perf: optimize system concurrency, I/O stability and fix WebSocket disconnects
This commit is contained in:
@@ -517,111 +517,129 @@ async def handle_get_stock_similar_days(gateway: Any, websocket: Any, data: dict
|
||||
|
||||
|
||||
async def handle_get_stock_technical_indicators(gateway: Any, websocket: Any, data: dict[str, Any]) -> None:
|
||||
ticker = normalize_symbol(data.get("ticker", ""))
|
||||
if not ticker:
|
||||
await websocket.send(json.dumps({
|
||||
"type": "stock_technical_indicators_loaded",
|
||||
"ticker": ticker,
|
||||
"indicators": None,
|
||||
"error": "ticker is required",
|
||||
}, ensure_ascii=False))
|
||||
return
|
||||
ticker = normalize_symbol(data.get("ticker", ""))
|
||||
if not ticker:
|
||||
await websocket.send(json.dumps({
|
||||
"type": "stock_technical_indicators_loaded",
|
||||
"ticker": ticker,
|
||||
"indicators": None,
|
||||
"error": "ticker is required",
|
||||
}, ensure_ascii=False))
|
||||
return
|
||||
|
||||
try:
|
||||
end_date = datetime.now()
|
||||
start_date = end_date - timedelta(days=250)
|
||||
try:
|
||||
end_date = datetime.now()
|
||||
# Reduced from 250 to 150 days to lower CPU/memory pressure while still supporting MA200 (approx 140 trading days)
|
||||
start_date = end_date - timedelta(days=150)
|
||||
|
||||
prices = None
|
||||
response = await gateway._call_trading_service(
|
||||
"get_prices",
|
||||
lambda client: client.get_prices(
|
||||
ticker=ticker,
|
||||
start_date=start_date.strftime("%Y-%m-%d"),
|
||||
end_date=end_date.strftime("%Y-%m-%d"),
|
||||
),
|
||||
)
|
||||
if response is not None:
|
||||
prices = response.prices
|
||||
prices = None
|
||||
response = await gateway._call_trading_service(
|
||||
"get_prices",
|
||||
lambda client: client.get_prices(
|
||||
ticker=ticker,
|
||||
start_date=start_date.strftime("%Y-%m-%d"),
|
||||
end_date=end_date.strftime("%Y-%m-%d"),
|
||||
),
|
||||
)
|
||||
if response is not None:
|
||||
prices = response.prices
|
||||
|
||||
if prices is None:
|
||||
payload = trading_domain.get_prices_payload(
|
||||
ticker=ticker,
|
||||
start_date=start_date.strftime("%Y-%m-%d"),
|
||||
end_date=end_date.strftime("%Y-%m-%d"),
|
||||
)
|
||||
prices = payload.get("prices") or []
|
||||
if prices is None:
|
||||
# Offload domain logic to thread
|
||||
payload = await asyncio.to_thread(
|
||||
trading_domain.get_prices_payload,
|
||||
ticker=ticker,
|
||||
start_date=start_date.strftime("%Y-%m-%d"),
|
||||
end_date=end_date.strftime("%Y-%m-%d"),
|
||||
)
|
||||
prices = payload.get("prices") or []
|
||||
|
||||
if not prices or len(prices) < 20:
|
||||
await websocket.send(json.dumps({
|
||||
"type": "stock_technical_indicators_loaded",
|
||||
"ticker": ticker,
|
||||
"indicators": None,
|
||||
"error": "Insufficient price data",
|
||||
}, ensure_ascii=False))
|
||||
return
|
||||
if not prices or len(prices) < 20:
|
||||
await websocket.send(json.dumps({
|
||||
"type": "stock_technical_indicators_loaded",
|
||||
"ticker": ticker,
|
||||
"indicators": None,
|
||||
"error": "Insufficient price data",
|
||||
}, ensure_ascii=False))
|
||||
return
|
||||
|
||||
df = prices_to_df(prices)
|
||||
signal = gateway._technical_analyzer.analyze(ticker, df)
|
||||
def _calc():
|
||||
df = prices_to_df(prices)
|
||||
signal = gateway._technical_analyzer.analyze(ticker, df)
|
||||
df_sorted = df.sort_values("time").reset_index(drop=True)
|
||||
df_sorted["returns"] = df_sorted["close"].pct_change()
|
||||
v10 = float(df_sorted["returns"].tail(10).std() * (252**0.5) * 100) if len(df_sorted) >= 10 else None
|
||||
v20 = float(df_sorted["returns"].tail(20).std() * (252**0.5) * 100) if len(df_sorted) >= 20 else None
|
||||
v60 = float(df_sorted["returns"].tail(60).std() * (252**0.5) * 100) if len(df_sorted) >= 60 else None
|
||||
|
||||
df_sorted = df.sort_values("time").reset_index(drop=True)
|
||||
df_sorted["returns"] = df_sorted["close"].pct_change()
|
||||
vol_10 = float(df_sorted["returns"].tail(10).std() * (252**0.5) * 100) if len(df_sorted) >= 10 else None
|
||||
vol_20 = float(df_sorted["returns"].tail(20).std() * (252**0.5) * 100) if len(df_sorted) >= 20 else None
|
||||
vol_60 = float(df_sorted["returns"].tail(60).std() * (252**0.5) * 100) if len(df_sorted) >= 60 else None
|
||||
ma_distance = {}
|
||||
for ma_key in ["ma5", "ma10", "ma20", "ma50", "ma200"]:
|
||||
ma_value = getattr(signal, ma_key, None)
|
||||
ma_distance[ma_key] = ((signal.current_price - ma_value) / ma_value) * 100 if ma_value and ma_value > 0 else None
|
||||
ma_dist = {}
|
||||
for ma_key in ["ma5", "ma10", "ma20", "ma50", "ma200"]:
|
||||
ma_val = getattr(signal, ma_key, None)
|
||||
ma_dist[ma_key] = ((signal.current_price - ma_val) / ma_val) * 100 if ma_val and ma_val > 0 else None
|
||||
|
||||
indicators = {
|
||||
"ticker": ticker,
|
||||
"current_price": signal.current_price,
|
||||
"ma": {
|
||||
"ma5": signal.ma5,
|
||||
"ma10": signal.ma10,
|
||||
"ma20": signal.ma20,
|
||||
"ma50": signal.ma50,
|
||||
"ma200": signal.ma200,
|
||||
"distance": ma_distance,
|
||||
},
|
||||
"rsi": {
|
||||
"rsi14": signal.rsi14,
|
||||
"status": "oversold" if signal.rsi14 < 30 else "overbought" if signal.rsi14 > 70 else "neutral",
|
||||
},
|
||||
"macd": {
|
||||
"macd": signal.macd,
|
||||
"signal": signal.macd_signal,
|
||||
"histogram": signal.macd - signal.macd_signal,
|
||||
},
|
||||
"bollinger": {
|
||||
"upper": signal.bollinger_upper,
|
||||
"mid": signal.bollinger_mid,
|
||||
"lower": signal.bollinger_lower,
|
||||
},
|
||||
"volatility": {
|
||||
"vol_10d": vol_10,
|
||||
"vol_20d": vol_20,
|
||||
"vol_60d": vol_60,
|
||||
"annualized": signal.annualized_volatility_pct,
|
||||
"risk_level": signal.risk_level,
|
||||
},
|
||||
"trend": signal.trend,
|
||||
"mean_reversion": signal.mean_reversion_signal,
|
||||
}
|
||||
return {
|
||||
"ticker": ticker,
|
||||
"current_price": signal.current_price,
|
||||
"ma": {
|
||||
"ma5": signal.ma5,
|
||||
"ma10": signal.ma10,
|
||||
"ma20": signal.ma20,
|
||||
"ma50": signal.ma50,
|
||||
"ma200": signal.ma200,
|
||||
"distance": ma_dist,
|
||||
},
|
||||
"rsi": {
|
||||
"rsi14": signal.rsi14,
|
||||
"status": "oversold" if signal.rsi14 < 30 else "overbought" if signal.rsi14 > 70 else "neutral",
|
||||
},
|
||||
"macd": {
|
||||
"macd": signal.macd,
|
||||
"signal": signal.macd_signal,
|
||||
"histogram": signal.macd - signal.macd_signal,
|
||||
},
|
||||
"bollinger": {
|
||||
"upper": signal.bollinger_upper,
|
||||
"mid": signal.bollinger_mid,
|
||||
"lower": signal.bollinger_lower,
|
||||
},
|
||||
"volatility": {
|
||||
"vol_10d": v10,
|
||||
"vol_20d": v20,
|
||||
"vol_60d": v60,
|
||||
"annualized": signal.annualized_volatility_pct,
|
||||
"risk_level": signal.risk_level,
|
||||
},
|
||||
"trend": signal.trend,
|
||||
"mean_reversion": signal.mean_reversion_signal,
|
||||
}
|
||||
|
||||
await websocket.send(json.dumps({
|
||||
"type": "stock_technical_indicators_loaded",
|
||||
"ticker": ticker,
|
||||
"indicators": indicators,
|
||||
}, ensure_ascii=False, default=str))
|
||||
except Exception as exc:
|
||||
logger.exception("Error getting technical indicators for %s", ticker)
|
||||
await websocket.send(json.dumps({
|
||||
"type": "stock_technical_indicators_loaded",
|
||||
"ticker": ticker,
|
||||
"indicators": None,
|
||||
"error": str(exc),
|
||||
}, ensure_ascii=False))
|
||||
# Use a semaphore to prevent too many concurrent CPU-intensive calculations
|
||||
# which can block the event loop heartbeats.
|
||||
if not hasattr(gateway, "_calc_sem"):
|
||||
gateway._calc_sem = asyncio.Semaphore(3)
|
||||
|
||||
async with gateway._calc_sem:
|
||||
indicators = await asyncio.to_thread(_calc)
|
||||
|
||||
# Also offload JSON serialization to thread to avoid blocking main loop
|
||||
msg = await asyncio.to_thread(json.dumps, {
|
||||
"type": "stock_technical_indicators_loaded",
|
||||
"ticker": ticker,
|
||||
"indicators": indicators,
|
||||
}, ensure_ascii=False, default=str)
|
||||
|
||||
if websocket.state.name == 'OPEN':
|
||||
await websocket.send(msg)
|
||||
else:
|
||||
logger.warning("Websocket closed for %s, skipping indicator send", ticker)
|
||||
except Exception as exc:
|
||||
logger.exception("Error getting technical indicators for %s", ticker)
|
||||
await websocket.send(json.dumps({
|
||||
"type": "stock_technical_indicators_loaded",
|
||||
"ticker": ticker,
|
||||
"indicators": None,
|
||||
"error": str(exc),
|
||||
}, ensure_ascii=False))
|
||||
|
||||
|
||||
async def handle_run_stock_enrich(gateway: Any, websocket: Any, data: dict[str, Any]) -> None:
|
||||
|
||||
Reference in New Issue
Block a user