chore: sync backend/frontend/docs changes before push

backend/app/data_manager.py

@@ -2,6 +2,7 @@ import yaml
 import os
 import json
 from typing import Any, Dict, List, Optional
+from numbers import Number
 from app.data_providers.base import BaseDataProvider
 from app.data_providers.tushare import TushareProvider
 # from app.data_providers.ifind import TonghsProvider
@@ -44,20 +45,9 @@ class DataManager:
             
         self.providers = {}
 
-        # Build provider base config from environment variables and config/config.json, then initialize providers
+        # Build provider base config ONLY from config/config.json (do not read env vars)
         base_cfg: Dict[str, Any] = {"data_sources": {}}
 
-        # 1) Prefer env vars when present
-        for name, source_config in (self.config.get('data_sources') or {}).items():
-            env_var = source_config.get('api_key_env')
-            if env_var:
-                api_key = os.getenv(env_var)
-                if api_key:
-                    base_cfg["data_sources"][name] = {"api_key": api_key}
-                else:
-                    logger.warning(f"Env var '{env_var}' for provider '{name}' not set; will try config.json.")
-
-        # 2) Fallback to config/config.json if tokens are provided there
         try:
             # Use the same REPO_ROOT calculation as data_sources.yaml
             current_dir = os.path.dirname(__file__)
@@ -76,7 +66,7 @@ class DataManager:
                     cfg_json = json.load(jf)
                 ds_from_json = (cfg_json.get("data_sources") or {})
                 for name, node in ds_from_json.items():
-                    if name not in base_cfg["data_sources"] and node.get("api_key"):
+                    if node.get("api_key"):
                         base_cfg["data_sources"][name] = {"api_key": node.get("api_key")}
                         logger.info(f"Loaded API key for provider '{name}' from config.json")
             else:
@@ -106,10 +96,8 @@ class DataManager:
         }
 
         for name, provider_class in provider_map.items():
-            token = None
+            token = base_cfg.get("data_sources", {}).get(name, {}).get("api_key")
             source_config = self.config['data_sources'].get(name, {})
-            if source_config and source_config.get('api_key_env'):
-                token = base_cfg.get("data_sources", {}).get(name, {}).get("api_key")
 
             # Initialize the provider if a token is found or not required
             if token or not source_config.get('api_key_env'):
@@ -118,7 +106,7 @@ class DataManager:
                 except Exception as e:
                     logger.error(f"Failed to initialize provider '{name}': {e}")
             else:
-                logger.warning(f"Provider '{name}' requires token env '{source_config.get('api_key_env')}', but none provided. Skipping.")
+                logger.warning(f"Provider '{name}' requires API key but none provided in config.json. Skipping.")
             
     def _detect_market(self, stock_code: str) -> str:
         if stock_code.endswith(('.SH', '.SZ')):
@@ -143,7 +131,17 @@ class DataManager:
             try:
                 method = getattr(provider, method_name)
                 data = await method(stock_code=stock_code, **kwargs)
-                if data is not None and (not isinstance(data, list) or data):
+                is_success = False
+                if data is None:
+                    is_success = False
+                elif isinstance(data, list):
+                    is_success = len(data) > 0
+                elif isinstance(data, dict):
+                    is_success = len(data) > 0
+                else:
+                    is_success = True
+
+                if is_success:
                     logger.info(f"Data successfully fetched from '{provider_name}' for '{stock_code}'.")
                     return data
             except Exception as e:
@@ -171,11 +169,18 @@ class DataManager:
                 for key, value in report.items():
                     if key in ['ts_code', 'stock_code', 'year', 'end_date', 'period', 'ann_date', 'f_ann_date', 'report_type']:
                         continue
-                    if isinstance(value, (int, float)) and value is not None:
+                    # Accept numpy/pandas numeric types as well as builtin numbers
+                    if value is not None and isinstance(value, Number):
                         if key not in series:
                             series[key] = []
                         if not any(d['year'] == year for d in series[key]):
-                            series[key].append({"year": year, "value": value})
+                            # Store as builtin float to avoid JSON serialization issues
+                            try:
+                                numeric_value = float(value)
+                            except Exception:
+                                # Fallback: skip if cannot coerce to float
+                                continue
+                            series[key].append({"year": year, "value": numeric_value})
             return series
         else:
             return {}

backend/app/data_providers/finnhub.py

@@ -5,6 +5,7 @@ import pandas as pd
 from datetime import datetime, timedelta
 import asyncio
 import logging
+import httpx
 
 logger = logging.getLogger(__name__)
 
@@ -14,11 +15,37 @@ class FinnhubProvider(BaseDataProvider):
         if not self.token:
             raise ValueError("Finnhub API key not provided.")
         self.client = finnhub.Client(api_key=self.token)
+        try:
+            masked = f"***{self.token[-4:]}" if isinstance(self.token, str) and len(self.token) >= 4 else "***"
+            logger.info(f"[Finnhub] client initialized (token={masked})")
+        except Exception:
+            # 避免日志失败影响初始化
+            pass
 
     async def get_stock_basic(self, stock_code: str) -> Optional[Dict[str, Any]]:
-        async def _fetch():
+        def _fetch():
             try:
-                profile = self.client.company_profile2(symbol=stock_code)
+                profile = None
+                try:
+                    profile = self.client.company_profile2(symbol=stock_code)
+                    logger.debug(f"[Finnhub] SDK company_profile2 ok symbol={stock_code} name={profile.get('name') if isinstance(profile, dict) else None}")
+                except Exception as e:
+                    logger.warning(f"[Finnhub] SDK company_profile2 failed for {stock_code}: {e}")
+                    # Fallback to direct HTTP if SDK call fails
+                    try:
+                        resp = httpx.get(
+                            'https://finnhub.io/api/v1/stock/profile2',
+                            params={'symbol': stock_code},
+                            headers={'X-Finnhub-Token': self.token},
+                            timeout=20.0,
+                        )
+                        logger.debug(f"[Finnhub] HTTP profile2 status={resp.status_code} len={len(resp.text)}")
+                        if resp.status_code == 200:
+                            profile = resp.json()
+                        else:
+                            logger.error(f"[Finnhub] HTTP profile2 failed status={resp.status_code} body={resp.text[:200]}")
+                    except Exception:
+                        profile = None
                 if not profile:
                     return None
                 
@@ -39,13 +66,18 @@ class FinnhubProvider(BaseDataProvider):
         return await loop.run_in_executor(None, _fetch)
 
     async def get_daily_price(self, stock_code: str, start_date: str, end_date: str) -> List[Dict[str, Any]]:
-        async def _fetch():
+        def _fetch():
             try:
                 start_ts = int(datetime.strptime(start_date, '%Y%m%d').timestamp())
                 end_ts = int(datetime.strptime(end_date, '%Y%m%d').timestamp())
                 
+                logger.debug(f"[Finnhub] stock_candles symbol={stock_code} D {start_date}->{end_date}")
                 res = self.client.stock_candles(stock_code, 'D', start_ts, end_ts)
                 if res.get('s') != 'ok':
+                    try:
+                        logger.warning(f"[Finnhub] stock_candles not ok symbol={stock_code} status={res.get('s')}")
+                    except Exception:
+                        pass
                     return []
                 
                 df = pd.DataFrame(res)
@@ -68,72 +100,207 @@ class FinnhubProvider(BaseDataProvider):
         return await loop.run_in_executor(None, _fetch)
 
     async def get_financial_statements(self, stock_code: str, report_dates: List[str]) -> List[Dict[str, Any]]:
-        async def _fetch():
+        def _fetch():
             try:
-                # Finnhub provides financials as a whole, not by specific date ranges in one call
+                # 1) 拉取年度报表（financials_reported, annual）
-                # We fetch all available and then filter.
+                res = None
-                # Note: 'freq' can be 'annual' or 'quarterly'. We'll use annual.
+                try:
-                res = self.client.financials_reported(symbol=stock_code, freq='annual')
+                    res = self.client.financials_reported(symbol=stock_code, freq='annual')
+                except Exception as e:
+                    logger.warning(f"[Finnhub] SDK financials_reported failed for {stock_code}: {e}")
+                    # Fallback: direct HTTP
+                    try:
+                        r = httpx.get(
+                            'https://finnhub.io/api/v1/stock/financials-reported',
+                            params={'symbol': stock_code, 'freq': 'annual'},
+                            headers={'X-Finnhub-Token': self.token},
+                            timeout=30.0,
+                        )
+                        logger.debug(f"[Finnhub] HTTP financials-reported status={r.status_code} len={len(r.text)}")
+                        if r.status_code == 200:
+                            res = r.json()
+                        else:
+                            logger.error(f"[Finnhub] HTTP financials-reported failed status={r.status_code} body={r.text[:300]}")
+                    except Exception:
+                        res = None
                 if not res or not res.get('data'):
+                    logger.warning(f"[Finnhub] financials-reported empty for {stock_code}")
                     return []
 
                 df = pd.DataFrame(res['data'])
+                if df.empty:
+                    logger.warning(f"[Finnhub] financials-reported dataframe empty for {stock_code}")
+                    return []
 
-                # Filter by requested dates
+                # 2) 仅保留请求的年份
-                years_to_fetch = {date[:4] for date in report_dates}
+                years_to_fetch = {str(date)[:4] for date in report_dates}
-                df = df[df['year'].astype(str).isin(years_to_fetch)]
+                logger.debug(f"[Finnhub] filter years {sorted(list(years_to_fetch))} before={len(df)}")
+                if 'year' in df.columns:
+                    df = df[df['year'].astype(str).isin(years_to_fetch)]
+                # 兜底：如果缺失 year 列，则用 endDate 推断
+                if 'year' not in df.columns and 'endDate' in df.columns:
+                    df = df[df['endDate'].astype(str).str[:4].isin(years_to_fetch)]
 
-                # The data is deeply nested in 'report'. We need to extract and pivot it.
+                if df.empty:
-                all_reports = []
+                    logger.warning(f"[Finnhub] financials-reported no rows after filter for {stock_code}")
-                for index, row in df.iterrows():
+                    return []
-                    report_data = {'ts_code': stock_code, 'end_date': row['endDate']}
 
-                    # Extract concepts from balance sheet, income statement, and cash flow
+                def _normalize_key(s: Optional[str]) -> str:
-                    for item in row['report'].get('bs', []):
+                    if not isinstance(s, str):
-                        report_data[item['concept']] = item['value']
+                        return ""
-                    for item in row['report'].get('ic', []):
+                    return ''.join(ch.lower() for ch in s if ch.isalnum())
-                        report_data[item['concept']] = item['value']
-                    for item in row['report'].get('cf', []):
-                        report_data[item['concept']] = item['value']
 
-                    all_reports.append(report_data)
+                def pick(report_block: List[Dict[str, Any]], concept_candidates: List[str], label_candidates: List[str] = []) -> Optional[float]:
+                    if not report_block:
+                        return None
+                    try:
+                        by_concept = { _normalize_key(item.get('concept')): item.get('value') for item in report_block if isinstance(item, dict) }
+                        by_label   = { _normalize_key(item.get('label')): item.get('value') for item in report_block if isinstance(item, dict) }
+                    except Exception:
+                        return None
+                    for key in concept_candidates:
+                        v = by_concept.get(_normalize_key(key))
+                        if v is not None:
+                            try:
+                                return float(v)
+                            except Exception:
+                                continue
+                    for key in label_candidates:
+                        v = by_label.get(_normalize_key(key))
+                        if v is not None:
+                            try:
+                                return float(v)
+                            except Exception:
+                                continue
+                    return None
 
-                # Further normalization of keys would be needed here to match a common format
+                # 3) 遍历年度记录，展开并标准化字段名
-                # e.g. 'AssetsTotal' -> 'total_assets'
+                flat_reports: List[Dict[str, Any]] = []
-                # This is a complex task and depends on the desired final schema.
+                for _, row in df.iterrows():
+                    bs = (row.get('report') or {}).get('bs', [])
+                    ic = (row.get('report') or {}).get('ic', [])
+                    cf = (row.get('report') or {}).get('cf', [])
 
-                # We will now normalize and calculate derived metrics
+                    end_date = str(row.get('endDate') or '')
-                normalized_reports = []
+
-                for report in all_reports:
+                    revenue = pick(
-                    normalized_report = {
+                        ic,
-                        "ts_code": report.get("ts_code"),
+                        concept_candidates=['Revenues', 'RevenueFromContractWithCustomerExcludingAssessedTax', 'SalesRevenueNet', 'Revenue', 'RevenuesNet', 'SalesRevenueGoodsNet'],
-                        "end_date": report.get("end_date"),
+                        label_candidates=['Total revenue', 'Revenue', 'Sales revenue']
-                        # Balance Sheet
+                    )
-                        "total_assets": report.get("AssetsTotal"),
+                    net_income = pick(
-                        "total_liabilities": report.get("LiabilitiesTotal"),
+                        ic,
-                        "equity": report.get("StockholdersEquityTotal"),
+                        concept_candidates=['NetIncomeLoss', 'ProfitLoss', 'NetIncomeLossAvailableToCommonStockholdersBasic', 'NetIncomeLossAvailableToCommonStockholdersDiluted'],
-                        # Income Statement
+                        label_candidates=['Net income', 'Net income (loss)']
-                        "revenue": report.get("RevenuesTotal"),
+                    )
-                        "net_income": report.get("NetIncomeLoss"),
+                    gross_profit = pick(
-                        "gross_profit": report.get("GrossProfit"),
+                        ic,
-                        # Cash Flow
+                        concept_candidates=['GrossProfit'],
-                        "net_cash_flow_operating": report.get("NetCashFlowOperating"),
+                        label_candidates=['Gross profit']
+                    )
+
+                    total_assets = pick(
+                        bs,
+                        concept_candidates=['Assets', 'AssetsTotal', 'AssetsCurrentAndNoncurrent', 'AssetsIncludingAssetsMeasuredAtFairValue'],
+                        label_candidates=['Total assets']
+                    )
+                    total_equity = pick(
+                        bs,
+                        concept_candidates=['StockholdersEquityIncludingPortionAttributableToNoncontrollingInterest', 'StockholdersEquity', 'StockholdersEquityTotal', 'Equity'],
+                        label_candidates=['Total equity', "Stockholders' equity"]
+                    )
+                    goodwill = pick(
+                        bs,
+                        concept_candidates=['Goodwill', 'GoodwillAndIntangibleAssets'],
+                        label_candidates=['Goodwill', 'Goodwill and intangible assets']
+                    )
+
+                    n_cashflow_act = pick(
+                        cf,
+                        concept_candidates=['NetCashProvidedByUsedInOperatingActivities', 'NetCashProvidedByUsedInOperatingActivitiesContinuingOperations', 'NetCashFlowOperating'],
+                        label_candidates=['Net cash provided by operating activities']
+                    )
+                    capex = pick(
+                        cf,
+                        concept_candidates=['CapitalExpenditures', 'PaymentsToAcquirePropertyPlantAndEquipment', 'PaymentsToAcquireProductiveAssets'],
+                        label_candidates=['Capital expenditures']
+                    )
+
+                    # 计算衍生指标
+                    free_cash_flow = None
+                    if isinstance(n_cashflow_act, (int, float)) and isinstance(capex, (int, float)):
+                        free_cash_flow = n_cashflow_act - capex
+
+                    normalized = {
+                        # 基本元字段
+                        'ts_code': stock_code,
+                        'end_date': end_date,  # DataManager 会从这里抽取 year
+
+                        # 标准命名（见 financial_data_dictionary）
+                        'revenue': revenue,
+                        'n_income': net_income,
+                        'gross_profit': gross_profit,
+
+                        'total_assets': total_assets,
+                        'total_hldr_eqy_exc_min_int': total_equity,
+                        'goodwill': goodwill,
+
+                        'n_cashflow_act': n_cashflow_act,
+                        'c_pay_acq_const_fiolta': capex,
+                        '__free_cash_flow': free_cash_flow,
                     }
 
-                    # Calculate derived metrics
+                    # 一些常用比率（若有足够数据则计算），命名对齐文档
-                    if normalized_report["revenue"] and normalized_report["revenue"] > 0:
+                    if isinstance(revenue, (int, float)) and revenue > 0 and isinstance(gross_profit, (int, float)):
-                        normalized_report["gross_margin"] = (normalized_report["gross_profit"] / normalized_report["revenue"]) if normalized_report["gross_profit"] else None
+                        normalized['grossprofit_margin'] = gross_profit / revenue
-                        normalized_report["net_margin"] = (normalized_report["net_income"] / normalized_report["revenue"]) if normalized_report["net_income"] else None
+                    if isinstance(revenue, (int, float)) and revenue > 0 and isinstance(net_income, (int, float)):
+                        normalized['netprofit_margin'] = net_income / revenue
+                    if isinstance(total_assets, (int, float)) and total_assets > 0 and isinstance(net_income, (int, float)):
+                        normalized['roa'] = net_income / total_assets
+                    if isinstance(total_equity, (int, float)) and total_equity > 0 and isinstance(net_income, (int, float)):
+                        normalized['roe'] = net_income / total_equity
 
-                    if normalized_report["total_assets"] and normalized_report["total_assets"] > 0:
+                    flat_reports.append(normalized)
-                        normalized_report["roa"] = (normalized_report["net_income"] / normalized_report["total_assets"]) if normalized_report["net_income"] else None
+                    try:
+                        logger.debug(
+                            f"[Finnhub] row endDate={end_date} revenue={revenue} net_income={net_income} gross_profit={gross_profit} "
+                            f"assets={total_assets} equity={total_equity} goodwill={goodwill} n_cfo={n_cashflow_act} capex={capex}"
+                        )
+                    except Exception:
+                        pass
 
-                    if normalized_report["equity"] and normalized_report["equity"] > 0:
+                # Convert flat reports to series dict directly to match DataManager expected format
-                        normalized_report["roe"] = (normalized_report["net_income"] / normalized_report["equity"]) if normalized_report["net_income"] else None
+                series: Dict[str, List[Dict[str, Any]]] = {}
+                for report in flat_reports:
+                    end_date = str(report.get('end_date') or '')
+                    year = end_date[:4] if len(end_date) >= 4 else None
+                    if not year:
+                        continue
+                    period = f"{year}1231"
 
-                    normalized_reports.append(normalized_report)
+                    for key, value in report.items():
+                        if key in ['ts_code', 'end_date']:
+                            continue
+                        # Only collect numeric values
+                        try:
+                            if value is None:
+                                continue
+                            num = float(value)
+                        except Exception:
+                            continue
+                        if key not in series:
+                            series[key] = []
+                        # Avoid duplicate period entries
+                        exists = any(dp.get('period') == period for dp in series[key])
+                        if not exists:
+                            series[key].append({'period': period, 'value': num})
 
-                return normalized_reports
+                try:
+                    total_points = sum(len(v) for v in series.values())
+                    logger.info(f"[Finnhub] built series for {stock_code} keys={len(series)} points={total_points}")
+                except Exception:
+                    pass
+                return series
 
             except Exception as e:
                 logger.error(f"Finnhub get_financial_statements failed for {stock_code}: {e}")

backend/app/data_providers/yfinance.py

@@ -21,7 +21,7 @@ class YfinanceProvider(BaseDataProvider):
         return stock_code
 
     async def get_stock_basic(self, stock_code: str) -> Optional[Dict[str, Any]]:
-        async def _fetch():
+        def _fetch():
             try:
                 ticker = yf.Ticker(self._map_stock_code(stock_code))
                 info = ticker.info
@@ -44,7 +44,7 @@ class YfinanceProvider(BaseDataProvider):
         return await loop.run_in_executor(None, _fetch)
 
     async def get_daily_price(self, stock_code: str, start_date: str, end_date: str) -> List[Dict[str, Any]]:
-        async def _fetch():
+        def _fetch():
             try:
                 # yfinance date format is YYYY-MM-DD
                 start_fmt = datetime.strptime(start_date, '%Y%m%d').strftime('%Y-%m-%d')

backend/app/routers/financial.py

@@ -5,6 +5,7 @@ import json
 import os
 import time
 from datetime import datetime, timezone, timedelta
+from enum import Enum
 from typing import Dict, List
 
 from fastapi import APIRouter, HTTPException, Query
@@ -46,6 +47,13 @@ def get_dm():
 
 router = APIRouter()
 
+
+class MarketEnum(str, Enum):
+    cn = "cn"
+    us = "us"
+    hk = "hk"
+    jp = "jp"
+
 # Load metric config from file (project root is repo root, not backend/)
 # routers/ -> app/ -> backend/ -> repo root
 REPO_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
@@ -257,9 +265,10 @@ async def get_financial_config():
     return FinancialConfigResponse(api_groups=api_groups)
 
 
-@router.get("/china/{ts_code}", response_model=BatchFinancialDataResponse)
+@router.get("/{market}/{stock_code}", response_model=BatchFinancialDataResponse)
-async def get_china_financials(
+async def get_financials(
-    ts_code: str,
+    market: MarketEnum,
+    stock_code: str,
     years: int = Query(10, ge=1, le=10),
 ):
     # Load metric config
@@ -274,11 +283,11 @@ async def get_china_financials(
     steps: List[StepRecord] = []
     
     # Get company name
-    company_name = ts_code
+    company_name = stock_code
     try:
-        basic_data = await get_dm().get_stock_basic(stock_code=ts_code)
+        basic_data = await get_dm().get_stock_basic(stock_code=stock_code)
         if basic_data:
-            company_name = basic_data.get("name", ts_code)
+            company_name = basic_data.get("name", stock_code)
     except Exception:
         pass # Continue without it
 
@@ -295,7 +304,7 @@ async def get_china_financials(
     steps.append(step_financials)
 
     # Fetch all financial statements at once (already in series format from provider)
-    series = await get_dm().get_financial_statements(stock_code=ts_code, report_dates=report_dates)
+    series = await get_dm().get_financial_statements(stock_code=stock_code, report_dates=report_dates)
 
     # Get the latest current year report period for market data
     latest_current_year_report = None
@@ -322,7 +331,8 @@ async def get_china_financials(
         has_daily_basic = bool(api_groups.get("daily_basic"))
         has_daily = bool(api_groups.get("daily"))
 
-        if has_daily_basic or has_daily:
+        # 目前仅对中国市场启用 daily_basic/daily 数据拉取，其他市场由对应 provider 后续实现
+        if market == MarketEnum.cn and (has_daily_basic or has_daily):
             step_market = StepRecord(name="拉取市值与股价", start_ts=datetime.now(timezone.utc).isoformat(), status="running")
             steps.append(step_market)
 
@@ -339,7 +349,7 @@ async def get_china_financials(
 
             try:
                 if has_daily_basic:
-                    db_rows = await get_dm().get_data('get_daily_basic_points', stock_code=ts_code, trade_dates=market_dates)
+                    db_rows = await get_dm().get_data('get_daily_basic_points', stock_code=stock_code, trade_dates=market_dates)
                     if isinstance(db_rows, list):
                         for row in db_rows:
                             trade_date = row.get('trade_date') or row.get('trade_dt') or row.get('date')
@@ -369,7 +379,7 @@ async def get_china_financials(
                                     else:
                                         series[key].append({"period": period, "value": value})
                 if has_daily:
-                    d_rows = await get_dm().get_data('get_daily_points', stock_code=ts_code, trade_dates=market_dates)
+                    d_rows = await get_dm().get_data('get_daily_points', stock_code=stock_code, trade_dates=market_dates)
                     if isinstance(d_rows, list):
                         for row in d_rows:
                             trade_date = row.get('trade_date') or row.get('trade_dt') or row.get('date')
@@ -413,10 +423,23 @@ async def get_china_financials(
     if not series:
         raise HTTPException(status_code=502, detail={"message": "No data returned from any data source", "errors": errors})
 
-    # Truncate periods and sort (the data should already be mostly correct, but we ensure)
+    # 统一 period 字段；若仅有 year 则映射为 YYYY1231；然后去重与排序
-    for key, arr in series.items():
+    for key, arr in list(series.items()):
-        # Deduplicate and sort desc by period, then cut to requested periods, and return asc
+        normalized: List[Dict] = []
-        uniq = {item["period"]: item for item in arr}
+        for item in arr:
+            period = item.get("period")
+            if not period:
+                year = item.get("year")
+                if year:
+                    period = f"{str(year)}1231"
+            if not period:
+                # 跳过无法确定 period 的项
+                continue
+            value = item.get("value")
+            normalized.append({"period": str(period), "value": value})
+
+        # Deduplicate by period
+        uniq = {it["period"]: it for it in normalized}
         arr_sorted_desc = sorted(uniq.values(), key=lambda x: x["period"], reverse=True)
         arr_limited = arr_sorted_desc[:years]
         arr_sorted = sorted(arr_limited, key=lambda x: x["period"])
@@ -438,7 +461,7 @@ async def get_china_financials(
         steps=steps,
     )
 
-    return BatchFinancialDataResponse(ts_code=ts_code, name=company_name, series=series, meta=meta)
+    return BatchFinancialDataResponse(ts_code=stock_code, name=company_name, series=series, meta=meta)
 
 
 @router.get("/china/{ts_code}/company-profile", response_model=CompanyProfileResponse)
@@ -800,6 +823,66 @@ async def get_today_snapshot(ts_code: str):
         raise HTTPException(status_code=500, detail=f"Failed to fetch snapshot: {e}")
 
 
+@router.get("/{market}/{stock_code}/snapshot", response_model=TodaySnapshotResponse)
+async def get_market_snapshot(market: MarketEnum, stock_code: str):
+    """
+    市场无关的“昨日快照”接口。
+    - CN: 复用中国市场的快照逻辑（daily_basic/daily）。
+    - 其他市场: 兜底使用日行情获取最近交易日收盘价；其余字段暂返回空值。
+    """
+    if market == MarketEnum.cn:
+        return await get_today_snapshot(stock_code)
+
+    try:
+        # 公司名称（可选）
+        company_name = None
+        try:
+            basic = await get_dm().get_stock_basic(stock_code=stock_code)
+            if basic:
+                company_name = basic.get("name")
+        except Exception:
+            company_name = None
+
+        base_dt = (datetime.now() - timedelta(days=1)).date()
+        base_str = base_dt.strftime("%Y%m%d")
+
+        # 为了稳妥拿到最近交易日，回看近 10 天
+        start_dt = base_dt - timedelta(days=10)
+        start_str = start_dt.strftime("%Y%m%d")
+        end_dt = base_dt + timedelta(days=1)
+        end_str = end_dt.strftime("%Y%m%d")
+
+        rows = await get_dm().get_daily_price(stock_code=stock_code, start_date=start_str, end_date=end_str)
+        trade_date = None
+        close = None
+        if isinstance(rows, list) and rows:
+            # 选择 <= base_str 的最后一条记录
+            try:
+                candidates = [r for r in rows if str(r.get("trade_date") or r.get("date") or "") <= base_str]
+                if candidates:
+                    last = sorted(candidates, key=lambda r: str(r.get("trade_date") or r.get("date") or ""))[-1]
+                    trade_date = str(last.get("trade_date") or last.get("date") or base_str)
+                    close = last.get("close")
+            except Exception:
+                pass
+
+        if trade_date is None:
+            trade_date = base_str
+
+        return TodaySnapshotResponse(
+            ts_code=stock_code,
+            trade_date=trade_date,
+            name=company_name,
+            close=close,
+            pe=None,
+            pb=None,
+            dv_ratio=None,
+            total_mv=None,
+        )
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to fetch snapshot: {e}")
+
+
 @router.get("/china/{ts_code}/analysis/{analysis_type}/stream")
 async def stream_analysis(
     ts_code: str,
@@ -925,3 +1008,16 @@ async def stream_analysis(
         "X-Accel-Buffering": "no",
     }
     return StreamingResponse(streamer(), media_type="text/plain; charset=utf-8", headers=headers)
+
+
+@router.get("/{market}/{stock_code}/analysis/{analysis_type}/stream")
+async def stream_analysis_market(
+    market: MarketEnum,
+    stock_code: str,
+    analysis_type: str,
+    company_name: str = Query(None, description="Company name for better context"),
+):
+    """
+    市场无关的分析流接口。逻辑与中国市场一致，仅路径不同。
+    """
+    return await stream_analysis(stock_code, analysis_type, company_name)

docs/已完成任务/tasks.md

@@ -19,9 +19,9 @@
 - [x] **T2.1 [Backend/DB]**: 根据设计文档，使用SQLAlchemy ORM定义`Report`, `AnalysisModule`, `ProgressTracking`, `SystemConfig`四个核心数据模型。 **[完成 - 2025-10-21]**
 - [x] **T2.2 [Backend/DB]**: 创建第一个Alembic迁移脚本，在数据库中生成上述四张表。 **[完成 - 2025-10-21]**
 - [x] **T2.3 [Backend]**: 实现`ConfigManager`服务，完成从`config.json`加载配置并与数据库配置合并的逻辑。 **[完成 - 2025-10-21]**
-- **T2.4 [Backend/API]**: 创建Pydantic Schema，用于配置接口的请求和响应 (`ConfigResponse`, `ConfigUpdateRequest`, `ConfigTestRequest`, `ConfigTestResponse`)。
+- [x] **T2.4 [Backend/API]**: 创建Pydantic Schema，用于配置接口的请求和响应 (`ConfigResponse`, `ConfigUpdateRequest`, `ConfigTestRequest`, `ConfigTestResponse`)。
-- **T2.5 [Backend/API]**: 实现`/api/config`的`GET`和`PUT`端点，用于读取和更新系统配置。
+- [x] **T2.5 [Backend/API]**: 实现`/api/config`的`GET`和`PUT`端点，用于读取和更新系统配置。
-- **T2.6 [Backend/API]**: 实现`/api/config/test`的`POST`端点，用于验证数据库连接等配置的有效性。
+- [x] **T2.6 [Backend/API]**: 实现`/api/config/test`的`POST`端点，用于验证数据库连接等配置的有效性。
 
 ## Phase 3: 前端基础与配置页面 (P1)
 
@@ -39,8 +39,8 @@
 
 此阶段是项目的核心，重点开发后端的报告生成流程和前端的实时进度展示。
 
-- **T4.1 [Backend/Service]**: 实现`DataSourceManager`，封装对Tushare和Yahoo Finance的数据获取逻辑。
+- [x] **T4.1 [Backend/Service]**: 实现`DataSourceManager`，封装对Tushare和Yahoo Finance的数据获取逻辑。
-- **T4.2 [Backend/Service]**: 实现`AIService`，封装对Google Gemini API的调用逻辑，包括Token使用统计。
+- [x] **T4.2 [Backend/Service]**: 实现`AIService`，封装对Google Gemini API的调用逻辑，包括Token使用统计。
 - **T4.3 [Backend/Service]**: 实现`ProgressTracker`服务，提供`initialize`, `start_step`, `complete_step`, `get_progress`等方法，并与数据库交互。
 - **T4.4 [Backend/Service]**: 定义`AnalysisModule`的基类/接口，并初步实现一到两个模块（如`FinancialDataModule`）作为示例。
 - **T4.5 [Backend/Service]**: 实现核心的`ReportGenerator`服务，编排数据获取、各分析模块调用、进度更新的完整流程。

docs/未完成任务/us_market_integration_tasks.md

@@ -0,0 +1,67 @@
+# 美国市场数据集成任务清单
+
+本文档用于跟踪和管理为项目集成美国市场数据（使用 Finnhub 作为数据源）所需的各项开发任务。
+
+## 任务列表
+
+- [x] **后端：实现 FinnhubProvider 数据映射**
+  - **目标**：根据 `docs/financial_data_dictionary.md` 中的定义，在 `backend/app/data_providers/finnhub.py` 文件中，完成从 Finnhub API 原始数据到系统标准字段的完整映射。
+  - **关键点**：
+    - [x] 处理直接映射的字段。
+    - [x] 实现所有需要通过计算得出的衍生指标。
+    - [x] 确保处理 `null` 或空值，避免计算错误。
+    - [x] 验证返回的数据结构符合 `DataManager` 的预期。
+
+- [x] **后端：按市场分段的 API 路由**
+  - **目标**：在 `backend/app/routers/financial.py` 中，将现有的 `/api/v1/financials/china/{ts_code}` 改为按市场分段：`/api/v1/financials/{market}/{stock_code}`（示例：`/api/v1/financials/us/AAPL`，`/api/v1/financials/cn/600519.SH`）。
+  - **关键点**：
+    - [x] 去除硬编码的 `china`，新增路径参数 `market`，并对取值做校验（`cn/us/hk/jp`）。
+    - [x] 使用单一处理函数，根据 `market` 分派到相应的数据提供方与代码格式规范。
+
+- [x] **前端：更新 API 调用**
+  - **目标**：修改前端调用，基于用户选择的市场与股票代码，请求新的按市场分段路由。
+  - **关键点**：
+    - [x] 替换 `useChinaFinancials`，新增通用 `useFinancials(market, stockCode, years)`。
+    - [x] 将请求路径改为 `/api/financials/{market}/{stock_code}?years=...`（代理到后端对应的 `/api/v1/financials/{market}/{stock_code}`）。
+    - [ ] 确保展示与错误处理兼容美国、香港、日本等市场。
+
+- [ ] **测试与验证**
+  - **目标**：对整个流程进行端到端测试，确保两个市场的功能都稳定可靠。
+  - **关键点**：
+    - [ ] **中国市场回归测试**：使用多个中国 A 股代码测试，确保原有功能不受影响。
+    - [ ] **美国市场功能测试**：使用多个美国股票代码（如 `AAPL`, `MSFT`）测试，验证报告能否成功生成。
+    - [ ] **数据一致性验证**：抽样对比 Finnhub 返回的数据和前端展示的数据，确保映射和计算的准确性。
+    - [ ] **错误处理测试**：测试无效的股票代码，检查系统是否能给出清晰的错误提示。
+
+  - **前置条件**：
+    - [ ] 在 `config/config.json` 或环境变量中配置 `FINNHUB_API_KEY`。
+    - [ ] 后端已启动（默认 `http://127.0.0.1:8000/api`），前端已启动（默认 `http://127.0.0.1:3000`）。
+
+  - **接口用例（后端）**：
+    - [ ] GET `/api/v1/financials/cn/600519.SH?years=10`
+      - 期望：`200`；返回 `ts_code`、`name`、`series`（含 `revenue`、`n_income` 等关键指标，period/年序列齐全）。
+    - [ ] GET `/api/v1/financials/cn/000001.SZ?years=5`
+      - 期望：`200`；返回与上同，近 5 年序列。
+    - [ ] GET `/api/v1/financials/us/AAPL?years=10`
+      - 期望：`200`；`series` 至少包含：`revenue`、`n_income`、`total_assets`、`total_hldr_eqy_exc_min_int`、`__free_cash_flow`、`grossprofit_margin`、`netprofit_margin`、`roe`、`roa`。
+    - [ ] GET `/api/v1/financials/us/MSFT?years=10`
+      - 期望：`200`；字段与口径同 AAPL。
+    - [ ] GET `/api/v1/financials/us/INVALID?years=10`
+      - 期望：`4xx/5xx`；`detail.message` 含可读错误。
+
+  - **页面用例（前端）**：
+    - [ ] 打开 `/report/600519.SH?market=cn`
+      - 期望：基本信息与“昨日快照”显示；“财务数据（来自 Tushare）”表格展示 10 期内主要指标。
+    - [ ] 打开 `/report/000001.SZ?market=cn`
+      - 期望：与上同；代码规范化逻辑（无后缀时自动补 `.SZ/.SH`）正常。
+    - [ ] 打开 `/report/AAPL?market=us`
+      - 期望：“股价图表”正常；“财务数据”表格展示主要指标（含自由现金流、毛利率、净利率、ROA、ROE）。
+    - [ ] 打开 `/report/MSFT?market=us`
+      - 期望：与上同。
+    - [ ] 打开 `/report/INVALID?market=us`
+      - 期望：顶部状态为“读取失败”并有错误提示文案。
+
+  - **验收标准**：
+    - [ ] 中国市场功能无回归；美国市场关键指标齐全、值域合理（百分比类 ∈ [-1000%, 1000%]，金额类为有限数）。
+    - [ ] 报错信息清晰可读；网络/密钥缺失时提示明确。
+    - [ ] 页内主要表格不出现 `NaN/Infinity`；空值以 `-` 展示。

frontend/src/app/fonts/README.md

@@ -18,3 +18,5 @@
 
 
 
+
+

frontend/src/app/report/[symbol]/page.tsx

@@ -1,7 +1,7 @@
 'use client';
 
 import { useParams, useSearchParams } from 'next/navigation';
-import { useChinaFinancials, useFinancialConfig, useAnalysisConfig, generateFullAnalysis, useChinaSnapshot } from '@/hooks/useApi';
+import { useChinaFinancials, useFinancials, useFinancialConfig, useAnalysisConfig, generateFullAnalysis, useSnapshot } from '@/hooks/useApi';
 import { Spinner } from '@/components/ui/spinner';
 import { Button } from '@/components/ui/button';
 import { CheckCircle, XCircle, RotateCw } from 'lucide-react';
@@ -20,11 +20,18 @@ export default function ReportPage() {
   const params = useParams();
   const searchParams = useSearchParams();
   const symbol = params.symbol as string;
-  const market = (searchParams.get('market') || '').toLowerCase();
+  const marketParam = (searchParams.get('market') || '').toLowerCase();
+  const normalizedMarket = (() => {
+    if (marketParam === 'usa') return 'us';
+    if (marketParam === 'china') return 'cn';
+    if (marketParam === 'hkex') return 'hk';
+    if (marketParam === 'jpn') return 'jp';
+    return marketParam;
+  })();
 
-  const displayMarket = market === 'china' ? '中国' : market;
+  const displayMarket = marketParam === 'china' ? '中国' : marketParam;
 
-  const isChina = market === 'china' || market === 'cn';
+  const isChina = normalizedMarket === 'cn';
 
   // 规范化中国市场 ts_code：若为6位数字或无后缀，自动推断交易所
   const normalizedTsCode = (() => {
@@ -40,8 +47,13 @@ export default function ReportPage() {
     return symbol.toUpperCase();
   })();
 
-  const { data: financials, error, isLoading } = useChinaFinancials(isChina ? normalizedTsCode : undefined, 10);
+  const chinaFin = useChinaFinancials(isChina ? normalizedTsCode : undefined, 10);
-  const { data: snapshot, error: snapshotError, isLoading: snapshotLoading } = useChinaSnapshot(isChina ? normalizedTsCode : undefined);
+  const otherFin = useFinancials(!isChina ? normalizedMarket : undefined, !isChina ? symbol : undefined, 10);
+  const financials = (chinaFin.data ?? otherFin.data) as any;
+  const error = chinaFin.error ?? otherFin.error;
+  const isLoading = chinaFin.isLoading || otherFin.isLoading;
+  const unifiedSymbol = isChina ? normalizedTsCode : symbol;
+  const { data: snapshot, error: snapshotError, isLoading: snapshotLoading } = useSnapshot(normalizedMarket, unifiedSymbol);
   const { data: financialConfig } = useFinancialConfig();
   const { data: analysisConfig } = useAnalysisConfig();
   
@@ -139,7 +151,7 @@ export default function ReportPage() {
   }
   
   const runFullAnalysis = async () => {
-    if (!isChina || !financials || !analysisConfig?.analysis_modules || isAnalysisRunningRef.current) {
+    if (!financials || !analysisConfig?.analysis_modules || isAnalysisRunningRef.current) {
       return;
     }
 
@@ -321,7 +333,7 @@ export default function ReportPage() {
   }, [startTime]);
   
   const retryAnalysis = async (analysisType: string) => {
-    if (!isChina || !financials || !analysisConfig?.analysis_modules) {
+    if (!financials || !analysisConfig?.analysis_modules) {
       return;
     }
     analysisFetchedRefs.current[analysisType] = false;
@@ -344,7 +356,7 @@ export default function ReportPage() {
     try {
       const startedMsLocal = Date.now();
       const response = await fetch(
-        `/api/financials/china/${normalizedTsCode}/analysis/${analysisType}/stream?company_name=${encodeURIComponent(financials?.name || normalizedTsCode)}`
+        `/api/financials/${normalizedMarket}/${unifiedSymbol}/analysis/${analysisType}/stream?company_name=${encodeURIComponent(financials?.name || unifiedSymbol)}`
       );
       if (!response.ok) {
         throw new Error(`HTTP error! status: ${response.status}`);
@@ -420,7 +432,7 @@ export default function ReportPage() {
   };
 
   useEffect(() => {
-    if (!isChina || isLoading || error || !financials || !analysisConfig?.analysis_modules || analysisTypes.length === 0) {
+    if (isLoading || error || !financials || !analysisConfig?.analysis_modules || analysisTypes.length === 0) {
       return;
     }
     if (isAnalysisRunningRef.current) {
@@ -477,7 +489,7 @@ export default function ReportPage() {
             abortControllerRef.current = new AbortController();
             const startedMsLocal = Date.now();
             const response = await fetch(
-              `/api/financials/china/${normalizedTsCode}/analysis/${analysisType}/stream?company_name=${encodeURIComponent(financials?.name || normalizedTsCode)}`,
+              `/api/financials/${normalizedMarket}/${unifiedSymbol}/analysis/${analysisType}/stream?company_name=${encodeURIComponent(financials?.name || unifiedSymbol)}`,
               { signal: abortControllerRef.current.signal }
             );
             if (!response.ok) {
@@ -572,7 +584,7 @@ export default function ReportPage() {
       }
     };
     runAnalysesSequentially();
-  }, [isChina, isLoading, error, financials, analysisConfig, analysisTypes, normalizedTsCode, manualRunKey]);
+  }, [isLoading, error, financials, analysisConfig, analysisTypes, normalizedTsCode, manualRunKey]);
 
   const stopAll = () => {
     stopRequestedRef.current = true;
@@ -603,7 +615,7 @@ export default function ReportPage() {
           <CardContent className="space-y-2 text-sm">
             <div className="flex items-center gap-2">
               <span className="text-muted-foreground min-w-20">股票代码:</span>
-              <span className="font-medium">{normalizedTsCode}</span>
+              <span className="font-medium">{unifiedSymbol}</span>
             </div>
             <div className="flex items-center gap-2">
               <span className="text-muted-foreground min-w-20">交易市场:</span>
@@ -627,8 +639,7 @@ export default function ReportPage() {
             
           </CardContent>
         </Card>
-        {isChina && (
+        <Card className="w-80 flex-shrink-0">
-          <Card className="w-80 flex-shrink-0">
             <CardHeader>
               <CardTitle className="text-lg">昨日快照</CardTitle>
             </CardHeader>
@@ -714,9 +725,7 @@ export default function ReportPage() {
               </div>
             </CardContent>
           </Card>
-        )}
+        <Card className="w-40 flex-shrink-0">
-        {isChina && (
-          <Card className="w-40 flex-shrink-0">
             <CardContent className="flex flex-col gap-2">
               <Button onClick={runFullAnalysis} disabled={isAnalysisRunningRef.current}>
                 {isAnalysisRunningRef.current ? '正在分析…' : '开始分析'}
@@ -729,9 +738,7 @@ export default function ReportPage() {
               </Button>
             </CardContent>
           </Card>
-        )}
+        <Card className="w-80">
-        {isChina && (
-          <Card className="w-80">
             <CardHeader className="flex flex-col space-y-2 pb-2">
               <div className="flex flex-row items-center justify-between w-full">
                 <CardTitle className="text-xl">任务状态</CardTitle>
@@ -774,11 +781,9 @@ export default function ReportPage() {
               )}
             </CardContent>
           </Card>
-        )}
       </div>
 
-      {isChina && (
+      <Tabs defaultValue="chart" className="mt-4">
-        <Tabs defaultValue="chart" className="mt-4">
           <TabsList className="flex-wrap">
             <TabsTrigger value="chart">股价图表</TabsTrigger>
             <TabsTrigger value="financial">财务数据</TabsTrigger>
@@ -795,19 +800,19 @@ export default function ReportPage() {
             <div className="flex items-center gap-3 text-sm mb-4">
               <CheckCircle className="size-4 text-green-600" />
               <div className="text-muted-foreground">
-                实时股价图表 - {normalizedTsCode}
+                实时股价图表 - {unifiedSymbol}
               </div>
             </div>
             
             <TradingViewWidget 
-              symbol={normalizedTsCode} 
+              symbol={unifiedSymbol} 
-              market={market}
+              market={marketParam}
               height={500}
             />
           </TabsContent>
           
           <TabsContent value="financial" className="space-y-4">
-            <h2 className="text-lg font-medium">财务数据（来自 Tushare）</h2>
+            <h2 className="text-lg font-medium">财务数据</h2>
             <div className="flex items-center gap-3 text-sm">
               {isLoading ? (
                 <Spinner className="size-4" />
@@ -817,11 +822,7 @@ export default function ReportPage() {
                 <CheckCircle className="size-4 text-green-600" />
               )}
               <div className="text-muted-foreground">
-                {isLoading
+                {isLoading ? '正在读取数据…' : error ? '读取失败' : '读取完成'}
-                  ? '正在读取 Tushare 数据…'
-                  : error
-                  ? '读取失败'
-                  : '读取完成'}
               </div>
             </div>
             {error && <p className="text-red-500">加载失败</p>}
@@ -1527,7 +1528,6 @@ export default function ReportPage() {
             )}
           </TabsContent>
         </Tabs>
-      )}
     </div>
   );
 }

frontend/src/hooks/useApi.ts

@@ -63,7 +63,7 @@ export function useFinancialConfig() {
 
 export function useChinaFinancials(ts_code?: string, years: number = 10) {
   return useSWR<BatchFinancialDataResponse>(
-    ts_code ? `/api/financials/china/${encodeURIComponent(ts_code)}?years=${encodeURIComponent(String(years))}` : null,
+    ts_code ? `/api/financials/cn/${encodeURIComponent(ts_code)}?years=${encodeURIComponent(String(years))}` : null,
     fetcher,
     {
       revalidateOnFocus: false,      // 不在窗口聚焦时重新验证
@@ -74,6 +74,28 @@ export function useChinaFinancials(ts_code?: string, years: number = 10) {
   );
 }
 
+export function useFinancials(market?: string, stockCode?: string, years: number = 10) {
+  const normalizeMarket = (m?: string) => {
+    const t = (m || '').toLowerCase();
+    if (t === 'usa') return 'us';
+    if (t === 'china') return 'cn';
+    if (t === 'hkex') return 'hk';
+    if (t === 'jpn') return 'jp';
+    return t;
+  };
+  const mkt = normalizeMarket(market);
+  return useSWR<BatchFinancialDataResponse>(
+    mkt && stockCode ? `/api/financials/${encodeURIComponent(mkt)}/${encodeURIComponent(stockCode)}?years=${encodeURIComponent(String(years))}` : null,
+    fetcher,
+    {
+      revalidateOnFocus: false,
+      revalidateOnReconnect: false,
+      dedupingInterval: 300000,
+      errorRetryCount: 1,
+    }
+  );
+}
+
 export function useAnalysisConfig() {
   return useSWR<AnalysisConfigResponse>('/api/financials/analysis-config', fetcher);
 }
@@ -124,3 +146,25 @@ export function useChinaSnapshot(ts_code?: string) {
     }
   );
 }
+
+export function useSnapshot(market?: string, stockCode?: string) {
+  const normalizeMarket = (m?: string) => {
+    const t = (m || '').toLowerCase();
+    if (t === 'usa') return 'us';
+    if (t === 'china') return 'cn';
+    if (t === 'hkex') return 'hk';
+    if (t === 'jpn') return 'jp';
+    return t;
+  };
+  const mkt = normalizeMarket(market);
+  return useSWR<TodaySnapshotResponse>(
+    mkt && stockCode ? `/api/financials/${encodeURIComponent(mkt)}/${encodeURIComponent(stockCode)}/snapshot` : null,
+    fetcher,
+    {
+      revalidateOnFocus: false,
+      revalidateOnReconnect: false,
+      dedupingInterval: 120000,
+      errorRetryCount: 1,
+    }
+  );
+}

frontend/src/lib/prisma.ts

@@ -40,3 +40,5 @@ if (process.env.NODE_ENV !== 'production') globalForPrisma.prisma = prisma
 
 
 
+
+