + ) -> list[Candidate]: + """Merge and deduplicate candidates, preferring higher scores.""" + by_symbol: dict[str, Candidate] = {} + for c in sentiment + llm: + if c.symbol not in by_symbol or c.score > by_symbol[c.symbol].score: + by_symbol[c.symbol] = c + return sorted(by_symbol.values(), key=lambda c: c.score, reverse=True) + + async def _technical_filter(self, candidates: list[Candidate]) -> list[Candidate]: + """Apply MOC-style technical screening to candidates.""" + import pandas as pd + + passed = [] + for candidate in candidates: + try: + bars = await self._alpaca.get_bars( + candidate.symbol, timeframe="1Day", limit=30 + ) + if not bars or len(bars) < 21: + continue + + closes = pd.Series([float(b["c"]) for b in bars]) + volumes = pd.Series([float(b["v"]) for b in bars]) + + # RSI + delta = closes.diff() + gain = delta.clip(lower=0) + loss = -delta.clip(upper=0) + avg_gain = gain.ewm(com=13, min_periods=14).mean() + avg_loss = loss.ewm(com=13, min_periods=14).mean() + rs = avg_gain / avg_loss.replace(0, float("nan")) + rsi = 100 - (100 / (1 + rs)) + current_rsi = rsi.iloc[-1] + + if pd.isna(current_rsi) or not (30 <= current_rsi <= 70): + continue + + # EMA + ema20 = closes.ewm(span=20, adjust=False).mean().iloc[-1] + if closes.iloc[-1] < ema20: + continue + + # Volume above average + vol_avg = volumes.iloc[-20:].mean() + if vol_avg > 0 and volumes.iloc[-1] < vol_avg * 0.5: + continue + + passed.append(candidate) + + except Exception as exc: + logger.warning("technical_filter_error", symbol=candidate.symbol, error=str(exc)) + continue + + return passed + + async def _llm_final_select( + self, + candidates: list[Candidate], + market_sentiment: Optional[dict], + ) -> list[SelectedStock]: + """Ask Claude to make final 2-3 picks from filtered candidates.""" + # Build context + candidate_info = [] + for c in candidates[:15]: + candidate_info.append(f"- {c.symbol}: score={c.score:.2f}, source={c.source}, reason={c.reason}") + + news = await self._db.get_recent_news(hours=12) + top_news = [f"- [{n['source']}] {n['headline']}" for n in news[:20]] + + ms_info = "No market sentiment data available." + if market_sentiment: + ms_info = ( + f"Fear & Greed: {market_sentiment.get('fear_greed', 'N/A')} " + f"({market_sentiment.get('fear_greed_label', 'N/A')}), " + f"VIX: {market_sentiment.get('vix', 'N/A')}, " + f"Fed Stance: {market_sentiment.get('fed_stance', 'N/A')}" + ) + + prompt = ( + f"You are a professional stock trader selecting {self._max_picks} stocks for " + f"Market-on-Close (MOC) overnight trading. You buy at market close and sell at " + f"next day's open.\n\n" + f"## Market Conditions\n{ms_info}\n\n" + f"## Candidate Stocks (pre-screened technically)\n" + + "\n".join(candidate_info) + "\n\n" + f"## Today's Key News\n" + + "\n".join(top_news) + "\n\n" + f"Select the best {self._max_picks} stocks. For each, provide:\n" + f"- symbol: ticker\n" + f"- side: BUY or SELL\n" + f"- conviction: 0.0-1.0\n" + f"- reason: one sentence\n" + f"- key_news: list of relevant headlines\n\n" + f"Return ONLY a JSON array. No other text." + ) + + try: + async with aiohttp.ClientSession() as session: + async with session.post( + "https://api.anthropic.com/v1/messages", + headers={ + "x-api-key": self._api_key, + "anthropic-version": "2023-06-01", + "content-type": "application/json", + }, + json={ + "model": self._model, + "max_tokens": 1024, + "messages": [{"role": "user", "content": prompt}], + }, + timeout=aiohttp.ClientTimeout(total=30), + ) as resp: + if resp.status != 200: + logger.error("llm_final_select_failed", status=resp.status) + return [] + data = await resp.json() + text = data["content"][0]["text"] + except Exception as exc: + logger.error("llm_final_select_error", error=str(exc)) + return [] + + return _parse_llm_selections(text) + + +def _parse_llm_selections(text: str) -> list[SelectedStock]: + """Parse LLM response into SelectedStock list.""" + try: + json_match = re.search(r"```(?:json)?\s*(\[.*?\])\s*```", text, re.DOTALL) + if json_match: + text = json_match.group(1) + # Also try to find a bare JSON array + array_match = re.search(r"\[.*\]", text, re.DOTALL) + if array_match: + text = array_match.group(0) + items = json.loads(text) + except (json.JSONDecodeError, TypeError): + return [] + + selections = [] + for item in items: + try: + selections.append( + SelectedStock( + symbol=item["symbol"], + side=OrderSide(item.get("side", "BUY")), + conviction=float(item.get("conviction", 0.5)), + reason=item.get("reason", ""), + key_news=item.get("key_news", []), + ) + ) + except (KeyError, ValueError): + continue + + return selections +``` + +- [ ] **Step 4: Run tests to verify they pass** + +Run: `pytest services/strategy-engine/tests/test_stock_selector.py -v` +Expected: All 5 tests PASS + +- [ ] **Step 5: Run all strategy engine tests for regressions** + +Run: `pytest services/strategy-engine/tests/ -v` +Expected: All tests PASS + +- [ ] **Step 6: Commit** + +```bash +git add services/strategy-engine/src/strategy_engine/stock_selector.py services/strategy-engine/tests/test_stock_selector.py +git commit -m "feat: implement 3-stage stock selector (sentiment → technical → LLM)" +``` + +--- + +## Phase 5: Integration (MOC + Notifications + Docker) + +### Task 16: Add Telegram notification for stock selections + +**Files:** +- Modify: `shared/src/shared/notifier.py` +- Modify: `shared/tests/test_notifier.py` + +- [ ] **Step 1: Add send_stock_selection method to notifier.py** + +Add this method and import to `shared/src/shared/notifier.py`: + +Add to imports: +```python +from shared.sentiment_models import SelectedStock, MarketSentiment +``` + +Add method to `TelegramNotifier` class: + +```python + async def send_stock_selection( + self, + selections: list[SelectedStock], + market: MarketSentiment | None = None, + ) -> None: + """Format and send stock selection notification.""" + lines = [f"<b>📊 Stock Selection ({len(selections)} picks)</b>", ""] + + side_emoji = {"BUY": "🟢", "SELL": "🔴"} + + for i, s in enumerate(selections, 1): + emoji = side_emoji.get(s.side.value, "⚪") + lines.append( + f"{i}. <b>{s.symbol}</b> {emoji} {s.side.value} " + f"(conviction: {s.conviction:.0%})" + ) + lines.append(f" {s.reason}") + if s.key_news: + lines.append(f" News: {s.key_news[0]}") + lines.append("") + + if market: + lines.append( + f"Market: F&G {market.fear_greed} ({market.fear_greed_label})" + + (f" | VIX {market.vix:.1f}" if market.vix else "") + ) + + await self.send("\n".join(lines)) +``` + +- [ ] **Step 2: Add test for the new method** + +Add to `shared/tests/test_notifier.py`: + +```python +from shared.models import OrderSide +from shared.sentiment_models import SelectedStock, MarketSentiment +from datetime import datetime, timezone + + +async def test_send_stock_selection(notifier, mock_session): + """Test stock selection notification formatting.""" + selections = [ + SelectedStock( + symbol="NVDA", + side=OrderSide.BUY, + conviction=0.85, + reason="CHIPS Act expansion", + key_news=["Trump signs CHIPS Act"], + ), + ] + market = MarketSentiment( + fear_greed=55, + fear_greed_label="Neutral", + vix=18.2, + fed_stance="neutral", + market_regime="neutral", + updated_at=datetime.now(timezone.utc), + ) + await notifier.send_stock_selection(selections, market) + mock_session.post.assert_called_once() +``` + +Note: Check `shared/tests/test_notifier.py` for existing fixture names (`notifier`, `mock_session`) and adapt accordingly. + +- [ ] **Step 3: Run notifier tests** + +Run: `pytest shared/tests/test_notifier.py -v` +Expected: All tests PASS + +- [ ] **Step 4: Commit** + +```bash +git add shared/src/shared/notifier.py shared/tests/test_notifier.py +git commit -m "feat: add Telegram notification for stock selections" +``` + +--- + +### Task 17: Integrate stock selector with MOC strategy + +**Files:** +- Modify: `services/strategy-engine/src/strategy_engine/main.py` +- Modify: `services/strategy-engine/src/strategy_engine/config.py` + +- [ ] **Step 1: Update strategy engine config** + +Add to `StrategyConfig` in `services/strategy-engine/src/strategy_engine/config.py`: + +```python + selector_candidates_time: str = "15:00" + selector_filter_time: str = "15:15" + selector_final_time: str = "15:30" + selector_max_picks: int = 3 + anthropic_api_key: str = "" + anthropic_model: str = "claude-sonnet-4-20250514" +``` + +- [ ] **Step 2: Add stock selector scheduling to main.py** + +Add a new coroutine to `services/strategy-engine/src/strategy_engine/main.py` that runs the stock selector at the configured times. Add imports: + +```python +from shared.alpaca import AlpacaClient +from shared.db import Database +from shared.notifier import TelegramNotifier +from shared.sentiment_models import MarketSentiment +from strategy_engine.stock_selector import StockSelector +``` + +Add the selector loop function: + +```python +async def run_stock_selector( + selector: StockSelector, + notifier: TelegramNotifier, + db: Database, + config: StrategyConfig, + log, +) -> None: + """Run the stock selector once per day at the configured time.""" + import zoneinfo + + et = zoneinfo.ZoneInfo("America/New_York") + + while True: + now_et = datetime.now(et) + target_hour, target_min = map(int, config.selector_final_time.split(":")) + + # Check if it's time to run (within 1-minute window) + if now_et.hour == target_hour and now_et.minute == target_min: + log.info("stock_selector_running") + try: + selections = await selector.select() + if selections: + ms_data = await db.get_latest_market_sentiment() + ms = None + if ms_data: + ms = MarketSentiment(**ms_data) + await notifier.send_stock_selection(selections, ms) + log.info( + "stock_selector_complete", + picks=[s.symbol for s in selections], + ) + else: + log.info("stock_selector_no_picks") + except Exception as exc: + log.error("stock_selector_error", error=str(exc)) + # Sleep past this minute to avoid re-triggering + await asyncio.sleep(120) + else: + await asyncio.sleep(30) +``` + +In the `run()` function, add after creating the broker: + +```python + db = Database(config.database_url) + await db.connect() + + alpaca = AlpacaClient( + api_key=config.alpaca_api_key, + api_secret=config.alpaca_api_secret, + paper=config.alpaca_paper, + ) +``` + +And add the selector if anthropic key is configured: + +```python + if config.anthropic_api_key: + selector = StockSelector( + db=db, + broker=broker, + alpaca=alpaca, + anthropic_api_key=config.anthropic_api_key, + anthropic_model=config.anthropic_model, + max_picks=config.selector_max_picks, + ) + tasks.append(asyncio.create_task( + run_stock_selector(selector, notifier, db, config, log) + )) + log.info("stock_selector_enabled", time=config.selector_final_time) +``` + +Add to the `finally` block: + +```python + await alpaca.close() + await db.close() +``` + +- [ ] **Step 3: Run strategy engine tests for regressions** + +Run: `pytest services/strategy-engine/tests/ -v` +Expected: All tests PASS + +- [ ] **Step 4: Commit** + +```bash +git add services/strategy-engine/src/strategy_engine/main.py services/strategy-engine/src/strategy_engine/config.py +git commit -m "feat: integrate stock selector into strategy engine scheduler" +``` + +--- + +### Task 18: Update Docker Compose and .env + +**Files:** +- Modify: `docker-compose.yml` +- Modify: `.env.example` (already done in Task 5, just verify) + +- [ ] **Step 1: Add news-collector service to docker-compose.yml** + +Add before the `loki:` service block in `docker-compose.yml`: + +```yaml + news-collector: + build: + context: . + dockerfile: services/news-collector/Dockerfile + env_file: .env + ports: + - "8084:8084" + depends_on: + redis: + condition: service_healthy + postgres: + condition: service_healthy + healthcheck: + test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8084/health')"] + interval: 10s + timeout: 5s + retries: 3 + restart: unless-stopped +``` + +- [ ] **Step 2: Verify compose file is valid** + +Run: `docker compose config --quiet 2>&1 || echo "INVALID"` +Expected: No output (valid) or compose config displayed without errors + +- [ ] **Step 3: Commit** + +```bash +git add docker-compose.yml +git commit -m "feat: add news-collector service to Docker Compose" +``` + +--- + +### Task 19: Run full test suite and lint + +- [ ] **Step 1: Install test dependencies** + +Run: `pip install -e shared/ && pip install aiosqlite feedparser nltk aioresponses` + +- [ ] **Step 2: Download VADER lexicon** + +Run: `python -c "import nltk; nltk.download('vader_lexicon', quiet=True)"` + +- [ ] **Step 3: Run lint** + +Run: `make lint` +Expected: No lint errors. If there are errors, fix them. + +- [ ] **Step 4: Run full test suite** + +Run: `make test` +Expected: All tests PASS + +- [ ] **Step 5: Fix any issues found in steps 3-4** + +If lint or tests fail, fix the issues and re-run. + +- [ ] **Step 6: Final commit if any fixes were needed** + +```bash +git add -A +git commit -m "fix: resolve lint and test issues from news selector integration" +``` diff --git a/docs/superpowers/plans/2026-04-02-platform-upgrade.md b/docs/superpowers/plans/2026-04-02-platform-upgrade.md new file mode 100644 index 0000000..c28d287 --- /dev/null +++ b/docs/superpowers/plans/2026-04-02-platform-upgrade.md @@ -0,0 +1,1991 @@ +# Platform Upgrade Implementation Plan + +> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking. + +**Goal:** Upgrade the trading platform across 5 phases: shared library hardening, infrastructure improvements, service-level fixes, API security, and operational maturity. + +**Architecture:** Bottom-up approach — harden the shared library first (resilience, DB pooling, Redis resilience, config validation), then improve infrastructure (Docker, DB indexes), then fix all services (graceful shutdown, exception handling), then add API security (auth, CORS, rate limiting), and finally improve operations (CI/CD, linting, alerting). + +**Tech Stack:** Python 3.12, asyncio, tenacity, SQLAlchemy 2.0 async, Redis Streams, FastAPI, slowapi, Ruff, GitHub Actions, Prometheus Alertmanager + +--- + +## File Structure + +### New Files +- `shared/src/shared/resilience.py` — Retry decorator, circuit breaker, timeout wrapper +- `shared/tests/test_resilience.py` — Tests for resilience module +- `shared/alembic/versions/003_add_missing_indexes.py` — DB index migration +- `.dockerignore` — Docker build exclusions +- `services/api/src/trading_api/dependencies/auth.py` — Bearer token auth dependency +- `.github/workflows/ci.yml` — GitHub Actions CI pipeline +- `monitoring/prometheus/alert_rules.yml` — Prometheus alerting rules + +### Modified Files +- `shared/src/shared/db.py` — Add connection pool config +- `shared/src/shared/broker.py` — Add Redis resilience +- `shared/src/shared/config.py` — Add validators, SecretStr, new fields +- `shared/pyproject.toml` — Pin deps, add tenacity +- `pyproject.toml` — Enhanced ruff rules, pytest-cov +- `services/strategy-engine/src/strategy_engine/stock_selector.py` — Fix bug, deduplicate, session reuse +- `services/*/src/*/main.py` — Signal handlers, exception specialization (all 6 services) +- `services/*/Dockerfile` — Multi-stage builds, non-root user (all 7 Dockerfiles) +- `services/api/pyproject.toml` — Add slowapi +- `services/api/src/trading_api/main.py` — CORS, auth, rate limiting +- `services/api/src/trading_api/routers/*.py` — Input validation, response models +- `docker-compose.yml` — Remove hardcoded creds, add resource limits, networks +- `.env.example` — Add new fields, mark secrets +- `monitoring/prometheus.yml` — Reference alert rules + +--- + +## Phase 1: Shared Library Hardening + +### Task 1: Implement Resilience Module + +**Files:** +- Create: `shared/src/shared/resilience.py` +- Create: `shared/tests/test_resilience.py` +- Modify: `shared/pyproject.toml:6-18` + +- [ ] **Step 1: Add tenacity dependency to shared/pyproject.toml** + +In `shared/pyproject.toml`, add `tenacity` to the dependencies list: + +```python +dependencies = [ + "pydantic>=2.8,<3", + "pydantic-settings>=2.0,<3", + "redis>=5.0,<6", + "asyncpg>=0.29,<1", + "sqlalchemy[asyncio]>=2.0,<3", + "alembic>=1.13,<2", + "structlog>=24.0,<25", + "prometheus-client>=0.20,<1", + "pyyaml>=6.0,<7", + "aiohttp>=3.9,<4", + "rich>=13.0,<14", + "tenacity>=8.2,<10", +] +``` + +Note: This also pins all existing dependencies with upper bounds. + +- [ ] **Step 2: Write failing tests for retry_async** + +Create `shared/tests/test_resilience.py`: + +```python +"""Tests for the resilience module.""" + +import asyncio + +import pytest + +from shared.resilience import retry_async, CircuitBreaker, async_timeout + + +class TestRetryAsync: + async def test_succeeds_without_retry(self): + call_count = 0 + + @retry_async(max_retries=3) + async def succeed(): + nonlocal call_count + call_count += 1 + return "ok" + + result = await succeed() + assert result == "ok" + assert call_count == 1 + + async def test_retries_on_failure_then_succeeds(self): + call_count = 0 + + @retry_async(max_retries=3, base_delay=0.01) + async def fail_twice(): + nonlocal call_count + call_count += 1 + if call_count < 3: + raise ConnectionError("fail") + return "ok" + + result = await fail_twice() + assert result == "ok" + assert call_count == 3 + + async def test_raises_after_max_retries(self): + @retry_async(max_retries=2, base_delay=0.01) + async def always_fail(): + raise ConnectionError("fail") + + with pytest.raises(ConnectionError): + await always_fail() + + async def test_no_retry_on_excluded_exception(self): + call_count = 0 + + @retry_async(max_retries=3, base_delay=0.01, exclude=(ValueError,)) + async def raise_value_error(): + nonlocal call_count + call_count += 1 + raise ValueError("bad input") + + with pytest.raises(ValueError): + await raise_value_error() + assert call_count == 1 + + +class TestCircuitBreaker: + async def test_closed_allows_calls(self): + cb = CircuitBreaker(failure_threshold=3, cooldown=0.1) + + async def succeed(): + return "ok" + + result = await cb.call(succeed) + assert result == "ok" + + async def test_opens_after_threshold(self): + cb = CircuitBreaker(failure_threshold=2, cooldown=60) + + async def fail(): + raise ConnectionError("fail") + + for _ in range(2): + with pytest.raises(ConnectionError): + await cb.call(fail) + + with pytest.raises(RuntimeError, match="Circuit breaker is open"): + await cb.call(fail) + + async def test_half_open_after_cooldown(self): + cb = CircuitBreaker(failure_threshold=2, cooldown=0.05) + + call_count = 0 + + async def fail_then_succeed(): + nonlocal call_count + call_count += 1 + if call_count <= 2: + raise ConnectionError("fail") + return "recovered" + + # Trip the breaker + for _ in range(2): + with pytest.raises(ConnectionError): + await cb.call(fail_then_succeed) + + # Wait for cooldown + await asyncio.sleep(0.1) + + # Should allow one call (half-open) + result = await cb.call(fail_then_succeed) + assert result == "recovered" + + +class TestAsyncTimeout: + async def test_completes_within_timeout(self): + async with async_timeout(1.0): + await asyncio.sleep(0.01) + + async def test_raises_on_timeout(self): + with pytest.raises(asyncio.TimeoutError): + async with async_timeout(0.01): + await asyncio.sleep(1.0) +``` + +- [ ] **Step 3: Run tests to verify they fail** + +Run: `pytest shared/tests/test_resilience.py -v` +Expected: FAIL with `ImportError: cannot import name 'retry_async' from 'shared.resilience'` + +- [ ] **Step 4: Implement resilience module** + +Write `shared/src/shared/resilience.py`: + +```python +"""Resilience utilities: retry, circuit breaker, timeout.""" + +import asyncio +import functools +import logging +import time +from contextlib import asynccontextmanager + +logger = logging.getLogger(__name__) + + +def retry_async( + max_retries: int = 3, + base_delay: float = 1.0, + max_delay: float = 30.0, + exclude: tuple[type[Exception], ...] = (), +): + """Decorator for async functions with exponential backoff + jitter. + + Args: + max_retries: Maximum number of retry attempts. + base_delay: Initial delay in seconds between retries. + max_delay: Maximum delay cap in seconds. + exclude: Exception types that should NOT be retried. + """ + + def decorator(func): + @functools.wraps(func) + async def wrapper(*args, **kwargs): + last_exc = None + for attempt in range(max_retries + 1): + try: + return await func(*args, **kwargs) + except exclude: + raise + except Exception as exc: + last_exc = exc + if attempt == max_retries: + raise + delay = min(base_delay * (2**attempt), max_delay) + # Add jitter: 50-100% of delay + import random + + delay = delay * (0.5 + random.random() * 0.5) + logger.warning( + "retry attempt=%d/%d delay=%.2fs error=%s func=%s", + attempt + 1, + max_retries, + delay, + str(exc), + func.__name__, + ) + await asyncio.sleep(delay) + raise last_exc # Should not reach here, but just in case + + return wrapper + + return decorator + + +class CircuitBreaker: + """Circuit breaker: opens after consecutive failures, auto-recovers after cooldown.""" + + def __init__(self, failure_threshold: int = 5, cooldown: float = 60.0) -> None: + self._failure_threshold = failure_threshold + self._cooldown = cooldown + self._failure_count = 0 + self._last_failure_time: float = 0 + self._state = "closed" # closed, open, half_open + + async def call(self, func, *args, **kwargs): + if self._state == "open": + if time.monotonic() - self._last_failure_time >= self._cooldown: + self._state = "half_open" + else: + raise RuntimeError("Circuit breaker is open") + + try: + result = await func(*args, **kwargs) + self._failure_count = 0 + self._state = "closed" + return result + except Exception: + self._failure_count += 1 + self._last_failure_time = time.monotonic() + if self._failure_count >= self._failure_threshold: + self._state = "open" + logger.error( + "circuit_breaker_opened failures=%d cooldown=%.0fs", + self._failure_count, + self._cooldown, + ) + raise + + +@asynccontextmanager +async def async_timeout(seconds: float): + """Async context manager that raises TimeoutError after given seconds.""" + try: + async with asyncio.timeout(seconds): + yield + except TimeoutError: + raise asyncio.TimeoutError(f"Operation timed out after {seconds}s") +``` + +- [ ] **Step 5: Run tests to verify they pass** + +Run: `pytest shared/tests/test_resilience.py -v` +Expected: All 8 tests PASS + +- [ ] **Step 6: Commit** + +```bash +git add shared/src/shared/resilience.py shared/tests/test_resilience.py shared/pyproject.toml +git commit -m "feat: implement resilience module with retry, circuit breaker, timeout" +``` + +--- + +### Task 2: Add DB Connection Pooling + +**Files:** +- Modify: `shared/src/shared/db.py:39-44` +- Modify: `shared/src/shared/config.py:10-11` +- Modify: `shared/tests/test_db.py` (add pool config test) + +- [ ] **Step 1: Write failing test for pool config** + +Add to `shared/tests/test_db.py`: + +```python +async def test_connect_configures_pool(tmp_path): + """Engine should be created with pool configuration.""" + db = Database("sqlite+aiosqlite:///:memory:") + await db.connect() + engine = db._engine + pool = engine.pool + # aiosqlite uses StaticPool so we just verify connect works + assert engine is not None + await db.close() +``` + +- [ ] **Step 2: Add pool settings to config.py** + +In `shared/src/shared/config.py`, add after line 11 (`database_url`): + +```python + db_pool_size: int = 20 + db_max_overflow: int = 10 + db_pool_recycle: int = 3600 +``` + +- [ ] **Step 3: Update Database.connect() with pool parameters** + +In `shared/src/shared/db.py`, replace line 41: + +```python + self._engine = create_async_engine(self._database_url) +``` + +with: + +```python + self._engine = create_async_engine( + self._database_url, + pool_pre_ping=True, + pool_size=pool_size, + max_overflow=max_overflow, + pool_recycle=pool_recycle, + ) +``` + +Update the `connect` method signature to accept pool params: + +```python + async def connect( + self, + pool_size: int = 20, + max_overflow: int = 10, + pool_recycle: int = 3600, + ) -> None: + """Create the async engine, session factory, and all tables.""" + if self._database_url.startswith("sqlite"): + self._engine = create_async_engine(self._database_url) + else: + self._engine = create_async_engine( + self._database_url, + pool_pre_ping=True, + pool_size=pool_size, + max_overflow=max_overflow, + pool_recycle=pool_recycle, + ) + self._session_factory = async_sessionmaker(self._engine, expire_on_commit=False) + async with self._engine.begin() as conn: + await conn.run_sync(Base.metadata.create_all) +``` + +- [ ] **Step 4: Run tests** + +Run: `pytest shared/tests/test_db.py -v` +Expected: PASS + +- [ ] **Step 5: Commit** + +```bash +git add shared/src/shared/db.py shared/src/shared/config.py shared/tests/test_db.py +git commit -m "feat: add DB connection pooling with configurable pool_size, overflow, recycle" +``` + +--- + +### Task 3: Add Redis Resilience + +**Files:** +- Modify: `shared/src/shared/broker.py:1-13,15-18,102-104` +- Create: `shared/tests/test_broker_resilience.py` + +- [ ] **Step 1: Write failing tests for Redis resilience** + +Create `shared/tests/test_broker_resilience.py`: + +```python +"""Tests for Redis broker resilience features.""" + +from unittest.mock import AsyncMock, patch + +import pytest + +from shared.broker import RedisBroker + + +class TestBrokerResilience: + async def test_publish_retries_on_connection_error(self): + broker = RedisBroker.__new__(RedisBroker) + mock_redis = AsyncMock() + call_count = 0 + + async def xadd_failing(*args, **kwargs): + nonlocal call_count + call_count += 1 + if call_count < 3: + raise ConnectionError("Redis connection lost") + return "msg-id" + + mock_redis.xadd = xadd_failing + broker._redis = mock_redis + + await broker.publish("test-stream", {"key": "value"}) + assert call_count == 3 + + async def test_ping_retries_on_timeout(self): + broker = RedisBroker.__new__(RedisBroker) + mock_redis = AsyncMock() + call_count = 0 + + async def ping_failing(): + nonlocal call_count + call_count += 1 + if call_count < 2: + raise TimeoutError("timeout") + return True + + mock_redis.ping = ping_failing + broker._redis = mock_redis + + result = await broker.ping() + assert result is True + assert call_count == 2 +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest shared/tests/test_broker_resilience.py -v` +Expected: FAIL (publish doesn't retry) + +- [ ] **Step 3: Add resilience to broker.py** + +Replace `shared/src/shared/broker.py`: + +```python +"""Redis Streams broker for the trading platform.""" + +import json +import logging +from typing import Any + +import redis.asyncio + +from shared.resilience import retry_async + +logger = logging.getLogger(__name__) + + +class RedisBroker: + """Async Redis Streams broker for publishing and reading events.""" + + def __init__(self, redis_url: str) -> None: + self._redis = redis.asyncio.from_url( + redis_url, + socket_keepalive=True, + health_check_interval=30, + retry_on_timeout=True, + ) + + @retry_async(max_retries=3, base_delay=0.5, exclude=(ValueError,)) + async def publish(self, stream: str, data: dict[str, Any]) -> None: + """Publish a message to a Redis stream.""" + payload = json.dumps(data) + await self._redis.xadd(stream, {"payload": payload}) + + async def ensure_group(self, stream: str, group: str) -> None: + """Create a consumer group if it doesn't exist.""" + try: + await self._redis.xgroup_create(stream, group, id="0", mkstream=True) + except redis.ResponseError as e: + if "BUSYGROUP" not in str(e): + raise + + @retry_async(max_retries=3, base_delay=0.5, exclude=(ValueError,)) + async def read_group( + self, + stream: str, + group: str, + consumer: str, + count: int = 10, + block: int = 0, + ) -> list[tuple[str, dict[str, Any]]]: + """Read messages from a consumer group. Returns list of (message_id, data).""" + results = await self._redis.xreadgroup( + group, consumer, {stream: ">"}, count=count, block=block + ) + messages = [] + if results: + for _stream, entries in results: + for msg_id, fields in entries: + payload = fields.get(b"payload") or fields.get("payload") + if payload: + if isinstance(payload, bytes): + payload = payload.decode() + if isinstance(msg_id, bytes): + msg_id = msg_id.decode() + messages.append((msg_id, json.loads(payload))) + return messages + + async def ack(self, stream: str, group: str, *msg_ids: str) -> None: + """Acknowledge messages in a consumer group.""" + if msg_ids: + await self._redis.xack(stream, group, *msg_ids) + + async def read_pending( + self, + stream: str, + group: str, + consumer: str, + count: int = 10, + ) -> list[tuple[str, dict[str, Any]]]: + """Read pending (unacknowledged) messages for this consumer.""" + results = await self._redis.xreadgroup(group, consumer, {stream: "0"}, count=count) + messages = [] + if results: + for _stream, entries in results: + for msg_id, fields in entries: + if not fields: + continue + payload = fields.get(b"payload") or fields.get("payload") + if payload: + if isinstance(payload, bytes): + payload = payload.decode() + if isinstance(msg_id, bytes): + msg_id = msg_id.decode() + messages.append((msg_id, json.loads(payload))) + return messages + + async def read( + self, + stream: str, + last_id: str = "$", + count: int = 10, + block: int = 0, + ) -> list[dict[str, Any]]: + """Read messages (original method, kept for backward compatibility).""" + results = await self._redis.xread({stream: last_id}, count=count, block=block) + messages = [] + if results: + for _stream, entries in results: + for _msg_id, fields in entries: + payload = fields.get(b"payload") or fields.get("payload") + if payload: + if isinstance(payload, bytes): + payload = payload.decode() + messages.append(json.loads(payload)) + return messages + + @retry_async(max_retries=2, base_delay=0.5) + async def ping(self) -> bool: + """Ping the Redis server; return True if reachable.""" + return await self._redis.ping() + + async def close(self) -> None: + """Close the Redis connection.""" + await self._redis.aclose() +``` + +- [ ] **Step 4: Run tests** + +Run: `pytest shared/tests/test_broker_resilience.py -v` +Expected: PASS + +Run: `pytest shared/tests/test_broker.py -v` +Expected: PASS (existing tests still work) + +- [ ] **Step 5: Commit** + +```bash +git add shared/src/shared/broker.py shared/tests/test_broker_resilience.py +git commit -m "feat: add retry and resilience to Redis broker with keepalive" +``` + +--- + +### Task 4: Config Validation & SecretStr + +**Files:** +- Modify: `shared/src/shared/config.py` +- Create: `shared/tests/test_config_validation.py` + +- [ ] **Step 1: Write failing tests for config validation** + +Create `shared/tests/test_config_validation.py`: + +```python +"""Tests for config validation.""" + +import pytest +from pydantic import ValidationError + +from shared.config import Settings + + +class TestConfigValidation: + def test_valid_defaults(self): + settings = Settings() + assert settings.risk_max_position_size == 0.1 + + def test_invalid_position_size(self): + with pytest.raises(ValidationError, match="risk_max_position_size"): + Settings(risk_max_position_size=-0.1) + + def test_invalid_health_port(self): + with pytest.raises(ValidationError, match="health_port"): + Settings(health_port=80) + + def test_invalid_log_level(self): + with pytest.raises(ValidationError, match="log_level"): + Settings(log_level="INVALID") + + def test_secret_fields_masked(self): + settings = Settings(alpaca_api_key="my-secret-key") + assert "my-secret-key" not in repr(settings) + assert settings.alpaca_api_key.get_secret_value() == "my-secret-key" +``` + +- [ ] **Step 2: Run tests to verify they fail** + +Run: `pytest shared/tests/test_config_validation.py -v` +Expected: FAIL + +- [ ] **Step 3: Update config.py with validators and SecretStr** + +Replace `shared/src/shared/config.py`: + +```python +"""Shared configuration settings for the trading platform.""" + +from pydantic import SecretStr, field_validator +from pydantic_settings import BaseSettings + + +class Settings(BaseSettings): + # Alpaca + alpaca_api_key: SecretStr = SecretStr("") + alpaca_api_secret: SecretStr = SecretStr("") + alpaca_paper: bool = True + # Infrastructure + redis_url: SecretStr = SecretStr("redis://localhost:6379") + database_url: SecretStr = SecretStr("postgresql://trading:trading@localhost:5432/trading") + # DB pool + db_pool_size: int = 20 + db_max_overflow: int = 10 + db_pool_recycle: int = 3600 + # Logging + log_level: str = "INFO" + log_format: str = "json" + # Health + health_port: int = 8080 + metrics_auth_token: str = "" + # Risk + risk_max_position_size: float = 0.1 + risk_stop_loss_pct: float = 5.0 + risk_daily_loss_limit_pct: float = 10.0 + risk_trailing_stop_pct: float = 0.0 + risk_max_open_positions: int = 10 + risk_volatility_lookback: int = 20 + risk_volatility_scale: bool = False + risk_max_portfolio_exposure: float = 0.8 + risk_max_correlated_exposure: float = 0.5 + risk_correlation_threshold: float = 0.7 + risk_var_confidence: float = 0.95 + risk_var_limit_pct: float = 5.0 + risk_drawdown_reduction_threshold: float = 0.1 + risk_drawdown_halt_threshold: float = 0.2 + risk_max_consecutive_losses: int = 5 + risk_loss_pause_minutes: int = 60 + dry_run: bool = True + # Telegram + telegram_bot_token: SecretStr = SecretStr("") + telegram_chat_id: str = "" + telegram_enabled: bool = False + # News + finnhub_api_key: SecretStr = SecretStr("") + news_poll_interval: int = 300 + sentiment_aggregate_interval: int = 900 + # Stock selector + selector_final_time: str = "15:30" + selector_max_picks: int = 3 + # LLM + anthropic_api_key: SecretStr = SecretStr("") + anthropic_model: str = "claude-sonnet-4-20250514" + # API security + api_auth_token: SecretStr = SecretStr("") + cors_origins: str = "http://localhost:3000" + + model_config = {"env_file": ".env", "env_file_encoding": "utf-8", "extra": "ignore"} + + @field_validator("risk_max_position_size") + @classmethod + def validate_position_size(cls, v: float) -> float: + if v <= 0 or v > 1: + raise ValueError("risk_max_position_size must be between 0 and 1 (exclusive)") + return v + + @field_validator("health_port") + @classmethod + def validate_health_port(cls, v: int) -> int: + if v < 1024 or v > 65535: + raise ValueError("health_port must be between 1024 and 65535") + return v + + @field_validator("log_level") + @classmethod + def validate_log_level(cls, v: str) -> str: + valid = {"DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"} + if v.upper() not in valid: + raise ValueError(f"log_level must be one of {valid}") + return v.upper() +``` + +- [ ] **Step 4: Update all consumers to use .get_secret_value()** + +Every place that reads `settings.alpaca_api_key` etc. must now call `.get_secret_value()`. Key files to update: + +**`shared/src/shared/alpaca.py`** — where AlpacaClient is instantiated (in each service main.py), change: +```python +# Before: +alpaca = AlpacaClient(cfg.alpaca_api_key, cfg.alpaca_api_secret, paper=cfg.alpaca_paper) +# After: +alpaca = AlpacaClient( + cfg.alpaca_api_key.get_secret_value(), + cfg.alpaca_api_secret.get_secret_value(), + paper=cfg.alpaca_paper, +) +``` + +**Each service main.py** — where `Database(cfg.database_url)` and `RedisBroker(cfg.redis_url)` are called: +```python +# Before: +db = Database(cfg.database_url) +broker = RedisBroker(cfg.redis_url) +# After: +db = Database(cfg.database_url.get_secret_value()) +broker = RedisBroker(cfg.redis_url.get_secret_value()) +``` + +**`shared/src/shared/notifier.py`** — where telegram_bot_token is used: +```python +# Change token access to .get_secret_value() +``` + +**`services/strategy-engine/src/strategy_engine/main.py`** — where anthropic_api_key is passed: +```python +# Before: +anthropic_api_key=cfg.anthropic_api_key, +# After: +anthropic_api_key=cfg.anthropic_api_key.get_secret_value(), +``` + +**`services/news-collector/src/news_collector/main.py`** — where finnhub_api_key is used: +```python +# Before: +cfg.finnhub_api_key +# After: +cfg.finnhub_api_key.get_secret_value() +``` + +- [ ] **Step 5: Run all tests** + +Run: `pytest shared/tests/test_config_validation.py -v` +Expected: PASS + +Run: `pytest -v` +Expected: All tests PASS (no regressions from SecretStr changes) + +- [ ] **Step 6: Commit** + +```bash +git add shared/src/shared/config.py shared/tests/test_config_validation.py +git add services/*/src/*/main.py shared/src/shared/notifier.py +git commit -m "feat: add config validation, SecretStr for secrets, API security fields" +``` + +--- + +### Task 5: Pin All Dependencies + +**Files:** +- Modify: `shared/pyproject.toml` (already done in Task 1) +- Modify: `services/strategy-engine/pyproject.toml` +- Modify: `services/backtester/pyproject.toml` +- Modify: `services/api/pyproject.toml` +- Modify: `services/news-collector/pyproject.toml` +- Modify: `services/data-collector/pyproject.toml` +- Modify: `services/order-executor/pyproject.toml` +- Modify: `services/portfolio-manager/pyproject.toml` + +- [ ] **Step 1: Pin service dependencies** + +`services/strategy-engine/pyproject.toml`: +```toml +dependencies = [ + "pandas>=2.1,<3", + "numpy>=1.26,<3", + "trading-shared", +] +``` + +`services/backtester/pyproject.toml`: +```toml +dependencies = ["pandas>=2.1,<3", "numpy>=1.26,<3", "rich>=13.0,<14", "trading-shared"] +``` + +`services/api/pyproject.toml`: +```toml +dependencies = [ + "fastapi>=0.110,<1", + "uvicorn>=0.27,<1", + "slowapi>=0.1.9,<1", + "trading-shared", +] +``` + +`services/news-collector/pyproject.toml`: +```toml +dependencies = [ + "trading-shared", + "feedparser>=6.0,<7", + "nltk>=3.8,<4", + "aiohttp>=3.9,<4", +] +``` + +`shared/pyproject.toml` optional deps: +```toml +[project.optional-dependencies] +dev = [ + "pytest>=8.0,<9", + "pytest-asyncio>=0.23,<1", + "ruff>=0.4,<1", +] +claude = [ + "anthropic>=0.40,<1", +] +``` + +- [ ] **Step 2: Verify installation works** + +Run: `pip install -e shared/ && pip install -e services/strategy-engine/ && pip install -e services/api/` +Expected: No errors + +- [ ] **Step 3: Commit** + +```bash +git add shared/pyproject.toml services/*/pyproject.toml +git commit -m "chore: pin all dependencies with upper bounds" +``` + +--- + +## Phase 2: Infrastructure Hardening + +### Task 6: Docker Secrets & Environment Cleanup + +**Files:** +- Modify: `docker-compose.yml:17-21` +- Modify: `.env.example` + +- [ ] **Step 1: Replace hardcoded Postgres credentials in docker-compose.yml** + +In `docker-compose.yml`, replace the postgres service environment: + +```yaml + postgres: + image: postgres:16-alpine + environment: + POSTGRES_USER: ${POSTGRES_USER:-trading} + POSTGRES_PASSWORD: ${POSTGRES_PASSWORD:-trading} + POSTGRES_DB: ${POSTGRES_DB:-trading} +``` + +- [ ] **Step 2: Update .env.example with secret annotations** + +Add to `.env.example`: + +```bash +# === SECRETS (keep secure, do not commit .env) === +ALPACA_API_KEY= +ALPACA_API_SECRET= +DATABASE_URL=postgresql+asyncpg://trading:trading@localhost:5432/trading +REDIS_URL=redis://localhost:6379 +TELEGRAM_BOT_TOKEN= +FINNHUB_API_KEY= +ANTHROPIC_API_KEY= +API_AUTH_TOKEN= +POSTGRES_USER=trading +POSTGRES_PASSWORD=trading +POSTGRES_DB=trading + +# === CONFIGURATION === +ALPACA_PAPER=true +DRY_RUN=true +LOG_LEVEL=INFO +LOG_FORMAT=json +HEALTH_PORT=8080 +# ... (keep existing config vars) + +# === API SECURITY === +CORS_ORIGINS=http://localhost:3000 +``` + +- [ ] **Step 3: Commit** + +```bash +git add docker-compose.yml .env.example +git commit -m "fix: move hardcoded postgres credentials to .env, annotate secrets" +``` + +--- + +### Task 7: Dockerfile Optimization + +**Files:** +- Create: `.dockerignore` +- Modify: All 7 Dockerfiles in `services/*/Dockerfile` + +- [ ] **Step 1: Create .dockerignore** + +Create `.dockerignore` at project root: + +``` +__pycache__ +*.pyc +*.pyo +.git +.github +.venv +.env +.env.* +!.env.example +tests/ +docs/ +*.md +.ruff_cache +.pytest_cache +.mypy_cache +monitoring/ +scripts/ +cli/ +``` + +- [ ] **Step 2: Update data-collector Dockerfile** + +Replace `services/data-collector/Dockerfile`: + +```dockerfile +FROM python:3.12-slim AS builder +WORKDIR /app +COPY shared/ shared/ +RUN pip install --no-cache-dir ./shared +COPY services/data-collector/ services/data-collector/ +RUN pip install --no-cache-dir ./services/data-collector + +FROM python:3.12-slim +RUN useradd -r -s /bin/false appuser +WORKDIR /app +COPY --from=builder /usr/local/lib/python3.12/site-packages /usr/local/lib/python3.12/site-packages +COPY --from=builder /usr/local/bin /usr/local/bin +ENV PYTHONPATH=/app +USER appuser +CMD ["python", "-m", "data_collector.main"] +``` + +- [ ] **Step 3: Update all other Dockerfiles with same pattern** + +Apply the same multi-stage + non-root pattern to: +- `services/strategy-engine/Dockerfile` (also copies strategies/) +- `services/order-executor/Dockerfile` +- `services/portfolio-manager/Dockerfile` +- `services/api/Dockerfile` (also copies strategies/, uses uvicorn CMD) +- `services/news-collector/Dockerfile` (also runs nltk download) +- `services/backtester/Dockerfile` (also copies strategies/) + +For **strategy-engine** Dockerfile: +```dockerfile +FROM python:3.12-slim AS builder +WORKDIR /app +COPY shared/ shared/ +RUN pip install --no-cache-dir ./shared +COPY services/strategy-engine/ services/strategy-engine/ +RUN pip install --no-cache-dir ./services/strategy-engine + +FROM python:3.12-slim +RUN useradd -r -s /bin/false appuser +WORKDIR /app +COPY --from=builder /usr/local/lib/python3.12/site-packages /usr/local/lib/python3.12/site-packages +COPY --from=builder /usr/local/bin /usr/local/bin +COPY services/strategy-engine/strategies/ /app/strategies/ +ENV PYTHONPATH=/app +USER appuser +CMD ["python", "-m", "strategy_engine.main"] +``` + +For **news-collector** Dockerfile: +```dockerfile +FROM python:3.12-slim AS builder +WORKDIR /app +COPY shared/ shared/ +RUN pip install --no-cache-dir ./shared +COPY services/news-collector/ services/news-collector/ +RUN pip install --no-cache-dir ./services/news-collector +RUN python -c "import nltk; nltk.download('vader_lexicon', download_dir='/usr/local/nltk_data')" + +FROM python:3.12-slim +RUN useradd -r -s /bin/false appuser +WORKDIR /app +COPY --from=builder /usr/local/lib/python3.12/site-packages /usr/local/lib/python3.12/site-packages +COPY --from=builder /usr/local/bin /usr/local/bin +COPY --from=builder /usr/local/nltk_data /usr/local/nltk_data +ENV PYTHONPATH=/app +USER appuser +CMD ["python", "-m", "news_collector.main"] +``` + +For **api** Dockerfile: +```dockerfile +FROM python:3.12-slim AS builder +WORKDIR /app +COPY shared/ shared/ +RUN pip install --no-cache-dir ./shared +COPY services/api/ services/api/ +RUN pip install --no-cache-dir ./services/api +COPY services/strategy-engine/ services/strategy-engine/ +RUN pip install --no-cache-dir ./services/strategy-engine + +FROM python:3.12-slim +RUN useradd -r -s /bin/false appuser +WORKDIR /app +COPY --from=builder /usr/local/lib/python3.12/site-packages /usr/local/lib/python3.12/site-packages +COPY --from=builder /usr/local/bin /usr/local/bin +COPY services/strategy-engine/strategies/ /app/strategies/ +ENV PYTHONPATH=/app STRATEGIES_DIR=/app/strategies +USER appuser +CMD ["uvicorn", "trading_api.main:app", "--host", "0.0.0.0", "--port", "8000", "--timeout-graceful-shutdown", "30"] +``` + +For **order-executor**, **portfolio-manager**, **backtester** — same pattern as data-collector, adjusting the service name and CMD. + +- [ ] **Step 4: Verify Docker build works** + +Run: `docker compose build --quiet` +Expected: All images build successfully + +- [ ] **Step 5: Commit** + +```bash +git add .dockerignore services/*/Dockerfile +git commit -m "feat: optimize Dockerfiles with multi-stage builds, non-root user, .dockerignore" +``` + +--- + +### Task 8: Database Index Migration + +**Files:** +- Create: `shared/alembic/versions/003_add_missing_indexes.py` + +- [ ] **Step 1: Create migration file** + +Create `shared/alembic/versions/003_add_missing_indexes.py`: + +```python +"""Add missing indexes for common query patterns. + +Revision ID: 003 +Revises: 002 +""" + +from alembic import op + +revision = "003" +down_revision = "002" + + +def upgrade(): + op.create_index("idx_signals_symbol_created", "signals", ["symbol", "created_at"]) + op.create_index("idx_orders_symbol_status_created", "orders", ["symbol", "status", "created_at"]) + op.create_index("idx_trades_order_id", "trades", ["order_id"]) + op.create_index("idx_trades_symbol_traded", "trades", ["symbol", "traded_at"]) + op.create_index("idx_portfolio_snapshots_at", "portfolio_snapshots", ["snapshot_at"]) + op.create_index("idx_symbol_scores_symbol", "symbol_scores", ["symbol"], unique=True) + + +def downgrade(): + op.drop_index("idx_symbol_scores_symbol", table_name="symbol_scores") + op.drop_index("idx_portfolio_snapshots_at", table_name="portfolio_snapshots") + op.drop_index("idx_trades_symbol_traded", table_name="trades") + op.drop_index("idx_trades_order_id", table_name="trades") + op.drop_index("idx_orders_symbol_status_created", table_name="orders") + op.drop_index("idx_signals_symbol_created", table_name="signals") +``` + +- [ ] **Step 2: Verify migration runs (requires infra)** + +Run: `make infra && cd shared && alembic upgrade head` +Expected: Migration 003 applied successfully + +- [ ] **Step 3: Commit** + +```bash +git add shared/alembic/versions/003_add_missing_indexes.py +git commit -m "feat: add missing DB indexes for signals, orders, trades, snapshots" +``` + +--- + +### Task 9: Docker Compose Resource Limits & Networks + +**Files:** +- Modify: `docker-compose.yml` + +- [ ] **Step 1: Add networks and resource limits** + +Add to `docker-compose.yml` at bottom: + +```yaml +networks: + internal: + driver: bridge + monitoring: + driver: bridge +``` + +Add `networks: [internal]` to all application services (redis, postgres, data-collector, strategy-engine, order-executor, portfolio-manager, api, news-collector). + +Add `networks: [internal, monitoring]` to prometheus, grafana. Add `networks: [monitoring]` to loki, promtail. + +Add to each application service: + +```yaml + deploy: + resources: + limits: + memory: 512M + cpus: '1.0' +``` + +For strategy-engine and backtester, use `memory: 1G` instead. + +- [ ] **Step 2: Verify compose config is valid** + +Run: `docker compose config --quiet` +Expected: No errors + +- [ ] **Step 3: Commit** + +```bash +git add docker-compose.yml +git commit -m "feat: add resource limits and network isolation to docker-compose" +``` + +--- + +## Phase 3: Service-Level Improvements + +### Task 10: Graceful Shutdown for All Services + +**Files:** +- Modify: `services/data-collector/src/data_collector/main.py` +- Modify: `services/strategy-engine/src/strategy_engine/main.py` +- Modify: `services/order-executor/src/order_executor/main.py` +- Modify: `services/portfolio-manager/src/portfolio_manager/main.py` +- Modify: `services/news-collector/src/news_collector/main.py` +- Modify: `services/api/src/trading_api/main.py` + +- [ ] **Step 1: Create a shared shutdown helper** + +Add to `shared/src/shared/shutdown.py`: + +```python +"""Graceful shutdown utilities for services.""" + +import asyncio +import logging +import signal + +logger = logging.getLogger(__name__) + + +class GracefulShutdown: + """Manages graceful shutdown via SIGTERM/SIGINT signals.""" + + def __init__(self) -> None: + self._event = asyncio.Event() + + @property + def is_shutting_down(self) -> bool: + return self._event.is_set() + + async def wait(self) -> None: + await self._event.wait() + + def trigger(self) -> None: + logger.info("shutdown_signal_received") + self._event.set() + + def install_handlers(self) -> None: + loop = asyncio.get_running_loop() + for sig in (signal.SIGTERM, signal.SIGINT): + loop.add_signal_handler(sig, self.trigger) +``` + +- [ ] **Step 2: Add shutdown to data-collector main loop** + +In `services/data-collector/src/data_collector/main.py`, add at the start of `run()`: + +```python +from shared.shutdown import GracefulShutdown + +shutdown = GracefulShutdown() +shutdown.install_handlers() +``` + +Replace the main `while True` loop condition with `while not shutdown.is_shutting_down`. + +- [ ] **Step 3: Apply same pattern to all other services** + +For each service's `main.py`, add `GracefulShutdown` import, install handlers at start of `run()`, and replace infinite loops with `while not shutdown.is_shutting_down`. + +For strategy-engine: also cancel tasks on shutdown. +For portfolio-manager: also cancel snapshot_loop task. +For news-collector: also cancel all collector loop tasks. + +- [ ] **Step 4: Run tests** + +Run: `pytest -v` +Expected: All tests PASS + +- [ ] **Step 5: Commit** + +```bash +git add shared/src/shared/shutdown.py services/*/src/*/main.py +git commit -m "feat: add graceful shutdown with SIGTERM/SIGINT handlers to all services" +``` + +--- + +### Task 11: Exception Handling Specialization + +**Files:** +- Modify: All service `main.py` files +- Modify: `shared/src/shared/db.py` + +- [ ] **Step 1: Specialize exceptions in data-collector/main.py** + +Replace broad `except Exception` blocks. For example, in the fetch loop: + +```python +# Before: +except Exception as exc: + log.warning("fetch_bar_failed", symbol=symbol, error=str(exc)) + +# After: +except (ConnectionError, TimeoutError, aiohttp.ClientError) as exc: + log.warning("fetch_bar_network_error", symbol=symbol, error=str(exc)) +except (ValueError, KeyError) as exc: + log.warning("fetch_bar_parse_error", symbol=symbol, error=str(exc)) +except Exception as exc: + log.error("fetch_bar_unexpected", symbol=symbol, error=str(exc), exc_info=True) +``` + +- [ ] **Step 2: Specialize exceptions in strategy-engine, order-executor, portfolio-manager, news-collector** + +Apply the same pattern: network errors → warning + retry, parse errors → warning + skip, unexpected → error + exc_info. + +- [ ] **Step 3: Specialize exceptions in db.py** + +In `shared/src/shared/db.py`, the transaction pattern can distinguish: + +```python +except (asyncpg.PostgresError, sqlalchemy.exc.OperationalError) as exc: + await session.rollback() + logger.error("db_operation_error", error=str(exc)) + raise +except Exception: + await session.rollback() + raise +``` + +- [ ] **Step 4: Run tests** + +Run: `pytest -v` +Expected: All tests PASS + +- [ ] **Step 5: Commit** + +```bash +git add services/*/src/*/main.py shared/src/shared/db.py +git commit -m "refactor: specialize exception handling across all services" +``` + +--- + +### Task 12: Fix Stock Selector (Bug Fix + Dedup + Session Reuse) + +**Files:** +- Modify: `services/strategy-engine/src/strategy_engine/stock_selector.py` +- Modify: `services/strategy-engine/tests/test_stock_selector.py` (if exists, otherwise create) + +- [ ] **Step 1: Fix the critical bug on line 217** + +In `stock_selector.py` line 217, replace: +```python +self._session = anthropic_model +``` +with: +```python +self._model = anthropic_model +``` + +- [ ] **Step 2: Extract common JSON parsing function** + +Replace the duplicate parsing logic. Add at module level (replacing `_parse_llm_selections`): + +```python +def _extract_json_array(text: str) -> list[dict] | None: + """Extract a JSON array from text that may contain markdown code blocks.""" + code_block = re.search(r"```(?:json)?\s*(\[.*?\])\s*```", text, re.DOTALL) + if code_block: + raw = code_block.group(1) + else: + array_match = re.search(r"\[.*\]", text, re.DOTALL) + if array_match: + raw = array_match.group(0) + else: + raw = text.strip() + + try: + data = json.loads(raw) + if isinstance(data, list): + return [item for item in data if isinstance(item, dict)] + return None + except (json.JSONDecodeError, TypeError): + return None + + +def _parse_llm_selections(text: str) -> list[SelectedStock]: + """Parse LLM response into SelectedStock list.""" + items = _extract_json_array(text) + if items is None: + return [] + selections = [] + for item in items: + try: + selections.append( + SelectedStock( + symbol=item["symbol"], + side=OrderSide(item["side"]), + conviction=float(item["conviction"]), + reason=item.get("reason", ""), + key_news=item.get("key_news", []), + ) + ) + except (KeyError, ValueError) as e: + logger.warning("Skipping invalid selection item: %s", e) + return selections +``` + +Update `LLMCandidateSource._parse_candidates()` to use `_extract_json_array`: + +```python + def _parse_candidates(self, text: str) -> list[Candidate]: + items = _extract_json_array(text) + if items is None: + return [] + candidates = [] + for item in items: + try: + direction_str = item.get("direction", "BUY") + direction = OrderSide(direction_str) + except ValueError: + direction = None + candidates.append( + Candidate( + symbol=item["symbol"], + source="llm", + direction=direction, + score=float(item.get("score", 0.5)), + reason=item.get("reason", ""), + ) + ) + return candidates +``` + +- [ ] **Step 3: Add session reuse to StockSelector** + +Add `_http_session` to `StockSelector.__init__()`: + +```python +self._http_session: aiohttp.ClientSession | None = None +``` + +Add helper method: + +```python +async def _ensure_session(self) -> aiohttp.ClientSession: + if self._http_session is None or self._http_session.closed: + self._http_session = aiohttp.ClientSession() + return self._http_session + +async def close(self) -> None: + if self._http_session and not self._http_session.closed: + await self._http_session.close() +``` + +Replace `async with aiohttp.ClientSession() as session:` in both `LLMCandidateSource.get_candidates()` and `StockSelector._llm_final_select()` with session reuse. For `LLMCandidateSource`, accept an optional session parameter. For `StockSelector._llm_final_select()`, use `self._ensure_session()`. + +- [ ] **Step 4: Run tests** + +Run: `pytest services/strategy-engine/tests/ -v` +Expected: All tests PASS + +- [ ] **Step 5: Commit** + +```bash +git add services/strategy-engine/src/strategy_engine/stock_selector.py +git commit -m "fix: fix model attr bug, deduplicate LLM parsing, reuse aiohttp sessions" +``` + +--- + +## Phase 4: API Security + +### Task 13: Bearer Token Authentication + +**Files:** +- Create: `services/api/src/trading_api/dependencies/__init__.py` +- Create: `services/api/src/trading_api/dependencies/auth.py` +- Modify: `services/api/src/trading_api/main.py` + +- [ ] **Step 1: Create auth dependency** + +Create `services/api/src/trading_api/dependencies/__init__.py` (empty file). + +Create `services/api/src/trading_api/dependencies/auth.py`: + +```python +"""Bearer token authentication dependency.""" + +import logging + +from fastapi import Depends, HTTPException, status +from fastapi.security import HTTPAuthorizationCredentials, HTTPBearer + +from shared.config import Settings + +logger = logging.getLogger(__name__) + +_security = HTTPBearer(auto_error=False) +_settings = Settings() + + +async def verify_token( + credentials: HTTPAuthorizationCredentials | None = Depends(_security), +) -> None: + """Verify Bearer token. Skip auth if API_AUTH_TOKEN is not configured.""" + token = _settings.api_auth_token.get_secret_value() + if not token: + return # Auth disabled in dev mode + + if credentials is None or credentials.credentials != token: + raise HTTPException( + status_code=status.HTTP_401_UNAUTHORIZED, + detail="Invalid or missing authentication token", + headers={"WWW-Authenticate": "Bearer"}, + ) +``` + +- [ ] **Step 2: Apply auth to all API routes** + +In `services/api/src/trading_api/main.py`, add auth dependency to routers: + +```python +from trading_api.dependencies.auth import verify_token +from fastapi import Depends + +app.include_router(portfolio_router, prefix="/api/v1/portfolio", dependencies=[Depends(verify_token)]) +app.include_router(orders_router, prefix="/api/v1/orders", dependencies=[Depends(verify_token)]) +app.include_router(strategies_router, prefix="/api/v1/strategies", dependencies=[Depends(verify_token)]) +``` + +Log a warning on startup if token is empty: + +```python +@asynccontextmanager +async def lifespan(app: FastAPI): + cfg = Settings() + if not cfg.api_auth_token.get_secret_value(): + logger.warning("API_AUTH_TOKEN not set; API authentication is disabled") + # ... rest of lifespan +``` + +- [ ] **Step 3: Write tests for auth** + +Add to `services/api/tests/test_auth.py`: + +```python +"""Tests for API authentication.""" + +from unittest.mock import patch + +import pytest +from httpx import ASGITransport, AsyncClient + +from trading_api.main import app + + +class TestAuth: + @patch("trading_api.dependencies.auth._settings") + async def test_rejects_missing_token_when_configured(self, mock_settings): + from pydantic import SecretStr + mock_settings.api_auth_token = SecretStr("test-token") + async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as ac: + resp = await ac.get("/api/v1/portfolio/positions") + assert resp.status_code == 401 + + @patch("trading_api.dependencies.auth._settings") + async def test_accepts_valid_token(self, mock_settings): + from pydantic import SecretStr + mock_settings.api_auth_token = SecretStr("test-token") + async with AsyncClient(transport=ASGITransport(app=app), base_url="http://test") as ac: + resp = await ac.get( + "/api/v1/portfolio/positions", + headers={"Authorization": "Bearer test-token"}, + ) + # May fail with 500 if DB not available, but should NOT be 401 + assert resp.status_code != 401 +``` + +- [ ] **Step 4: Run tests** + +Run: `pytest services/api/tests/test_auth.py -v` +Expected: PASS + +- [ ] **Step 5: Commit** + +```bash +git add services/api/src/trading_api/dependencies/ services/api/src/trading_api/main.py services/api/tests/test_auth.py +git commit -m "feat: add Bearer token authentication to API endpoints" +``` + +--- + +### Task 14: CORS & Rate Limiting + +**Files:** +- Modify: `services/api/src/trading_api/main.py` +- Modify: `services/api/pyproject.toml` + +- [ ] **Step 1: Add slowapi dependency** + +Already done in Task 5 (`services/api/pyproject.toml` has `slowapi>=0.1.9,<1`). + +- [ ] **Step 2: Add CORS and rate limiting to main.py** + +In `services/api/src/trading_api/main.py`: + +```python +from fastapi.middleware.cors import CORSMiddleware +from slowapi import Limiter, _rate_limit_exceeded_handler +from slowapi.util import get_remote_address +from slowapi.errors import RateLimitExceeded + +from shared.config import Settings + +cfg = Settings() + +limiter = Limiter(key_func=get_remote_address) +app = FastAPI(title="Trading Platform API") +app.state.limiter = limiter +app.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler) + +app.add_middleware( + CORSMiddleware, + allow_origins=cfg.cors_origins.split(","), + allow_methods=["GET", "POST"], + allow_headers=["Authorization", "Content-Type"], +) +``` + +- [ ] **Step 3: Add rate limits to order endpoints** + +In `services/api/src/trading_api/routers/orders.py`: + +```python +from slowapi import Limiter +from slowapi.util import get_remote_address + +limiter = Limiter(key_func=get_remote_address) + +@router.get("/") +@limiter.limit("60/minute") +async def get_orders(request: Request, limit: int = 50): + ... +``` + +- [ ] **Step 4: Run tests** + +Run: `pytest services/api/tests/ -v` +Expected: PASS + +- [ ] **Step 5: Commit** + +```bash +git add services/api/src/trading_api/main.py services/api/src/trading_api/routers/ +git commit -m "feat: add CORS middleware and rate limiting to API" +``` + +--- + +### Task 15: API Input Validation & Response Models + +**Files:** +- Modify: `services/api/src/trading_api/routers/portfolio.py` +- Modify: `services/api/src/trading_api/routers/orders.py` + +- [ ] **Step 1: Add Query validation to portfolio.py** + +```python +from fastapi import Query + +@router.get("/snapshots") +async def get_snapshots(request: Request, days: int = Query(30, ge=1, le=365)): + ... +``` + +- [ ] **Step 2: Add Query validation to orders.py** + +```python +from fastapi import Query + +@router.get("/") +async def get_orders(request: Request, limit: int = Query(50, ge=1, le=1000)): + ... + +@router.get("/signals") +async def get_signals(request: Request, limit: int = Query(50, ge=1, le=1000)): + ... +``` + +- [ ] **Step 3: Run tests** + +Run: `pytest services/api/tests/ -v` +Expected: PASS + +- [ ] **Step 4: Commit** + +```bash +git add services/api/src/trading_api/routers/ +git commit -m "feat: add input validation with Query bounds to API endpoints" +``` + +--- + +## Phase 5: Operational Maturity + +### Task 16: Enhanced Ruff Configuration + +**Files:** +- Modify: `pyproject.toml:12-14` + +- [ ] **Step 1: Update ruff config in pyproject.toml** + +Replace the ruff section in root `pyproject.toml`: + +```toml +[tool.ruff] +target-version = "py312" +line-length = 100 + +[tool.ruff.lint] +select = ["E", "W", "F", "I", "B", "UP", "ASYNC", "PERF", "C4", "RUF"] +ignore = ["E501"] + +[tool.ruff.lint.per-file-ignores] +"tests/*" = ["F841"] +"*/tests/*" = ["F841"] + +[tool.ruff.lint.isort] +known-first-party = ["shared"] +``` + +- [ ] **Step 2: Auto-fix existing violations** + +Run: `ruff check --fix . && ruff format .` +Expected: Fixes applied + +- [ ] **Step 3: Verify no remaining errors** + +Run: `ruff check . && ruff format --check .` +Expected: No errors + +- [ ] **Step 4: Run tests to verify no regressions** + +Run: `pytest -v` +Expected: All tests PASS + +- [ ] **Step 5: Commit** + +```bash +git add pyproject.toml +git commit -m "chore: enhance ruff lint rules with ASYNC, bugbear, isort, pyupgrade" +``` + +Then commit auto-fixes separately: + +```bash +git add -A +git commit -m "style: auto-fix lint violations from enhanced ruff rules" +``` + +--- + +### Task 17: GitHub Actions CI Pipeline + +**Files:** +- Create: `.github/workflows/ci.yml` + +- [ ] **Step 1: Create CI workflow** + +Create `.github/workflows/ci.yml`: + +```yaml +name: CI + +on: + push: + branches: [master] + pull_request: + branches: [master] + +jobs: + lint: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-python@v5 + with: + python-version: "3.12" + - run: pip install ruff + - run: ruff check . + - run: ruff format --check . + + test: + runs-on: ubuntu-latest + services: + redis: + image: redis:7-alpine + ports: [6379:6379] + options: >- + --health-cmd "redis-cli ping" + --health-interval 5s + --health-timeout 3s + --health-retries 5 + postgres: + image: postgres:16-alpine + env: + POSTGRES_USER: trading + POSTGRES_PASSWORD: trading + POSTGRES_DB: trading + ports: [5432:5432] + options: >- + --health-cmd pg_isready + --health-interval 5s + --health-timeout 3s + --health-retries 5 + steps: + - uses: actions/checkout@v4 + - uses: actions/setup-python@v5 + with: + python-version: "3.12" + - run: | + pip install -e shared/[dev] + pip install -e services/strategy-engine/[dev] + pip install -e services/data-collector/[dev] + pip install -e services/order-executor/[dev] + pip install -e services/portfolio-manager/[dev] + pip install -e services/news-collector/[dev] + pip install -e services/api/[dev] + pip install -e services/backtester/[dev] + pip install pytest-cov + - run: pytest -v --cov=shared/src --cov=services --cov-report=xml --cov-report=term-missing + env: + DATABASE_URL: postgresql+asyncpg://trading:trading@localhost:5432/trading + REDIS_URL: redis://localhost:6379 + - uses: actions/upload-artifact@v4 + with: + name: coverage-report + path: coverage.xml + + docker: + runs-on: ubuntu-latest + needs: [lint, test] + if: github.ref == 'refs/heads/master' + steps: + - uses: actions/checkout@v4 + - run: docker compose build --quiet +``` + +- [ ] **Step 2: Commit** + +```bash +mkdir -p .github/workflows +git add .github/workflows/ci.yml +git commit -m "feat: add GitHub Actions CI pipeline with lint, test, docker build" +``` + +--- + +### Task 18: Prometheus Alerting Rules + +**Files:** +- Create: `monitoring/prometheus/alert_rules.yml` +- Modify: `monitoring/prometheus.yml` + +- [ ] **Step 1: Create alert rules** + +Create `monitoring/prometheus/alert_rules.yml`: + +```yaml +groups: + - name: trading-platform + rules: + - alert: ServiceDown + expr: up == 0 + for: 1m + labels: + severity: critical + annotations: + summary: "Service {{ $labels.job }} is down" + description: "{{ $labels.instance }} has been unreachable for 1 minute." + + - alert: HighErrorRate + expr: rate(errors_total[5m]) > 10 + for: 2m + labels: + severity: warning + annotations: + summary: "High error rate on {{ $labels.job }}" + description: "Error rate is {{ $value }} errors/sec over 5 minutes." + + - alert: HighProcessingLatency + expr: histogram_quantile(0.95, rate(processing_seconds_bucket[5m])) > 5 + for: 5m + labels: + severity: warning + annotations: + summary: "High p95 latency on {{ $labels.job }}" + description: "95th percentile processing time is {{ $value }}s." +``` + +- [ ] **Step 2: Reference alert rules in prometheus.yml** + +In `monitoring/prometheus.yml`, add after `global:`: + +```yaml +rule_files: + - "/etc/prometheus/alert_rules.yml" +``` + +Update `docker-compose.yml` prometheus service to mount the file: + +```yaml + prometheus: + volumes: + - ./monitoring/prometheus.yml:/etc/prometheus/prometheus.yml + - ./monitoring/prometheus/alert_rules.yml:/etc/prometheus/alert_rules.yml +``` + +- [ ] **Step 3: Commit** + +```bash +git add monitoring/prometheus/alert_rules.yml monitoring/prometheus.yml docker-compose.yml +git commit -m "feat: add Prometheus alerting rules for service health, errors, latency" +``` + +--- + +### Task 19: Code Coverage Configuration + +**Files:** +- Modify: `pyproject.toml` + +- [ ] **Step 1: Add pytest-cov config** + +Add to `pyproject.toml`: + +```toml +[tool.coverage.run] +branch = true +source = ["shared/src", "services"] +omit = ["*/tests/*", "*/alembic/*"] + +[tool.coverage.report] +fail_under = 60 +show_missing = true +exclude_lines = [ + "pragma: no cover", + "if __name__", + "if TYPE_CHECKING", +] +``` + +Update pytest addopts: +```toml +[tool.pytest.ini_options] +asyncio_mode = "auto" +testpaths = ["shared/tests", "services", "cli/tests", "tests"] +addopts = "--import-mode=importlib" +``` + +Note: `--cov` flags are passed explicitly in CI, not in addopts (to avoid slowing local dev). + +- [ ] **Step 2: Verify coverage works** + +Run: `pip install pytest-cov && pytest --cov=shared/src --cov-report=term-missing` +Expected: Coverage report printed, no errors + +- [ ] **Step 3: Commit** + +```bash +git add pyproject.toml +git commit -m "chore: add pytest-cov configuration with 60% minimum coverage threshold" +``` + +--- + +## Summary + +| Phase | Tasks | Estimated Commits | +|-------|-------|-------------------| +| 1: Shared Library | Tasks 1-5 | 5 commits | +| 2: Infrastructure | Tasks 6-9 | 4 commits | +| 3: Service Fixes | Tasks 10-12 | 3 commits | +| 4: API Security | Tasks 13-15 | 3 commits | +| 5: Operations | Tasks 16-19 | 5 commits | +| **Total** | **19 tasks** | **~20 commits** | diff --git a/docs/superpowers/specs/2026-04-01-crypto-trading-platform-design.md b/docs/superpowers/specs/2026-04-01-crypto-trading-platform-design.md deleted file mode 100644 index aa32eb4..0000000 --- a/docs/superpowers/specs/2026-04-01-crypto-trading-platform-design.md +++ /dev/null @@ -1,374 +0,0 @@ -# Crypto Trading Platform — Design Spec - -## Overview - -Binance 현물 암호화폐 자동매매 플랫폼. 마이크로서비스 아키텍처 기반으로 데이터 수집, 전략 실행, 주문 처리, 포트폴리오 관리, 백테스팅을 독립 서비스로 운영한다. CLI로 제어하며, 전략은 플러그인 방식으로 확장 가능하다. - -- **시장:** 암호화폐 (Binance 현물) -- **언어:** Python -- **인터페이스:** CLI (Click) -- **아키텍처:** 마이크로서비스 (Docker Compose) - ---- - -## Architecture - -### 서비스 구성 - -``` -┌─────────────┐ ┌──────────────────┐ ┌─────────────────┐ -│ Data │───▶│ Message Broker │◀──│ Strategy │ -│ Collector │ │ (Redis Streams) │ │ Engine │ -└─────────────┘ └──────────────────┘ └─────────────────┘ - │ ▲ │ - ▼ │ ▼ - ┌──────────────────┐ ┌─────────────────┐ - │ Backtester │ │ Order │ - │ │ │ Executor │ - └──────────────────┘ └─────────────────┘ - │ - ┌────────────────────────┘ - ▼ - ┌──────────────────┐ - │ Portfolio │ - │ Manager │ - └──────────────────┘ - - CLI ──────▶ 각 서비스에 명령 전달 -``` - -| 서비스 | 역할 | 상시 실행 | -|--------|------|-----------| -| **data-collector** | Binance WebSocket/REST로 시세 수집, DB 저장 | Yes | -| **strategy-engine** | 플러그인 전략 로드 및 시그널 생성 | 봇 실행 시 | -| **order-executor** | 시그널 받아 실제 주문 실행 + 리스크 관리 | 봇 실행 시 | -| **portfolio-manager** | 잔고, 손익, 포지션 추적 | Yes | -| **backtester** | 과거 데이터로 전략 검증 | 요청 시 | -| **shared** | 공통 모델, 이벤트 정의, 유틸리티 (라이브러리) | — | -| **cli** | 사용자 인터페이스, 각 서비스 제어 | — | - -### 통신 흐름 - -``` -[Binance WS] - │ - ▼ -data-collector ──publish──▶ Redis Stream: "candles.{symbol}" - │ - ┌───────────────┤ - ▼ ▼ - strategy-engine backtester (과거 데이터는 DB에서) - │ - ▼ - Redis Stream: "signals" - │ - ▼ - order-executor - │ - ┌───────┴───────┐ - ▼ ▼ - [Binance API] Redis Stream: "orders" - │ - ▼ - portfolio-manager -``` - ---- - -## Project Structure - -``` -trading/ -├── services/ -│ ├── data-collector/ -│ │ ├── src/ -│ │ │ ├── __init__.py -│ │ │ ├── main.py # 서비스 진입점 -│ │ │ ├── binance_ws.py # WebSocket 실시간 시세 -│ │ │ ├── binance_rest.py # REST 과거 데이터 수집 -│ │ │ ├── storage.py # DB 저장 로직 -│ │ │ └── config.py -│ │ ├── tests/ -│ │ ├── Dockerfile -│ │ └── pyproject.toml -│ │ -│ ├── strategy-engine/ -│ │ ├── src/ -│ │ │ ├── __init__.py -│ │ │ ├── main.py -│ │ │ ├── engine.py # 전략 로더 + 실행기 -│ │ │ ├── plugin_loader.py # 플러그인 동적 로드 -│ │ │ └── config.py -│ │ ├── strategies/ # 플러그인 전략 디렉토리 -│ │ │ ├── base.py # 전략 추상 클래스 -│ │ │ ├── rsi_strategy.py # 예시: RSI 전략 -│ │ │ └── grid_strategy.py # 예시: 그리드 전략 -│ │ ├── tests/ -│ │ ├── Dockerfile -│ │ └── pyproject.toml -│ │ -│ ├── order-executor/ -│ │ ├── src/ -│ │ │ ├── __init__.py -│ │ │ ├── main.py -│ │ │ ├── executor.py # 주문 실행 로직 -│ │ │ ├── risk_manager.py # 리스크 관리 (손절/익절) -│ │ │ └── config.py -│ │ ├── tests/ -│ │ ├── Dockerfile -│ │ └── pyproject.toml -│ │ -│ ├── portfolio-manager/ -│ │ ├── src/ -│ │ │ ├── __init__.py -│ │ │ ├── main.py -│ │ │ ├── portfolio.py # 잔고/포지션 추적 -│ │ │ ├── pnl.py # 손익 계산 -│ │ │ └── config.py -│ │ ├── tests/ -│ │ ├── Dockerfile -│ │ └── pyproject.toml -│ │ -│ └── backtester/ -│ ├── src/ -│ │ ├── __init__.py -│ │ ├── main.py -│ │ ├── engine.py # 백테스팅 엔진 -│ │ ├── simulator.py # 가상 주문 시뮬레이터 -│ │ ├── reporter.py # 결과 리포트 생성 -│ │ └── config.py -│ ├── tests/ -│ ├── Dockerfile -│ └── pyproject.toml -│ -├── shared/ -│ ├── src/shared/ -│ │ ├── __init__.py -│ │ ├── models.py # 공통 데이터 모델 -│ │ ├── events.py # 이벤트 타입 정의 -│ │ ├── broker.py # Redis Streams 클라이언트 -│ │ ├── db.py # DB 연결 (PostgreSQL) -│ │ └── config.py # 공통 설정 -│ ├── tests/ -│ └── pyproject.toml -│ -├── cli/ -│ ├── src/ -│ │ ├── __init__.py -│ │ ├── main.py # Click 기반 CLI 진입점 -│ │ ├── commands/ -│ │ │ ├── data.py # 데이터 수집 명령 -│ │ │ ├── trade.py # 매매 시작/중지 -│ │ │ ├── backtest.py # 백테스팅 실행 -│ │ │ ├── portfolio.py # 포트폴리오 조회 -│ │ │ └── strategy.py # 전략 관리 -│ │ └── config.py -│ ├── tests/ -│ └── pyproject.toml -│ -├── docker-compose.yml # 전체 서비스 오케스트레이션 -├── .env.example # 환경변수 템플릿 -├── Makefile # 공통 명령어 -└── README.md -``` - ---- - -## Tech Stack - -| 용도 | 라이브러리 | -|------|-----------| -| 거래소 API | **ccxt** | -| 메시지 브로커 | **Redis Streams** | -| DB | **PostgreSQL** + **asyncpg** | -| CLI | **Click** | -| 데이터 분석 | **pandas**, **numpy** | -| 기술 지표 | **pandas-ta** | -| 비동기 처리 | **asyncio** + **aiohttp** | -| 설정 관리 | **pydantic-settings** | -| 컨테이너 | **Docker** + **docker-compose** | -| 테스트 | **pytest** + **pytest-asyncio** | - ---- - -## Data Models - -### Core Models (shared/models.py) - -```python -class Candle: - symbol: str # "BTCUSDT" - timeframe: str # "1m", "5m", "1h" - open_time: datetime - open: Decimal - high: Decimal - low: Decimal - close: Decimal - volume: Decimal - -class Signal: - strategy: str # "rsi_strategy" - symbol: str - side: "BUY" | "SELL" - price: Decimal - quantity: Decimal - reason: str # 시그널 발생 근거 - -class Order: - id: str - signal_id: str # 추적용 - symbol: str - side: "BUY" | "SELL" - type: "MARKET" | "LIMIT" - price: Decimal - quantity: Decimal - status: "PENDING" | "FILLED" | "CANCELLED" | "FAILED" - created_at: datetime - filled_at: datetime | None - -class Position: - symbol: str - quantity: Decimal - avg_entry_price: Decimal - current_price: Decimal - unrealized_pnl: Decimal -``` - -### PostgreSQL Tables - -| 테이블 | 용도 | -|--------|------| -| `candles` | 시세 이력 (파티셔닝: symbol + timeframe) | -| `signals` | 전략 시그널 이력 | -| `orders` | 주문 이력 | -| `trades` | 체결 이력 | -| `positions` | 현재 포지션 | -| `portfolio_snapshots` | 일별 포트폴리오 스냅샷 | - -### Storage Strategy - -- **실시간 시세:** Redis 캐싱 + PostgreSQL 영구 저장 -- **주문/체결:** PostgreSQL 즉시 기록 -- **백테스팅 데이터:** PostgreSQL에서 bulk read (pandas DataFrame) - ---- - -## Strategy Plugin System - -### Base Interface - -```python -from abc import ABC, abstractmethod -from shared.models import Candle, Signal - -class BaseStrategy(ABC): - @abstractmethod - def on_candle(self, candle: Candle) -> Signal | None: - """캔들 데이터 수신 시 시그널 반환""" - pass - - @abstractmethod - def configure(self, params: dict) -> None: - """전략 파라미터 설정""" - pass -``` - -새 전략 추가 = `BaseStrategy` 상속 파일 하나 작성 후 `strategies/` 디렉토리에 배치. - -### 예시 전략 - -- **RSI Strategy:** RSI 과매도 시 매수, 과매수 시 매도 -- **Grid Strategy:** 가격 구간을 나눠 자동 매수/매도 주문 배치 - ---- - -## CLI Interface - -```bash -# 데이터 수집 -trading data collect --symbol BTCUSDT --timeframe 1m -trading data history --symbol BTCUSDT --from 2025-01-01 -trading data list - -# 자동매매 -trading trade start --strategy rsi --symbol BTCUSDT -trading trade stop --strategy rsi -trading trade status - -# 수동매매 -trading order buy --symbol BTCUSDT --quantity 0.01 -trading order sell --symbol BTCUSDT --price 70000 -trading order cancel --id abc123 - -# 백테스팅 -trading backtest run --strategy rsi --symbol BTCUSDT \ - --from 2025-01-01 --to 2025-12-31 -trading backtest report --id latest - -# 포트폴리오 -trading portfolio show -trading portfolio history --days 30 - -# 전략 관리 -trading strategy list -trading strategy info --name rsi - -# 서비스 관리 -trading service up -trading service down -trading service logs --name strategy-engine -``` - ---- - -## Risk Management - -### Risk Check Pipeline (order-executor) - -시그널 수신 시 다음 체크를 순서대로 통과해야 주문 실행: - -1. 최대 포지션 크기 초과 여부 -2. 일일 최대 손실 한도 도달 여부 -3. 동일 심볼 중복 주문 방지 -4. 주문 금액 < 가용 잔고 확인 -5. 가격 급변 감지 (슬리피지 보호) - -### Safety Mechanisms - -| 장치 | 설명 | -|------|------| -| **긴급 정지 (Kill Switch)** | `trading trade stop-all` — 모든 봇 중지, 미체결 주문 전량 취소 | -| **일일 손실 한도** | 설정 비율 초과 시 자동 매매 중단 | -| **최대 포지션 제한** | 총 자산 대비 단일 심볼 비율 제한 | -| **연결 끊김 대응** | Binance 연결 끊기면 신규 주문 중단, 재연결 시도 | -| **드라이런 모드** | 실제 주문 없이 시그널만 생성 — 전략 검증용 | - ---- - -## Configuration (.env) - -``` -BINANCE_API_KEY= -BINANCE_API_SECRET= -REDIS_URL=redis://localhost:6379 -DATABASE_URL=postgresql://user:pass@localhost:5432/trading -LOG_LEVEL=INFO -RISK_MAX_POSITION_SIZE=0.1 -RISK_STOP_LOSS_PCT=5 -RISK_DAILY_LOSS_LIMIT_PCT=10 -DRY_RUN=true -``` - ---- - -## Docker Compose Services - -```yaml -services: - redis: # 메시지 브로커 (항상 실행) - postgres: # 데이터 저장소 (항상 실행) - data-collector: # 시세 수집 (항상 실행) - strategy-engine: # 전략 엔진 (봇 실행 시) - order-executor: # 주문 실행 (봇 실행 시) - portfolio-manager: # 포트폴리오 (항상 실행) -``` diff --git a/docs/superpowers/specs/2026-04-01-operations-and-strategy-expansion-design.md b/docs/superpowers/specs/2026-04-01-operations-and-strategy-expansion-design.md deleted file mode 100644 index e1aea74..0000000 --- a/docs/superpowers/specs/2026-04-01-operations-and-strategy-expansion-design.md +++ /dev/null @@ -1,458 +0,0 @@ -# Operations Infrastructure & Strategy Expansion — Design Spec - -## Overview - -기존 Binance 현물 암호화폐 자동매매 플랫폼의 두 가지 영역을 강화한다: - -1. **운영 인프라** — DB 마이그레이션, 구조화된 로깅, Telegram 알림, 에러 복구, 메트릭 수집 -2. **전략 확장** — 추세 추종/스캘핑 전략 추가, 백테스트 고도화 - -접근 순서: 운영 인프라 먼저 완성 → 전략 추가. 안정적인 모니터링/알림 기반 위에서 새 전략을 검증할 수 있어야 한다. - ---- - -## Part 1: Operations Infrastructure - -### 1.1 DB Layer Migration (asyncpg → SQLAlchemy 2.0 Async + Alembic) - -**목표:** raw SQL과 asyncpg 직접 사용을 SQLAlchemy 2.0 async ORM으로 교체하고, Alembic으로 마이그레이션을 관리한다. - -**변경 사항:** - -- `shared/src/shared/db.py` — AsyncSession 기반으로 재작성 - - `create_async_engine()` + `async_sessionmaker()` 사용 - - asyncpg는 SQLAlchemy의 내부 드라이버로 유지 (`postgresql+asyncpg://`) - - 기존 raw SQL 함수들을 ORM 쿼리로 전환 - -- `shared/src/shared/sa_models.py` — SQLAlchemy ORM 모델 (신규) - - 기존 Pydantic 모델(models.py)과 1:1 매핑되는 SA 테이블 정의 - - `Candle`, `Signal`, `Order`, `Trade`, `Position`, `PortfolioSnapshot` 테이블 - - Pydantic 모델은 이벤트 직렬화/API 전용으로 유지 - -- `shared/alembic/` — Alembic 마이그레이션 환경 (신규) - - `alembic.ini` — 설정 파일 (DATABASE_URL 참조) - - `env.py` — async 엔진 설정, SA 모델 메타데이터 참조 - - `versions/` — 마이그레이션 파일들 - - 초기 마이그레이션: 기존 `db.py`의 CREATE TABLE 로직을 마이그레이션으로 이전 - -- `Makefile` 타겟 추가: - - `make migrate` — `alembic upgrade head` - - `make migrate-down` — `alembic downgrade -1` - - `make migrate-new MSG="description"` — `alembic revision --autogenerate -m "description"` - -- 각 서비스의 DB 접근 코드를 AsyncSession 기반으로 업데이트: - - `data-collector/storage.py` — bulk insert 쿼리를 SA ORM으로 - - `order-executor/executor.py` — order CRUD를 SA ORM으로 - - `portfolio-manager/portfolio.py` — position/snapshot 쿼리를 SA ORM으로 - - `backtester/engine.py` — candle 조회를 SA ORM으로 - -**의존성 추가:** `sqlalchemy[asyncio]>=2.0`, `alembic>=1.13` -**의존성 제거:** `asyncpg` (직접 의존 → SQLAlchemy 내부 의존으로 변경) - ---- - -### 1.2 Structured Logging (structlog) - -**목표:** 전 서비스에 JSON 구조화 로깅을 적용하고, 에러 로그를 Telegram 알림과 연결한다. - -**변경 사항:** - -- `shared/src/shared/logging.py` (신규) - - `setup_logging(service_name: str, log_level: str)` 함수 - - structlog 프로세서 체인: timestamp, log level, service_name 바인딩, JSON 렌더러 - - 개발 환경: 컬러 콘솔 출력 / 프로덕션: JSON stdout - - `LOG_FORMAT` 환경변수로 전환 (`console` | `json`, 기본값: `json`) - -- 각 서비스 `main.py`에서 `setup_logging()` 호출 -- 기존 `logging.getLogger()` 호출을 `structlog.get_logger()` 로 교체 -- 컨텍스트 바인딩 예시: - ```python - log = structlog.get_logger().bind(service="strategy-engine", symbol="BTCUSDT") - log.info("signal_generated", strategy="rsi", side="BUY", price=68500) - ``` - -- ERROR 이상 로그 → Telegram 알림 트리거 (1.3절 TelegramNotifier 연동) - - structlog 커스텀 프로세서로 구현 - - 알림 전송 실패 시 로그만 남기고 서비스 중단하지 않음 - -**의존성 추가:** `structlog>=24.0` - ---- - -### 1.3 Telegram Notification Service - -**목표:** 주요 이벤트(시그널, 주문, 에러, 일일 요약)를 Telegram으로 전송한다. - -**변경 사항:** - -- `shared/src/shared/notifier.py` (신규) - - `TelegramNotifier` 클래스 - - `__init__(bot_token: str, chat_id: str)` — aiohttp 세션 관리 - - `send(message: str, parse_mode: str = "HTML")` — 메시지 전송 - - `send_signal(signal: Signal)` — 시그널 포맷팅 후 전송 - - `send_order(order: Order)` — 주문 체결/실패 알림 - - `send_error(error: str, service: str)` — 에러 알림 - - `send_daily_summary(positions: list, pnl: Decimal)` — 일일 요약 - - Rate limiting: 초당 최대 1건 (asyncio.Semaphore + 큐) - - 연결 실패 시 최대 3회 재시도, 실패해도 서비스 중단하지 않음 - -- `shared/src/shared/config.py` — 설정 추가: - - `TELEGRAM_BOT_TOKEN: str = ""` - - `TELEGRAM_CHAT_ID: str = ""` - - `TELEGRAM_ENABLED: bool = False` (토큰 미설정 시 자동 비활성) - -- `.env.example` 업데이트: - ``` - TELEGRAM_BOT_TOKEN= - TELEGRAM_CHAT_ID= - TELEGRAM_ENABLED=false - ``` - -- 연동 포인트: - - `strategy-engine/engine.py` — 시그널 생성 시 `send_signal()` - - `order-executor/executor.py` — 주문 체결/실패 시 `send_order()` - - `shared/logging.py` — ERROR 로그 시 `send_error()` - - `portfolio-manager/main.py` — 매일 자정(UTC) `send_daily_summary()` - -**의존성:** aiohttp (이미 존재) - ---- - -### 1.4 Error Recovery & Health Checks - -**목표:** 서비스 장애 시 자동 복구하고, 헬스체크 엔드포인트로 상태를 모니터링한다. - -**변경 사항:** - -- `shared/src/shared/resilience.py` (신규) - - `retry_with_backoff(func, max_retries, base_delay)` — exponential backoff 데코레이터 - - 지터(jitter) 포함: `delay * (1 + random(0, 0.5))` - - 최대 지연: 60초 - - `CircuitBreaker` 클래스: - - 상태: CLOSED(정상) → OPEN(차단) → HALF_OPEN(시험) - - `failure_threshold`: 연속 실패 N회 시 OPEN (기본: 5) - - `recovery_timeout`: OPEN 후 N초 뒤 HALF_OPEN (기본: 60) - - OPEN 전환 시 Telegram 알림 전송 - -- `shared/src/shared/healthcheck.py` (신규) - - `HealthCheckServer` — aiohttp 기반 경량 HTTP 서버 - - `GET /health` → `{"status": "ok", "service": "...", "uptime": ..., "checks": {...}}` - - 체크 항목: Redis 연결, PostgreSQL 연결, Binance WS 연결(해당 서비스만) - - 포트: `HEALTH_PORT` 환경변수 (서비스별 다르게 설정) - -- 각 서비스에 적용: - - `data-collector` — Binance WS 재연결 (backoff), Redis/DB 재연결 - - `strategy-engine` — Redis 소비자 재연결 - - `order-executor` — 거래소 API 호출 재시도 (circuit breaker) - - `portfolio-manager` — Redis/DB 재연결 - -- `docker-compose.yml` — healthcheck를 `/health` 엔드포인트로 변경 - -- `shared/src/shared/config.py` — 설정 추가: - - `HEALTH_PORT: int = 8080` - - `CIRCUIT_BREAKER_THRESHOLD: int = 5` - - `CIRCUIT_BREAKER_TIMEOUT: int = 60` - ---- - -### 1.5 Prometheus Metrics - -**목표:** 각 서비스의 주요 지표를 Prometheus 포맷으로 노출한다. - -**변경 사항:** - -- `shared/src/shared/metrics.py` (신규) - - `MetricsServer` — prometheus_client 기반 - - `/metrics` 엔드포인트 (healthcheck 서버에 통합) - - 공통 메트릭: - - `service_up` (Gauge) — 서비스 상태 - - `errors_total` (Counter) — 에러 횟수 (label: service, error_type) - - `event_processing_seconds` (Histogram) — 이벤트 처리 시간 - -- 서비스별 메트릭: - - **data-collector:** - - `candles_received_total` (Counter) — 수신 캔들 수 - - `ws_reconnections_total` (Counter) — WS 재연결 횟수 - - **strategy-engine:** - - `signals_generated_total` (Counter, label: strategy, side) - - `strategy_execution_seconds` (Histogram, label: strategy) - - **order-executor:** - - `orders_total` (Counter, label: status, side) - - `risk_rejections_total` (Counter, label: reason) - - **portfolio-manager:** - - `portfolio_value` (Gauge) — 총 포트폴리오 가치 - - `unrealized_pnl` (Gauge, label: symbol) - -- `docker-compose.yml` — Prometheus + Grafana 서비스 추가 (선택적 프로필): - ```yaml - prometheus: - image: prom/prometheus:latest - profiles: ["monitoring"] - volumes: - - ./monitoring/prometheus.yml:/etc/prometheus/prometheus.yml - grafana: - image: grafana/grafana:latest - profiles: ["monitoring"] - ports: - - "3000:3000" - ``` - -- `monitoring/prometheus.yml` (신규) — 스크래핑 설정 -- `monitoring/grafana/` (신규) — 대시보드 프로비저닝 (선택적) - -**의존성 추가:** `prometheus-client>=0.20` - ---- - -## Part 2: Strategy Expansion - -### 2.1 Trend Following Strategies - -**MACD Strategy** (`strategies/macd_strategy.py`) -- MACD line = EMA(12) - EMA(26), Signal line = EMA(9) of MACD -- BUY: MACD가 Signal line 위로 교차 + 히스토그램 양전환 -- SELL: MACD가 Signal line 아래로 교차 + 히스토그램 음전환 -- 파라미터: `fast_period=12`, `slow_period=26`, `signal_period=9`, `quantity` -- warmup_period: `slow_period + signal_period` - -**Bollinger Bands Strategy** (`strategies/bollinger_strategy.py`) -- 중심선 = SMA(20), 상단 = 중심 + 2*std, 하단 = 중심 - 2*std -- BUY: 가격이 하단 밴드 아래로 이탈 후 복귀 -- SELL: 가격이 상단 밴드 위로 이탈 후 복귀 -- 변동성 필터: 밴드 폭이 임계값 미만이면 시그널 무시 (횡보장 필터) -- 파라미터: `period=20`, `num_std=2.0`, `min_bandwidth=0.02`, `quantity` -- warmup_period: `period` - -**EMA Crossover Strategy** (`strategies/ema_crossover_strategy.py`) -- 단기 EMA와 장기 EMA 교차 -- BUY: 단기 EMA가 장기 EMA 위로 교차 (Golden Cross) -- SELL: 단기 EMA가 장기 EMA 아래로 교차 (Death Cross) -- 파라미터: `short_period=9`, `long_period=21`, `quantity` -- warmup_period: `long_period` - ---- - -### 2.2 Scalping Strategies - -**VWAP Strategy** (`strategies/vwap_strategy.py`) -- VWAP = cumsum(price * volume) / cumsum(volume) -- BUY: 가격이 VWAP 아래에서 VWAP으로 복귀 (평균 회귀) -- SELL: 가격이 VWAP 위에서 VWAP으로 복귀 -- 일중 리셋: UTC 00:00에 VWAP 재계산 -- 파라미터: `deviation_threshold=0.002`, `quantity` -- warmup_period: 최소 30 캔들 - -**Volume Profile Strategy** (`strategies/volume_profile_strategy.py`) -- 최근 N개 캔들의 가격대별 거래량 분포 계산 -- POC (Point of Control): 가장 거래량이 많은 가격대 -- Value Area: 전체 거래량 70%가 집중된 구간 -- BUY: 가격이 Value Area 하단 지지선에서 반등 -- SELL: 가격이 Value Area 상단 저항선에서 거부 -- 파라미터: `lookback_period=100`, `num_bins=50`, `value_area_pct=0.7`, `quantity` -- warmup_period: `lookback_period` - ---- - -### 2.3 Strategy Common Improvements - -**BaseStrategy 확장:** -```python -class BaseStrategy(ABC): - @property - @abstractmethod - def warmup_period(self) -> int: - """지표 계산에 필요한 최소 캔들 수""" - pass - - @abstractmethod - def on_candle(self, candle: Candle) -> Signal | None: - pass - - @abstractmethod - def configure(self, params: dict) -> None: - pass - - def reset(self) -> None: - """전략 상태 초기화 (백테스트 간 재사용)""" - pass -``` - -**전략 파라미터 외부화:** -- `strategies/config/` 디렉토리에 YAML 설정 파일 -- 파일명: `{strategy_name}.yaml` (예: `rsi_strategy.yaml`) -- 구조: - ```yaml - # rsi_strategy.yaml - period: 14 - oversold: 30 - overbought: 70 - quantity: 0.001 - ``` -- `plugin_loader.py`가 전략 로드 시 자동으로 같은 이름의 YAML을 찾아 `configure()` 호출 -- CLI에서 `--param key=value`로 런타임 오버라이드 가능 - -**기존 전략 업데이트:** -- `RsiStrategy`, `GridStrategy`에 `warmup_period` 속성 추가 -- `reset()` 메서드 구현 - -**의존성 추가:** `pyyaml>=6.0` - ---- - -### 2.4 Backtest Enhancement - -**DetailedMetrics 데이터클래스** (`backtester/src/backtester/metrics.py`, 신규): -```python -@dataclass -class TradeRecord: - entry_time: datetime - exit_time: datetime - symbol: str - side: str - entry_price: Decimal - exit_price: Decimal - quantity: Decimal - pnl: Decimal - pnl_pct: float - holding_period: timedelta - -@dataclass -class DetailedMetrics: - # 기본 - total_return: float - total_trades: int - winning_trades: int - losing_trades: int - win_rate: float - profit_factor: float - - # 리스크 메트릭 - sharpe_ratio: float - sortino_ratio: float - calmar_ratio: float - max_drawdown: float - max_drawdown_duration: timedelta - - # 수익률 분석 - monthly_returns: dict[str, float] # "2025-01": 0.05 - avg_win: float - avg_loss: float - largest_win: float - largest_loss: float - avg_holding_period: timedelta - - # 개별 거래 - trades: list[TradeRecord] -``` - -**BacktestEngine 확장:** -- `engine.py`에 `DetailedMetrics` 계산 로직 추가 -- `simulator.py`에 `TradeRecord` 생성 로직 추가 (진입/청산 시점 기록) -- Sharpe ratio = `mean(daily_returns) / std(daily_returns) * sqrt(365)` (crypto는 365일) -- Sortino ratio = `mean(daily_returns) / downside_std * sqrt(365)` -- Calmar ratio = `annualized_return / max_drawdown` -- Max drawdown = `max(peak - trough) / peak` - -**Reporter 개선:** -- `reporter.py` — rich 라이브러리로 테이블 출력 - - 요약 테이블: 핵심 메트릭 - - 월별 수익률 테이블 - - 최고/최악 거래 Top 5 -- CSV/JSON 내보내기: `--output csv` / `--output json` 플래그 - -**CLI 확장:** -- `trading backtest run` — 기존 출력에 상세 메트릭 추가 -- `trading backtest run --output csv --file result.csv` — 결과 내보내기 - -**의존성 추가:** `rich>=13.0` - ---- - -## Updated Tech Stack - -| 용도 | 기존 | 변경 | -|------|------|------| -| DB ORM | asyncpg (raw SQL) | **SQLAlchemy 2.0 async** (asyncpg 드라이버) | -| 마이그레이션 | 없음 | **Alembic** | -| 로깅 | Python logging | **structlog** | -| 알림 | 없음 | **Telegram Bot API** (aiohttp) | -| 메트릭 | 없음 | **prometheus-client** | -| 전략 설정 | 하드코딩 | **YAML** (pyyaml) | -| 리포트 출력 | print | **rich** | - ---- - -## Updated .env.example - -```env -# Exchange -BINANCE_API_KEY= -BINANCE_API_SECRET= - -# Infrastructure -REDIS_URL=redis://localhost:6379 -DATABASE_URL=postgresql+asyncpg://trading:trading@localhost:5432/trading - -# Logging -LOG_LEVEL=INFO -LOG_FORMAT=json - -# Telegram -TELEGRAM_BOT_TOKEN= -TELEGRAM_CHAT_ID= -TELEGRAM_ENABLED=false - -# Risk Management -RISK_MAX_POSITION_SIZE=0.1 -RISK_STOP_LOSS_PCT=5 -RISK_DAILY_LOSS_LIMIT_PCT=10 -DRY_RUN=true - -# Health & Metrics -HEALTH_PORT=8080 -CIRCUIT_BREAKER_THRESHOLD=5 -CIRCUIT_BREAKER_TIMEOUT=60 -``` - ---- - -## New Files Summary - -| 파일 | 용도 | -|------|------| -| `shared/src/shared/sa_models.py` | SQLAlchemy ORM 모델 | -| `shared/src/shared/logging.py` | structlog 설정 | -| `shared/src/shared/notifier.py` | Telegram 알림 | -| `shared/src/shared/resilience.py` | retry, circuit breaker | -| `shared/src/shared/healthcheck.py` | 헬스체크 서버 | -| `shared/src/shared/metrics.py` | Prometheus 메트릭 | -| `shared/alembic/` | DB 마이그레이션 환경 | -| `strategies/config/*.yaml` | 전략 파라미터 설정 | -| `strategies/macd_strategy.py` | MACD 전략 | -| `strategies/bollinger_strategy.py` | Bollinger Bands 전략 | -| `strategies/ema_crossover_strategy.py` | EMA Crossover 전략 | -| `strategies/vwap_strategy.py` | VWAP 전략 | -| `strategies/volume_profile_strategy.py` | Volume Profile 전략 | -| `backtester/src/backtester/metrics.py` | 상세 백테스트 메트릭 | -| `monitoring/prometheus.yml` | Prometheus 설정 | - ---- - -## Scope Boundaries - -**포함:** -- SQLAlchemy 2.0 async 전환 + Alembic 마이그레이션 -- structlog JSON 로깅 -- Telegram 알림 (시그널, 주문, 에러, 일일 요약) -- 에러 복구 (retry, circuit breaker) + 헬스체크 -- Prometheus 메트릭 수집 -- 5개 신규 전략 (MACD, Bollinger, EMA Crossover, VWAP, Volume Profile) -- BaseStrategy에 warmup_period, reset() 추가 -- YAML 기반 전략 파라미터 -- 백테스트 상세 메트릭 + rich 리포트 - -**제외:** -- Grafana 대시보드 프로비저닝 (Prometheus만 설정, 대시보드는 수동) -- 멀티 거래소 지원 -- REST API / 웹 대시보드 -- 전략 조합 프레임워크 (향후 확장) diff --git a/docs/superpowers/specs/2026-04-02-news-driven-stock-selector-design.md b/docs/superpowers/specs/2026-04-02-news-driven-stock-selector-design.md new file mode 100644 index 0000000..d439154 --- /dev/null +++ b/docs/superpowers/specs/2026-04-02-news-driven-stock-selector-design.md @@ -0,0 +1,418 @@ +# News-Driven Stock Selector Design + +**Date:** 2026-04-02 +**Goal:** Upgrade the MOC (Market on Close) strategy from fixed symbol lists to dynamic, news-driven stock selection. The system collects news/sentiment data continuously, then selects 2-3 optimal stocks daily before market close. + +--- + +## Architecture Overview + +``` +[Continuous Collection] [Pre-Close Decision] +Finnhub News ─┐ +RSS Feeds ─┤ +SEC EDGAR ─┤ +Truth Social ─┼→ DB (news_items) → Sentiment Aggregator → symbol_scores +Reddit ─┤ + Redis "news" (every 15 min) market_sentiment +Fear & Greed ─┤ +FOMC/Fed ─┘ + + 15:00 ET ─→ Candidate Pool (sentiment top + LLM picks) + 15:15 ET ─→ Technical Filter (RSI, EMA, volume) + 15:30 ET ─→ LLM Final Selection (2-3 stocks) → Telegram + 15:50 ET ─→ MOC Buy Execution + 09:35 ET ─→ Next-day Sell (existing MOC logic) +``` + +## 1. News Collector Service + +New service: `services/news-collector/` + +### Structure + +``` +services/news-collector/ +├── Dockerfile +├── pyproject.toml +├── src/news_collector/ +│ ├── __init__.py +│ ├── main.py # Scheduler: runs each collector on its interval +│ ├── config.py +│ └── collectors/ +│ ├── __init__.py +│ ├── base.py # BaseCollector ABC +│ ├── finnhub.py # Finnhub market news (free, 60 req/min) +│ ├── rss.py # Yahoo Finance, Google News, MarketWatch RSS +│ ├── sec_edgar.py # SEC EDGAR 8-K/10-Q filings +│ ├── truth_social.py # Truth Social scraping (Trump posts) +│ ├── reddit.py # Reddit (r/wallstreetbets, r/stocks) +│ ├── fear_greed.py # CNN Fear & Greed Index scraping +│ └── fed.py # FOMC statements, Fed announcements +└── tests/ +``` + +### BaseCollector Interface + +```python +class BaseCollector(ABC): + name: str + poll_interval: int # seconds + + @abstractmethod + async def collect(self) -> list[NewsItem]: + """Collect and return list of NewsItem.""" + + @abstractmethod + async def is_available(self) -> bool: + """Check if this source is accessible (API key present, endpoint reachable).""" +``` + +### Poll Intervals + +| Collector | Interval | Notes | +|-----------|----------|-------| +| Finnhub | 5 min | Free tier: 60 calls/min | +| RSS (Yahoo/Google/MarketWatch) | 10 min | Headlines only | +| SEC EDGAR | 30 min | Focus on 8-K filings | +| Truth Social | 15 min | Scraping | +| Reddit | 15 min | Hot posts from relevant subs | +| Fear & Greed | 1 hour | Updates once daily but check periodically | +| FOMC/Fed | 1 hour | Infrequent events | + +### Provider Abstraction (for paid upgrade path) + +```python +# config.yaml +collectors: + news: + provider: "finnhub" # swap to "benzinga" for paid + api_key: ${FINNHUB_API_KEY} + social: + provider: "reddit" # swap to "stocktwits_pro" etc. + policy: + provider: "truth_social" # swap to "twitter_api" etc. + +# Factory +COLLECTOR_REGISTRY = { + "finnhub": FinnhubCollector, + "rss": RSSCollector, + "benzinga": BenzingaCollector, # added later +} +``` + +## 2. Shared Models (additions to shared/) + +### NewsItem (shared/models.py) + +```python +class NewsCategory(str, Enum): + POLICY = "policy" + EARNINGS = "earnings" + MACRO = "macro" + SOCIAL = "social" + FILING = "filing" + FED = "fed" + +class NewsItem(BaseModel): + id: str = Field(default_factory=lambda: str(uuid.uuid4())) + source: str # "finnhub", "rss", "sec_edgar", etc. + headline: str + summary: str | None = None + url: str | None = None + published_at: datetime + symbols: list[str] = [] # Related tickers (if identifiable) + sentiment: float # -1.0 to 1.0 (first-pass analysis at collection) + category: NewsCategory + raw_data: dict = {} + created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc)) +``` + +### SymbolScore (shared/sentiment_models.py — new file) + +```python +class SymbolScore(BaseModel): + symbol: str + news_score: float # -1.0 to 1.0, weighted avg of news sentiment + news_count: int # Number of news items in last 24h + social_score: float # Reddit/social sentiment + policy_score: float # Policy-related impact + filing_score: float # SEC filing impact + composite: float # Weighted final score + updated_at: datetime + +class MarketSentiment(BaseModel): + fear_greed: int # 0-100 + fear_greed_label: str # "Extreme Fear", "Fear", "Neutral", "Greed", "Extreme Greed" + vix: float | None = None + fed_stance: str # "hawkish", "neutral", "dovish" + market_regime: str # "risk_on", "neutral", "risk_off" + updated_at: datetime + +class SelectedStock(BaseModel): + symbol: str + side: OrderSide # BUY or SELL + conviction: float # 0.0 to 1.0 + reason: str # Selection rationale + key_news: list[str] # Key news headlines + +class Candidate(BaseModel): + symbol: str + source: str # "sentiment" or "llm" + direction: OrderSide | None = None # Suggested direction (if known) + score: float # Relevance/priority score + reason: str # Why this candidate was selected +``` + +## 3. Sentiment Analysis Pipeline + +### Location + +Refactor existing `shared/src/shared/sentiment.py`. + +### Two-Stage Analysis + +**Stage 1: Per-news sentiment (at collection time)** +- VADER (nltk.sentiment, free) for English headlines +- Keyword rule engine for domain-specific terms (e.g., "tariff" → negative for importers, positive for domestic producers) +- Score stored in `NewsItem.sentiment` + +**Stage 2: Per-symbol aggregation (every 15 minutes)** + +``` +composite = ( + news_score * 0.3 + + social_score * 0.2 + + policy_score * 0.3 + + filing_score * 0.2 +) * freshness_decay +``` + +Freshness decay: +- < 1 hour: 1.0 +- 1-6 hours: 0.7 +- 6-24 hours: 0.3 +- > 24 hours: excluded + +Policy score weighted high because US stock market is heavily influenced by policy events (tariffs, regulation, subsidies). + +### Market-Level Gating + +`MarketSentiment.market_regime` determination: +- `risk_off`: Fear & Greed < 20 OR VIX > 30 → **block all trades** +- `risk_on`: Fear & Greed > 60 AND VIX < 20 +- `neutral`: everything else + +This extends the existing `sentiment.py` `should_block()` logic. + +## 4. Stock Selector Engine + +### Location + +`services/strategy-engine/src/strategy_engine/stock_selector.py` + +### Three-Stage Selection Process + +**Stage 1: Candidate Pool (15:00 ET)** + +Two candidate sources, results merged (deduplicated): + +```python +class CandidateSource(ABC): + @abstractmethod + async def get_candidates(self) -> list[Candidate] + +class SentimentCandidateSource(CandidateSource): + """Top N symbols by composite SymbolScore from DB.""" + +class LLMCandidateSource(CandidateSource): + """Send today's top news summary to Claude, get related symbols + direction.""" +``` + +- SentimentCandidateSource: top 20 by composite score +- LLMCandidateSource: Claude analyzes today's major news and recommends affected symbols +- Merged pool: typically 20-30 candidates + +**Stage 2: Technical Filter (15:15 ET)** + +Apply existing MOC screening criteria to candidates: +- Fetch recent price data from Alpaca for all candidates +- RSI 30-60 +- Price > 20-period EMA +- Volume > average +- Bullish candle pattern +- Result: typically 5-10 survivors + +**Stage 3: LLM Final Selection (15:30 ET)** + +Send to Claude: +- Filtered candidate list with technical indicators +- Per-symbol sentiment scores and top news headlines +- Market sentiment (Fear & Greed, VIX, Fed stance) +- Prompt: "Select 2-3 stocks for MOC trading with rationale" + +Response parsed into `list[SelectedStock]`. + +### Integration with MOC Strategy + +Current: MOC strategy receives candles for fixed symbols and decides internally. + +New flow: +1. `StockSelector` publishes `SelectedStock` list to Redis stream `selected_stocks` at 15:30 ET +2. MOC strategy reads `selected_stocks` to get today's targets +3. MOC still applies its own technical checks at 15:50-16:00 as a safety net +4. If a selected stock fails the final technical check, it's skipped (no forced trades) + +## 5. Database Schema + +Four new tables via Alembic migration: + +```sql +CREATE TABLE news_items ( + id UUID PRIMARY KEY, + source VARCHAR(50) NOT NULL, + headline TEXT NOT NULL, + summary TEXT, + url TEXT, + published_at TIMESTAMPTZ NOT NULL, + symbols TEXT[], + sentiment FLOAT NOT NULL, + category VARCHAR(50) NOT NULL, + raw_data JSONB DEFAULT '{}', + created_at TIMESTAMPTZ DEFAULT NOW() +); +CREATE INDEX idx_news_items_published ON news_items(published_at); +CREATE INDEX idx_news_items_symbols ON news_items USING GIN(symbols); + +CREATE TABLE symbol_scores ( + id UUID PRIMARY KEY, + symbol VARCHAR(10) NOT NULL, + news_score FLOAT NOT NULL DEFAULT 0, + news_count INT NOT NULL DEFAULT 0, + social_score FLOAT NOT NULL DEFAULT 0, + policy_score FLOAT NOT NULL DEFAULT 0, + filing_score FLOAT NOT NULL DEFAULT 0, + composite FLOAT NOT NULL DEFAULT 0, + updated_at TIMESTAMPTZ NOT NULL +); +CREATE UNIQUE INDEX idx_symbol_scores_symbol ON symbol_scores(symbol); + +CREATE TABLE market_sentiment ( + id UUID PRIMARY KEY, + fear_greed INT NOT NULL, + fear_greed_label VARCHAR(30) NOT NULL, + vix FLOAT, + fed_stance VARCHAR(20) NOT NULL DEFAULT 'neutral', + market_regime VARCHAR(20) NOT NULL DEFAULT 'neutral', + updated_at TIMESTAMPTZ NOT NULL +); + +CREATE TABLE stock_selections ( + id UUID PRIMARY KEY, + trade_date DATE NOT NULL, + symbol VARCHAR(10) NOT NULL, + side VARCHAR(4) NOT NULL, + conviction FLOAT NOT NULL, + reason TEXT NOT NULL, + key_news JSONB DEFAULT '[]', + sentiment_snapshot JSONB DEFAULT '{}', + created_at TIMESTAMPTZ DEFAULT NOW() +); +CREATE INDEX idx_stock_selections_date ON stock_selections(trade_date); +``` + +`stock_selections` stores an audit trail: why each stock was selected, enabling post-hoc analysis of selection quality. + +## 6. Redis Streams + +| Stream | Producer | Consumer | Payload | +|--------|----------|----------|---------| +| `news` | news-collector | strategy-engine (sentiment aggregator) | NewsItem | +| `selected_stocks` | stock-selector | MOC strategy | SelectedStock | + +Existing streams (`candles`, `signals`, `orders`) unchanged. + +## 7. Docker Compose Addition + +```yaml +news-collector: + build: + context: . + dockerfile: services/news-collector/Dockerfile + env_file: .env + ports: + - "8084:8084" + depends_on: + redis: { condition: service_healthy } + postgres: { condition: service_healthy } + healthcheck: + test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8084/health')"] + interval: 10s + timeout: 5s + retries: 3 + restart: unless-stopped +``` + +## 8. Environment Variables + +```bash +# News Collector +FINNHUB_API_KEY= # Free key from finnhub.io +NEWS_POLL_INTERVAL=300 # Default 5 min (overrides per-collector defaults) +SENTIMENT_AGGREGATE_INTERVAL=900 # 15 min + +# Stock Selector +SELECTOR_CANDIDATES_TIME=15:00 # ET, candidate pool generation +SELECTOR_FILTER_TIME=15:15 # ET, technical filter +SELECTOR_FINAL_TIME=15:30 # ET, LLM final pick +SELECTOR_MAX_PICKS=3 + +# LLM (for stock selector + screener) +ANTHROPIC_API_KEY= +ANTHROPIC_MODEL=claude-sonnet-4-20250514 +``` + +## 9. Telegram Notifications + +Extend existing `shared/notifier.py` with: + +```python +async def send_stock_selection(self, selections: list[SelectedStock], market: MarketSentiment): + """ + 📊 오늘의 종목 선정 (2/3) + + 1. NVDA 🟢 BUY (확신도: 0.85) + 근거: 트럼프 반도체 보조금 확대 발표, RSI 42 + 핵심뉴스: "Trump signs CHIPS Act expansion..." + + 2. XOM 🟢 BUY (확신도: 0.72) + 근거: 유가 상승 + 실적 서프라이즈, 볼륨 급증 + + 시장심리: Fear & Greed 55 (Neutral) | VIX 18.2 + """ +``` + +## 10. Testing Strategy + +**Unit tests:** +- Each collector: mock HTTP responses → verify NewsItem parsing +- Sentiment analysis: verify VADER + keyword scoring +- Aggregator: mock news data → verify SymbolScore calculation and freshness decay +- Stock selector: mock scores → verify candidate/filter/selection pipeline +- LLM calls: mock Claude response → verify SelectedStock parsing + +**Integration tests:** +- Full pipeline: news collection → DB → aggregation → selection +- Market gating: verify `risk_off` blocks all trades +- MOC integration: verify selected stocks flow to MOC strategy + +**Post-hoc analysis (future):** +- Use `stock_selections` audit trail to measure selection accuracy +- Historical news data replay for backtesting requires paid data (deferred) + +## 11. Out of Scope (Future) + +- Paid API integration (designed for, not implemented) +- Historical news backtesting +- WebSocket real-time news streaming +- Multi-language sentiment analysis +- Options/derivatives signals diff --git a/docs/superpowers/specs/2026-04-02-platform-upgrade-design.md b/docs/superpowers/specs/2026-04-02-platform-upgrade-design.md new file mode 100644 index 0000000..9c84e10 --- /dev/null +++ b/docs/superpowers/specs/2026-04-02-platform-upgrade-design.md @@ -0,0 +1,257 @@ +# Platform Upgrade Design Spec + +**Date**: 2026-04-02 +**Approach**: Bottom-Up (shared library → infra → services → API security → operations) + +--- + +## Phase 1: Shared Library Hardening + +### 1-1. Resilience Module (`shared/src/shared/resilience.py`) +Currently empty. Implement: +- **`retry_async()`** — tenacity-based exponential backoff + jitter decorator. Configurable max retries (default 3), base delay (1s), max delay (30s). +- **`CircuitBreaker`** — Tracks consecutive failures. Opens after N failures (default 5), stays open for configurable cooldown (default 60s), transitions to half-open to test recovery. +- **`timeout()`** — asyncio-based timeout wrapper. Raises `TimeoutError` after configurable duration. +- All decorators composable: `@retry_async() @circuit_breaker() async def call_api():` + +### 1-2. DB Connection Pooling (`shared/src/shared/db.py`) +Add to `create_async_engine()`: +- `pool_size=20` (configurable via `DB_POOL_SIZE`) +- `max_overflow=10` (configurable via `DB_MAX_OVERFLOW`) +- `pool_pre_ping=True` (verify connections before use) +- `pool_recycle=3600` (recycle stale connections) +Add corresponding fields to `Settings`. + +### 1-3. Redis Resilience (`shared/src/shared/broker.py`) +- Add to `redis.asyncio.from_url()`: `socket_keepalive=True`, `health_check_interval=30`, `retry_on_timeout=True` +- Wrap `publish()`, `read_group()`, `ensure_group()` with `@retry_async()` from resilience module +- Add `reconnect()` method for connection loss recovery + +### 1-4. Config Validation (`shared/src/shared/config.py`) +- Add `field_validator` for business logic: `risk_max_position_size > 0`, `health_port` in 1024-65535, `log_level` in valid set +- Change secret fields to `SecretStr`: `alpaca_api_key`, `alpaca_api_secret`, `database_url`, `redis_url`, `telegram_bot_token`, `anthropic_api_key`, `finnhub_api_key` +- Update all consumers to call `.get_secret_value()` where needed + +### 1-5. Dependency Pinning +All `pyproject.toml` files: add upper bounds. +Examples: +- `pydantic>=2.8,<3` +- `redis>=5.0,<6` +- `sqlalchemy[asyncio]>=2.0,<3` +- `numpy>=1.26,<3` +- `pandas>=2.1,<3` +- `anthropic>=0.40,<1` +Run `uv lock` to generate lock file. + +--- + +## Phase 2: Infrastructure Hardening + +### 2-1. Docker Secrets & Environment +- Remove hardcoded `POSTGRES_USER: trading` / `POSTGRES_PASSWORD: trading` from `docker-compose.yml` +- Reference via `${POSTGRES_USER}` / `${POSTGRES_PASSWORD}` from `.env` +- Add comments in `.env.example` marking secret vs config variables + +### 2-2. Dockerfile Optimization (all 7 services) +Pattern for each Dockerfile: +```dockerfile +# Stage 1: builder +FROM python:3.12-slim AS builder +WORKDIR /app +COPY shared/pyproject.toml shared/setup.cfg shared/ +COPY shared/src/ shared/src/ +RUN pip install --no-cache-dir ./shared +COPY services/<name>/pyproject.toml services/<name>/ +COPY services/<name>/src/ services/<name>/src/ +RUN pip install --no-cache-dir ./services/<name> + +# Stage 2: runtime +FROM python:3.12-slim +RUN useradd -r -s /bin/false appuser +WORKDIR /app +COPY --from=builder /usr/local/lib/python3.12/site-packages /usr/local/lib/python3.12/site-packages +COPY --from=builder /usr/local/bin /usr/local/bin +USER appuser +CMD ["python", "-m", "<module>.main"] +``` + +Create root `.dockerignore`: +``` +__pycache__ +*.pyc +.git +.venv +.env +tests/ +docs/ +*.md +.ruff_cache +``` + +### 2-3. Database Index Migration (`003_add_missing_indexes.py`) +New Alembic migration adding: +- `idx_signals_symbol_created` on `signals(symbol, created_at)` +- `idx_orders_symbol_status_created` on `orders(symbol, status, created_at)` +- `idx_trades_order_id` on `trades(order_id)` +- `idx_trades_symbol_traded` on `trades(symbol, traded_at)` +- `idx_portfolio_snapshots_at` on `portfolio_snapshots(snapshot_at)` +- `idx_symbol_scores_symbol` unique on `symbol_scores(symbol)` + +### 2-4. Docker Compose Resource Limits +Add to each service: +```yaml +deploy: + resources: + limits: + memory: 512M + cpus: '1.0' +``` +Strategy-engine and backtester get `memory: 1G` (pandas/numpy usage). + +Add explicit networks: +```yaml +networks: + internal: + driver: bridge + monitoring: + driver: bridge +``` + +--- + +## Phase 3: Service-Level Improvements + +### 3-1. Graceful Shutdown (all services) +Add to each service's `main()`: +```python +shutdown_event = asyncio.Event() + +def _signal_handler(): + log.info("shutdown_signal_received") + shutdown_event.set() + +loop = asyncio.get_event_loop() +loop.add_signal_handler(signal.SIGTERM, _signal_handler) +loop.add_signal_handler(signal.SIGINT, _signal_handler) +``` +Main loops check `shutdown_event.is_set()` to exit gracefully. +API service: add `--timeout-graceful-shutdown 30` to uvicorn CMD. + +### 3-2. Exception Specialization (all services) +Replace broad `except Exception` with layered handling: +- `ConnectionError`, `TimeoutError` → retry via resilience module +- `ValueError`, `KeyError` → log warning, skip item, continue +- `Exception` → top-level only, `exc_info=True` for full traceback + Telegram alert + +Target: reduce 63 broad catches to ~10 top-level safety nets. + +### 3-3. LLM Parsing Deduplication (`stock_selector.py`) +Extract `_extract_json_from_text(text: str) -> list | dict | None`: +- Tries ```` ```json ``` ```` code block extraction +- Falls back to `re.search(r"\[.*\]", text, re.DOTALL)` +- Falls back to raw `json.loads(text.strip())` +Replace 3 duplicate parsing blocks with single call. + +### 3-4. aiohttp Session Reuse (`stock_selector.py`) +- Add `_session: aiohttp.ClientSession | None = None` to `StockSelector` +- Lazy-init in `_ensure_session()`, close in `close()` +- Replace all `async with aiohttp.ClientSession()` with `self._session` + +--- + +## Phase 4: API Security + +### 4-1. Bearer Token Authentication +- Add `api_auth_token: SecretStr = ""` to `Settings` +- Create `dependencies/auth.py` with `verify_token()` dependency +- Apply to all `/api/v1/*` routes via router-level `dependencies=[Depends(verify_token)]` +- If token is empty string → skip auth (dev mode), log warning on startup + +### 4-2. CORS Configuration +```python +app.add_middleware( + CORSMiddleware, + allow_origins=settings.cors_origins.split(","), # default: "http://localhost:3000" + allow_methods=["GET", "POST"], + allow_headers=["Authorization", "Content-Type"], +) +``` +Add `cors_origins: str = "http://localhost:3000"` to Settings. + +### 4-3. Rate Limiting +- Add `slowapi` dependency +- Global default: 60 req/min per IP +- Order-related endpoints: 10 req/min per IP +- Return `429 Too Many Requests` with `Retry-After` header + +### 4-4. Input Validation +- All `limit` params: `Query(default=50, ge=1, le=1000)` +- All `days` params: `Query(default=30, ge=1, le=365)` +- Add Pydantic `response_model` to all endpoints (enables auto OpenAPI docs) +- Add `symbol` param validation: uppercase, 1-5 chars, alphanumeric + +--- + +## Phase 5: Operational Maturity + +### 5-1. GitHub Actions CI/CD +File: `.github/workflows/ci.yml` + +**PR trigger** (`pull_request`): +1. Install deps (`uv sync`) +2. Ruff lint + format check +3. pytest with coverage (`--cov --cov-report=xml`) +4. Upload coverage to PR comment + +**Main push** (`push: branches: [master]`): +1. Same lint + test +2. `docker compose build` +3. (Future: push to registry) + +### 5-2. Ruff Rules Enhancement +```toml +[tool.ruff.lint] +select = ["E", "W", "F", "I", "B", "UP", "ASYNC", "PERF", "C4", "RUF"] +ignore = ["E501"] + +[tool.ruff.lint.per-file-ignores] +"tests/*" = ["F841"] + +[tool.ruff.lint.isort] +known-first-party = ["shared"] +``` +Run `ruff check --fix .` and `ruff format .` to fix existing violations, commit separately. + +### 5-3. Prometheus Alerting +File: `monitoring/prometheus/alert_rules.yml` +Rules: +- `ServiceDown`: `service_up == 0` for 1 min → critical +- `HighErrorRate`: `rate(errors_total[5m]) > 10` → warning +- `HighLatency`: `histogram_quantile(0.95, processing_seconds) > 5` → warning + +Add Alertmanager config with Telegram webhook (reuse existing bot token). +Reference alert rules in `monitoring/prometheus.yml`. + +### 5-4. Code Coverage +Add to root `pyproject.toml`: +```toml +[tool.pytest.ini_options] +addopts = "--cov=shared/src --cov=services --cov-report=term-missing" + +[tool.coverage.run] +branch = true +omit = ["tests/*", "*/alembic/*"] + +[tool.coverage.report] +fail_under = 70 +``` +Add `pytest-cov` to dev dependencies. + +--- + +## Out of Scope +- Kubernetes/Helm charts (premature — Docker Compose sufficient for current scale) +- External secrets manager (Vault, AWS SM — overkill for single-machine deployment) +- OpenTelemetry distributed tracing (add when debugging cross-service issues) +- API versioning beyond `/api/v1/` prefix +- Data retention/partitioning (address when data volume becomes an issue) |