实现全部 CHOICE 财务接口, 补充测试/文档/部署配置

- 新增 9 个抓取模块: 三大报表/盈利能力/资本结构/营运能力/成长能力/杜邦/分红
- api.py 新增 10 个 /fin/* 接口并统一无数据返回
- 新增 _emchoice.py 共享请求辅助 (emws 跳转取 URL / datacenter 报表拉取)
- 新增冒烟测试 tests/test_interfaces.py (24 用例)
- 新增接口文档 api_manual.md 与施工蓝图 blueprint.md
- 新增 Dockerfile / docker-compose.yml / deploy.sh 部署配置

utils/fin_profitability.py

@@ -0,0 +1,74 @@
+"""东方财富 CHOICE API 盈利能力与收益质量抓取工具。
+- 输入: 股票代码列表 (如 ['603233.SH'])
+- 输出: pandas DataFrame (按报告期的盈利能力/收益质量指标)
+- 不需要登录, 不需要 cookie, 无文件落盘
+"""
+from __future__ import annotations
+
+import pandas as pd
+
+from utils._emchoice import get_data_url, fetch_report
+
+
+_PATH = "/stock/f9/CWFX_YLNLYSYZL"
+
+# 默认报告期类型: 1=一季报, 3=三季报, 5=中报, 6=年报 (注意: 该接口需带引号)
+_DEFAULT_REPORT_PERIOD_TYPE = '"1","5","3","6","7"'
+
+
+def _build_params(
+    secucode: str,
+    start_date: str,
+    end_date: str,
+    report_period_type: str,
+) -> dict[str, str]:
+    """构造 CWFX_YLNLYSYZL 请求参数 (其余参数沿用 docs/api_docs.md 抓包值)."""
+    return {
+        "SecurityCode": secucode,
+        "StartDate": start_date,
+        "EndDate": end_date,
+        "ReportPeriodType": report_period_type,
+        "Sort": "-1",
+        "Digits": "2",
+        "IsShowEmptyRow": "true",
+    }
+
+
+def _fetch_one(
+    secucode: str,
+    years: int,
+    report_period_type: str,
+) -> pd.DataFrame:
+    """拉一只股票的盈利能力与收益质量指标."""
+    today = pd.Timestamp.today()
+    start = (today - pd.DateOffset(years=years)).strftime("%Y-%m-%d")
+    end = today.strftime("%Y-%m-%d")
+
+    params = _build_params(secucode, start, end, report_period_type)
+    data_url = get_data_url(_PATH, params)
+    rows = fetch_report(data_url)
+    df = pd.DataFrame(rows)
+    if not df.empty:
+        df["SECUCODE"] = secucode
+    return df
+
+
+def get_profitability(
+    secucodes: list[str],
+    years: int = 3,
+    report_period_type: str = _DEFAULT_REPORT_PERIOD_TYPE,
+) -> pd.DataFrame:
+    """抓取指定股票的盈利能力与收益质量指标并按股票合并。"""
+    codes = [code.strip() for code in secucodes if code.strip()]
+    if not codes:
+        return pd.DataFrame()
+
+    frames: list[pd.DataFrame] = []
+    for code in codes:
+        df = _fetch_one(code, years, report_period_type)
+        if not df.empty:
+            frames.append(df)
+
+    if not frames:
+        return pd.DataFrame()
+    return pd.concat(frames, ignore_index=True)