Initial commit: cc-cursor 全链路量化研究平台

7 Sprints 全部完成: Sprint 0: 基础设施 (DataManager + MariaDB) Sprint 1: 因子引擎 (34因子/12分类) Sprint 2: VectorBT 回测 (5策略+截面) Sprint 3: Optuna 优化 (+Walk-Forward) Sprint 4: ML 模型 (LightGBM+CatBoost) Sprint 5: Qwen 情绪因子 (三源新闻+日期对齐) Sprint 6: Agent 系统 (4Agent+日报.md/.html) 生产加固 (15项): Tushare双源fallback, SSH自动恢复, pool_pre_ping, save_daily先删后插, load_dotenv绝对路径, 日报5d/20d修复, RiskAgent改上证指数, 昨日对比+数据截止, mac_report utf8mb4, CLAUDE-*.md 9条已知Bug, demo全参数化, djapi数据源归一化, indexDatas API修正 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-07 15:59:05 +08:00
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+"""
+AkShare 数据源封装。
+
+统一封装 AkShare 调用，返回标准化的 DataFrame。
+所有网络请求都在这一层处理，包含重试和容错。
+
+支持个股和指数两种数据接口。
+"""
+
+# 指数代码识别：.SH 后缀为主板指数，399xxx 为深证指数
+# 注意区分：000001.SZ 是平安银行(个股)，000001.SH 是上证指数
+def is_index_code(ts_code: str) -> bool:
+    """判断是否为指数代码。排除 000xxx.SZ 个股。"""
+    if not ts_code:
+        return False
+    code = ts_code.upper()
+    # .SH 开头 000 是指数
+    if code.endswith(".SH") and (code.startswith("000") or code.startswith("399")):
+        return True
+    # 深交所 399xxx 指数
+    if code.startswith("399"):
+        return True
+    # 无后缀的纯数字 000xxx（上证指数常见写法）
+    if code == "000001":
+        return True
+    return False
+
+import time
+import pandas as pd
+import akshare as ak
+
+from config.settings import AKSHARE_CONFIG
+
+
+class AkShareSource:
+    """AkShare 数据源。"""
+
+    def __init__(self):
+        self._timeout = AKSHARE_CONFIG["request_timeout"]
+        self._retry = AKSHARE_CONFIG["retry_times"]
+        self._delay = AKSHARE_CONFIG["retry_delay"]
+
+    def _retry_call(self, fn, name: str, **kwargs):
+        """带重试的 API 调用包装。重试间隔递增。"""
+        last_err = None
+        for i in range(self._retry):
+            try:
+                return fn(**kwargs)
+            except Exception as e:
+                last_err = e
+                wait = self._delay * (i + 1)
+                print(f"  [retry] {name} 失败 ({e})，{wait}s 后重试 ({i + 1}/{self._retry})...")
+                if i < self._retry - 1:
+                    time.sleep(wait)
+        raise last_err  # type: ignore
+
+    # ── 股票列表 ──────────────────────────────────────────
+
+    def fetch_stock_list(self) -> pd.DataFrame:
+        """获取 A 股股票列表。"""
+        df = self._retry_call(ak.stock_info_a_code_name, "stock_list")
+        df = df.rename(columns={
+            "code": "ts_code",
+            "name": "name",
+        })
+        return df[["ts_code", "name"]]
+
+    # ── 日线数据 ──────────────────────────────────────────
+
+    def fetch_daily(
+        self, ts_code: str, start: str, end: str | None = None
+    ) -> pd.DataFrame:
+        """
+        获取单只股票日线行情。
+
+        参数:
+            ts_code: 股票代码，如 '000001'（纯数字格式，AkShare 要求）
+            start: 起始日期 'YYYYMMDD'
+            end: 结束日期 'YYYYMMDD'，None 表示今天
+        """
+        symbol = ts_code.replace(".SZ", "").replace(".SH", "").replace(".BJ", "")
+        end = end or time.strftime("%Y%m%d")
+        df = self._retry_call(
+            ak.stock_zh_a_hist,
+            "daily",
+            symbol=symbol,
+            period="daily",
+            start_date=start,
+            end_date=end,
+            adjust="qfq",  # 前复权
+        )
+        if df.empty:
+            return df
+
+        df = df.rename(columns={
+            "日期": "trade_date",
+            "开盘": "open",
+            "收盘": "close",
+            "最高": "high",
+            "最低": "low",
+            "成交量": "vol",
+            "成交额": "amount",
+            "振幅": "amplitude",
+            "涨跌幅": "pct_chg",
+            "涨跌额": "change",
+            "换手率": "turnover_rate",
+        })
+        df["ts_code"] = ts_code
+        # AkShare 返回 'YYYY-MM-DD'，统一转为 'YYYYMMDD'
+        df["trade_date"] = df["trade_date"].astype(str).str.replace("-", "")
+        return df
+
+    # ── 指数日线 ──────────────────────────────────────────
+
+    def fetch_index_daily(
+        self, ts_code: str, start: str, end: str | None = None
+    ) -> pd.DataFrame:
+        """
+        获取指数日线行情。
+
+        AkShare index_zh_a_hist 接口，symbol 为纯数字（如 '000001'）。
+        """
+        symbol = ts_code.replace(".SH", "").replace(".SZ", "").replace(".BJ", "")
+        end = end or time.strftime("%Y%m%d")
+        df = self._retry_call(
+            ak.index_zh_a_hist,
+            "index_daily",
+            symbol=symbol, period="daily",
+            start_date=start, end_date=end,
+        )
+        if df.empty:
+            return df
+
+        df = df.rename(columns={
+            "日期": "trade_date",
+            "开盘": "open",
+            "收盘": "close",
+            "最高": "high",
+            "最低": "low",
+            "成交量": "vol",
+            "成交额": "amount",
+            "涨跌幅": "pct_chg",
+            "涨跌额": "change",
+        })
+        df["ts_code"] = ts_code
+        df["trade_date"] = df["trade_date"].astype(str)
+        return df
+
+    # ── 财务数据 ──────────────────────────────────────────
+
+    def fetch_financial(self, ts_code: str) -> pd.DataFrame:
+        """获取单只股票核心财务指标（同花顺接口）。"""
+        symbol = ts_code.replace(".SZ", "").replace(".SH", "").replace(".BJ", "")
+        try:
+            df = ak.stock_financial_abstract_ths(symbol=symbol)
+            if df.empty:
+                return pd.DataFrame()
+
+            df = df.rename(columns={
+                "报告期": "end_date",
+                "净利润": "net_profit",
+                "净利润同比增长率": "net_profit_yoy",
+                "扣非净利润": "deducted_net_profit",
+                "扣非净利润同比增长率": "deducted_net_profit_yoy",
+                "营业总收入": "total_revenue",
+                "营业总收入同比增长率": "total_revenue_yoy",
+                "基本每股收益": "eps",
+                "每股净资产": "bvps",
+                "每股资本公积金": "capital_reserve_ps",
+                "每股未分配利润": "undistributed_profit_ps",
+                "每股经营现金流": "ocf_ps",
+                "销售净利率": "net_profit_margin",
+                "净资产收益率": "roe",
+                "净资产收益率-摊薄": "roe_diluted",
+                "营业周期": "operating_cycle",
+                "应收账款周转天数": "receivables_days",
+                "流动比率": "current_ratio",
+                "速动比率": "quick_ratio",
+                "保守速动比率": "conservative_quick_ratio",
+                "产权比率": "equity_ratio",
+                "资产负债率": "debt_to_assets",
+            })
+            df["ts_code"] = ts_code
+            # 日期格式统一
+            df["end_date"] = df["end_date"].astype(str).str.replace("-", "")
+            # 数值列清洗：去掉 万/亿/% 等单位
+            for col in df.columns:
+                if col in ("ts_code", "end_date"):
+                    continue
+                df[col] = self._parse_financial_value(df[col])
+            return df
+        except Exception:
+            return pd.DataFrame()
+
+    @staticmethod
+    def _parse_financial_value(series: pd.Series) -> pd.Series:
+        """解析财务数值字符串 '4302.00万', '64.75%', 'False' → float"""
+        def _parse(v):
+            if v is None or v == "False" or v == "":
+                return None
+            if isinstance(v, (int, float)):
+                return float(v)
+            s = str(v).strip()
+            if not s:
+                return None
+            try:
+                if s.endswith("%"):
+                    return float(s[:-1])
+                if "万" in s:
+                    return float(s.replace("万", "")) * 1e4
+                if "亿" in s:
+                    return float(s.replace("亿", "")) * 1e8
+                return float(s)
+            except ValueError:
+                return None
+        return series.apply(_parse).astype("float64")