gavindiaz/DinQuant
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

V2.2.1: Membership & Billing, USDT TRC20 payment, VIP free indicators, AI Trading Radar, simplified strategy creation, system settings simplification, bug fixes and UI improvements

Browse Source
This commit is contained in:
TIANHE
2026-02-27 01:57:04 +08:00
parent ae82cc0d4e
commit ffdd2ffbae
71 changed files with 4067 additions and 6073 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend_api_python/app/routes/global_market.py
+255 -112
View File
@@ -2,7 +2,7 @@
Global Market Dashboard APIs.
Provides aggregated global market data including:
- Major indices (US, China, Hong Kong, Europe, Japan)
- Major indices (US, Europe, Japan, Korea, Australia, India)
- Forex pairs
- Crypto prices
- Market heatmap data (crypto, stocks, forex)
@@ -53,7 +53,7 @@ CACHE_TTL = {
"market_news": 180, # 3分钟 - 新闻
"economic_calendar": 3600, # 1小时 - 日历事件
"market_sentiment": 21600, # 6小时 - 宏观情绪变化缓慢
"trading_opportunities": 60, # 1分钟 - 交易机会需要较新
"trading_opportunities": 3600, # 1小时 - 每小时更新一次
}
@@ -257,12 +257,6 @@ def _fetch_stock_indices() -> List[Dict[str, Any]]:
{"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},
@@ -977,12 +971,12 @@ def _fetch_financial_news(lang: str = "all") -> Dict[str, List[Dict[str, Any]]]:
# 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",
"美股市场最新消息",
"外汇市场分析",
"全球经济数据",
"期货市场动态",
]
# English news queries
@@ -1106,42 +1100,6 @@ def _get_economic_calendar() -> List[Dict[str, Any]]:
"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",
@@ -1634,80 +1592,265 @@ def market_sentiment():
return jsonify({"code": 0, "msg": str(e), "data": None}), 500
def _fetch_stock_opportunity_prices() -> List[Dict[str, Any]]:
"""Fetch popular US stock prices for opportunity scanning."""
stocks = [
{"symbol": "AAPL", "name": "Apple"},
{"symbol": "MSFT", "name": "Microsoft"},
{"symbol": "GOOGL", "name": "Alphabet"},
{"symbol": "AMZN", "name": "Amazon"},
{"symbol": "TSLA", "name": "Tesla"},
{"symbol": "NVDA", "name": "NVIDIA"},
{"symbol": "META", "name": "Meta"},
{"symbol": "NFLX", "name": "Netflix"},
{"symbol": "AMD", "name": "AMD"},
{"symbol": "CRM", "name": "Salesforce"},
{"symbol": "COIN", "name": "Coinbase"},
{"symbol": "BABA", "name": "Alibaba"},
{"symbol": "NIO", "name": "NIO"},
{"symbol": "PLTR", "name": "Palantir"},
{"symbol": "INTC", "name": "Intel"},
]
try:
import yfinance as yf
symbols = [s["symbol"] for s in stocks]
tickers = yf.Tickers(" ".join(symbols))
result = []
for stock in stocks:
try:
ticker = tickers.tickers.get(stock["symbol"])
if ticker:
hist = ticker.history(period="2d")
if len(hist) >= 2:
prev_close = float(hist["Close"].iloc[-2])
current = float(hist["Close"].iloc[-1])
change = ((current - prev_close) / prev_close) * 100
elif len(hist) == 1:
current = float(hist["Close"].iloc[-1])
change = 0
else:
continue
result.append({
"symbol": stock["symbol"],
"name": stock["name"],
"price": round(current, 2),
"change": round(change, 2)
})
except Exception as e:
logger.debug(f"Failed to fetch stock {stock['symbol']}: {e}")
return result
except Exception as e:
logger.error(f"Failed to fetch stock opportunity prices: {e}")
return []
def _analyze_opportunities_crypto(opportunities: list):
"""Scan crypto market for trading opportunities."""
crypto_data = _get_cached("crypto_prices")
if not crypto_data:
crypto_data = _fetch_crypto_prices()
if crypto_data:
_set_cached("crypto_prices", crypto_data)
for coin in (crypto_data or [])[:20]:
change = _safe_float(coin.get("change_24h", 0))
change_7d = _safe_float(coin.get("change_7d", 0))
symbol = coin.get("symbol", "")
name = coin.get("name", "")
price = _safe_float(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())
})
def _analyze_opportunities_stocks(opportunities: list):
"""Scan US stocks for trading opportunities."""
stock_data = _get_cached("stock_opportunity_prices")
if not stock_data:
stock_data = _fetch_stock_opportunity_prices()
if stock_data:
_set_cached("stock_opportunity_prices", stock_data, 3600)
for stock in (stock_data or []):
change = _safe_float(stock.get("change", 0))
symbol = stock.get("symbol", "")
name = stock.get("name", "")
price = _safe_float(stock.get("price", 0))
signal = None
strength = "medium"
reason = ""
impact = "neutral"
# US stocks: smaller thresholds than crypto
if change > 5:
signal = "overbought"
strength = "strong"
reason = f"日涨幅{change:.1f}%，短期涨幅较大，注意回调风险"
impact = "bearish"
elif change > 3:
signal = "bullish_momentum"
strength = "medium"
reason = f"日涨幅{change:.1f}%，上涨动能强劲"
impact = "bullish"
elif change < -5:
signal = "oversold"
strength = "strong"
reason = f"日跌幅{abs(change):.1f}%，可能超卖反弹"
impact = "bullish"
elif change < -3:
signal = "bearish_momentum"
strength = "medium"
reason = f"日跌幅{abs(change):.1f}%，下跌趋势明显"
impact = "bearish"
if signal:
opportunities.append({
"symbol": symbol,
"name": name,
"price": price,
"change_24h": change,
"signal": signal,
"strength": strength,
"reason": reason,
"impact": impact,
"market": "USStock",
"timestamp": int(time.time())
})
def _analyze_opportunities_forex(opportunities: list):
"""Scan forex pairs for trading opportunities."""
forex_data = _get_cached("forex_pairs")
if not forex_data:
forex_data = _fetch_forex_pairs()
if forex_data:
_set_cached("forex_pairs", forex_data, 3600)
for pair in (forex_data or []):
change = _safe_float(pair.get("change", 0))
symbol = pair.get("symbol", pair.get("name", ""))
name = pair.get("name_cn", pair.get("name", ""))
price = _safe_float(pair.get("price", 0))
signal = None
strength = "medium"
reason = ""
impact = "neutral"
# Forex: even smaller thresholds
if change > 1.5:
signal = "overbought"
strength = "strong"
reason = f"日涨幅{change:.2f}%，汇率波动剧烈，注意回调"
impact = "bearish"
elif change > 0.8:
signal = "bullish_momentum"
strength = "medium"
reason = f"日涨幅{change:.2f}%，上涨动能较强"
impact = "bullish"
elif change < -1.5:
signal = "oversold"
strength = "strong"
reason = f"日跌幅{abs(change):.2f}%，汇率波动剧烈，可能反弹"
impact = "bullish"
elif change < -0.8:
signal = "bearish_momentum"
strength = "medium"
reason = f"日跌幅{abs(change):.2f}%，下跌趋势明显"
impact = "bearish"
if signal:
opportunities.append({
"symbol": symbol,
"name": name,
"price": price,
"change_24h": change,
"signal": signal,
"strength": strength,
"reason": reason,
"impact": impact,
"market": "Forex",
"timestamp": int(time.time())
})
@global_market_bp.route("/opportunities", methods=["GET"])
@login_required
def trading_opportunities():
"""
Scan for trading opportunities based on technical indicators.
Scan for trading opportunities across Crypto, US Stocks, and Forex.
Cached for 1 hour. Pass ?force=true to skip cache.
"""
try:
cached = _get_cached("trading_opportunities", 60)
if cached:
return jsonify({"code": 1, "msg": "success", "data": cached})
force = request.args.get("force", "").lower() in ("true", "1")
if not force:
cached = _get_cached("trading_opportunities")
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
# 1) Crypto
_analyze_opportunities_crypto(opportunities)
# 2) US Stocks
_analyze_opportunities_stocks(opportunities)
# 3) Forex
_analyze_opportunities_forex(opportunities)
# Sort by absolute change descending
opportunities.sort(key=lambda x: abs(x.get("change_24h", 0)), reverse=True)
_set_cached("trading_opportunities", opportunities, 60)
_set_cached("trading_opportunities", opportunities, 3600)
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