trading/services/trade_executor/main.py

"""Trade Executor service -- main entry point.

Consumes ``signals:generated`` from Redis Streams, runs risk checks,
submits orders via the brokerage abstraction layer, records trades
in the database, and publishes ``TradeExecution`` messages to
``trades:executed``.
"""

from __future__ import annotations

import asyncio
import logging
import signal
import time
import uuid

from redis.asyncio import Redis

from services.trade_executor.config import TradeExecutorConfig
from services.trade_executor.risk_manager import RiskManager
from shared.broker.alpaca_broker import AlpacaBroker
from shared.redis_streams import StreamConsumer, StreamPublisher
from shared.schemas.trading import (
    OrderRequest,
    OrderSide,
    OrderStatus,
    SignalDirection,
    TradeExecution,
    TradeSignal,
)
from shared.telemetry import setup_telemetry

logger = logging.getLogger(__name__)


async def process_signal(
    signal: TradeSignal,
    risk_manager: RiskManager,
    broker: AlpacaBroker,
    publisher: StreamPublisher,
    counters: dict,
) -> None:
    """Process a single trade signal: risk check, order, record, publish.

    Parameters
    ----------
    signal:
        The trade signal to act on.
    risk_manager:
        Performs pre-trade risk checks and position sizing.
    broker:
        Brokerage adapter for submitting orders.
    publisher:
        Publishes execution results to ``trades:executed``.
    counters:
        Dict of OpenTelemetry counter/histogram instruments.
    """
    # --- Step 1: risk check ---
    approved, reason = await risk_manager.check_risk(signal)
    if not approved:
        logger.info("Signal REJECTED for %s: %s", signal.ticker, reason)
        counters["rejections"].add(1, {"reason": reason.split(" ")[0]})
        return

    # --- Step 2: calculate position size ---
    account = await broker.get_account()
    qty = risk_manager.calculate_position_size(signal, account)
    if qty <= 0:
        logger.info("Position size is zero for %s — skipping", signal.ticker)
        counters["rejections"].add(1, {"reason": "zero_position_size"})
        return

    # --- Step 3: create order ---
    side = OrderSide.BUY if signal.direction == SignalDirection.LONG else OrderSide.SELL
    order_request = OrderRequest(
        ticker=signal.ticker,
        side=side,
        qty=float(qty),
    )

    # --- Step 4: submit order ---
    start = time.monotonic()
    result = await broker.submit_order(order_request)
    elapsed = time.monotonic() - start
    counters["fill_latency"].record(elapsed)

    # --- Step 5: build trade execution ---
    trade_id = uuid.uuid4()
    execution = TradeExecution(
        trade_id=trade_id,
        ticker=signal.ticker,
        side=side,
        qty=result.qty,
        price=result.filled_price or 0.0,
        status=result.status,
        signal_id=None,
        strategy_id=None,
        timestamp=result.timestamp,
    )

    # --- Step 6: publish to trades:executed ---
    await publisher.publish(execution.model_dump(mode="json"))
    counters["trades_executed"].add(1)
    logger.info(
        "Trade executed: %s %s %.0f shares @ %s status=%s",
        side.value,
        signal.ticker,
        result.qty,
        result.filled_price,
        result.status.value,
    )


async def run(config: TradeExecutorConfig | None = None) -> None:
    """Main service loop.

    Connects to Redis, initialises the broker and risk manager, then
    continuously consumes from ``signals:generated`` and publishes
    execution results to ``trades:executed``.
    """
    if config is None:
        config = TradeExecutorConfig()

    logging.basicConfig(level=config.log_level)
    logger.info("Starting Trade Executor service")

    # --- Telemetry ---
    meter = setup_telemetry("trade-executor", config.otel_metrics_port)
    counters = {
        "trades_executed": meter.create_counter(
            "trades_executed",
            description="Total trades successfully submitted",
        ),
        "rejections": meter.create_counter(
            "trade_rejections",
            description="Signals rejected by risk checks",
        ),
        "fill_latency": meter.create_histogram(
            "order_fill_latency_seconds",
            description="Time from order submission to response",
            unit="s",
        ),
    }

    # --- Redis ---
    redis = Redis.from_url(config.redis_url, decode_responses=False)
    consumer = StreamConsumer(redis, "signals:generated", "trade-executor", "worker-1")
    publisher = StreamPublisher(redis, "trades:executed")

    # --- Broker ---
    broker = AlpacaBroker(
        api_key=config.alpaca_api_key,
        secret_key=config.alpaca_secret_key,
        paper=config.paper_trading,
    )

    # --- Risk manager ---
    risk_manager = RiskManager(config, broker)

    logger.info("Consuming from signals:generated, publishing to trades:executed")

    # Graceful shutdown on SIGTERM/SIGINT
    shutdown_event = asyncio.Event()
    loop = asyncio.get_running_loop()
    for sig in (signal.SIGTERM, signal.SIGINT):
        loop.add_signal_handler(sig, shutdown_event.set)

    # --- Consume loop ---
    try:
        async for _msg_id, data in consumer.consume():
            if shutdown_event.is_set():
                break
            try:
                signal_msg = TradeSignal.model_validate(data)
                await process_signal(signal_msg, risk_manager, broker, publisher, counters)
            except Exception:
                logger.exception("Error processing signal: %s", data)
    finally:
        await redis.aclose()
        logger.info("Trade executor stopped gracefully")


def main() -> None:
    """CLI entry point."""
    asyncio.run(run())


if __name__ == "__main__":
    main()