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Refactor and translate comments and docstrings in utility modules to English for better clarity and maintainability. Update Gunicorn and application startup messages for consistency in language. Enhance documentation with English translations for better accessibility.

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dienakdz
2026-04-06 16:47:36 +07:00
parent 3ca291a346
commit 11e2e5aaa6
64 changed files with 2323 additions and 2336 deletions
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backend_api_python/app/routes/global_market.py
+40 -40
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@@ -38,22 +38,22 @@ logger = get_logger(__name__)
global_market_bp = Blueprint("global_market", __name__)
# Cache for market data (simple in-memory cache)
# 多用户场景下，合理的缓存可以大幅减少 API 请求
# In multi-user scenarios, reasonable caching can significantly reduce API requests.
_cache: Dict[str, Dict[str, Any]] = {}
_cache_ttl = 60 # Default 60 seconds cache
# 缓存时间配置（秒）
# Cache time configuration (seconds)
CACHE_TTL = {
"crypto_heatmap": 300, # 5分钟 - 加密货币变化快但热力图不需要实时
"forex_pairs": 120, # 2分钟 - 外汇日内波动较小
"stock_indices": 120, # 2分钟 - 指数变化较慢
"market_overview": 120, # 2分钟 - 概览数据
"market_heatmap": 120, # 2分钟 - 热力图
"commodities": 120, # 2分钟 - 大宗商品
"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": 3600, # 1小时 - 每小时更新一次
"crypto_heatmap": 300, # 5 minutes - Cryptocurrencies change fast but heatmaps don’t need to be real-time
"forex_pairs": 120, # 2 minutes - Forex intraday fluctuations are small
"stock_indices": 120, # 2 minutes - index changes slowly
"market_overview": 120, # 2 minutes - overview data
"market_heatmap": 120, # 2 minutes - heat map
"commodities": 120, # 2 minutes - Commodities
"market_news": 180, # 3 minutes - News
"economic_calendar": 3600, # 1 hour - calendar event
"market_sentiment": 21600, # 6 hours - Macro sentiment changes slowly
"trading_opportunities": 3600, # 1 hour - updated every hour
}
@@ -61,7 +61,7 @@ def _get_cached(key: str, ttl: int = None) -> Optional[Any]:
"""Get cached data if not expired."""
if key in _cache:
entry = _cache[key]
# 优先使用传入的 ttl，然后是 CACHE_TTL 配置，最后是默认值
# Use the incoming ttl first, then the CACHE_TTL configuration, then the default value
cache_ttl = ttl or CACHE_TTL.get(key, entry.get("ttl", _cache_ttl))
if time.time() - entry.get("ts", 0) < cache_ttl:
return entry.get("data")
@@ -253,7 +253,7 @@ def _fetch_crypto_prices() -> List[Dict[str, Any]]:
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
# US Markets - Coordinates are staggered to avoid overlap
{"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},
@@ -520,12 +520,12 @@ def _fetch_fear_greed_index() -> Dict[str, Any]:
def _fetch_vix() -> Dict[str, Any]:
"""Fetch VIX (CBOE Volatility Index) with multiple fallbacks."""
# 默认值 - 合理的市场中性水平
# Default - a reasonable market neutral level
DEFAULT_VIX = {"value": 18, "change": 0, "level": "low",
"interpretation": "低波动 - 市场稳定",
"interpretation_en": "Low - Market Stable"}
# 1) 尝试 yfinance
# 1) Try yfinance
try:
import yfinance as yf
logger.debug("Fetching VIX from yfinance")
@@ -551,10 +551,10 @@ def _fetch_vix() -> Dict[str, Any]:
except Exception as e:
logger.warning(f"yfinance VIX failed, trying akshare: {e}")
# 2) 尝试 Akshare (对中国服务器友好)
# 2) Try Akshare (friendly for Chinese servers)
try:
import akshare as ak
vix_df = ak.index_vix() # VIX指数
vix_df = ak.index_vix() # VIX index
if vix_df is not None and len(vix_df) > 0:
current = float(vix_df.iloc[-1]['close'])
prev_close = float(vix_df.iloc[-2]['close']) if len(vix_df) >= 2 else current
@@ -602,7 +602,7 @@ def _fetch_vix() -> Dict[str, Any]:
def _fetch_dollar_index() -> Dict[str, Any]:
"""Fetch US Dollar Index (DXY) with multiple fallbacks."""
# 默认值 - 合理的中性水平
# Default - reasonably neutral level
DEFAULT_DXY = {"value": 104, "change": 0, "level": "moderate_strong",
"interpretation": "美元偏强 - 关注资金流向",
"interpretation_en": "Moderately Strong - Watch capital flows"}
@@ -610,7 +610,7 @@ def _fetch_dollar_index() -> Dict[str, Any]:
current = 0
change = 0
# 1) 尝试 yfinance
# 1) Try yfinance
try:
import yfinance as yf
logger.debug("Fetching DXY from yfinance")
@@ -636,15 +636,15 @@ def _fetch_dollar_index() -> Dict[str, Any]:
except Exception as e:
logger.warning(f"yfinance DXY failed, trying akshare: {e}")
# 2) 尝试 Akshare 获取美元指数
# 2) Try Akshare to get USD Index
try:
import akshare as ak
# Akshare 外汇数据
# Akshare Forex Data
fx_df = ak.currency_boc_sina(symbol="美元")
if fx_df is not None and len(fx_df) > 0:
# 使用中行汇率估算 DXY (近似值)
# Estimate DXY using Bank of China exchange rate (approximate value)
usd_cny = float(fx_df.iloc[-1]['中行汇买价']) / 100
current = usd_cny * 14.5 # 大致换算
current = usd_cny * 14.5 # Approximate conversion
change = 0
logger.info(f"DXY estimated from akshare: {current:.2f}")
else:
@@ -698,14 +698,14 @@ def _fetch_yield_curve() -> Dict[str, Any]:
# 10-year Treasury yield
tnx = yf.Ticker("^TNX")
# 使用 try-except 包裹 history 调用
# Use try-except to wrap history calls
try:
tnx_hist = tnx.history(period="5d")
except Exception as hist_err:
logger.warning(f"TNX history fetch failed: {hist_err}")
tnx_hist = None
# 安全检查
# security check
if tnx_hist is None or tnx_hist.empty:
logger.warning("TNX history is None or empty, returning default")
return {
@@ -1070,7 +1070,7 @@ def _fetch_financial_news(lang: str = "all") -> Dict[str, List[Dict[str, Any]]]:
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)
Impact: bullish (positive), bearish (negative), neutral (neutral)
"""
today = datetime.now()
events = []
@@ -1084,7 +1084,7 @@ def _get_economic_calendar() -> List[Dict[str, Any]]:
"importance": "high",
"forecast": "180K",
"previous": "175K",
"impact_if_above": "bullish", # 高于预期利多美元
"impact_if_above": "bullish", # Higher than expected bullish for dollar
"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"
@@ -1096,7 +1096,7 @@ def _get_economic_calendar() -> List[Dict[str, Any]]:
"importance": "high",
"forecast": "5.25%",
"previous": "5.25%",
"impact_if_above": "bearish", # 加息利空股市
"impact_if_above": "bearish", # Raising interest rates is bad for the stock market
"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"
@@ -1108,7 +1108,7 @@ def _get_economic_calendar() -> List[Dict[str, Any]]:
"importance": "high",
"forecast": "0.3%",
"previous": "0.4%",
"impact_if_above": "bearish", # CPI高利空
"impact_if_above": "bearish", # High CPI is negative
"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"
@@ -1132,7 +1132,7 @@ def _get_economic_calendar() -> List[Dict[str, Any]]:
"importance": "high",
"forecast": "0.10%",
"previous": "0.10%",
"impact_if_above": "bullish", # 日本加息利多日元
"impact_if_above": "bullish", # Japan's interest rate hikes are bullish for the yen
"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"
@@ -1315,11 +1315,11 @@ def _generate_heatmap_data() -> Dict[str, Any]:
"crypto": [],
"sectors": [],
"forex": [],
"commodities": [], # 新增大宗商品热力图
"commodities": [], # Added commodity heat map
"indices": []
}
# Commodities heatmap (黄金、白银、原油等)
# Commodities heatmap (gold, silver, crude oil, etc.)
commodities_data = _get_cached("commodities")
if not commodities_data:
commodities_data = _fetch_commodities()
@@ -1563,7 +1563,7 @@ def market_sentiment():
Includes: Fear & Greed, VIX, DXY, Yield Curve, VXN, GVZ, VIX Term Structure.
"""
try:
# 缓存6小时 (21600秒)，宏观数据变化缓慢，减少 API 调用
# Cache for 6 hours (21600 seconds), macro data changes slowly, reducing API calls
MACRO_CACHE_TTL = 21600 # 6 hours
cached = _get_cached("market_sentiment", MACRO_CACHE_TTL)
if cached:
@@ -1863,7 +1863,7 @@ def _analyze_opportunities_forex(opportunities: list):
def _analyze_opportunities_polymarket(opportunities: list):
"""扫描预测市场机会"""
"""Scan for prediction market opportunities"""
try:
from app.data_sources.polymarket import PolymarketDataSource
from app.services.polymarket_analyzer import PolymarketAnalyzer
@@ -1871,24 +1871,24 @@ def _analyze_opportunities_polymarket(opportunities: list):
polymarket_source = PolymarketDataSource()
analyzer = PolymarketAnalyzer()
# 获取热门市场
# Get popular markets
markets = polymarket_source.get_trending_markets(limit=20)
for market in markets:
try:
# AI分析
# AI analysis
analysis = analyzer.analyze_market(market['market_id'])
if analysis.get('error'):
continue
# 只添加高分机会
# Only add high score chances
if analysis.get('opportunity_score', 0) > 75:
opportunities.append({
"symbol": market['question'][:50], # 简化显示
"symbol": market['question'][:50], # Simplified display
"name": market['question'],
"price": market['current_probability'],
"change_24h": 0, # 预测市场没有24h涨跌幅概念
"change_24h": 0, # There is no concept of 24h rise and fall in the prediction market
"signal": "prediction_opportunity",
"strength": "strong" if analysis.get('opportunity_score', 0) > 85 else "medium",
"reason": f"AI预测概率{analysis.get('ai_predicted_probability', 0):.1f}%，市场概率{market['current_probability']:.1f}%，差异{analysis.get('divergence', 0):.1f}%",