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The-Ouroboros/src/main.py
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feat: implement daily trading mode with batch decisions (issue #57)
Add API-efficient daily trading mode for Gemini Free tier compatibility:

## Features

- **Batch Decisions**: GeminiClient.decide_batch() analyzes multiple stocks
  in a single API call using compressed JSON format
- **Daily Trading Mode**: run_daily_session() executes N sessions per day
  at configurable intervals (default: 4 sessions, 6 hours apart)
- **Mode Selection**: TRADE_MODE env var switches between daily (batch)
  and realtime (per-stock) modes
- **Requirements Log**: docs/requirements-log.md tracks user feedback
  chronologically for project evolution

## Configuration

- TRADE_MODE: "daily" (default) | "realtime"
- DAILY_SESSIONS: 1-10 (default: 4)
- SESSION_INTERVAL_HOURS: 1-24 (default: 6)

## API Efficiency

- 2 markets × 4 sessions = 8 API calls/day (within Free tier 20 calls)
- 3 markets × 4 sessions = 12 API calls/day (within Free tier 20 calls)

## Testing

- 9 new batch decision tests (all passing)
- All existing tests maintained (298 passed)

## Documentation

- docs/architecture.md: Trading Modes section with daily vs realtime
- CLAUDE.md: Requirements Management section
- docs/requirements-log.md: Initial entries for API efficiency needs

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-02-05 09:28:10 +09:00

857 lines
33 KiB
Python

"""The Ouroboros — main trading loop.
Orchestrates the broker, brain, and risk manager into a continuous
trading cycle with configurable intervals.
"""
from __future__ import annotations
import argparse
import asyncio
import logging
import signal
import sys
from datetime import UTC, datetime
from typing import Any
from src.analysis.scanner import MarketScanner
from src.analysis.volatility import VolatilityAnalyzer
from src.brain.gemini_client import GeminiClient
from src.broker.kis_api import KISBroker
from src.broker.overseas import OverseasBroker
from src.config import Settings
from src.context.layer import ContextLayer
from src.context.store import ContextStore
from src.core.criticality import CriticalityAssessor
from src.core.priority_queue import PriorityTaskQueue
from src.core.risk_manager import CircuitBreakerTripped, FatFingerRejected, RiskManager
from src.db import init_db, log_trade
from src.logging.decision_logger import DecisionLogger
from src.logging_config import setup_logging
from src.markets.schedule import MarketInfo, get_next_market_open, get_open_markets
from src.notifications.telegram_client import TelegramClient
logger = logging.getLogger(__name__)
def safe_float(value: str | float | None, default: float = 0.0) -> float:
"""Convert to float, handling empty strings and None.
Args:
value: Value to convert (string, float, or None)
default: Default value if conversion fails
Returns:
Converted float or default value
Examples:
>>> safe_float("123.45")
123.45
>>> safe_float("")
0.0
>>> safe_float(None)
0.0
>>> safe_float("invalid", 99.0)
99.0
"""
if value is None or value == "":
return default
try:
return float(value)
except (ValueError, TypeError):
return default
# Target stock codes to monitor per market
WATCHLISTS = {
"KR": ["005930", "000660", "035420"], # Samsung, SK Hynix, NAVER
"US_NASDAQ": ["AAPL", "MSFT", "GOOGL"], # Example US stocks
"US_NYSE": ["JPM", "BAC"], # Example NYSE stocks
"JP": ["7203", "6758"], # Toyota, Sony
}
TRADE_INTERVAL_SECONDS = 60
SCAN_INTERVAL_SECONDS = 60 # Scan markets every 60 seconds
MAX_CONNECTION_RETRIES = 3
# Daily trading mode constants (for Free tier API efficiency)
DAILY_TRADE_SESSIONS = 4 # Number of trading sessions per day
TRADE_SESSION_INTERVAL_HOURS = 6 # Hours between sessions
# Full stock universe per market (for scanning)
# In production, this would be loaded from a database or API
STOCK_UNIVERSE = {
"KR": ["005930", "000660", "035420", "051910", "005380", "005490"],
"US_NASDAQ": ["AAPL", "MSFT", "GOOGL", "AMZN", "NVDA", "TSLA"],
"US_NYSE": ["JPM", "BAC", "XOM", "JNJ", "V"],
"JP": ["7203", "6758", "9984", "6861"],
}
async def trading_cycle(
broker: KISBroker,
overseas_broker: OverseasBroker,
brain: GeminiClient,
risk: RiskManager,
db_conn: Any,
decision_logger: DecisionLogger,
context_store: ContextStore,
criticality_assessor: CriticalityAssessor,
telegram: TelegramClient,
market: MarketInfo,
stock_code: str,
) -> None:
"""Execute one trading cycle for a single stock."""
cycle_start_time = asyncio.get_event_loop().time()
# 1. Fetch market data
if market.is_domestic:
orderbook = await broker.get_orderbook(stock_code)
balance_data = await broker.get_balance()
output2 = balance_data.get("output2", [{}])
total_eval = safe_float(output2[0].get("tot_evlu_amt", "0")) if output2 else 0
total_cash = safe_float(
balance_data.get("output2", [{}])[0].get("dnca_tot_amt", "0")
if output2
else "0"
)
purchase_total = safe_float(output2[0].get("pchs_amt_smtl_amt", "0")) if output2 else 0
current_price = safe_float(orderbook.get("output1", {}).get("stck_prpr", "0"))
foreigner_net = safe_float(orderbook.get("output1", {}).get("frgn_ntby_qty", "0"))
else:
# Overseas market
price_data = await overseas_broker.get_overseas_price(
market.exchange_code, stock_code
)
balance_data = await overseas_broker.get_overseas_balance(market.exchange_code)
output2 = balance_data.get("output2", [{}])
# Handle both list and dict response formats
if isinstance(output2, list) and output2:
balance_info = output2[0]
elif isinstance(output2, dict):
balance_info = output2
else:
balance_info = {}
total_eval = safe_float(balance_info.get("frcr_evlu_tota", "0") or "0")
total_cash = safe_float(balance_info.get("frcr_dncl_amt_2", "0") or "0")
purchase_total = safe_float(balance_info.get("frcr_buy_amt_smtl", "0") or "0")
current_price = safe_float(price_data.get("output", {}).get("last", "0"))
foreigner_net = 0.0 # Not available for overseas
# Calculate daily P&L %
pnl_pct = (
((total_eval - purchase_total) / purchase_total * 100)
if purchase_total > 0
else 0.0
)
market_data = {
"stock_code": stock_code,
"market_name": market.name,
"current_price": current_price,
"foreigner_net": foreigner_net,
}
# 1.5. Get volatility metrics from context store (L7_REALTIME)
latest_timeframe = context_store.get_latest_timeframe(ContextLayer.L7_REALTIME)
volatility_score = 50.0 # Default normal volatility
volume_surge = 1.0
price_change_1m = 0.0
if latest_timeframe:
volatility_data = context_store.get_context(
ContextLayer.L7_REALTIME,
latest_timeframe,
f"volatility_{stock_code}",
)
if volatility_data:
volatility_score = volatility_data.get("momentum_score", 50.0)
volume_surge = volatility_data.get("volume_surge", 1.0)
price_change_1m = volatility_data.get("price_change_1m", 0.0)
# 1.6. Assess criticality based on market conditions
criticality = criticality_assessor.assess_market_conditions(
pnl_pct=pnl_pct,
volatility_score=volatility_score,
volume_surge=volume_surge,
price_change_1m=price_change_1m,
is_market_open=True,
)
logger.info(
"Criticality for %s (%s): %s (pnl=%.2f%%, volatility=%.1f, volume_surge=%.1fx)",
stock_code,
market.name,
criticality.value,
pnl_pct,
volatility_score,
volume_surge,
)
# 2. Ask the brain for a decision
decision = await brain.decide(market_data)
logger.info(
"Decision for %s (%s): %s (confidence=%d)",
stock_code,
market.name,
decision.action,
decision.confidence,
)
# 2.5. Log decision with context snapshot
context_snapshot = {
"L1": {
"current_price": current_price,
"foreigner_net": foreigner_net,
},
"L2": {
"total_eval": total_eval,
"total_cash": total_cash,
"purchase_total": purchase_total,
"pnl_pct": pnl_pct,
},
# L3-L7 will be populated when context tree is implemented
}
input_data = {
"current_price": current_price,
"foreigner_net": foreigner_net,
"total_eval": total_eval,
"total_cash": total_cash,
"pnl_pct": pnl_pct,
}
decision_logger.log_decision(
stock_code=stock_code,
market=market.code,
exchange_code=market.exchange_code,
action=decision.action,
confidence=decision.confidence,
rationale=decision.rationale,
context_snapshot=context_snapshot,
input_data=input_data,
)
# 3. Execute if actionable
if decision.action in ("BUY", "SELL"):
# Determine order size (simplified: 1 lot)
quantity = 1
order_amount = current_price * quantity
# 4. Risk check BEFORE order
try:
risk.validate_order(
current_pnl_pct=pnl_pct,
order_amount=order_amount,
total_cash=total_cash,
)
except FatFingerRejected as exc:
try:
await telegram.notify_fat_finger(
stock_code=stock_code,
order_amount=exc.order_amount,
total_cash=exc.total_cash,
max_pct=exc.max_pct,
)
except Exception as notify_exc:
logger.warning("Fat finger notification failed: %s", notify_exc)
raise # Re-raise to prevent trade
# 5. Send order
if market.is_domestic:
result = await broker.send_order(
stock_code=stock_code,
order_type=decision.action,
quantity=quantity,
price=0, # market order
)
else:
result = await overseas_broker.send_overseas_order(
exchange_code=market.exchange_code,
stock_code=stock_code,
order_type=decision.action,
quantity=quantity,
price=0.0, # market order
)
logger.info("Order result: %s", result.get("msg1", "OK"))
# 5.5. Notify trade execution
try:
await telegram.notify_trade_execution(
stock_code=stock_code,
market=market.name,
action=decision.action,
quantity=quantity,
price=current_price,
confidence=decision.confidence,
)
except Exception as exc:
logger.warning("Telegram notification failed: %s", exc)
# 6. Log trade
log_trade(
conn=db_conn,
stock_code=stock_code,
action=decision.action,
confidence=decision.confidence,
rationale=decision.rationale,
market=market.code,
exchange_code=market.exchange_code,
)
# 7. Latency monitoring
cycle_end_time = asyncio.get_event_loop().time()
cycle_latency = cycle_end_time - cycle_start_time
timeout = criticality_assessor.get_timeout(criticality)
if timeout and cycle_latency > timeout:
logger.warning(
"Trading cycle exceeded timeout for %s (criticality=%s, latency=%.2fs, timeout=%.2fs)",
stock_code,
criticality.value,
cycle_latency,
timeout,
)
else:
logger.debug(
"Trading cycle completed within timeout for %s (criticality=%s, latency=%.2fs)",
stock_code,
criticality.value,
cycle_latency,
)
async def run_daily_session(
broker: KISBroker,
overseas_broker: OverseasBroker,
brain: GeminiClient,
risk: RiskManager,
db_conn: Any,
decision_logger: DecisionLogger,
context_store: ContextStore,
criticality_assessor: CriticalityAssessor,
telegram: TelegramClient,
settings: Settings,
) -> None:
"""Execute one daily trading session.
Designed for API efficiency with Gemini Free tier:
- Batch decision making (1 API call per market)
- Runs N times per day at fixed intervals
- Minimizes API usage while maintaining trading capability
"""
# Get currently open markets
open_markets = get_open_markets(settings.enabled_market_list)
if not open_markets:
logger.info("No markets open for this session")
return
logger.info("Starting daily trading session for %d markets", len(open_markets))
# Process each open market
for market in open_markets:
# Get watchlist for this market
watchlist = WATCHLISTS.get(market.code, [])
if not watchlist:
logger.debug("No watchlist for market %s", market.code)
continue
logger.info("Processing market: %s (%d stocks)", market.name, len(watchlist))
# Collect market data for all stocks in the watchlist
stocks_data = []
for stock_code in watchlist:
try:
if market.is_domestic:
orderbook = await broker.get_orderbook(stock_code)
current_price = safe_float(orderbook.get("output1", {}).get("stck_prpr", "0"))
foreigner_net = safe_float(
orderbook.get("output1", {}).get("frgn_ntby_qty", "0")
)
else:
price_data = await overseas_broker.get_overseas_price(
market.exchange_code, stock_code
)
current_price = safe_float(price_data.get("output", {}).get("last", "0"))
foreigner_net = 0.0
stocks_data.append(
{
"stock_code": stock_code,
"market_name": market.name,
"current_price": current_price,
"foreigner_net": foreigner_net,
}
)
except Exception as exc:
logger.error("Failed to fetch data for %s: %s", stock_code, exc)
continue
if not stocks_data:
logger.warning("No valid stock data for market %s", market.code)
continue
# Get batch decisions (1 API call for all stocks in this market)
logger.info("Requesting batch decision for %d stocks in %s", len(stocks_data), market.name)
decisions = await brain.decide_batch(stocks_data)
# Get balance data once for the market
if market.is_domestic:
balance_data = await broker.get_balance()
output2 = balance_data.get("output2", [{}])
total_eval = safe_float(output2[0].get("tot_evlu_amt", "0")) if output2 else 0
total_cash = safe_float(output2[0].get("dnca_tot_amt", "0")) if output2 else 0
purchase_total = safe_float(output2[0].get("pchs_amt_smtl_amt", "0")) if output2 else 0
else:
balance_data = await overseas_broker.get_overseas_balance(market.exchange_code)
output2 = balance_data.get("output2", [{}])
if isinstance(output2, list) and output2:
balance_info = output2[0]
elif isinstance(output2, dict):
balance_info = output2
else:
balance_info = {}
total_eval = safe_float(balance_info.get("frcr_evlu_tota", "0") or "0")
total_cash = safe_float(balance_info.get("frcr_dncl_amt_2", "0") or "0")
purchase_total = safe_float(balance_info.get("frcr_buy_amt_smtl", "0") or "0")
# Calculate daily P&L %
pnl_pct = (
((total_eval - purchase_total) / purchase_total * 100) if purchase_total > 0 else 0.0
)
# Execute decisions for each stock
for stock_data in stocks_data:
stock_code = stock_data["stock_code"]
decision = decisions.get(stock_code)
if not decision:
logger.warning("No decision for %s — skipping", stock_code)
continue
logger.info(
"Decision for %s (%s): %s (confidence=%d)",
stock_code,
market.name,
decision.action,
decision.confidence,
)
# Log decision
context_snapshot = {
"L1": {
"current_price": stock_data["current_price"],
"foreigner_net": stock_data["foreigner_net"],
},
"L2": {
"total_eval": total_eval,
"total_cash": total_cash,
"purchase_total": purchase_total,
"pnl_pct": pnl_pct,
},
}
input_data = {
"current_price": stock_data["current_price"],
"foreigner_net": stock_data["foreigner_net"],
"total_eval": total_eval,
"total_cash": total_cash,
"pnl_pct": pnl_pct,
}
decision_logger.log_decision(
stock_code=stock_code,
market=market.code,
exchange_code=market.exchange_code,
action=decision.action,
confidence=decision.confidence,
rationale=decision.rationale,
context_snapshot=context_snapshot,
input_data=input_data,
)
# Execute if actionable
if decision.action in ("BUY", "SELL"):
quantity = 1
order_amount = stock_data["current_price"] * quantity
# Risk check
try:
risk.validate_order(
current_pnl_pct=pnl_pct,
order_amount=order_amount,
total_cash=total_cash,
)
except FatFingerRejected as exc:
try:
await telegram.notify_fat_finger(
stock_code=stock_code,
order_amount=exc.order_amount,
total_cash=exc.total_cash,
max_pct=exc.max_pct,
)
except Exception as notify_exc:
logger.warning("Fat finger notification failed: %s", notify_exc)
continue # Skip this order
except CircuitBreakerTripped as exc:
logger.critical("Circuit breaker tripped — stopping session")
try:
await telegram.notify_circuit_breaker(
pnl_pct=exc.pnl_pct,
threshold=exc.threshold,
)
except Exception as notify_exc:
logger.warning("Circuit breaker notification failed: %s", notify_exc)
raise
# Send order
try:
if market.is_domestic:
result = await broker.send_order(
stock_code=stock_code,
order_type=decision.action,
quantity=quantity,
price=0, # market order
)
else:
result = await overseas_broker.send_overseas_order(
exchange_code=market.exchange_code,
stock_code=stock_code,
order_type=decision.action,
quantity=quantity,
price=0.0, # market order
)
logger.info("Order result: %s", result.get("msg1", "OK"))
# Notify trade execution
try:
await telegram.notify_trade_execution(
stock_code=stock_code,
market=market.name,
action=decision.action,
quantity=quantity,
price=stock_data["current_price"],
confidence=decision.confidence,
)
except Exception as exc:
logger.warning("Telegram notification failed: %s", exc)
except Exception as exc:
logger.error("Order execution failed for %s: %s", stock_code, exc)
continue
# Log trade
log_trade(
conn=db_conn,
stock_code=stock_code,
action=decision.action,
confidence=decision.confidence,
rationale=decision.rationale,
market=market.code,
exchange_code=market.exchange_code,
)
logger.info("Daily trading session completed")
async def run(settings: Settings) -> None:
"""Main async loop — iterate over open markets on a timer."""
broker = KISBroker(settings)
overseas_broker = OverseasBroker(broker)
brain = GeminiClient(settings)
risk = RiskManager(settings)
db_conn = init_db(settings.DB_PATH)
decision_logger = DecisionLogger(db_conn)
context_store = ContextStore(db_conn)
# Initialize Telegram notifications
telegram = TelegramClient(
bot_token=settings.TELEGRAM_BOT_TOKEN,
chat_id=settings.TELEGRAM_CHAT_ID,
enabled=settings.TELEGRAM_ENABLED,
)
# Initialize volatility hunter
volatility_analyzer = VolatilityAnalyzer(min_volume_surge=2.0, min_price_change=1.0)
market_scanner = MarketScanner(
broker=broker,
overseas_broker=overseas_broker,
volatility_analyzer=volatility_analyzer,
context_store=context_store,
top_n=5,
max_concurrent_scans=1, # Fully serialized to avoid EGW00201
)
# Initialize latency control system
criticality_assessor = CriticalityAssessor(
critical_pnl_threshold=-2.5, # Near circuit breaker at -3.0%
critical_price_change_threshold=5.0, # 5% in 1 minute
critical_volume_surge_threshold=10.0, # 10x average
high_volatility_threshold=70.0,
low_volatility_threshold=30.0,
)
priority_queue = PriorityTaskQueue(max_size=1000)
# Track last scan time for each market
last_scan_time: dict[str, float] = {}
# Track market open/close state for notifications
_market_states: dict[str, bool] = {} # market_code -> is_open
shutdown = asyncio.Event()
def _signal_handler() -> None:
logger.info("Shutdown signal received")
shutdown.set()
loop = asyncio.get_running_loop()
for sig in (signal.SIGINT, signal.SIGTERM):
loop.add_signal_handler(sig, _signal_handler)
logger.info("The Ouroboros is alive. Mode: %s, Trading: %s", settings.MODE, settings.TRADE_MODE)
logger.info("Enabled markets: %s", settings.enabled_market_list)
# Notify system startup
try:
await telegram.notify_system_start(settings.MODE, settings.enabled_market_list)
except Exception as exc:
logger.warning("System startup notification failed: %s", exc)
try:
# Branch based on trading mode
if settings.TRADE_MODE == "daily":
# Daily trading mode: batch decisions at fixed intervals
logger.info(
"Daily trading mode: %d sessions every %d hours",
settings.DAILY_SESSIONS,
settings.SESSION_INTERVAL_HOURS,
)
session_interval = settings.SESSION_INTERVAL_HOURS * 3600 # Convert to seconds
while not shutdown.is_set():
try:
await run_daily_session(
broker,
overseas_broker,
brain,
risk,
db_conn,
decision_logger,
context_store,
criticality_assessor,
telegram,
settings,
)
except CircuitBreakerTripped:
logger.critical("Circuit breaker tripped — shutting down")
shutdown.set()
break
except Exception as exc:
logger.exception("Daily session error: %s", exc)
# Wait for next session or shutdown
logger.info("Next session in %.1f hours", session_interval / 3600)
try:
await asyncio.wait_for(shutdown.wait(), timeout=session_interval)
except TimeoutError:
pass # Normal — time for next session
else:
# Realtime trading mode: original per-stock loop
logger.info("Realtime trading mode: 60s interval per stock")
while not shutdown.is_set():
# Get currently open markets
open_markets = get_open_markets(settings.enabled_market_list)
if not open_markets:
# Notify market close for any markets that were open
for market_code, is_open in list(_market_states.items()):
if is_open:
try:
from src.markets.schedule import MARKETS
market_info = MARKETS.get(market_code)
if market_info:
await telegram.notify_market_close(market_info.name, 0.0)
except Exception as exc:
logger.warning("Market close notification failed: %s", exc)
_market_states[market_code] = False
# No markets open — wait until next market opens
try:
next_market, next_open_time = get_next_market_open(
settings.enabled_market_list
)
now = datetime.now(UTC)
wait_seconds = (next_open_time - now).total_seconds()
logger.info(
"No markets open. Next market: %s, opens in %.1f hours",
next_market.name,
wait_seconds / 3600,
)
await asyncio.wait_for(shutdown.wait(), timeout=wait_seconds)
except TimeoutError:
continue # Market should be open now
except ValueError as exc:
logger.error("Failed to find next market open: %s", exc)
await asyncio.sleep(TRADE_INTERVAL_SECONDS)
continue
# Process each open market
for market in open_markets:
if shutdown.is_set():
break
# Notify market open if it just opened
if not _market_states.get(market.code, False):
try:
await telegram.notify_market_open(market.name)
except Exception as exc:
logger.warning("Market open notification failed: %s", exc)
_market_states[market.code] = True
# Volatility Hunter: Scan market periodically to update watchlist
now_timestamp = asyncio.get_event_loop().time()
last_scan = last_scan_time.get(market.code, 0.0)
if now_timestamp - last_scan >= SCAN_INTERVAL_SECONDS:
try:
# Scan all stocks in the universe
stock_universe = STOCK_UNIVERSE.get(market.code, [])
if stock_universe:
logger.info("Volatility Hunter: Scanning %s market", market.name)
scan_result = await market_scanner.scan_market(
market, stock_universe
)
# Update watchlist with top movers
current_watchlist = WATCHLISTS.get(market.code, [])
updated_watchlist = market_scanner.get_updated_watchlist(
current_watchlist,
scan_result,
max_replacements=2,
)
WATCHLISTS[market.code] = updated_watchlist
logger.info(
"Volatility Hunter: Watchlist updated for %s (%d top movers, %d breakouts)",
market.name,
len(scan_result.top_movers),
len(scan_result.breakouts),
)
last_scan_time[market.code] = now_timestamp
except Exception as exc:
logger.error("Volatility Hunter scan failed for %s: %s", market.name, exc)
# Get watchlist for this market
watchlist = WATCHLISTS.get(market.code, [])
if not watchlist:
logger.debug("No watchlist for market %s", market.code)
continue
logger.info("Processing market: %s (%d stocks)", market.name, len(watchlist))
# Process each stock in the watchlist
for stock_code in watchlist:
if shutdown.is_set():
break
# Retry logic for connection errors
for attempt in range(1, MAX_CONNECTION_RETRIES + 1):
try:
await trading_cycle(
broker,
overseas_broker,
brain,
risk,
db_conn,
decision_logger,
context_store,
criticality_assessor,
telegram,
market,
stock_code,
)
break # Success — exit retry loop
except CircuitBreakerTripped as exc:
logger.critical("Circuit breaker tripped — shutting down")
try:
await telegram.notify_circuit_breaker(
pnl_pct=exc.pnl_pct,
threshold=exc.threshold,
)
except Exception as notify_exc:
logger.warning(
"Circuit breaker notification failed: %s", notify_exc
)
raise
except ConnectionError as exc:
if attempt < MAX_CONNECTION_RETRIES:
logger.warning(
"Connection error for %s (attempt %d/%d): %s",
stock_code,
attempt,
MAX_CONNECTION_RETRIES,
exc,
)
await asyncio.sleep(2**attempt) # Exponential backoff
else:
logger.error(
"Connection error for %s (all retries exhausted): %s",
stock_code,
exc,
)
break # Give up on this stock
except Exception as exc:
logger.exception("Unexpected error for %s: %s", stock_code, exc)
break # Don't retry on unexpected errors
# Log priority queue metrics periodically
metrics = await priority_queue.get_metrics()
if metrics.total_enqueued > 0:
logger.info(
"Priority queue metrics: enqueued=%d, dequeued=%d, size=%d, timeouts=%d, errors=%d",
metrics.total_enqueued,
metrics.total_dequeued,
metrics.current_size,
metrics.total_timeouts,
metrics.total_errors,
)
# Wait for next cycle or shutdown
try:
await asyncio.wait_for(shutdown.wait(), timeout=TRADE_INTERVAL_SECONDS)
except TimeoutError:
pass # Normal — timeout means it's time for next cycle
finally:
# Clean up resources
await broker.close()
await telegram.close()
db_conn.close()
logger.info("The Ouroboros rests.")
def main() -> None:
parser = argparse.ArgumentParser(description="The Ouroboros Trading Agent")
parser.add_argument(
"--mode",
choices=["paper", "live"],
default="paper",
help="Trading mode (default: paper)",
)
args = parser.parse_args()
setup_logging()
settings = Settings(MODE=args.mode) # type: ignore[call-arg]
asyncio.run(run(settings))
if __name__ == "__main__":
main()