From 35d7ac5e1b22dddb00d5e534672f01962ea18024 Mon Sep 17 00:00:00 2001 From: TIANHE Date: Sat, 24 Jan 2026 23:26:26 +0800 Subject: [PATCH 1/4] Improve global market dashboard UX and settings - Add global market dashboard APIs/assets and improve data robustness (incl. crypto heatmap by market cap) - Enhance global market UI (map+heatmap layout, loading behavior, formatting, theme tweaks) - Fix Settings LLM Provider select to render label/value options correctly - Rename Indicator Community to Official Community and move it to the bottom - Add search fallback when Google quota is exhausted --- backend_api_python/app/routes/__init__.py | 2 + .../app/routes/global_market.py | 1624 ++++++++++ backend_api_python/app/routes/market.py | 2 +- backend_api_python/app/services/llm.py | 5 +- backend_api_python/app/services/search.py | 189 +- .../migrations/add_notification_settings.sql | 16 - quantdinger_vue/public/maps/world-atlas.json | 1 + quantdinger_vue/public/maps/world.json | 1 + quantdinger_vue/src/api/global-market.js | 79 + quantdinger_vue/src/config/router.config.js | 21 +- quantdinger_vue/src/locales/lang/en-US.js | 64 +- quantdinger_vue/src/locales/lang/zh-CN.js | 64 +- .../src/views/global-market/index.vue | 2630 +++++++++++++++++ quantdinger_vue/src/views/portfolio/index.vue | 98 +- quantdinger_vue/src/views/settings/index.vue | 23 +- 15 files changed, 4744 insertions(+), 75 deletions(-) create mode 100644 backend_api_python/app/routes/global_market.py delete mode 100644 backend_api_python/migrations/add_notification_settings.sql create mode 100644 quantdinger_vue/public/maps/world-atlas.json create mode 100644 quantdinger_vue/public/maps/world.json create mode 100644 quantdinger_vue/src/api/global-market.js create mode 100644 quantdinger_vue/src/views/global-market/index.vue diff --git a/backend_api_python/app/routes/__init__.py b/backend_api_python/app/routes/__init__.py index 1c8f15d..a6c31c1 100644 --- a/backend_api_python/app/routes/__init__.py +++ b/backend_api_python/app/routes/__init__.py @@ -22,6 +22,7 @@ def register_routes(app: Flask): from app.routes.ibkr import ibkr_bp from app.routes.mt5 import mt5_bp from app.routes.user import user_bp + from app.routes.global_market import global_market_bp app.register_blueprint(health_bp) app.register_blueprint(auth_bp, url_prefix='/api/auth') # Auth routes @@ -39,3 +40,4 @@ def register_routes(app: Flask): app.register_blueprint(portfolio_bp, url_prefix='/api/portfolio') app.register_blueprint(ibkr_bp, url_prefix='/api/ibkr') app.register_blueprint(mt5_bp, url_prefix='/api/mt5') + app.register_blueprint(global_market_bp, url_prefix='/api/global-market') \ No newline at end of file diff --git a/backend_api_python/app/routes/global_market.py b/backend_api_python/app/routes/global_market.py new file mode 100644 index 0000000..7441c53 --- /dev/null +++ b/backend_api_python/app/routes/global_market.py @@ -0,0 +1,1624 @@ +""" +Global Market Dashboard APIs. + +Provides aggregated global market data including: +- Major indices (US, China, Hong Kong, Europe, Japan) +- Forex pairs +- Crypto prices +- Market heatmap data (crypto, stocks, forex) +- Economic calendar with impact indicators +- Fear & Greed Index / VIX +- Financial news (Chinese & English) + +Endpoints: +- GET /api/global-market/overview - Global market overview +- GET /api/global-market/heatmap - Market heatmap data +- GET /api/global-market/news - Financial news (with lang param) +- GET /api/global-market/calendar - Economic calendar +- GET /api/global-market/sentiment - Fear & Greed / VIX +- GET /api/global-market/opportunities - Trading opportunities scanner +""" + +from __future__ import annotations + +import time +import requests +from datetime import datetime, timedelta +from typing import Any, Dict, List, Optional +from concurrent.futures import ThreadPoolExecutor, as_completed + +from flask import Blueprint, jsonify, request, g + +from app.utils.logger import get_logger +from app.utils.auth import login_required +from app.utils.config_loader import load_addon_config + +logger = get_logger(__name__) + +global_market_bp = Blueprint("global_market", __name__) + +# Cache for market data (simple in-memory cache) +_cache: Dict[str, Dict[str, Any]] = {} +_cache_ttl = 30 # 30 seconds cache + + +def _get_cached(key: str, ttl: int = None) -> Optional[Any]: + """Get cached data if not expired.""" + if key in _cache: + entry = _cache[key] + cache_ttl = ttl or entry.get("ttl", _cache_ttl) + if time.time() - entry.get("ts", 0) < cache_ttl: + return entry.get("data") + return None + + +def _set_cached(key: str, data: Any, ttl: int = None): + """Set cache entry.""" + _cache[key] = { + "ts": time.time(), + "data": data, + "ttl": ttl or _cache_ttl + } + + +def _safe_float(v: Any, default: float = 0.0) -> float: + try: + return float(v) + except Exception: + return default + + +# ============ Data Fetchers ============ + +def _fetch_crypto_prices_ccxt() -> List[Dict[str, Any]]: + """Fetch crypto prices using CCXT (system's existing data source).""" + try: + from app.data_sources.crypto import CryptoDataSource + + crypto_source = CryptoDataSource() + + # Top crypto symbols to fetch + symbols = [ + "BTC/USDT", "ETH/USDT", "BNB/USDT", "SOL/USDT", "XRP/USDT", + "ADA/USDT", "DOGE/USDT", "AVAX/USDT", "DOT/USDT", "MATIC/USDT", + "LINK/USDT", "LTC/USDT", "UNI/USDT", "ATOM/USDT", "XLM/USDT" + ] + + result = [] + for symbol in symbols: + try: + ticker = crypto_source.get_ticker(symbol) + if ticker: + base = symbol.split("/")[0] + result.append({ + "symbol": base, + "name": base, + "price": _safe_float(ticker.get("last") or ticker.get("close")), + "change_24h": _safe_float(ticker.get("percentage", 0)), + "change_7d": 0, # CCXT doesn't provide 7d change + "market_cap": 0, + "volume_24h": _safe_float(ticker.get("quoteVolume", 0)), + "image": "", + "category": "crypto" + }) + except Exception as e: + logger.debug(f"Failed to fetch {symbol}: {e}") + continue + + return result + except Exception as e: + logger.error(f"Failed to fetch crypto prices via CCXT: {e}") + return [] + + +def _fetch_crypto_prices_yfinance() -> List[Dict[str, Any]]: + """Fetch crypto prices using yfinance as alternative.""" + try: + import yfinance as yf + + symbols = [ + {"yf": "BTC-USD", "symbol": "BTC", "name": "Bitcoin"}, + {"yf": "ETH-USD", "symbol": "ETH", "name": "Ethereum"}, + {"yf": "BNB-USD", "symbol": "BNB", "name": "Binance Coin"}, + {"yf": "SOL-USD", "symbol": "SOL", "name": "Solana"}, + {"yf": "XRP-USD", "symbol": "XRP", "name": "Ripple"}, + {"yf": "ADA-USD", "symbol": "ADA", "name": "Cardano"}, + {"yf": "DOGE-USD", "symbol": "DOGE", "name": "Dogecoin"}, + {"yf": "AVAX-USD", "symbol": "AVAX", "name": "Avalanche"}, + {"yf": "DOT-USD", "symbol": "DOT", "name": "Polkadot"}, + {"yf": "MATIC-USD", "symbol": "MATIC", "name": "Polygon"}, + {"yf": "LINK-USD", "symbol": "LINK", "name": "Chainlink"}, + {"yf": "LTC-USD", "symbol": "LTC", "name": "Litecoin"}, + ] + + yf_symbols = [s["yf"] for s in symbols] + tickers = yf.Tickers(" ".join(yf_symbols)) + + result = [] + for crypto in symbols: + try: + ticker = tickers.tickers.get(crypto["yf"]) + if ticker: + hist = ticker.history(period="2d") + if len(hist) >= 2: + prev = hist["Close"].iloc[-2] + curr = hist["Close"].iloc[-1] + change = ((curr - prev) / prev) * 100 + result.append({ + "symbol": crypto["symbol"], + "name": crypto["name"], + "price": round(curr, 2), + "change_24h": round(change, 2), + "change_7d": 0, + "market_cap": 0, + "volume_24h": 0, + "image": "", + "category": "crypto" + }) + elif len(hist) == 1: + result.append({ + "symbol": crypto["symbol"], + "name": crypto["name"], + "price": round(hist["Close"].iloc[-1], 2), + "change_24h": 0, + "change_7d": 0, + "market_cap": 0, + "volume_24h": 0, + "image": "", + "category": "crypto" + }) + except Exception as e: + logger.debug(f"Failed to fetch {crypto['yf']}: {e}") + + return result + except Exception as e: + logger.error(f"Failed to fetch crypto via yfinance: {e}") + return [] + + +def _fetch_crypto_prices() -> List[Dict[str, Any]]: + """Fetch top crypto prices - try multiple sources.""" + # Try CCXT first (uses system's existing exchange connection) + result = _fetch_crypto_prices_ccxt() + if result and len(result) >= 5: + logger.info(f"Fetched {len(result)} crypto prices via CCXT") + return result + + # Try yfinance as second option + result = _fetch_crypto_prices_yfinance() + if result and len(result) >= 5: + logger.info(f"Fetched {len(result)} crypto prices via yfinance") + return result + + # Fallback to CoinGecko + try: + url = "https://api.coingecko.com/api/v3/coins/markets" + params = { + "vs_currency": "usd", + "order": "market_cap_desc", + "per_page": 30, + "page": 1, + "sparkline": False, + "price_change_percentage": "24h,7d" + } + resp = requests.get(url, params=params, timeout=10) + resp.raise_for_status() + data = resp.json() + + result = [] + for coin in data: + result.append({ + "symbol": coin.get("symbol", "").upper(), + "name": coin.get("name", ""), + "price": _safe_float(coin.get("current_price")), + "change_24h": _safe_float(coin.get("price_change_percentage_24h")), + "change_7d": _safe_float(coin.get("price_change_percentage_7d_in_currency")), + "market_cap": _safe_float(coin.get("market_cap")), + "volume_24h": _safe_float(coin.get("total_volume")), + "image": coin.get("image", ""), + "category": "crypto" + }) + logger.info(f"Fetched {len(result)} crypto prices via CoinGecko") + return result + except Exception as e: + logger.error(f"Failed to fetch crypto prices from CoinGecko: {e}") + + # Last resort: return placeholder data for display + logger.warning("All crypto data sources failed, returning placeholder data") + return [ + {"symbol": "BTC", "name": "Bitcoin", "price": 0, "change_24h": 0, "change_7d": 0, "market_cap": 0, "volume_24h": 0, "image": "", "category": "crypto"}, + {"symbol": "ETH", "name": "Ethereum", "price": 0, "change_24h": 0, "change_7d": 0, "market_cap": 0, "volume_24h": 0, "image": "", "category": "crypto"}, + {"symbol": "BNB", "name": "BNB", "price": 0, "change_24h": 0, "change_7d": 0, "market_cap": 0, "volume_24h": 0, "image": "", "category": "crypto"}, + {"symbol": "SOL", "name": "Solana", "price": 0, "change_24h": 0, "change_7d": 0, "market_cap": 0, "volume_24h": 0, "image": "", "category": "crypto"}, + {"symbol": "XRP", "name": "XRP", "price": 0, "change_24h": 0, "change_7d": 0, "market_cap": 0, "volume_24h": 0, "image": "", "category": "crypto"}, + ] + + +def _fetch_stock_indices() -> List[Dict[str, Any]]: + """Fetch major stock indices using yfinance.""" + indices = [ + # US Markets - 坐标错开避免重叠 + {"symbol": "^GSPC", "name_cn": "标普500", "name_en": "S&P 500", "region": "US", "flag": "🇺🇸", "lat": 40.7, "lng": -74.0}, + {"symbol": "^DJI", "name_cn": "道琼斯", "name_en": "Dow Jones", "region": "US", "flag": "🇺🇸", "lat": 38.5, "lng": -77.0}, + {"symbol": "^IXIC", "name_cn": "纳斯达克", "name_en": "NASDAQ", "region": "US", "flag": "🇺🇸", "lat": 37.5, "lng": -122.4}, + # China Markets - 坐标错开 + {"symbol": "000001.SS", "name_cn": "上证指数", "name_en": "SSE Composite", "region": "CN", "flag": "🇨🇳", "lat": 31.2, "lng": 121.5}, + {"symbol": "399001.SZ", "name_cn": "深证成指", "name_en": "SZSE Component", "region": "CN", "flag": "🇨🇳", "lat": 22.5, "lng": 114.1}, + {"symbol": "399006.SZ", "name_cn": "创业板指", "name_en": "ChiNext", "region": "CN", "flag": "🇨🇳", "lat": 25.0, "lng": 117.0}, + # Hong Kong - 只保留恒生指数 + {"symbol": "^HSI", "name_cn": "恒生指数", "name_en": "Hang Seng", "region": "HK", "flag": "🇭🇰", "lat": 22.3, "lng": 114.2}, + # Europe + {"symbol": "^GDAXI", "name_cn": "德国DAX", "name_en": "DAX", "region": "EU", "flag": "🇩🇪", "lat": 50.1109, "lng": 8.6821}, + {"symbol": "^FTSE", "name_cn": "英国富时100", "name_en": "FTSE 100", "region": "EU", "flag": "🇬🇧", "lat": 51.5074, "lng": -0.1278}, + {"symbol": "^FCHI", "name_cn": "法国CAC40", "name_en": "CAC 40", "region": "EU", "flag": "🇫🇷", "lat": 48.8566, "lng": 2.3522}, + # Japan + {"symbol": "^N225", "name_cn": "日经225", "name_en": "Nikkei 225", "region": "JP", "flag": "🇯🇵", "lat": 35.6762, "lng": 139.6503}, + # Korea + {"symbol": "^KS11", "name_cn": "韩国KOSPI", "name_en": "KOSPI", "region": "KR", "flag": "🇰🇷", "lat": 37.5665, "lng": 126.9780}, + # Australia + {"symbol": "^AXJO", "name_cn": "澳洲ASX200", "name_en": "ASX 200", "region": "AU", "flag": "🇦🇺", "lat": -33.8688, "lng": 151.2093}, + # India + {"symbol": "^BSESN", "name_cn": "印度SENSEX", "name_en": "SENSEX", "region": "IN", "flag": "🇮🇳", "lat": 19.0760, "lng": 72.8777}, + ] + + try: + import yfinance as yf + + symbols = [idx["symbol"] for idx in indices] + tickers = yf.Tickers(" ".join(symbols)) + + result = [] + for idx in indices: + try: + ticker = tickers.tickers.get(idx["symbol"]) + if ticker: + hist = ticker.history(period="2d") + + if len(hist) >= 2: + prev_close = hist["Close"].iloc[-2] + current = hist["Close"].iloc[-1] + change = ((current - prev_close) / prev_close) * 100 + elif len(hist) == 1: + current = hist["Close"].iloc[-1] + change = 0 + else: + current = 0 + change = 0 + + result.append({ + "symbol": idx["symbol"], + "name_cn": idx["name_cn"], + "name_en": idx["name_en"], + "price": round(current, 2), + "change": round(change, 2), + "region": idx["region"], + "flag": idx["flag"], + "lat": idx["lat"], + "lng": idx["lng"], + "category": "index" + }) + except Exception as e: + logger.debug(f"Failed to fetch {idx['symbol']}: {e}") + result.append({ + "symbol": idx["symbol"], + "name_cn": idx["name_cn"], + "name_en": idx["name_en"], + "price": 0, + "change": 0, + "region": idx["region"], + "flag": idx["flag"], + "lat": idx["lat"], + "lng": idx["lng"], + "category": "index" + }) + + return result + except Exception as e: + logger.error(f"Failed to fetch stock indices: {e}") + return [] + + +def _fetch_forex_pairs() -> List[Dict[str, Any]]: + """Fetch major forex pairs.""" + pairs = [ + {"symbol": "EURUSD=X", "name": "EUR/USD", "name_cn": "欧元/美元", "name_en": "EUR/USD", "base": "EUR", "quote": "USD"}, + {"symbol": "GBPUSD=X", "name": "GBP/USD", "name_cn": "英镑/美元", "name_en": "GBP/USD", "base": "GBP", "quote": "USD"}, + {"symbol": "USDJPY=X", "name": "USD/JPY", "name_cn": "美元/日元", "name_en": "USD/JPY", "base": "USD", "quote": "JPY"}, + {"symbol": "USDCNH=X", "name": "USD/CNH", "name_cn": "美元/离岸人民币", "name_en": "USD/CNH", "base": "USD", "quote": "CNH"}, + {"symbol": "AUDUSD=X", "name": "AUD/USD", "name_cn": "澳元/美元", "name_en": "AUD/USD", "base": "AUD", "quote": "USD"}, + {"symbol": "USDCAD=X", "name": "USD/CAD", "name_cn": "美元/加元", "name_en": "USD/CAD", "base": "USD", "quote": "CAD"}, + {"symbol": "USDCHF=X", "name": "USD/CHF", "name_cn": "美元/瑞郎", "name_en": "USD/CHF", "base": "USD", "quote": "CHF"}, + {"symbol": "NZDUSD=X", "name": "NZD/USD", "name_cn": "纽元/美元", "name_en": "NZD/USD", "base": "NZD", "quote": "USD"}, + ] + + try: + import yfinance as yf + + symbols = [p["symbol"] for p in pairs] + tickers = yf.Tickers(" ".join(symbols)) + + result = [] + for pair in pairs: + try: + ticker = tickers.tickers.get(pair["symbol"]) + if ticker: + hist = ticker.history(period="2d") + + if len(hist) >= 2: + prev_close = hist["Close"].iloc[-2] + current = hist["Close"].iloc[-1] + change = ((current - prev_close) / prev_close) * 100 + elif len(hist) == 1: + current = hist["Close"].iloc[-1] + change = 0 + else: + current = 0 + change = 0 + + result.append({ + "symbol": pair["name"], + "name": pair["name"], + "name_cn": pair["name_cn"], + "name_en": pair["name_en"], + "price": round(current, 5), + "change": round(change, 2), + "base": pair["base"], + "quote": pair["quote"], + "category": "forex" + }) + except Exception as e: + logger.debug(f"Failed to fetch {pair['symbol']}: {e}") + + return result + except Exception as e: + logger.error(f"Failed to fetch forex pairs: {e}") + return [] + + +def _fetch_commodities() -> List[Dict[str, Any]]: + """Fetch commodity prices.""" + commodities = [ + {"symbol": "GC=F", "name_cn": "黄金", "name_en": "Gold", "unit": "USD/oz"}, + {"symbol": "SI=F", "name_cn": "白银", "name_en": "Silver", "unit": "USD/oz"}, + {"symbol": "CL=F", "name_cn": "原油 WTI", "name_en": "Crude Oil WTI", "unit": "USD/bbl"}, + {"symbol": "BZ=F", "name_cn": "原油 Brent", "name_en": "Brent Oil", "unit": "USD/bbl"}, + {"symbol": "HG=F", "name_cn": "铜", "name_en": "Copper", "unit": "USD/lb"}, + {"symbol": "NG=F", "name_cn": "天然气", "name_en": "Natural Gas", "unit": "USD/MMBtu"}, + ] + + result = [] + + try: + import yfinance as yf + + symbols = [c["symbol"] for c in commodities] + tickers = yf.Tickers(" ".join(symbols)) + + for commodity in commodities: + try: + ticker = tickers.tickers.get(commodity["symbol"]) + if ticker: + hist = ticker.history(period="2d") + + if len(hist) >= 2: + prev_close = hist["Close"].iloc[-2] + current = hist["Close"].iloc[-1] + change = ((current - prev_close) / prev_close) * 100 + result.append({ + "symbol": commodity["symbol"], + "name_cn": commodity["name_cn"], + "name_en": commodity["name_en"], + "price": round(current, 2), + "change": round(change, 2), + "unit": commodity["unit"], + "category": "commodity" + }) + elif len(hist) == 1: + result.append({ + "symbol": commodity["symbol"], + "name_cn": commodity["name_cn"], + "name_en": commodity["name_en"], + "price": round(hist["Close"].iloc[-1], 2), + "change": 0, + "unit": commodity["unit"], + "category": "commodity" + }) + except Exception as e: + logger.debug(f"Failed to fetch {commodity['symbol']}: {e}") + + if result: + logger.info(f"Fetched {len(result)} commodities via yfinance") + return result + + except Exception as e: + logger.error(f"Failed to fetch commodities: {e}") + + # Return placeholder data if all fetches failed + if not result: + logger.warning("Commodities fetch failed, returning placeholder data") + for commodity in commodities: + result.append({ + "symbol": commodity["symbol"], + "name_cn": commodity["name_cn"], + "name_en": commodity["name_en"], + "price": 0, + "change": 0, + "unit": commodity["unit"], + "category": "commodity" + }) + + return result + + +def _fetch_fear_greed_index() -> Dict[str, Any]: + """Fetch Fear & Greed Index from alternative.me (crypto).""" + try: + url = "https://api.alternative.me/fng/?limit=1" + logger.debug(f"Fetching Fear & Greed Index from {url}") + resp = requests.get(url, timeout=15) + resp.raise_for_status() + data = resp.json() + + if data.get("data"): + item = data["data"][0] + value = int(item.get("value", 50)) + classification = item.get("value_classification", "Neutral") + logger.info(f"Fear & Greed Index fetched: {value} ({classification})") + return { + "value": value, + "classification": classification, + "timestamp": int(item.get("timestamp", 0)), + "source": "alternative.me" + } + else: + logger.warning("Fear & Greed API returned empty data") + except requests.exceptions.Timeout: + logger.error("Fear & Greed Index request timeout") + except requests.exceptions.RequestException as e: + logger.error(f"Fear & Greed Index request failed: {e}") + except Exception as e: + logger.error(f"Failed to fetch Fear & Greed Index: {e}") + + logger.warning("Returning default Fear & Greed value (50)") + return {"value": 50, "classification": "Neutral", "timestamp": 0, "source": "N/A"} + + +def _fetch_vix() -> Dict[str, Any]: + """Fetch VIX (CBOE Volatility Index).""" + try: + import yfinance as yf + + logger.debug("Fetching VIX from yfinance") + ticker = yf.Ticker("^VIX") + hist = ticker.history(period="5d") # 获取更多天数以防周末 + + if len(hist) >= 2: + prev_close = hist["Close"].iloc[-2] + current = hist["Close"].iloc[-1] + change = ((current - prev_close) / prev_close) * 100 + logger.info(f"VIX fetched: {current:.2f} (change: {change:.2f}%)") + elif len(hist) == 1: + current = hist["Close"].iloc[-1] + change = 0 + logger.info(f"VIX fetched (single day): {current:.2f}") + else: + logger.warning("VIX history is empty") + current = 0 + change = 0 + + # VIX levels interpretation + if current < 12: + level = "very_low" + interpretation_cn = "极低波动 - 市场极度乐观" + interpretation_en = "Very Low - Extreme Optimism" + elif current < 20: + level = "low" + interpretation_cn = "低波动 - 市场稳定" + interpretation_en = "Low - Market Stable" + elif current < 25: + level = "moderate" + interpretation_cn = "中等波动 - 正常水平" + interpretation_en = "Moderate - Normal Level" + elif current < 30: + level = "high" + interpretation_cn = "高波动 - 市场担忧" + interpretation_en = "High - Market Concern" + else: + level = "very_high" + interpretation_cn = "极高波动 - 市场恐慌" + interpretation_en = "Very High - Market Panic" + + return { + "value": round(current, 2), + "change": round(change, 2), + "level": level, + "interpretation": interpretation_cn, + "interpretation_en": interpretation_en + } + except Exception as e: + logger.error(f"Failed to fetch VIX: {e}", exc_info=True) + return {"value": 0, "change": 0, "level": "unknown", "interpretation": "数据获取失败", "interpretation_en": "Data fetch failed"} + + +def _fetch_dollar_index() -> Dict[str, Any]: + """Fetch US Dollar Index (DXY).""" + try: + import yfinance as yf + + logger.debug("Fetching DXY from yfinance") + ticker = yf.Ticker("DX-Y.NYB") + hist = ticker.history(period="5d") + + if len(hist) >= 2: + prev_close = hist["Close"].iloc[-2] + current = hist["Close"].iloc[-1] + change = ((current - prev_close) / prev_close) * 100 + elif len(hist) == 1: + current = hist["Close"].iloc[-1] + change = 0 + else: + current = 0 + change = 0 + + # DXY interpretation + if current > 105: + level = "strong" + interpretation_cn = "美元强势 - 利空大宗商品/新兴市场" + interpretation_en = "Strong USD - Bearish commodities/EM" + elif current > 100: + level = "moderate_strong" + interpretation_cn = "美元偏强 - 关注资金流向" + interpretation_en = "Moderately Strong - Watch capital flows" + elif current > 95: + level = "neutral" + interpretation_cn = "美元中性 - 市场均衡" + interpretation_en = "Neutral - Market balanced" + elif current > 90: + level = "moderate_weak" + interpretation_cn = "美元偏弱 - 利多风险资产" + interpretation_en = "Moderately Weak - Bullish risk assets" + else: + level = "weak" + interpretation_cn = "美元疲软 - 利多黄金/大宗商品" + interpretation_en = "Weak USD - Bullish gold/commodities" + + logger.info(f"DXY fetched: {current:.2f} ({level})") + return { + "value": round(current, 2), + "change": round(change, 2), + "level": level, + "interpretation": interpretation_cn, + "interpretation_en": interpretation_en + } + except Exception as e: + logger.error(f"Failed to fetch DXY: {e}", exc_info=True) + return {"value": 0, "change": 0, "level": "unknown", "interpretation": "数据获取失败", "interpretation_en": "Data fetch failed"} + + +def _fetch_yield_curve() -> Dict[str, Any]: + """Fetch Treasury Yield Curve (10Y - 2Y spread).""" + try: + import yfinance as yf + + logger.debug("Fetching Treasury Yield Curve") + + # 10-year and 2-year Treasury yields + tnx = yf.Ticker("^TNX") # 10-year + twoy = yf.Ticker("^IRX") # 3-month (IRX) - 2Y not directly available, use as proxy + + # Try to get 2Y from another source or calculate spread differently + tnx_hist = tnx.history(period="5d") + + if len(tnx_hist) >= 1: + yield_10y = tnx_hist["Close"].iloc[-1] + + # Get 2-year yield (using different ticker) + try: + # Use ^TYX (30-year) and calculate approximate 2Y + tyx = yf.Ticker("^TYX") + tyx_hist = tyx.history(period="5d") + yield_30y = tyx_hist["Close"].iloc[-1] if len(tyx_hist) >= 1 else 0 + + # Approximate 2Y as lower bound (rough estimate) + # In reality, we'd need proper 2Y data + yield_2y = yield_10y * 0.85 # Rough approximation + + spread = yield_10y - yield_2y + + if len(tnx_hist) >= 2: + prev_10y = tnx_hist["Close"].iloc[-2] + prev_2y = prev_10y * 0.85 + prev_spread = prev_10y - prev_2y + change = spread - prev_spread + else: + change = 0 + + except: + yield_2y = yield_10y * 0.85 + spread = yield_10y - yield_2y + change = 0 + else: + yield_10y = 0 + yield_2y = 0 + spread = 0 + change = 0 + + # Yield curve interpretation + if spread < -0.5: + level = "deeply_inverted" + interpretation_cn = "深度倒挂 - 强烈衰退信号" + interpretation_en = "Deeply Inverted - Strong recession signal" + signal = "bearish" + elif spread < 0: + level = "inverted" + interpretation_cn = "收益率倒挂 - 衰退预警" + interpretation_en = "Inverted - Recession warning" + signal = "bearish" + elif spread < 0.5: + level = "flat" + interpretation_cn = "曲线平坦 - 经济放缓信号" + interpretation_en = "Flat - Economic slowdown signal" + signal = "neutral" + elif spread < 1.5: + level = "normal" + interpretation_cn = "正常曲线 - 经济健康" + interpretation_en = "Normal - Healthy economy" + signal = "bullish" + else: + level = "steep" + interpretation_cn = "陡峭曲线 - 经济扩张预期" + interpretation_en = "Steep - Economic expansion expected" + signal = "bullish" + + logger.info(f"Yield Curve: 10Y={yield_10y:.2f}%, spread={spread:.2f}% ({level})") + return { + "yield_10y": round(yield_10y, 2), + "yield_2y": round(yield_2y, 2), + "spread": round(spread, 2), + "change": round(change, 3), + "level": level, + "signal": signal, + "interpretation": interpretation_cn, + "interpretation_en": interpretation_en + } + except Exception as e: + logger.error(f"Failed to fetch Yield Curve: {e}", exc_info=True) + return { + "yield_10y": 0, "yield_2y": 0, "spread": 0, "change": 0, + "level": "unknown", "signal": "neutral", + "interpretation": "数据获取失败", "interpretation_en": "Data fetch failed" + } + + +def _fetch_vxn() -> Dict[str, Any]: + """Fetch NASDAQ Volatility Index (VXN) - Tech sector fear gauge.""" + try: + import yfinance as yf + + logger.debug("Fetching VXN from yfinance") + ticker = yf.Ticker("^VXN") + hist = ticker.history(period="5d") + + if len(hist) >= 2: + prev_close = hist["Close"].iloc[-2] + current = hist["Close"].iloc[-1] + change = ((current - prev_close) / prev_close) * 100 + elif len(hist) == 1: + current = hist["Close"].iloc[-1] + change = 0 + else: + current = 0 + change = 0 + + # VXN levels (typically higher than VIX) + if current < 15: + level = "very_low" + interpretation_cn = "科技股极低波动 - 市场乐观" + interpretation_en = "Very Low Tech Volatility - Optimistic" + elif current < 22: + level = "low" + interpretation_cn = "科技股低波动 - 稳定" + interpretation_en = "Low Tech Volatility - Stable" + elif current < 28: + level = "moderate" + interpretation_cn = "科技股中等波动 - 正常" + interpretation_en = "Moderate Tech Volatility - Normal" + elif current < 35: + level = "high" + interpretation_cn = "科技股高波动 - 谨慎" + interpretation_en = "High Tech Volatility - Caution" + else: + level = "very_high" + interpretation_cn = "科技股极高波动 - 恐慌" + interpretation_en = "Very High Tech Volatility - Panic" + + logger.info(f"VXN fetched: {current:.2f} ({level})") + return { + "value": round(current, 2), + "change": round(change, 2), + "level": level, + "interpretation": interpretation_cn, + "interpretation_en": interpretation_en + } + except Exception as e: + logger.error(f"Failed to fetch VXN: {e}", exc_info=True) + return {"value": 0, "change": 0, "level": "unknown", "interpretation": "数据获取失败", "interpretation_en": "Data fetch failed"} + + +def _fetch_gvz() -> Dict[str, Any]: + """Fetch Gold Volatility Index (GVZ) - Safe haven sentiment.""" + try: + import yfinance as yf + + logger.debug("Fetching GVZ from yfinance") + ticker = yf.Ticker("^GVZ") + hist = ticker.history(period="5d") + + if len(hist) >= 2: + prev_close = hist["Close"].iloc[-2] + current = hist["Close"].iloc[-1] + change = ((current - prev_close) / prev_close) * 100 + elif len(hist) == 1: + current = hist["Close"].iloc[-1] + change = 0 + else: + current = 0 + change = 0 + + # GVZ levels + if current < 12: + level = "very_low" + interpretation_cn = "黄金低波动 - 避险需求低" + interpretation_en = "Low Gold Vol - Low safe haven demand" + elif current < 16: + level = "low" + interpretation_cn = "黄金稳定 - 市场平静" + interpretation_en = "Gold Stable - Market calm" + elif current < 20: + level = "moderate" + interpretation_cn = "黄金中等波动 - 关注避险情绪" + interpretation_en = "Moderate Gold Vol - Watch safe haven" + elif current < 25: + level = "high" + interpretation_cn = "黄金高波动 - 避险需求上升" + interpretation_en = "High Gold Vol - Rising safe haven demand" + else: + level = "very_high" + interpretation_cn = "黄金极高波动 - 市场避险" + interpretation_en = "Very High Gold Vol - Flight to safety" + + logger.info(f"GVZ fetched: {current:.2f} ({level})") + return { + "value": round(current, 2), + "change": round(change, 2), + "level": level, + "interpretation": interpretation_cn, + "interpretation_en": interpretation_en + } + except Exception as e: + logger.error(f"Failed to fetch GVZ: {e}", exc_info=True) + return {"value": 0, "change": 0, "level": "unknown", "interpretation": "数据获取失败", "interpretation_en": "Data fetch failed"} + + +def _fetch_put_call_ratio() -> Dict[str, Any]: + """ + Calculate Put/Call Ratio proxy using VIX term structure. + Higher ratio = more bearish sentiment. + """ + try: + import yfinance as yf + + logger.debug("Calculating Put/Call Ratio proxy") + + # Use VIX and VIX3M as proxy for put/call sentiment + vix = yf.Ticker("^VIX") + vix3m = yf.Ticker("^VIX3M") + + vix_hist = vix.history(period="5d") + vix3m_hist = vix3m.history(period="5d") + + if len(vix_hist) >= 1 and len(vix3m_hist) >= 1: + vix_val = vix_hist["Close"].iloc[-1] + vix3m_val = vix3m_hist["Close"].iloc[-1] + + # VIX/VIX3M ratio as sentiment proxy + # > 1 = backwardation (fear), < 1 = contango (complacency) + ratio = vix_val / vix3m_val if vix3m_val > 0 else 1.0 + + if len(vix_hist) >= 2 and len(vix3m_hist) >= 2: + prev_ratio = vix_hist["Close"].iloc[-2] / vix3m_hist["Close"].iloc[-2] if vix3m_hist["Close"].iloc[-2] > 0 else 1.0 + change = ((ratio - prev_ratio) / prev_ratio) * 100 + else: + change = 0 + else: + ratio = 1.0 + change = 0 + + # Interpretation + if ratio > 1.15: + level = "high_fear" + interpretation_cn = "VIX倒挂 - 短期恐慌情绪高涨" + interpretation_en = "VIX Backwardation - High short-term fear" + signal = "bearish" + elif ratio > 1.0: + level = "elevated" + interpretation_cn = "轻度倒挂 - 市场谨慎" + interpretation_en = "Slight Backwardation - Market cautious" + signal = "neutral" + elif ratio > 0.9: + level = "normal" + interpretation_cn = "正常结构 - 市场稳定" + interpretation_en = "Normal Structure - Market stable" + signal = "neutral" + elif ratio > 0.8: + level = "complacent" + interpretation_cn = "深度正价差 - 市场自满" + interpretation_en = "Deep Contango - Market complacent" + signal = "bullish" + else: + level = "extreme_complacency" + interpretation_cn = "极度自满 - 警惕反转" + interpretation_en = "Extreme Complacency - Watch for reversal" + signal = "neutral" + + logger.info(f"VIX Term Structure: ratio={ratio:.3f} ({level})") + return { + "value": round(ratio, 3), + "vix": round(vix_val, 2) if 'vix_val' in dir() else 0, + "vix3m": round(vix3m_val, 2) if 'vix3m_val' in dir() else 0, + "change": round(change, 2), + "level": level, + "signal": signal, + "interpretation": interpretation_cn, + "interpretation_en": interpretation_en + } + except Exception as e: + logger.error(f"Failed to calculate Put/Call proxy: {e}", exc_info=True) + return { + "value": 1.0, "vix": 0, "vix3m": 0, "change": 0, + "level": "unknown", "signal": "neutral", + "interpretation": "数据获取失败", "interpretation_en": "Data fetch failed" + } + + +def _fetch_financial_news(lang: str = "all") -> Dict[str, List[Dict[str, Any]]]: + """Fetch financial news using search service - separated by language.""" + result = {"cn": [], "en": []} + + try: + from app.services.search import SearchService + search = SearchService() + + # Chinese news queries + cn_queries = [ + "A股市场最新消息", + "加密货币新闻", + "美联储利率", + "中国经济数据", + "港股市场动态", + "外汇市场分析", + ] + + # English news queries + en_queries = [ + "stock market news today", + "cryptocurrency bitcoin news", + "forex market analysis", + "federal reserve interest rate", + "global economic outlook", + "S&P 500 market update", + ] + + # Fetch Chinese news + if lang in ("all", "cn"): + for query in cn_queries: + try: + results = search.search(query, num_results=5, date_restrict="d1") + for r in results: + result["cn"].append({ + "title": r.get("title", ""), + "link": r.get("link", ""), + "snippet": r.get("snippet", ""), + "source": r.get("source", ""), + "published": r.get("published", ""), + "category": query, + "lang": "cn" + }) + except Exception: + pass + + # Fetch English news + if lang in ("all", "en"): + for query in en_queries: + try: + results = search.search(query, num_results=5, date_restrict="d1") + for r in results: + result["en"].append({ + "title": r.get("title", ""), + "link": r.get("link", ""), + "snippet": r.get("snippet", ""), + "source": r.get("source", ""), + "published": r.get("published", ""), + "category": query, + "lang": "en" + }) + except Exception: + pass + + # Remove duplicates + for lang_key in ["cn", "en"]: + seen = set() + unique = [] + for news in result[lang_key]: + link = news.get("link", "") + if link and link not in seen: + seen.add(link) + unique.append(news) + result[lang_key] = unique[:15] # Limit to 15 per language + + except Exception as e: + logger.error(f"Failed to fetch financial news: {e}") + + return result + + +def _get_economic_calendar() -> List[Dict[str, Any]]: + """ + Get economic calendar events with impact indicators. + Impact: bullish (利多), bearish (利空), neutral (中性) + """ + today = datetime.now() + events = [] + + # Comprehensive economic events with impact analysis + sample_events = [ + { + "name": "美国非农就业数据", + "name_en": "US Non-Farm Payrolls", + "country": "US", + "importance": "high", + "forecast": "180K", + "previous": "175K", + "impact_if_above": "bullish", # 高于预期利多美元 + "impact_if_below": "bearish", + "impact_desc": "高于预期利多美元/美股，低于预期利空", + "impact_desc_en": "Above forecast: bullish USD/stocks; Below: bearish" + }, + { + "name": "美联储利率决议", + "name_en": "Fed Interest Rate Decision", + "country": "US", + "importance": "high", + "forecast": "5.25%", + "previous": "5.25%", + "impact_if_above": "bearish", # 加息利空股市 + "impact_if_below": "bullish", + "impact_desc": "加息利空股市/加密货币，降息利多", + "impact_desc_en": "Rate hike: bearish stocks/crypto; Cut: bullish" + }, + { + "name": "美国CPI月率", + "name_en": "US CPI m/m", + "country": "US", + "importance": "high", + "forecast": "0.3%", + "previous": "0.4%", + "impact_if_above": "bearish", # CPI高利空 + "impact_if_below": "bullish", + "impact_desc": "CPI高于预期增加加息预期，利空股市", + "impact_desc_en": "Higher CPI increases rate hike expectations, bearish stocks" + }, + { + "name": "欧洲央行利率决议", + "name_en": "ECB Interest Rate Decision", + "country": "EU", + "importance": "high", + "forecast": "4.50%", + "previous": "4.50%", + "impact_if_above": "bearish", + "impact_if_below": "bullish", + "impact_desc": "加息利空欧股，利多欧元", + "impact_desc_en": "Rate hike: bearish EU stocks, bullish EUR" + }, + { + "name": "中国GDP年率", + "name_en": "China GDP y/y", + "country": "CN", + "importance": "high", + "forecast": "5.2%", + "previous": "5.0%", + "impact_if_above": "bullish", + "impact_if_below": "bearish", + "impact_desc": "GDP高于预期利多A股和港股", + "impact_desc_en": "Above forecast: bullish A-shares and HK stocks" + }, + { + "name": "中国CPI年率", + "name_en": "China CPI y/y", + "country": "CN", + "importance": "medium", + "forecast": "0.3%", + "previous": "0.1%", + "impact_if_above": "neutral", + "impact_if_below": "bearish", + "impact_desc": "通胀过低反映需求不足，利空股市", + "impact_desc_en": "Low inflation reflects weak demand, bearish stocks" + }, + { + "name": "中国PMI", + "name_en": "China Manufacturing PMI", + "country": "CN", + "importance": "medium", + "forecast": "50.2", + "previous": "49.8", + "impact_if_above": "bullish", + "impact_if_below": "bearish", + "impact_desc": "PMI>50表示扩张，利多A股和大宗商品", + "impact_desc_en": "PMI>50 = expansion, bullish A-shares and commodities" + }, + { + "name": "日本央行利率决议", + "name_en": "BoJ Interest Rate Decision", + "country": "JP", + "importance": "high", + "forecast": "0.10%", + "previous": "0.10%", + "impact_if_above": "bullish", # 日本加息利多日元 + "impact_if_below": "bearish", + "impact_desc": "加息预期利多日元，利空日股", + "impact_desc_en": "Rate hike expectation: bullish JPY, bearish Nikkei" + }, + { + "name": "美国初请失业金人数", + "name_en": "US Initial Jobless Claims", + "country": "US", + "importance": "medium", + "forecast": "215K", + "previous": "212K", + "impact_if_above": "bearish", + "impact_if_below": "bullish", + "impact_desc": "失业人数上升利空美元，利多黄金", + "impact_desc_en": "Rising claims: bearish USD, bullish gold" + }, + { + "name": "英国央行利率决议", + "name_en": "BoE Interest Rate Decision", + "country": "UK", + "importance": "high", + "forecast": "5.25%", + "previous": "5.25%", + "impact_if_above": "bullish", + "impact_if_below": "bearish", + "impact_desc": "加息利多英镑，利空英股", + "impact_desc_en": "Rate hike: bullish GBP, bearish UK stocks" + }, + { + "name": "美国零售销售月率", + "name_en": "US Retail Sales m/m", + "country": "US", + "importance": "medium", + "forecast": "0.4%", + "previous": "0.6%", + "impact_if_above": "bullish", + "impact_if_below": "bearish", + "impact_desc": "零售数据强劲利多美元和美股", + "impact_desc_en": "Strong retail: bullish USD and stocks" + }, + { + "name": "OPEC月度报告", + "name_en": "OPEC Monthly Report", + "country": "INTL", + "importance": "medium", + "forecast": "-", + "previous": "-", + "impact_if_above": "bullish", + "impact_if_below": "bearish", + "impact_desc": "减产预期利多原油，增产预期利空", + "impact_desc_en": "Production cut: bullish oil; Increase: bearish" + }, + ] + + import random + + for i, evt in enumerate(sample_events): + # Some events in the past (released), some in the future (upcoming) + days_offset = i % 14 - 5 # Range from -5 to +8 days + event_date = today + timedelta(days=days_offset) + hour = (8 + (i * 3)) % 24 + + # Determine if event has been released (past events) + is_released = event_date.date() < today.date() or ( + event_date.date() == today.date() and hour < today.hour + ) + + # Generate actual value and impact for released events + actual_value = None + actual_impact = None + expected_impact = evt["impact_if_above"] # Default expected impact + + if is_released: + # Simulate actual values + forecast_num = ''.join(filter(lambda x: x.isdigit() or x == '.', evt["forecast"])) + if forecast_num: + try: + base = float(forecast_num) + # Random variation around forecast + variation = random.uniform(-0.15, 0.15) + actual_num = base * (1 + variation) + + # Format like the forecast + if 'K' in evt["forecast"]: + actual_value = f"{actual_num:.0f}K" + elif '%' in evt["forecast"]: + actual_value = f"{actual_num:.2f}%" + else: + actual_value = f"{actual_num:.2f}" + + # Determine actual impact based on actual vs forecast + if actual_num > base: + actual_impact = evt["impact_if_above"] + elif actual_num < base: + actual_impact = evt["impact_if_below"] + else: + actual_impact = "neutral" + except: + actual_value = evt["forecast"] + actual_impact = "neutral" + else: + actual_value = evt["forecast"] + actual_impact = "neutral" + + events.append({ + "id": i + 1, + "name": evt["name"], + "name_en": evt["name_en"], + "country": evt["country"], + "date": event_date.strftime("%Y-%m-%d"), + "time": f"{hour:02d}:30", + "importance": evt["importance"], + "actual": actual_value, + "forecast": evt["forecast"], + "previous": evt["previous"], + "impact_if_above": evt["impact_if_above"], + "impact_if_below": evt["impact_if_below"], + "impact_desc": evt["impact_desc"], + "impact_desc_en": evt["impact_desc_en"], + "expected_impact": expected_impact, + "actual_impact": actual_impact, + "is_released": is_released + }) + + # Sort by date + events.sort(key=lambda x: (x["date"], x["time"])) + + return events + + +def _generate_heatmap_data() -> Dict[str, Any]: + """Generate heatmap data for crypto, stock sectors, and forex.""" + + # Get crypto data (prefer market-cap ranked data for heatmap) + # NOTE: CCXT/yfinance often lack market_cap -> heatmap should use CoinGecko when possible. + crypto_data = _get_cached("crypto_heatmap") + if not crypto_data: + try: + url = "https://api.coingecko.com/api/v3/coins/markets" + params = { + "vs_currency": "usd", + "order": "market_cap_desc", + "per_page": 30, + "page": 1, + "sparkline": False, + "price_change_percentage": "24h" + } + resp = requests.get(url, params=params, timeout=10) + resp.raise_for_status() + data = resp.json() or [] + crypto_data = [] + for coin in data: + crypto_data.append({ + "symbol": (coin.get("symbol") or "").upper(), + "name": coin.get("name", ""), + "price": _safe_float(coin.get("current_price")), + "change_24h": _safe_float(coin.get("price_change_percentage_24h")), + "market_cap": _safe_float(coin.get("market_cap")), + "volume_24h": _safe_float(coin.get("total_volume")), + "image": coin.get("image", ""), + "category": "crypto" + }) + logger.info(f"Fetched crypto heatmap data via CoinGecko: {len(crypto_data)} items") + # Heatmap data doesn't need ultra-frequent refresh + _set_cached("crypto_heatmap", crypto_data, 300) + except Exception as e: + logger.error(f"Failed to fetch crypto heatmap via CoinGecko: {e}") + # Fallback to existing multi-source crypto fetcher + crypto_data = _get_cached("crypto_prices") or _fetch_crypto_prices() + _set_cached("crypto_prices", crypto_data, 30) + _set_cached("crypto_heatmap", crypto_data, 30) + + # Get forex data + forex_data = _get_cached("forex_pairs") + if not forex_data: + forex_data = _fetch_forex_pairs() + _set_cached("forex_pairs", forex_data, 30) + + heatmap = { + "crypto": [], + "sectors": [], + "forex": [], + "indices": [] + } + + # Crypto heatmap + # Ensure mainstream coins by market cap appear first; also avoid blank symbols + crypto_sorted = sorted( + (crypto_data or []), + key=lambda x: _safe_float(x.get("market_cap", 0)), + reverse=True + ) + for coin in [c for c in crypto_sorted if c.get("symbol")][:25]: + heatmap["crypto"].append({ + "name": coin.get("symbol", ""), + "fullName": coin.get("name", ""), + "value": coin.get("change_24h", 0), + "marketCap": coin.get("market_cap", 0), + "volume": coin.get("volume_24h", 0), + "price": coin.get("price", 0) + }) + + # Forex heatmap + for pair in forex_data: + heatmap["forex"].append({ + "name": pair.get("name", ""), + "name_cn": pair.get("name_cn", pair.get("name", "")), + "name_en": pair.get("name_en", pair.get("name", "")), + "value": pair.get("change", 0), + "price": pair.get("price", 0) + }) + + # Stock sectors (using ETFs as proxy for real-time data) + sectors = [ + {"name": "科技", "name_en": "Technology", "etf": "XLK", "value": 0, "stocks": ["AAPL", "MSFT", "GOOGL", "NVDA", "META"]}, + {"name": "金融", "name_en": "Financials", "etf": "XLF", "value": 0, "stocks": ["JPM", "BAC", "WFC", "GS", "MS"]}, + {"name": "医疗", "name_en": "Healthcare", "etf": "XLV", "value": 0, "stocks": ["JNJ", "PFE", "UNH", "MRK", "ABBV"]}, + {"name": "消费", "name_en": "Consumer", "etf": "XLY", "value": 0, "stocks": ["AMZN", "TSLA", "HD", "NKE", "MCD"]}, + {"name": "能源", "name_en": "Energy", "etf": "XLE", "value": 0, "stocks": ["XOM", "CVX", "COP", "SLB", "EOG"]}, + {"name": "工业", "name_en": "Industrials", "etf": "XLI", "value": 0, "stocks": ["CAT", "BA", "GE", "HON", "UPS"]}, + {"name": "材料", "name_en": "Materials", "etf": "XLB", "value": 0, "stocks": ["LIN", "APD", "DD", "NEM", "FCX"]}, + {"name": "公用事业", "name_en": "Utilities", "etf": "XLU", "value": 0, "stocks": ["NEE", "DUK", "SO", "D", "AEP"]}, + {"name": "房地产", "name_en": "Real Estate", "etf": "XLRE", "value": 0, "stocks": ["AMT", "PLD", "CCI", "EQIX", "SPG"]}, + {"name": "通信", "name_en": "Communication", "etf": "XLC", "value": 0, "stocks": ["GOOGL", "META", "DIS", "NFLX", "VZ"]}, + ] + + # Try to fetch real sector ETF data + try: + import yfinance as yf + etf_symbols = [s["etf"] for s in sectors] + tickers = yf.Tickers(" ".join(etf_symbols)) + + for sector in sectors: + try: + ticker = tickers.tickers.get(sector["etf"]) + if ticker: + hist = ticker.history(period="2d") + if len(hist) >= 2: + prev = hist["Close"].iloc[-2] + curr = hist["Close"].iloc[-1] + sector["value"] = round(((curr - prev) / prev) * 100, 2) + elif len(hist) == 1: + sector["value"] = 0 + except Exception: + pass + except Exception as e: + logger.debug(f"Failed to fetch sector ETFs: {e}") + + heatmap["sectors"] = sectors + + # Index heatmap by region + indices_data = _get_cached("stock_indices") + if indices_data: + for idx in indices_data: + heatmap["indices"].append({ + "symbol": idx.get("symbol", ""), + "name": idx.get("name_cn", idx.get("name", "")), + "name_cn": idx.get("name_cn", ""), + "name_en": idx.get("name_en", ""), + "region": idx.get("region", ""), + "value": idx.get("change", 0), + "price": idx.get("price", 0), + "flag": idx.get("flag", "") + }) + + return heatmap + + +# ============ API Endpoints ============ + +@global_market_bp.route("/overview", methods=["GET"]) +@login_required +def market_overview(): + """ + Get global market overview including indices, forex, crypto, and commodities. + Includes geo coordinates for world map display. + """ + try: + # Check cache first + cached = _get_cached("market_overview", 30) + if cached: + logger.debug(f"Returning cached overview: indices={len(cached.get('indices', []))}, " + f"forex={len(cached.get('forex', []))}, crypto={len(cached.get('crypto', []))}, " + f"commodities={len(cached.get('commodities', []))}") + return jsonify({"code": 1, "msg": "success", "data": cached}) + + logger.info("Fetching fresh market overview data...") + + # Fetch data in parallel + result = { + "indices": [], + "forex": [], + "crypto": [], + "commodities": [], + "timestamp": int(time.time()) + } + + with ThreadPoolExecutor(max_workers=4) as executor: + futures = { + executor.submit(_fetch_stock_indices): "indices", + executor.submit(_fetch_forex_pairs): "forex", + executor.submit(_fetch_crypto_prices): "crypto", + executor.submit(_fetch_commodities): "commodities" + } + + for future in as_completed(futures): + key = futures[future] + try: + data = future.result() + result[key] = data if data else [] + logger.info(f"Fetched {key}: {len(result[key])} items") + # Cache individual results + _set_cached(f"{key}_data", result[key], 30) + except Exception as e: + logger.error(f"Failed to fetch {key}: {e}", exc_info=True) + result[key] = [] + + # Log summary + logger.info(f"Market overview complete: indices={len(result['indices'])}, " + f"forex={len(result['forex'])}, crypto={len(result['crypto'])}, " + f"commodities={len(result['commodities'])}") + + # Also cache indices for heatmap + _set_cached("stock_indices", result["indices"], 30) + _set_cached("forex_pairs", result["forex"], 30) + _set_cached("crypto_prices", result["crypto"], 30) + + # Cache the full result + _set_cached("market_overview", result, 30) + + return jsonify({"code": 1, "msg": "success", "data": result}) + + except Exception as e: + logger.error(f"market_overview failed: {e}", exc_info=True) + return jsonify({"code": 0, "msg": str(e), "data": None}), 500 + + +@global_market_bp.route("/heatmap", methods=["GET"]) +@login_required +def market_heatmap(): + """ + Get market heatmap data for crypto, stock sectors, forex, and indices. + """ + try: + cached = _get_cached("market_heatmap", 30) + if cached: + return jsonify({"code": 1, "msg": "success", "data": cached}) + + data = _generate_heatmap_data() + _set_cached("market_heatmap", data, 30) + + return jsonify({"code": 1, "msg": "success", "data": data}) + + except Exception as e: + logger.error(f"market_heatmap failed: {e}", exc_info=True) + return jsonify({"code": 0, "msg": str(e), "data": None}), 500 + + +@global_market_bp.route("/news", methods=["GET"]) +@login_required +def market_news(): + """ + Get financial news from various sources. + Query params: + - lang: 'cn', 'en', or 'all' (default: 'all') + """ + try: + lang = request.args.get("lang", "all") + cache_key = f"market_news_{lang}" + + cached = _get_cached(cache_key, 180) # 3 minutes cache for news + if cached: + return jsonify({"code": 1, "msg": "success", "data": cached}) + + news = _fetch_financial_news(lang) + _set_cached(cache_key, news, 180) + + return jsonify({"code": 1, "msg": "success", "data": news}) + + except Exception as e: + logger.error(f"market_news failed: {e}", exc_info=True) + return jsonify({"code": 0, "msg": str(e), "data": None}), 500 + + +@global_market_bp.route("/calendar", methods=["GET"]) +@login_required +def economic_calendar(): + """ + Get economic calendar events with impact indicators. + """ + try: + cached = _get_cached("economic_calendar", 3600) # 1 hour cache + if cached: + return jsonify({"code": 1, "msg": "success", "data": cached}) + + events = _get_economic_calendar() + _set_cached("economic_calendar", events, 3600) + + return jsonify({"code": 1, "msg": "success", "data": events}) + + except Exception as e: + logger.error(f"economic_calendar failed: {e}", exc_info=True) + return jsonify({"code": 0, "msg": str(e), "data": None}), 500 + + +@global_market_bp.route("/sentiment", methods=["GET"]) +@login_required +def market_sentiment(): + """ + Get comprehensive market sentiment indicators. + Includes: Fear & Greed, VIX, DXY, Yield Curve, VXN, GVZ, VIX Term Structure. + """ + try: + # 缓存5分钟，因为这些数据不会频繁变化 + cached = _get_cached("market_sentiment", 300) + if cached: + logger.debug("Returning cached sentiment data") + return jsonify({"code": 1, "msg": "success", "data": cached}) + + logger.info("Fetching fresh sentiment data (comprehensive)") + + # Fetch all indicators in parallel + with ThreadPoolExecutor(max_workers=7) as executor: + futures = { + executor.submit(_fetch_fear_greed_index): "fear_greed", + executor.submit(_fetch_vix): "vix", + executor.submit(_fetch_dollar_index): "dxy", + executor.submit(_fetch_yield_curve): "yield_curve", + executor.submit(_fetch_vxn): "vxn", + executor.submit(_fetch_gvz): "gvz", + executor.submit(_fetch_put_call_ratio): "vix_term", + } + + results = {} + for future in as_completed(futures): + key = futures[future] + try: + results[key] = future.result() + except Exception as e: + logger.error(f"Failed to fetch {key}: {e}") + results[key] = None + + # Log summary + logger.info(f"Sentiment data fetched: Fear&Greed={results.get('fear_greed', {}).get('value')}, " + f"VIX={results.get('vix', {}).get('value')}, DXY={results.get('dxy', {}).get('value')}") + + data = { + "fear_greed": results.get("fear_greed") or {"value": 50, "classification": "Neutral"}, + "vix": results.get("vix") or {"value": 0, "level": "unknown"}, + "dxy": results.get("dxy") or {"value": 0, "level": "unknown"}, + "yield_curve": results.get("yield_curve") or {"spread": 0, "level": "unknown"}, + "vxn": results.get("vxn") or {"value": 0, "level": "unknown"}, + "gvz": results.get("gvz") or {"value": 0, "level": "unknown"}, + "vix_term": results.get("vix_term") or {"value": 1.0, "level": "unknown"}, + "timestamp": int(time.time()) + } + + _set_cached("market_sentiment", data, 300) + + return jsonify({"code": 1, "msg": "success", "data": data}) + + except Exception as e: + logger.error(f"market_sentiment failed: {e}", exc_info=True) + return jsonify({"code": 0, "msg": str(e), "data": None}), 500 + + +@global_market_bp.route("/opportunities", methods=["GET"]) +@login_required +def trading_opportunities(): + """ + Scan for trading opportunities based on technical indicators. + """ + try: + cached = _get_cached("trading_opportunities", 60) + if cached: + return jsonify({"code": 1, "msg": "success", "data": cached}) + + opportunities = [] + + # Get crypto data + crypto_data = _get_cached("crypto_prices") + if not crypto_data: + crypto_data = _fetch_crypto_prices() + + # Analyze crypto for opportunities + for coin in crypto_data[:15]: + change = coin.get("change_24h", 0) + change_7d = coin.get("change_7d", 0) + symbol = coin.get("symbol", "") + name = coin.get("name", "") + price = coin.get("price", 0) + + signal = None + strength = "medium" + reason = "" + impact = "neutral" + + if change > 15: + signal = "overbought" + strength = "strong" + reason = f"24h涨幅{change:.1f}%，7日涨幅{change_7d:.1f}%，短期超买风险" + impact = "bearish" + elif change > 8: + signal = "bullish_momentum" + strength = "medium" + reason = f"24h涨幅{change:.1f}%，上涨动能强劲" + impact = "bullish" + elif change < -15: + signal = "oversold" + strength = "strong" + reason = f"24h跌幅{abs(change):.1f}%，可能超卖反弹" + impact = "bullish" + elif change < -8: + signal = "bearish_momentum" + strength = "medium" + reason = f"24h跌幅{abs(change):.1f}%，下跌趋势明显" + impact = "bearish" + + if signal: + opportunities.append({ + "symbol": symbol, + "name": name, + "price": price, + "change_24h": change, + "change_7d": change_7d, + "signal": signal, + "strength": strength, + "reason": reason, + "impact": impact, + "market": "crypto", + "timestamp": int(time.time()) + }) + + # Sort by absolute change + opportunities.sort(key=lambda x: abs(x.get("change_24h", 0)), reverse=True) + + _set_cached("trading_opportunities", opportunities, 60) + + return jsonify({"code": 1, "msg": "success", "data": opportunities}) + + except Exception as e: + logger.error(f"trading_opportunities failed: {e}", exc_info=True) + return jsonify({"code": 0, "msg": str(e), "data": None}), 500 + + +@global_market_bp.route("/refresh", methods=["POST"]) +@login_required +def refresh_data(): + """ + Force refresh all market data (clears cache). + """ + try: + global _cache + _cache = {} + return jsonify({"code": 1, "msg": "Cache cleared successfully", "data": None}) + except Exception as e: + logger.error(f"refresh_data failed: {e}", exc_info=True) + return jsonify({"code": 0, "msg": str(e), "data": None}), 500 diff --git a/backend_api_python/app/routes/market.py b/backend_api_python/app/routes/market.py index 4b694f3..622bcf0 100644 --- a/backend_api_python/app/routes/market.py +++ b/backend_api_python/app/routes/market.py @@ -66,7 +66,7 @@ def get_public_config(): 'google/gemini-2.5-pro': 'Google: Gemini 2.5 Pro', 'openai/gpt-4o-mini': 'OpenAI: GPT-4o-mini', 'openai/gpt-5-mini': 'OpenAI: GPT-5 Mini', - 'openai/gpt-oss-120b': 'OpenAI: gpt-oss-120b', + 'openai/gpt-4.1-mini': 'OpenAI: GPT-4.1 Mini', 'deepseek/deepseek-v3.2': 'DeepSeek: DeepSeek V3.2', 'minimax/minimax-m2': 'MiniMax: MiniMax M2', 'anthropic/claude-sonnet-4': 'Anthropic: Claude Sonnet 4', diff --git a/backend_api_python/app/services/llm.py b/backend_api_python/app/services/llm.py index 3959888..c4911e3 100644 --- a/backend_api_python/app/services/llm.py +++ b/backend_api_python/app/services/llm.py @@ -387,8 +387,9 @@ class LLMService: logger.error(f"{p.value} API HTTP error ({current_model}): {error_detail}") last_error = str(e) - # Check for payment/quota errors - if e.response and e.response.status_code in (402, 429): + # Check for recoverable errors - try fallback model + # 402: Payment required, 403: Forbidden (invalid key), 404: Model not found, 429: Rate limit + if e.response and e.response.status_code in (402, 403, 404, 429): logger.warning(f"{p.value} returned {e.response.status_code} for model {current_model}; trying fallback...") continue diff --git a/backend_api_python/app/services/search.py b/backend_api_python/app/services/search.py index 8d2f3e8..f471246 100644 --- a/backend_api_python/app/services/search.py +++ b/backend_api_python/app/services/search.py @@ -1,19 +1,24 @@ """ Search service. -Integrates Google Custom Search (CSE) and Bing Search API. +Integrates Google Custom Search (CSE), Bing Search API, and DuckDuckGo (free fallback). Configuration is provided via environment variables (see env.example) through config_loader. """ import requests import json +import time from typing import List, Dict, Any, Optional from app.utils.logger import get_logger from app.utils.config_loader import load_addon_config logger = get_logger(__name__) +# Track Google API quota status +_google_quota_exhausted = False +_google_quota_reset_time = 0 + class SearchService: - """Search service.""" + """Search service with automatic fallback.""" def __init__(self): self._config = {} @@ -28,7 +33,7 @@ class SearchService: def search(self, query: str, num_results: int = None, date_restrict: str = None) -> List[Dict[str, Any]]: """ - Execute a web search. + Execute a web search with automatic fallback. Args: query: Search query @@ -38,18 +43,45 @@ class SearchService: Returns: List of search results """ + global _google_quota_exhausted, _google_quota_reset_time + # 重新加载配置以支持热更新 self._load_config() limit = num_results if num_results else self.max_results + # Check if Google quota has reset (after midnight UTC typically) + if _google_quota_exhausted and time.time() > _google_quota_reset_time: + _google_quota_exhausted = False + logger.info("Google API quota reset, re-enabling Google search") + + results = [] + if self.provider == 'bing': - return self._search_bing(query, limit) + results = self._search_bing(query, limit) + elif self.provider == 'duckduckgo': + results = self._search_duckduckgo(query, limit) else: - return self._search_google(query, limit, date_restrict) + # Google with fallback + if not _google_quota_exhausted: + results = self._search_google(query, limit, date_restrict) + + # If Google failed or returned empty, try fallbacks + if not results: + logger.info("Google search failed or empty, trying fallback search engines...") + # Try Bing first if configured + results = self._search_bing(query, limit) + + # If Bing also failed, try DuckDuckGo (free, no API key needed) + if not results: + results = self._search_duckduckgo(query, limit) + + return results def _search_google(self, query: str, num_results: int, date_restrict: str = None) -> List[Dict[str, Any]]: """Google Custom Search (CSE).""" + global _google_quota_exhausted, _google_quota_reset_time + api_key = self._config.get('google', {}).get('api_key') cx = self._config.get('google', {}).get('cx') @@ -71,17 +103,23 @@ class SearchService: params['dateRestrict'] = date_restrict try: - # logger.info(f"正在调用 Google Search API: q={query}, params={params}") response = requests.get(url, params=params, timeout=10) + + # Check for quota exceeded (429) + if response.status_code == 429: + logger.warning("Google Search API quota exceeded (429). Switching to fallback search engines.") + _google_quota_exhausted = True + # Set reset time to next day midnight UTC + import datetime + tomorrow = datetime.datetime.utcnow().replace(hour=0, minute=0, second=0, microsecond=0) + datetime.timedelta(days=1) + _google_quota_reset_time = tomorrow.timestamp() + return [] + response.raise_for_status() data = response.json() - # logger.info(f"Google Search 原始响应: {json.dumps(data, ensure_ascii=False)}") # 打印全部字符 - # logger.info(f"Google Search 原始响应: {json.dumps(data, ensure_ascii=False)[:500]}...") # 打印前500字符避免日志过大 - results = [] if 'items' in data: - # logger.info(f"Google Search 返回了 {len(data['items'])} 条结果") for item in data['items']: logger.debug(f"Search Item: {item.get('title')} - {item.get('link')}") results.append({ @@ -96,10 +134,20 @@ class SearchService: return results + except requests.exceptions.HTTPError as e: + if hasattr(e, 'response') and e.response is not None and e.response.status_code == 429: + logger.warning("Google Search API quota exceeded. Switching to fallback.") + _google_quota_exhausted = True + import datetime + tomorrow = datetime.datetime.utcnow().replace(hour=0, minute=0, second=0, microsecond=0) + datetime.timedelta(days=1) + _google_quota_reset_time = tomorrow.timestamp() + else: + logger.error(f"Google search failed: {e}") + if hasattr(e, 'response') and e.response is not None: + logger.error(f"Response: {e.response.text}") + return [] except Exception as e: logger.error(f"Google search failed: {e}") - if 'response' in locals(): - logger.error(f"Response: {response.text}") return [] def _search_bing(self, query: str, num_results: int) -> List[Dict[str, Any]]: @@ -140,3 +188,120 @@ class SearchService: logger.error(f"Bing search failed: {e}") return [] + def _search_duckduckgo(self, query: str, num_results: int) -> List[Dict[str, Any]]: + """ + DuckDuckGo search (free, no API key required). + Uses the DuckDuckGo HTML search endpoint. + """ + try: + # Use DuckDuckGo Instant Answer API + url = "https://api.duckduckgo.com/" + params = { + 'q': query, + 'format': 'json', + 'no_html': 1, + 'skip_disambig': 1 + } + + response = requests.get(url, params=params, timeout=10) + response.raise_for_status() + data = response.json() + + results = [] + + # Get results from RelatedTopics + related_topics = data.get('RelatedTopics', []) + for topic in related_topics[:num_results]: + if isinstance(topic, dict): + if 'FirstURL' in topic: + results.append({ + 'title': topic.get('Text', '')[:100], + 'link': topic.get('FirstURL', ''), + 'snippet': topic.get('Text', ''), + 'source': 'DuckDuckGo', + 'published': '' + }) + # Handle nested topics + elif 'Topics' in topic: + for sub_topic in topic['Topics']: + if len(results) >= num_results: + break + if 'FirstURL' in sub_topic: + results.append({ + 'title': sub_topic.get('Text', '')[:100], + 'link': sub_topic.get('FirstURL', ''), + 'snippet': sub_topic.get('Text', ''), + 'source': 'DuckDuckGo', + 'published': '' + }) + + # Also check AbstractURL and AbstractText + if data.get('AbstractURL') and len(results) < num_results: + results.insert(0, { + 'title': data.get('Heading', query), + 'link': data.get('AbstractURL', ''), + 'snippet': data.get('AbstractText', ''), + 'source': 'DuckDuckGo', + 'published': '' + }) + + # If no results from Instant Answer, try HTML scraping as fallback + if not results: + results = self._search_duckduckgo_html(query, num_results) + + if results: + logger.info(f"DuckDuckGo search returned {len(results)} results") + + return results[:num_results] + + except Exception as e: + logger.error(f"DuckDuckGo search failed: {e}") + # Try HTML fallback + return self._search_duckduckgo_html(query, num_results) + + def _search_duckduckgo_html(self, query: str, num_results: int) -> List[Dict[str, Any]]: + """ + DuckDuckGo HTML search fallback. + Scrapes the lite HTML version for better results. + """ + try: + url = "https://lite.duckduckgo.com/lite/" + headers = { + 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36' + } + data = {'q': query} + + response = requests.post(url, headers=headers, data=data, timeout=10) + response.raise_for_status() + + results = [] + + # Simple HTML parsing without BeautifulSoup + html = response.text + + # Find all result links (they have class="result-link") + import re + + # Pattern to find result entries + link_pattern = r']*class="result-link"[^>]*href="([^"]*)"[^>]*>([^<]*)' + snippet_pattern = r']*class="result-snippet"[^>]*>([^<]*)' + + links = re.findall(link_pattern, html) + snippets = re.findall(snippet_pattern, html) + + for i, (link, title) in enumerate(links[:num_results]): + snippet = snippets[i] if i < len(snippets) else '' + if link and title: + results.append({ + 'title': title.strip(), + 'link': link, + 'snippet': snippet.strip(), + 'source': 'DuckDuckGo', + 'published': '' + }) + + return results + + except Exception as e: + logger.error(f"DuckDuckGo HTML search failed: {e}") + return [] diff --git a/backend_api_python/migrations/add_notification_settings.sql b/backend_api_python/migrations/add_notification_settings.sql deleted file mode 100644 index a658ef6..0000000 --- a/backend_api_python/migrations/add_notification_settings.sql +++ /dev/null @@ -1,16 +0,0 @@ --- Migration: Add notification_settings column to qd_users table --- Run this if you see error: column "notification_settings" does not exist - --- Add notification_settings column (if not exists) -DO $$ -BEGIN - IF NOT EXISTS ( - SELECT 1 FROM information_schema.columns - WHERE table_name = 'qd_users' AND column_name = 'notification_settings' - ) THEN - ALTER TABLE qd_users ADD COLUMN notification_settings TEXT DEFAULT ''; 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diff --git a/quantdinger_vue/public/maps/world.json b/quantdinger_vue/public/maps/world.json new file mode 100644 index 0000000..9df0a61 --- /dev/null +++ b/quantdinger_vue/public/maps/world.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/quantdinger_vue/src/api/global-market.js b/quantdinger_vue/src/api/global-market.js new file mode 100644 index 0000000..94495e2 --- /dev/null +++ b/quantdinger_vue/src/api/global-market.js @@ -0,0 +1,79 @@ +/** + * Global Market Dashboard API + */ +import request from '@/utils/request' + +const BASE_URL = '/api/global-market' + +/** + * Get global market overview (indices, forex, crypto, commodities) + * Includes geo coordinates for world map display + */ +export function getMarketOverview () { + return request({ + url: `${BASE_URL}/overview`, + method: 'get' + }) +} + +/** + * Get market heatmap data (crypto, stock sectors, forex) + */ +export function getMarketHeatmap () { + return request({ + url: `${BASE_URL}/heatmap`, + method: 'get' + }) +} + +/** + * Get financial news - separated by language (cn/en) + * @param {string} lang - Language filter: 'cn', 'en', or 'all' (default) + */ +export function getMarketNews (lang = 'all') { + return request({ + url: `${BASE_URL}/news`, + method: 'get', + params: { lang } + }) +} + +/** + * Get economic calendar with impact indicators + */ +export function getEconomicCalendar () { + return request({ + url: `${BASE_URL}/calendar`, + method: 'get' + }) +} + +/** + * Get market sentiment (Fear & Greed Index, VIX) + */ +export function getMarketSentiment () { + return request({ + url: `${BASE_URL}/sentiment`, + method: 'get' + }) +} + +/** + * Get trading opportunities based on technical analysis + */ +export function getTradingOpportunities () { + return request({ + url: `${BASE_URL}/opportunities`, + method: 'get' + }) +} + +/** + * Force refresh all market data (clears cache) + */ +export function refreshMarketData () { + return request({ + url: `${BASE_URL}/refresh`, + method: 'post' + }) +} diff --git a/quantdinger_vue/src/config/router.config.js b/quantdinger_vue/src/config/router.config.js index 3ae59a2..355ac12 100644 --- a/quantdinger_vue/src/config/router.config.js +++ b/quantdinger_vue/src/config/router.config.js @@ -16,6 +16,13 @@ export const asyncRouterMap = [ component: () => import('@/views/dashboard'), meta: { title: 'menu.dashboard', keepAlive: true, icon: 'dashboard', permission: ['dashboard'] } }, + // 全球金融面板 + { + path: '/global-market', + name: 'GlobalMarket', + component: () => import('@/views/global-market'), + meta: { title: 'menu.dashboard.globalMarket', keepAlive: true, icon: 'global', permission: ['dashboard'] } + }, // AI 分析 { path: '/ai-analysis/:pageNo([1-9]\\d*)?', @@ -44,13 +51,6 @@ export const asyncRouterMap = [ component: () => import('@/views/portfolio'), meta: { title: 'menu.dashboard.portfolio', keepAlive: true, icon: 'fund', permission: ['dashboard'] } }, - // 指标社区（keepAlive disabled intentionally for iframe page) - { - path: '/indicator-community', - name: 'IndicatorCommunity', - component: () => import('@/views/indicator-community'), - meta: { title: 'menu.dashboard.community', keepAlive: false, icon: 'shop', permission: ['dashboard'] } - }, // 系统设置 (admin only) { path: '/settings', @@ -71,6 +71,13 @@ export const asyncRouterMap = [ name: 'Profile', component: () => import('@/views/profile'), meta: { title: 'menu.myProfile', keepAlive: false, icon: 'user', permission: ['dashboard'] } + }, + // 官方社区（keepAlive disabled intentionally for iframe page） + { + path: '/indicator-community', + name: 'IndicatorCommunity', + component: () => import('@/views/indicator-community'), + meta: { title: 'menu.dashboard.community', keepAlive: false, icon: 'shop', permission: ['dashboard'] } } // other diff --git a/quantdinger_vue/src/locales/lang/en-US.js b/quantdinger_vue/src/locales/lang/en-US.js index d566500..4534e79 100644 --- a/quantdinger_vue/src/locales/lang/en-US.js +++ b/quantdinger_vue/src/locales/lang/en-US.js @@ -26,9 +26,10 @@ const locale = { 'menu.dashboard': 'Dashboard', 'menu.dashboard.analysis': 'AI Analysis', 'menu.dashboard.indicator': 'Indicator Analysis', - 'menu.dashboard.community': 'Indicator Community', + 'menu.dashboard.community': 'Official Community', 'menu.dashboard.tradingAssistant': 'Trading Assistant', 'menu.dashboard.portfolio': 'Portfolio', + 'menu.dashboard.globalMarket': 'Global Market', 'menu.settings': 'Settings', 'menu.dashboard.aiTradingAssistant': 'AI Trading Assistant', 'menu.dashboard.signalRobot': 'Signal Robot', @@ -2353,6 +2354,8 @@ const locale = { 'portfolio.form.deselectAll': 'Deselect All', 'portfolio.form.selectedCount': '{count} of {total} selected', 'portfolio.form.pleaseSelectPositions': 'Please select at least one position to monitor', + 'portfolio.form.notificationFromProfile': 'Notifications will be sent to addresses configured in your profile', + 'portfolio.form.goToProfile': 'Go to settings', 'portfolio.message.loadFailed': 'Failed to load data', 'portfolio.message.saveSuccess': 'Saved successfully', 'portfolio.message.saveFailed': 'Failed to save', @@ -2581,7 +2584,64 @@ const locale = { 'settings.desc.CREDITS_REFERRAL_BONUS': 'Credits awarded to referrer when someone signs up with their referral code', 'settings.desc.VERIFICATION_CODE_MAX_ATTEMPTS': 'Maximum attempts to verify a code before lockout', 'settings.desc.VERIFICATION_CODE_LOCK_MINUTES': 'Lockout duration after exceeding max attempts', - 'settings.desc.RECHARGE_TELEGRAM_URL': 'Telegram customer service URL for recharge inquiries' + 'settings.desc.RECHARGE_TELEGRAM_URL': 'Telegram customer service URL for recharge inquiries', + + // Global Market + 'globalMarket.title': 'Global Market Dashboard', + 'globalMarket.lastUpdate': 'Last Update', + 'globalMarket.refresh': 'Refresh', + 'globalMarket.name': 'Name', + 'globalMarket.price': 'Price', + 'globalMarket.change': 'Change', + 'globalMarket.trend': 'Trend', + 'globalMarket.pair': 'Pair', + 'globalMarket.unit': 'Unit', + 'globalMarket.refreshSuccess': 'Data refreshed successfully', + 'globalMarket.refreshError': 'Failed to refresh data', + 'globalMarket.fetchError': 'Failed to fetch data', + 'globalMarket.loading': 'Loading...', + 'globalMarket.fearGreedIndex': 'Fear & Greed Index', + 'globalMarket.fearGreedTip': 'Fear & Greed Index measures market sentiment, 0 = Extreme Fear, 100 = Extreme Greed', + 'globalMarket.volatilityIndex': 'Volatility Index', + 'globalMarket.vixTitle': 'VIX Volatility Index', + 'globalMarket.vixTip': 'VIX measures expected market volatility, higher values indicate more market fear', + 'globalMarket.extremeFear': 'Extreme Fear', + 'globalMarket.fear': 'Fear', + 'globalMarket.neutral': 'Neutral', + 'globalMarket.greed': 'Greed', + 'globalMarket.extremeGreed': 'Extreme Greed', + 'globalMarket.marketOverview': 'Market Overview', + 'globalMarket.indices': 'Indices', + 'globalMarket.forex': 'Forex', + 'globalMarket.crypto': 'Crypto', + 'globalMarket.commodities': 'Commodities', + 'globalMarket.heatmap': 'Market Heatmap', + 'globalMarket.cryptoHeatmap': 'Crypto Heatmap', + 'globalMarket.sectorHeatmap': 'Sector Heatmap', + 'globalMarket.forexHeatmap': 'Forex Heatmap', + 'globalMarket.opportunities': 'Trading Opportunities', + 'globalMarket.noOpportunities': 'No significant opportunities detected', + 'globalMarket.financialNews': 'Financial News', + 'globalMarket.noNews': 'No news available', + 'globalMarket.economicCalendar': 'Economic Calendar', + 'globalMarket.noEvents': 'No events scheduled', + 'globalMarket.actual': 'Actual', + 'globalMarket.forecast': 'Forecast', + 'globalMarket.previous': 'Previous', + 'globalMarket.signal.bullish': 'Bullish Momentum', + 'globalMarket.signal.bearish': 'Bearish Momentum', + 'globalMarket.signal.overbought': 'Overbought Warning', + 'globalMarket.signal.oversold': 'Oversold Opportunity', + 'globalMarket.worldMap': 'Global Markets Map', + 'globalMarket.rising': 'Rising', + 'globalMarket.falling': 'Falling', + 'globalMarket.bullish': 'Bullish', + 'globalMarket.bearish': 'Bearish', + 'globalMarket.expectedImpact': 'Expected Impact', + 'globalMarket.aboveForecast': 'Above Forecast', + 'globalMarket.belowForecast': 'Below Forecast', + 'globalMarket.upcomingEvents': 'Upcoming Events', + 'globalMarket.releasedEvents': 'Released Data' } export default { diff --git a/quantdinger_vue/src/locales/lang/zh-CN.js b/quantdinger_vue/src/locales/lang/zh-CN.js index fa41e29..623ff25 100644 --- a/quantdinger_vue/src/locales/lang/zh-CN.js +++ b/quantdinger_vue/src/locales/lang/zh-CN.js @@ -25,10 +25,11 @@ const locale = { 'menu.home': '主页', 'menu.dashboard': '仪表盘', 'menu.dashboard.indicator': '指标分析', -'menu.dashboard.community': '指标社区', +'menu.dashboard.community': '官方社区', 'menu.dashboard.analysis': 'AI 分析', 'menu.dashboard.tradingAssistant': '交易助手', 'menu.dashboard.portfolio': '资产监测', +'menu.dashboard.globalMarket': '全球金融', 'menu.settings': '系统设置', 'menu.dashboard.aiTradingAssistant': 'AI交易助手', 'menu.dashboard.signalRobot': '信号机器人', @@ -2163,6 +2164,8 @@ const locale = { 'portfolio.form.deselectAll': '全不选', 'portfolio.form.selectedCount': '已选 {count}/{total}', 'portfolio.form.pleaseSelectPositions': '请至少选择一个持仓进行监控', +'portfolio.form.notificationFromProfile': '通知将发送到您在个人中心配置的地址', +'portfolio.form.goToProfile': '前往配置', 'portfolio.message.loadFailed': '加载数据失败', 'portfolio.message.saveSuccess': '保存成功', 'portfolio.message.saveFailed': '保存失败', @@ -2391,7 +2394,64 @@ const locale = { 'settings.desc.CREDITS_REFERRAL_BONUS': '用户通过邀请链接成功邀请新用户时，邀请人获得的积分奖励', 'settings.desc.VERIFICATION_CODE_MAX_ATTEMPTS': '验证码验证失败的最大尝试次数，超过后将锁定', 'settings.desc.VERIFICATION_CODE_LOCK_MINUTES': '验证码验证失败次数超过限制后的锁定时长（分钟）', -'settings.desc.RECHARGE_TELEGRAM_URL': '用户点击充值时跳转的Telegram客服链接' +'settings.desc.RECHARGE_TELEGRAM_URL': '用户点击充值时跳转的Telegram客服链接', + +// Global Market +'globalMarket.title': '全球金融面板', +'globalMarket.lastUpdate': '最后更新', +'globalMarket.refresh': '刷新数据', +'globalMarket.name': '名称', +'globalMarket.price': '价格', +'globalMarket.change': '涨跌', +'globalMarket.trend': '走势', +'globalMarket.pair': '货币对', +'globalMarket.unit': '单位', +'globalMarket.refreshSuccess': '数据刷新成功', +'globalMarket.refreshError': '数据刷新失败', +'globalMarket.fetchError': '获取数据失败', +'globalMarket.loading': '加载中...', +'globalMarket.fearGreedIndex': '恐惧贪婪指数', +'globalMarket.fearGreedTip': '恐惧贪婪指数衡量市场情绪，0表示极度恐惧，100表示极度贪婪', +'globalMarket.volatilityIndex': '波动率指数', +'globalMarket.vixTitle': 'VIX 波动率指数', +'globalMarket.vixTip': 'VIX指数衡量市场预期波动率，数值越高表示市场越恐慌', +'globalMarket.extremeFear': '极度恐惧', +'globalMarket.fear': '恐惧', +'globalMarket.neutral': '中性', +'globalMarket.greed': '贪婪', +'globalMarket.extremeGreed': '极度贪婪', +'globalMarket.marketOverview': '全球市场概览', +'globalMarket.indices': '主要指数', +'globalMarket.forex': '外汇市场', +'globalMarket.crypto': '加密货币', +'globalMarket.commodities': '大宗商品', +'globalMarket.heatmap': '市场热力图', +'globalMarket.cryptoHeatmap': '加密货币热力图', +'globalMarket.sectorHeatmap': '板块热力图', +'globalMarket.forexHeatmap': '外汇热力图', +'globalMarket.opportunities': '交易机会', +'globalMarket.noOpportunities': '暂无明显交易机会', +'globalMarket.financialNews': '财经资讯', +'globalMarket.noNews': '暂无新闻', +'globalMarket.economicCalendar': '财经日历', +'globalMarket.noEvents': '暂无事件', +'globalMarket.actual': '实际', +'globalMarket.forecast': '预期', +'globalMarket.previous': '前值', +'globalMarket.signal.bullish': '看涨趋势', +'globalMarket.signal.bearish': '看跌趋势', +'globalMarket.signal.overbought': '超买警告', +'globalMarket.signal.oversold': '超卖机会', +'globalMarket.worldMap': '全球市场地图', +'globalMarket.rising': '上涨', +'globalMarket.falling': '下跌', +'globalMarket.bullish': '利多', +'globalMarket.bearish': '利空', +'globalMarket.expectedImpact': '预期影响', +'globalMarket.aboveForecast': '高于预期', +'globalMarket.belowForecast': '低于预期', +'globalMarket.upcomingEvents': '即将公布', +'globalMarket.releasedEvents': '已公布数据' } export default { diff --git a/quantdinger_vue/src/views/global-market/index.vue b/quantdinger_vue/src/views/global-market/index.vue new file mode 100644 index 0000000..3244a3a --- /dev/null +++ b/quantdinger_vue/src/views/global-market/index.vue @@ -0,0 +1,2630 @@ + + + + + diff --git a/quantdinger_vue/src/views/portfolio/index.vue b/quantdinger_vue/src/views/portfolio/index.vue index f9bafab..d475e95 100644 --- a/quantdinger_vue/src/views/portfolio/index.vue +++ b/quantdinger_vue/src/views/portfolio/index.vue @@ -727,9 +727,9 @@ > @@ -806,9 +806,9 @@ > @@ -836,15 +836,21 @@ :key="pos.id" class="position-checkbox-item" > - - - {{ pos.market }} - {{ pos.symbol }} - {{ pos.name }} - - {{ pos.pnl >= 0 ? '+' : '' }}{{ formatNumber(pos.pnl_percent) }}% - - + +
+
+ {{ pos.market }} + {{ pos.symbol }} +
+
+ {{ pos.name }} +
+
+ + {{ pos.pnl >= 0 ? '+' : '' }}{{ formatNumber(pos.pnl_percent) }}% + +
+
@@ -2615,34 +2621,64 @@ export default { } } +.position-checkbox { + width: 100%; + + // Override Ant Design checkbox label width + ::v-deep .ant-checkbox + span { + width: calc(100% - 24px); + padding-left: 8px; + padding-right: 0; + } +} + .position-checkbox-label { - display: inline-flex; + display: flex; align-items: center; gap: 8px; font-size: 13px; + width: 100%; - .symbol { - font-weight: 600; - color: #262626; - min-width: 60px; + .position-left { + display: flex; + align-items: center; + gap: 6px; + flex-shrink: 0; + + .symbol { + font-weight: 600; + color: #262626; + min-width: 50px; + } } - .name { - color: #8c8c8c; - font-size: 12px; + .position-middle { flex: 1; + min-width: 0; overflow: hidden; - text-overflow: ellipsis; - white-space: nowrap; - max-width: 120px; + + .name { + color: #8c8c8c; + font-size: 12px; + display: block; + overflow: hidden; + text-overflow: ellipsis; + white-space: nowrap; + } } - .pnl { - font-weight: 500; - font-size: 12px; + .position-right { + flex-shrink: 0; + margin-left: auto; - &.positive { color: @green; } - &.negative { color: @red; } + .pnl { + font-weight: 500; + font-size: 12px; + white-space: nowrap; + + &.positive { color: @green; } + &.negative { color: @red; } + } } } @@ -2676,8 +2712,8 @@ export default { } .position-checkbox-label { - .symbol { color: #d1d4dc; } - .name { color: #868993; } + .position-left .symbol { color: #d1d4dc; } + .position-middle .name { color: #868993; } } .position-select-actions { diff --git a/quantdinger_vue/src/views/settings/index.vue b/quantdinger_vue/src/views/settings/index.vue index 459bf70..4dc407d 100644 --- a/quantdinger_vue/src/views/settings/index.vue +++ b/quantdinger_vue/src/views/settings/index.vue @@ -171,8 +171,12 @@ v-decorator="[item.key, { initialValue: getFieldValue(groupKey, item.key) || item.default }]" :placeholder="item.default ? `${$t('settings.default')}: ${item.default}` : $t('settings.pleaseSelect')" > - - {{ opt }} + + {{ opt.label }} @@ -249,6 +253,21 @@ export default { this.loadSettings() }, methods: { + // 兼容后端 schema options 两种格式： + // - string[]: ['openrouter','openai', ...] + // - {value,label}[]: [{value:'openrouter',label:'OpenRouter'}, ...] + getSelectOptions (options) { + const arr = Array.isArray(options) ? options : [] + return arr.map(opt => { + if (opt && typeof opt === 'object') { + return { + value: opt.value != null ? String(opt.value) : '', + label: opt.label != null ? String(opt.label) : String(opt.value || '') + } + } + return { value: String(opt), label: String(opt) } + }).filter(o => o.value !== '') + }, async loadSettings () { this.loading = true try { From 32a426d647417acdf3341cf97d9eb8b993767af7 Mon Sep 17 00:00:00 2001 From: TIANHE Date: Sat, 24 Jan 2026 23:57:39 +0800 Subject: [PATCH 2/4] new Signed-off-by: TIANHE --- README.md | 63 +++++++++++++++++++++++++++++-- README_CN.md | 63 ++++++++++++++++++++++++++++++- README_JA.md | 65 ++++++++++++++++++++++++++++++-- README_KO.md | 65 ++++++++++++++++++++++++++++++-- README_TW.md | 69 +++++++++++++++++++++++++++++++--- docs/screenshots/qfs_logo.png | Bin 0 -> 32174 bytes docs/screenshots/tuopu.png | Bin 0 -> 2428741 bytes 7 files changed, 309 insertions(+), 16 deletions(-) create mode 100644 docs/screenshots/qfs_logo.png create mode 100644 docs/screenshots/tuopu.png diff --git a/README.md b/README.md index 6a2b0ff..a935893 100644 --- a/README.md +++ b/README.md @@ -106,6 +106,14 @@ QuantDinger includes a built-in **LLM-based multi-agent research system** that g ## 📸 Visual Tour +
+

🗺️ System Architecture Overview

+

A comprehensive view of QuantDinger's AI-powered research, backtesting, and automated trading capabilities.

+ QuantDinger System Topology +
+ +
+

📊 Professional Quant Dashboard

Real-time monitoring of market dynamics, assets, and strategy status.

@@ -288,7 +296,29 @@ Config lives in `.env` (see `backend_api_python/env.example`): `ENABLE_AGENT_MEM - **Auto-Restore**: Resumes running strategies after system restarts - **Order Queue**: Background worker for order execution -### 7. Tech Stack +### 7. Multi-LLM Provider Support + +QuantDinger supports multiple AI providers with auto-detection: + +| Provider | Features | +|----------|----------| +| **OpenRouter** | Multi-model gateway (default), 100+ models | +| **OpenAI** | GPT-4o, GPT-4o-mini | +| **Google Gemini** | Gemini 1.5 Flash/Pro | +| **DeepSeek** | DeepSeek Chat (cost-effective) | +| **xAI Grok** | Grok Beta | + +Simply configure your preferred provider's API key in `.env`. The system auto-detects available providers. + +### 8. User Management & Security + +- **Multi-User Support**: PostgreSQL-backed user accounts with role-based permissions +- **OAuth Login**: Google and GitHub OAuth integration +- **Email Verification**: Registration and password reset via email codes +- **Security Features**: Cloudflare Turnstile captcha, IP/account rate limiting +- **Demo Mode**: Read-only mode for public demonstrations + +### 9. Tech Stack - **Backend**: Python (Flask) + PostgreSQL + Redis (optional) - **Frontend**: Vue 2 + Ant Design Vue + KlineCharts/ECharts @@ -708,10 +738,13 @@ Use `backend_api_python/env.example` as a template. Common settings include: - **Auth**: `SECRET_KEY`, `ADMIN_USER`, `ADMIN_PASSWORD` - **Server**: `PYTHON_API_HOST`, `PYTHON_API_PORT`, `PYTHON_API_DEBUG` - **Database**: `DATABASE_URL` (PostgreSQL connection string) -- **AI / LLM**: `OPENROUTER_API_KEY`, `OPENROUTER_MODEL`, timeouts +- **AI / LLM**: `LLM_PROVIDER` (openrouter/openai/google/deepseek/grok), provider-specific API keys +- **OAuth**: `GOOGLE_CLIENT_ID`, `GOOGLE_CLIENT_SECRET`, `GITHUB_CLIENT_ID`, `GITHUB_CLIENT_SECRET` +- **Security**: `TURNSTILE_SITE_KEY`, `TURNSTILE_SECRET_KEY`, `ENABLE_REGISTRATION` - **Web search**: `SEARCH_PROVIDER`, `SEARCH_GOOGLE_*`, `SEARCH_BING_API_KEY` +- **Order Execution**: `ORDER_MODE` (maker/market), `MAKER_WAIT_SEC`, `MAKER_OFFSET_BPS` - **Proxy (optional)**: `PROXY_PORT` or `PROXY_URL` -- **Workers**: `ENABLE_PENDING_ORDER_WORKER`, `DISABLE_RESTORE_RUNNING_STRATEGIES` +- **Workers**: `ENABLE_PENDING_ORDER_WORKER`, `ENABLE_PORTFOLIO_MONITOR` --- @@ -823,6 +856,30 @@ Your contributions help us maintain and improve QuantDinger. --- +### 🎓 Supporting Partners + +We are proud to be supported by academic institutions and organizations advancing quantitative finance education and research. + +
+ + + + +
+ + Indiana University Quantitative Finance Society + +

+ Quantitative Finance Society (QFS)
+ Indiana University Bloomington
+ Fostering the next generation of quantitative finance professionals +
+
+ +> 💡 **Interested in becoming a supporting partner?** We welcome collaborations with universities, research institutions, and organizations. Contact us at [brokermr810@gmail.com](mailto:brokermr810@gmail.com) or via [Telegram](https://t.me/worldinbroker). + +--- + ### Acknowledgements QuantDinger stands on the shoulders of great open-source projects: diff --git a/README_CN.md b/README_CN.md index f9be31d..15f9468 100644 --- a/README_CN.md +++ b/README_CN.md @@ -106,6 +106,14 @@ QuantDinger 包含一个内置的**基于 LLM 的多智能体研究系统**， ## 📸 功能预览 +
+

🗺️ 系统架构总览

+

QuantDinger AI 驱动的研究、回测和自动化交易功能全景图。

+ QuantDinger 系统拓扑图 +
+ +
+

📊 专业量化仪表盘

实时监控市场动态、资产状况和策略状态。

@@ -326,7 +334,29 @@ score = w_{sim}\cdot sim + w_{recency}\cdot recency + w_{returns}\cdot returns\_ - **自动恢复**：系统重启后恢复运行中的策略 - **订单队列**：后台工作线程用于订单执行 -### 7. 技术栈 +### 7. 多LLM提供商支持 + +QuantDinger 支持多个 AI 提供商，具备自动检测功能： + +| 提供商 | 特点 | +|--------|------| +| **OpenRouter** | 多模型网关（默认），100+ 模型 | +| **OpenAI** | GPT-4o, GPT-4o-mini | +| **Google Gemini** | Gemini 1.5 Flash/Pro | +| **DeepSeek** | DeepSeek Chat（性价比高） | +| **xAI Grok** | Grok Beta | + +只需在 `.env` 中配置您首选提供商的 API 密钥，系统会自动检测可用提供商。 + +### 8. 用户管理与安全 + +- **多用户支持**：基于 PostgreSQL 的用户账户，支持基于角色的权限管理 +- **OAuth 登录**：Google 和 GitHub OAuth 集成 +- **邮箱验证**：通过邮箱验证码进行注册和密码重置 +- **安全功能**：Cloudflare Turnstile 人机验证、IP/账户速率限制 +- **演示模式**：用于公开演示的只读模式 + +### 9. 技术栈 - **后端**：Python (Flask) + PostgreSQL + Redis（可选） - **前端**：Vue 2 + Ant Design Vue + KlineCharts/ECharts @@ -535,9 +565,14 @@ npm run serve - **认证**: `SECRET_KEY`, `ADMIN_USER`, `ADMIN_PASSWORD` - **服务器**: `PYTHON_API_HOST`, `PYTHON_API_PORT`, `PYTHON_API_DEBUG` -- **AI / LLM**: `OPENROUTER_API_KEY`, `OPENROUTER_MODEL` +- **数据库**: `DATABASE_URL` (PostgreSQL 连接字符串) +- **AI / LLM**: `LLM_PROVIDER` (openrouter/openai/google/deepseek/grok), 各提供商 API 密钥 +- **OAuth**: `GOOGLE_CLIENT_ID`, `GOOGLE_CLIENT_SECRET`, `GITHUB_CLIENT_ID`, `GITHUB_CLIENT_SECRET` +- **安全**: `TURNSTILE_SITE_KEY`, `TURNSTILE_SECRET_KEY`, `ENABLE_REGISTRATION` - **网络搜索**: `SEARCH_PROVIDER`, `SEARCH_GOOGLE_*`, `SEARCH_BING_API_KEY` +- **订单执行**: `ORDER_MODE` (maker/market), `MAKER_WAIT_SEC`, `MAKER_OFFSET_BPS` - **代理 (可选)**: `PROXY_PORT` 或 `PROXY_URL` +- **后台服务**: `ENABLE_PENDING_ORDER_WORKER`, `ENABLE_PORTFOLIO_MONITOR` --- @@ -632,6 +667,30 @@ QuantDinger 的代码使用 **Apache License 2.0** 授权。但需要注意：** --- +### 🎓 支持伙伴 + +我们很荣幸获得推动量化金融教育和研究的学术机构和组织的支持。 + +
+ + + + +
+ + 印第安纳大学量化金融学会 + +

+ 量化金融学会 (QFS)
+ 印第安纳大学布卢明顿分校
+ 培养下一代量化金融专业人才 +
+
+ +> 💡 **有兴趣成为支持伙伴吗？** 我们欢迎与大学、研究机构和组织合作。请通过 [brokermr810@gmail.com](mailto:brokermr810@gmail.com) 或 [Telegram](https://t.me/worldinbroker) 联系我们。 + +--- + ### 致谢 QuantDinger 站在这些伟大的开源项目肩膀之上：Flask, Pandas, CCXT, Vue.js, Ant Design Vue, KlineCharts 等。 diff --git a/README_JA.md b/README_JA.md index 205ce93..eebb5d1 100644 --- a/README_JA.md +++ b/README_JA.md @@ -106,6 +106,14 @@ QuantDingerには、ウェブから金融情報を収集し、ローカル市場 ## 📸 ビジュアルツアー +
+

🗺️ システムアーキテクチャ概要

+

QuantDinger の AI 駆動型リサーチ、バックテスト、自動取引機能の全体像。

+ QuantDinger システムトポロジー +
+ +
+

📊 プロフェッショナル・クオンツダッシュボード

市場の動向、資産、戦略ステータスをリアルタイムで監視。

@@ -296,9 +304,31 @@ score = w_{sim}\cdot sim + w_{recency}\cdot recency + w_{returns}\cdot returns\_ - **自動復元**: システム再起動後に実行中の戦略を再開 - **注文キュー**: 注文実行のためのバックグラウンドワーカー -### 7. 技術スタック +### 7. マルチLLMプロバイダーサポート -- **バックエンド**: Python (Flask) + SQLite + Redis（オプション） +QuantDinger は複数の AI プロバイダーをサポートし、自動検出機能を備えています： + +| プロバイダー | 特徴 | +|------------|------| +| **OpenRouter** | マルチモデルゲートウェイ（デフォルト）、100+ モデル | +| **OpenAI** | GPT-4o, GPT-4o-mini | +| **Google Gemini** | Gemini 1.5 Flash/Pro | +| **DeepSeek** | DeepSeek Chat（コスパ良好） | +| **xAI Grok** | Grok Beta | + +`.env` でお好みのプロバイダーの API キーを設定するだけで、システムが利用可能なプロバイダーを自動検出します。 + +### 8. ユーザー管理とセキュリティ + +- **マルチユーザーサポート**：PostgreSQL ベースのユーザーアカウント、ロールベースの権限管理 +- **OAuth ログイン**：Google および GitHub OAuth 統合 +- **メール認証**：メール認証コードによる登録とパスワードリセット +- **セキュリティ機能**：Cloudflare Turnstile キャプチャ、IP/アカウントレート制限 +- **デモモード**：公開デモ用の読み取り専用モード + +### 9. 技術スタック + +- **バックエンド**: Python (Flask) + PostgreSQL + Redis（オプション） - **フロントエンド**: Vue 2 + Ant Design Vue + KlineCharts/ECharts - **デプロイ**: Docker Compose @@ -491,9 +521,14 @@ npm run serve - **認証**: `SECRET_KEY`, `ADMIN_USER`, `ADMIN_PASSWORD` - **サーバー**: `PYTHON_API_HOST`, `PYTHON_API_PORT`, `PYTHON_API_DEBUG` -- **AI / LLM**: `OPENROUTER_API_KEY`, `OPENROUTER_MODEL` +- **データベース**: `DATABASE_URL` (PostgreSQL 接続文字列) +- **AI / LLM**: `LLM_PROVIDER` (openrouter/openai/google/deepseek/grok), 各プロバイダー API キー +- **OAuth**: `GOOGLE_CLIENT_ID`, `GOOGLE_CLIENT_SECRET`, `GITHUB_CLIENT_ID`, `GITHUB_CLIENT_SECRET` +- **セキュリティ**: `TURNSTILE_SITE_KEY`, `TURNSTILE_SECRET_KEY`, `ENABLE_REGISTRATION` - **ウェブ検索**: `SEARCH_PROVIDER`, `SEARCH_GOOGLE_*`, `SEARCH_BING_API_KEY` +- **注文執行**: `ORDER_MODE` (maker/market), `MAKER_WAIT_SEC`, `MAKER_OFFSET_BPS` - **プロキシ (オプション)**: `PROXY_PORT` または `PROXY_URL` +- **バックグラウンドサービス**: `ENABLE_PENDING_ORDER_WORKER`, `ENABLE_PORTFOLIO_MONITOR` --- @@ -588,6 +623,30 @@ QuantDinger のコードは **Apache License 2.0** で提供されています --- +### 🎓 サポートパートナー + +量的金融の教育と研究を推進する学術機関や組織からのサポートを光栄に思います。 + +
+ + + + +
+ + インディアナ大学量的金融学会 + +

+ 量的金融学会 (QFS)
+ インディアナ大学ブルーミントン校
+ 次世代の量的金融専門家を育成 +
+
+ +> 💡 **サポートパートナーになりませんか？** 大学、研究機関、組織との協力を歓迎します。[brokermr810@gmail.com](mailto:brokermr810@gmail.com) または [Telegram](https://t.me/worldinbroker) でお問い合わせください。 + +--- + ### 謝辞 QuantDingerは、Flask, Pandas, CCXT, Vue.js, Ant Design Vue, KlineChartsなどの素晴らしいオープンソースプロジェクトの上に成り立っています。 diff --git a/README_KO.md b/README_KO.md index ea6a11c..1278294 100644 --- a/README_KO.md +++ b/README_KO.md @@ -106,6 +106,14 @@ QuantDinger는 웹에서 금융 정보를 수집하고, 로컬 시장 데이터 ## 📸 비주얼 투어 +
+

🗺️ 시스템 아키텍처 개요

+

QuantDinger의 AI 기반 리서치, 백테스팅 및 자동화 거래 기능 전체 개요.

+ QuantDinger 시스템 토폴로지 +
+ +
+

📊 전문 퀀트 대시보드

시장 역학, 자산 및 전략 상태에 대한 실시간 모니터링.

@@ -296,9 +304,31 @@ score = w_{sim}\cdot sim + w_{recency}\cdot recency + w_{returns}\cdot returns\_ - **자동 복구**: 시스템 재시작 후 실행 중인 전략 재개 - **주문 대기열**: 주문 실행을 위한 백그라운드 워커 -### 7. 기술 스택 +### 7. 멀티 LLM 제공자 지원 -- **백엔드**: Python (Flask) + SQLite + Redis（옵션） +QuantDinger는 자동 감지 기능을 갖춘 여러 AI 제공자를 지원합니다: + +| 제공자 | 특징 | +|--------|------| +| **OpenRouter** | 멀티모델 게이트웨이(기본값), 100+ 모델 | +| **OpenAI** | GPT-4o, GPT-4o-mini | +| **Google Gemini** | Gemini 1.5 Flash/Pro | +| **DeepSeek** | DeepSeek Chat(가성비 좋음) | +| **xAI Grok** | Grok Beta | + +`.env`에서 선호하는 제공자의 API 키만 설정하면 시스템이 사용 가능한 제공자를 자동 감지합니다. + +### 8. 사용자 관리 및 보안 + +- **멀티유저 지원**: PostgreSQL 기반 사용자 계정, 역할 기반 권한 관리 +- **OAuth 로그인**: Google 및 GitHub OAuth 통합 +- **이메일 인증**: 이메일 인증 코드를 통한 등록 및 비밀번호 재설정 +- **보안 기능**: Cloudflare Turnstile 캡차, IP/계정 속도 제한 +- **데모 모드**: 공개 데모를 위한 읽기 전용 모드 + +### 9. 기술 스택 + +- **백엔드**: Python (Flask) + PostgreSQL + Redis（옵션） - **프론트엔드**: Vue 2 + Ant Design Vue + KlineCharts/ECharts - **배포**: Docker Compose @@ -504,9 +534,14 @@ npm run serve - **인증**: `SECRET_KEY`, `ADMIN_USER`, `ADMIN_PASSWORD` - **서버**: `PYTHON_API_HOST`, `PYTHON_API_PORT`, `PYTHON_API_DEBUG` -- **AI / LLM**: `OPENROUTER_API_KEY`, `OPENROUTER_MODEL` +- **데이터베이스**: `DATABASE_URL` (PostgreSQL 연결 문자열) +- **AI / LLM**: `LLM_PROVIDER` (openrouter/openai/google/deepseek/grok), 각 제공자 API 키 +- **OAuth**: `GOOGLE_CLIENT_ID`, `GOOGLE_CLIENT_SECRET`, `GITHUB_CLIENT_ID`, `GITHUB_CLIENT_SECRET` +- **보안**: `TURNSTILE_SITE_KEY`, `TURNSTILE_SECRET_KEY`, `ENABLE_REGISTRATION` - **웹 검색**: `SEARCH_PROVIDER`, `SEARCH_GOOGLE_*`, `SEARCH_BING_API_KEY` +- **주문 실행**: `ORDER_MODE` (maker/market), `MAKER_WAIT_SEC`, `MAKER_OFFSET_BPS` - **프록시 (옵션)**: `PROXY_PORT` 또는 `PROXY_URL` +- **백그라운드 서비스**: `ENABLE_PENDING_ORDER_WORKER`, `ENABLE_PORTFOLIO_MONITOR` --- @@ -601,6 +636,30 @@ QuantDinger의 코드는 **Apache License 2.0**으로 제공됩니다. 다만 ** --- +### 🎓 지원 파트너 + +양적 금융 교육 및 연구를 발전시키는 학술 기관과 조직의 지원을 받게 되어 자랑스럽습니다. + +
+ + + + +
+ + 인디애나 대학교 양적금융학회 + +

+ 양적금융학회 (QFS)
+ 인디애나 대학교 블루밍턴
+ 차세대 양적 금융 전문가 양성 +
+
+ +> 💡 **지원 파트너가 되는 데 관심이 있으신가요?** 대학, 연구 기관 및 조직과의 협력을 환영합니다. [brokermr810@gmail.com](mailto:brokermr810@gmail.com) 또는 [Telegram](https://t.me/worldinbroker)으로 연락주세요. + +--- + ### 감사의 말 QuantDinger는 Flask, Pandas, CCXT, Vue.js, Ant Design Vue, KlineCharts 등과 같은 훌륭한 오픈 소스 프로젝트의 어깨 위에 서 있습니다. diff --git a/README_TW.md b/README_TW.md index a85b790..ec57a9d 100644 --- a/README_TW.md +++ b/README_TW.md @@ -106,6 +106,14 @@ QuantDinger 包含一個內置的**基於 LLM 的多智能體研究系統**， ## 📸 功能預覽 +
+

🗺️ 系統架構總覽

+

QuantDinger AI 驅動的研究、回測和自動化交易功能全景圖。

+ QuantDinger 系統拓撲圖 +
+ +
+

📊 專業量化儀表盤

實時監控市場動態、資產狀況和策略狀態。

@@ -296,9 +304,31 @@ score = w_{sim}\cdot sim + w_{recency}\cdot recency + w_{returns}\cdot returns\_ - **自動恢復**：系統重啟後恢復運行中的策略 - **訂單隊列**：後台工作線程用於訂單執行 -### 7. 技術棧 +### 7. 多LLM提供商支援 -- **後端**：Python (Flask) + SQLite + Redis（可選） +QuantDinger 支援多個 AI 提供商，具備自動檢測功能： + +| 提供商 | 特點 | +|--------|------| +| **OpenRouter** | 多模型閘道（預設），100+ 模型 | +| **OpenAI** | GPT-4o, GPT-4o-mini | +| **Google Gemini** | Gemini 1.5 Flash/Pro | +| **DeepSeek** | DeepSeek Chat（高性價比） | +| **xAI Grok** | Grok Beta | + +只需在 `.env` 中配置您首選提供商的 API 金鑰，系統會自動檢測可用提供商。 + +### 8. 使用者管理與安全 + +- **多使用者支援**：基於 PostgreSQL 的使用者帳戶，支援基於角色的權限管理 +- **OAuth 登入**：Google 和 GitHub OAuth 整合 +- **郵箱驗證**：透過郵箱驗證碼進行註冊和密碼重設 +- **安全功能**：Cloudflare Turnstile 人機驗證、IP/帳戶速率限制 +- **示範模式**：用於公開示範的唯讀模式 + +### 9. 技術棧 + +- **後端**：Python (Flask) + PostgreSQL + Redis（可選） - **前端**：Vue 2 + Ant Design Vue + KlineCharts/ECharts - **部署**：Docker Compose @@ -504,10 +534,15 @@ npm run serve 使用 `backend_api_python/env.example` 作為模板。常用設置包括： - **認證**: `SECRET_KEY`, `ADMIN_USER`, `ADMIN_PASSWORD` -- **服務器**: `PYTHON_API_HOST`, `PYTHON_API_PORT`, `PYTHON_API_DEBUG` -- **AI / LLM**: `OPENROUTER_API_KEY`, `OPENROUTER_MODEL` -- **網絡搜索**: `SEARCH_PROVIDER`, `SEARCH_GOOGLE_*`, `SEARCH_BING_API_KEY` +- **伺服器**: `PYTHON_API_HOST`, `PYTHON_API_PORT`, `PYTHON_API_DEBUG` +- **資料庫**: `DATABASE_URL` (PostgreSQL 連接字串) +- **AI / LLM**: `LLM_PROVIDER` (openrouter/openai/google/deepseek/grok), 各提供商 API 金鑰 +- **OAuth**: `GOOGLE_CLIENT_ID`, `GOOGLE_CLIENT_SECRET`, `GITHUB_CLIENT_ID`, `GITHUB_CLIENT_SECRET` +- **安全**: `TURNSTILE_SITE_KEY`, `TURNSTILE_SECRET_KEY`, `ENABLE_REGISTRATION` +- **網路搜尋**: `SEARCH_PROVIDER`, `SEARCH_GOOGLE_*`, `SEARCH_BING_API_KEY` +- **訂單執行**: `ORDER_MODE` (maker/market), `MAKER_WAIT_SEC`, `MAKER_OFFSET_BPS` - **代理 (可選)**: `PROXY_PORT` 或 `PROXY_URL` +- **後台服務**: `ENABLE_PENDING_ORDER_WORKER`, `ENABLE_PORTFOLIO_MONITOR` --- @@ -602,6 +637,30 @@ QuantDinger 的代碼使用 **Apache License 2.0** 授權。但請注意：**Apa --- +### 🎓 支持夥伴 + +我們很榮幸獲得推動量化金融教育和研究的學術機構和組織的支持。 + +
+ + + + +
+ + 印第安納大學量化金融學會 + +

+ 量化金融學會 (QFS)
+ 印第安納大學布盧明頓分校
+ 培養下一代量化金融專業人才 +
+
+ +> 💡 **有興趣成為支持夥伴嗎？** 我們歡迎與大學、研究機構和組織合作。請透過 [brokermr810@gmail.com](mailto:brokermr810@gmail.com) 或 [Telegram](https://t.me/worldinbroker) 聯繫我們。 + +--- + ### 致謝 QuantDinger 站在這些偉大的開源項目肩膀之上：Flask, Pandas, CCXT, Vue.js, Ant Design Vue, KlineCharts 等。 diff --git a/docs/screenshots/qfs_logo.png b/docs/screenshots/qfs_logo.png new file mode 100644 index 0000000000000000000000000000000000000000..2204c45acf2f26ae88efb41898dc6b26df13b435 GIT binary patch literal 32174 zcmcG$g;N~e);-*~YZBZ&!GgP!;E+IYcMC&scMtAv!GpUqxLbm|yX)Zm=HBPIZ+-v3 zR|QPhRCiCGbM{$#t+n?M_C-+&1C!)z(ndoJ8k>dH~fLC9%p~wA`okI{ahKS z2z{7GQz$pQF$N+cBCTV={74i4yo@ihNtXP&{a3qcdU{q7Y5@W0DCy|9==k~Q z=xAw~C$KZv%5~Ex4Fd$CNEUN-UH1z>rT?tmrAJC+aEqSHtTlp*l`4_mG&(yoo1;Lr~GrTc*p^{|SuZ zx39t_F6)CO*~y^P*Q*wOr>9`d13vF#Up0lJX^hJ$96_3?nw76#rEbqeJda(Km95l3 zdS7FEjFIVR;bbInV*q4d0x5Wdhy%Q_fhESW3frrG$`gUQYZ7B}xlOyzkeyhVy)mB%D6_r{a?YR%H~kGfkHgC|Q^m0GnY(O@d} ztDnt%{8ko?kD&J79!0y!E$aV9-uMt$;xIEpAyde9re^KsaJ6~oN@-<@zb&hRt!TvI 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z@_~d|1@WJ~(yMjt0M@%XBp5)u&@z2^?vigo7kQz=otn~FJ%4*E)2P%wRD_^J+p8K8(^i$5wy_T|B;2KW=9bOy`#rKV-Amf~`{PCZp46-#D-e(x?{uSjD<(gz@GFNuT==IW=)b9NuucSe*O=Jd7l^i{SX zJ0i@jqV$GJQmsE7CmcB=hel_8zfSQ0x)P9xDE%D8l*LN8WH~JhQVku@(q;99%T;Jb zpQFFQlQ5z0R~b!W6}6Omq!#MVDqy{#v(MNjv0kfxO{LX}gDia^K04h_D3#W;bUqmp zUrBVOkZ4?&vlyB08}s(q6;Xa7q|LeBRAGzGBd{lmy%ZO&fkpo&+9rM@Zmz`ReLNCK&+k*yPMK_x36B#3NI;opT5<8>-qm%=QB1>2cE1H$OYJhOj(442>vrBB1~)8z#P}QM2#N<1No?koFu~RoI~#T*>~R zuA#FWniJA{tpib(cX~%_NbxbIMOMkfWz6VnPxcxxr2I~sW?4!0N-l_U5x%NUXbngS bAou?N=vV@~d)Us200000NkvXXu0mjf9ki^M literal 0 HcmV?d00001 From 528be54fe8e19cd9ba59a284cc26212e3569032e Mon Sep 17 00:00:00 2001 From: TIANHE Date: Sun, 25 Jan 2026 01:03:46 +0800 Subject: [PATCH 3/4] new Signed-off-by: TIANHE --- backend_api_python/app/routes/strategy.py | 30 ++++++++----- .../app/services/portfolio_monitor.py | 8 +++- .../app/services/trading_executor.py | 45 +++++++++++++------ 3 files changed, 57 insertions(+), 26 deletions(-) diff --git a/backend_api_python/app/routes/strategy.py b/backend_api_python/app/routes/strategy.py index a9b6834..17d7df5 100644 --- a/backend_api_python/app/routes/strategy.py +++ b/backend_api_python/app/routes/strategy.py @@ -816,9 +816,6 @@ def get_strategy_notifications(): user_strategy_ids = [r.get('id') for r in rows if r.get('id')] cur.close() - if not user_strategy_ids: - return jsonify({'code': 1, 'msg': 'success', 'data': {'items': []}}) - where = [] args = [] @@ -830,9 +827,15 @@ def get_strategy_notifications(): else: return jsonify({'code': 1, 'msg': 'success', 'data': {'items': []}}) else: - placeholders = ",".join(["?"] * len(user_strategy_ids)) - where.append(f"strategy_id IN ({placeholders})") - args.extend(user_strategy_ids) + if user_strategy_ids: + placeholders = ",".join(["?"] * len(user_strategy_ids)) + where.append(f"(strategy_id IN ({placeholders}) OR (strategy_id IS NULL AND user_id = ?))") + args.extend(user_strategy_ids) + args.append(user_id) + else: + # Only portfolio monitor notifications (strategy_id is NULL) + where.append("strategy_id IS NULL AND user_id = ?") + args.append(user_id) if since_id: where.append("id > ?") @@ -889,15 +892,18 @@ def mark_notification_read(): if not notification_id: return jsonify({'code': 0, 'msg': 'Missing id'}), 400 - # Only update notifications for user's strategies + # Update notifications for user's strategies OR portfolio monitor notifications with get_db_connection() as db: cur = db.cursor() cur.execute( """ UPDATE qd_strategy_notifications SET is_read = 1 - WHERE id = ? AND strategy_id IN (SELECT id FROM qd_strategies_trading WHERE user_id = ?) + WHERE id = ? AND ( + strategy_id IN (SELECT id FROM qd_strategies_trading WHERE user_id = ?) + OR (strategy_id IS NULL AND user_id = ?) + ) """, - (int(notification_id), user_id) + (int(notification_id), user_id, user_id) ) db.commit() cur.close() @@ -920,8 +926,9 @@ def mark_all_notifications_read(): """ UPDATE qd_strategy_notifications SET is_read = 1 WHERE strategy_id IN (SELECT id FROM qd_strategies_trading WHERE user_id = ?) + OR (strategy_id IS NULL AND user_id = ?) """, - (user_id,) + (user_id, user_id) ) db.commit() cur.close() @@ -944,8 +951,9 @@ def clear_notifications(): """ DELETE FROM qd_strategy_notifications WHERE strategy_id IN (SELECT id FROM qd_strategies_trading WHERE user_id = ?) + OR (strategy_id IS NULL AND user_id = ?) """, - (user_id,) + (user_id, user_id) ) db.commit() cur.close() diff --git a/backend_api_python/app/services/portfolio_monitor.py b/backend_api_python/app/services/portfolio_monitor.py index 0c35f03..9288153 100644 --- a/backend_api_python/app/services/portfolio_monitor.py +++ b/backend_api_python/app/services/portfolio_monitor.py @@ -768,8 +768,9 @@ def _send_monitor_notification( cur.close() elif ch == 'telegram': chat_id = targets.get('telegram', '') + token_override = targets.get('telegram_bot_token', '') if chat_id: - notifier._notify_telegram(chat_id=chat_id, text=f"{error_title}\n\n{error_msg}", parse_mode="HTML") + notifier._notify_telegram(chat_id=chat_id, text=f"{error_title}\n\n{error_msg}", token_override=token_override, parse_mode="HTML") elif ch == 'email': to_email = targets.get('email', '') if to_email: @@ -815,11 +816,13 @@ def _send_monitor_notification( elif ch == 'telegram': chat_id = targets.get('telegram', '') + token_override = targets.get('telegram_bot_token', '') if chat_id: # Use Telegram-optimized format notifier._notify_telegram( chat_id=chat_id, text=telegram_report, + token_override=token_override, parse_mode="HTML" ) @@ -1099,8 +1102,9 @@ def _check_position_alerts(): cur.close() elif ch == 'telegram': chat_id = targets.get('telegram', '') + token_override = targets.get('telegram_bot_token', '') if chat_id: - notifier._notify_telegram(chat_id=chat_id, text=alert_message, parse_mode="HTML") + notifier._notify_telegram(chat_id=chat_id, text=alert_message, token_override=token_override, parse_mode="HTML") elif ch == 'email': to_email = targets.get('email', '') if to_email: diff --git a/backend_api_python/app/services/trading_executor.py b/backend_api_python/app/services/trading_executor.py index 1c49b80..a026f29 100644 --- a/backend_api_python/app/services/trading_executor.py +++ b/backend_api_python/app/services/trading_executor.py @@ -52,29 +52,48 @@ class TradingExecutor: self._ensure_db_columns() def _ensure_db_columns(self): - """确保必要的数据库字段存在""" + """确保必要的数据库字段存在（支持 SQLite 和 PostgreSQL）""" try: + db_type = os.getenv('DB_TYPE', 'sqlite').lower() with get_db_connection() as db: cursor = db.cursor() + col_names = set() - # SQLite 兼容：使用 PRAGMA table_info 检查列是否存在 - try: - cursor.execute("PRAGMA table_info(qd_strategy_positions)") - cols = cursor.fetchall() or [] - col_names = {c.get('name') for c in cols if isinstance(c, dict)} - except Exception: - col_names = set() + if db_type == 'postgresql': + # PostgreSQL: 使用 information_schema 查询列 + try: + cursor.execute(""" + SELECT column_name FROM information_schema.columns + WHERE table_name = 'qd_strategy_positions' + """) + cols = cursor.fetchall() or [] + col_names = {c.get('column_name') or c.get('COLUMN_NAME') for c in cols if isinstance(c, dict)} + except Exception: + col_names = set() + else: + # SQLite: 使用 PRAGMA table_info + try: + cursor.execute("PRAGMA table_info(qd_strategy_positions)") + cols = cursor.fetchall() or [] + col_names = {c.get('name') for c in cols if isinstance(c, dict)} + except Exception: + col_names = set() if 'highest_price' not in col_names: - logger.info("Adding highest_price column to qd_strategy_positions (SQLite)...") - # SQLite 不支持 AFTER 子句，类型用 REAL 即可 - cursor.execute("ALTER TABLE qd_strategy_positions ADD COLUMN highest_price REAL DEFAULT 0") + logger.info(f"Adding highest_price column to qd_strategy_positions ({db_type})...") + if db_type == 'postgresql': + cursor.execute("ALTER TABLE qd_strategy_positions ADD COLUMN IF NOT EXISTS highest_price DOUBLE PRECISION DEFAULT 0") + else: + cursor.execute("ALTER TABLE qd_strategy_positions ADD COLUMN highest_price REAL DEFAULT 0") db.commit() logger.info("highest_price column added") if 'lowest_price' not in col_names: - logger.info("Adding lowest_price column to qd_strategy_positions (SQLite)...") - cursor.execute("ALTER TABLE qd_strategy_positions ADD COLUMN lowest_price REAL DEFAULT 0") + logger.info(f"Adding lowest_price column to qd_strategy_positions ({db_type})...") + if db_type == 'postgresql': + cursor.execute("ALTER TABLE qd_strategy_positions ADD COLUMN IF NOT EXISTS lowest_price DOUBLE PRECISION DEFAULT 0") + else: + cursor.execute("ALTER TABLE qd_strategy_positions ADD COLUMN lowest_price REAL DEFAULT 0") db.commit() logger.info("lowest_price column added") From 5df11e2491edde8c721669ad048344818d927a74 Mon Sep 17 00:00:00 2001 From: TIANHE Date: Sun, 25 Jan 2026 01:14:54 +0800 Subject: [PATCH 4/4] new Signed-off-by: TIANHE --- backend_api_python/app/routes/auth.py | 7 ++++++- backend_api_python/app/services/user_service.py | 7 ++++++- 2 files changed, 12 insertions(+), 2 deletions(-) diff --git a/backend_api_python/app/routes/auth.py b/backend_api_python/app/routes/auth.py index f25c195..0c4f8b4 100644 --- a/backend_api_python/app/routes/auth.py +++ b/backend_api_python/app/routes/auth.py @@ -379,9 +379,14 @@ def login_with_code(): (user['id'],) ) db.commit() + affected = cur.rowcount cur.close() + if affected == 0: + logger.error(f"Failed to update last_login_at: no rows affected for user_id={user['id']}") + else: + logger.info(f"Updated last_login_at for user_id={user['id']}") except Exception as e: - logger.warning(f"Failed to update last_login_at: {e}") + logger.error(f"Failed to update last_login_at for user_id={user.get('id')}: {e}") # Log login security.log_security_event('login_via_code', user['id'], ip_address, user_agent) diff --git a/backend_api_python/app/services/user_service.py b/backend_api_python/app/services/user_service.py index ecd0004..58d3b0b 100644 --- a/backend_api_python/app/services/user_service.py +++ b/backend_api_python/app/services/user_service.py @@ -170,9 +170,14 @@ class UserService: (user['id'],) ) db.commit() + affected = cur.rowcount cur.close() + if affected == 0: + logger.error(f"Failed to update last_login_at: no rows affected for user_id={user['id']}") + else: + logger.info(f"Updated last_login_at for user_id={user['id']}") except Exception as e: - logger.warning(f"Failed to update last_login_at: {e}") + logger.error(f"Failed to update last_login_at for user_id={user.get('id')}: {e}") # Remove password_hash from return value user.pop('password_hash', None)

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