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fix: resolve 13 important issues from code review

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I1: Add graceful shutdown (SIGTERM/SIGINT) to all 5 background services
I2: Fix Dockerfile healthcheck to use curl on /metrics endpoint
I3: Fix StreamConsumer.ensure_group() to only catch BUSYGROUP errors
I4: Fix SimulatedBroker to reject orders with insufficient cash/shares
I5: Move ORM attribute access inside DB session context in trades routes
I6: Add Redis-based rate limiting (10 req/min/IP) on all auth endpoints
I8: Prevent backtest background task garbage collection
I9: Use Numeric(16,6) instead of Float for financial columns in migration
I10: Add index on trades.created_at for time-range queries
I11: Bind infrastructure ports to 127.0.0.1 in docker-compose
I12: Add migrations init service; all app services depend on it
I13: Fix user enumeration in login_begin (return options for non-existent users)
This commit is contained in:
Viktor Barzin 2026-02-22 17:58:01 +00:00
parent 2a56727267
commit 5a6b20c8f1
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GPG key ID: 0EB088298288D958
13 changed files with 355 additions and 188 deletions
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43
services/learning_engine/main.py
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@ -10,6 +10,7 @@ from __future__ import annotations
import asyncio
import json
import logging
import signal
from datetime import datetime, timezone
from uuid import UUID
@ -275,24 +276,36 @@ async def run(config: LearningEngineConfig | None = None) -> None:
logger.info("Consuming from 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 ---
async for _msg_id, data in consumer.consume():
try:
trade = TradeExecution.model_validate(data)
try:
async for _msg_id, data in consumer.consume():
if shutdown_event.is_set():
break
try:
trade = TradeExecution.model_validate(data)
if trade.status.value != "FILLED":
logger.debug("Skipping non-filled trade: %s", trade.status.value)
continue
if trade.status.value != "FILLED":
logger.debug("Skipping non-filled trade: %s", trade.status.value)
continue
adjustments = await process_trade(trade, redis, evaluator, adjuster, counters)
if adjustments:
logger.info(
"Made %d weight adjustment(s) for %s",
len(adjustments),
trade.ticker,
)
except Exception:
logger.exception("Error processing trade execution: %s", data)
adjustments = await process_trade(trade, redis, evaluator, adjuster, counters)
if adjustments:
logger.info(
"Made %d weight adjustment(s) for %s",
len(adjustments),
trade.ticker,
)
except Exception:
logger.exception("Error processing trade execution: %s", data)
finally:
await redis.aclose()
logger.info("Learning engine stopped gracefully")
def main() -> None: