feat: 新增北京证券交易所融资融券数据接口，与现有的深圳证券交易所融资融券接口对齐。

akshare/__init__.py

@@ -3270,6 +3270,7 @@
 1.18.62 fix: fix stock_market_activity_legu interface
 1.18.63 fix: fix stock_a_high_low_statistics interface
 1.18.64 fix: fix stock_buffett_index_lg interface
+1.18.65 add: add stock_margin_bse, stock_margin_detail_bse, stock_margin_underlying_info_bse interface
 """
 
 from akshare._version import __version__
@@ -4743,6 +4744,11 @@
     stock_margin_sse,
     stock_margin_ratio_pa,
 )
+from akshare.stock_feature.stock_margin_bse import (
+    stock_margin_bse,
+    stock_margin_detail_bse,
+    stock_margin_underlying_info_bse,
+)
 
 """
 期货交割和期转现

akshare/stock_feature/stock_margin_bse.py

@@ -0,0 +1,166 @@
+#!/usr/bin/env python
+# -*- coding:utf-8 -*-
+"""
+Date: 2024/6/14 17:00
+Desc: 北京证券交易所-融资融券数据
+https://www.bseinfo.net/disclosure/rzrq_trans_list.html
+"""
+
+import json
+import random
+import re
+import time
+import warnings
+from io import BytesIO
+
+import pandas as pd
+import requests
+
+
+def stock_margin_underlying_info_bse(date: str = "20260605") -> pd.DataFrame:
+    """
+    北京证券交易所-融资融券数据-标的证券信息
+    https://www.bseinfo.net/disclosure/rzrq_bdzq_list.html
+    :param date: 交易日
+    :type date: str
+    :return: 标的证券信息
+    :rtype: pandas.DataFrame
+    """
+    url = "https://www.bseinfo.net/rzrqbdzqController/export.do"
+    params = {
+        "zqdm": "",
+        "transDate": "-".join([date[:4], date[4:6], date[6:]]),
+    }
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
+        "Chrome/88.0.4324.150 Safari/537.36",
+    }
+    r = requests.get(url, params=params, headers=headers)
+    with warnings.catch_warnings(record=True):
+        warnings.simplefilter("always")
+        temp_df = pd.read_excel(BytesIO(r.content), engine="xlrd", dtype={"证券代码": str})
+    # 去掉最后一行的日期统计行
+    temp_df = temp_df[temp_df["证券代码"].str.match(r"^\d+$", na=False)]
+    return temp_df
+
+
+def stock_margin_bse(date: str = "20260603") -> pd.DataFrame:
+    """
+    北京证券交易所-融资融券数据-融资融券汇总
+    https://www.bseinfo.net/disclosure/rzrq_trans_list.html
+    :param date: 交易日
+    :type date: str
+    :return: 融资融券汇总
+    :rtype: pandas.DataFrame
+    """
+    url = "https://www.bseinfo.net/rzrqjyyexxController/summaryInfoResult.do"
+    # 生成jQuery风格的JSONP callback参数和防缓存参数
+    timestamp = int(time.time() * 1000)
+    callback = f"jQuery{random.randint(10**18, 10**19-1)}_{timestamp}"
+    params = {
+        "callback": callback,
+        "transDate": "-".join([date[:4], date[4:6], date[6:]]),
+        "page": "0",
+        "_": str(timestamp),
+    }
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
+        "Chrome/88.0.4324.150 Safari/537.36",
+    }
+    r = requests.get(url, params=params, headers=headers)
+    # 解析JSONP响应
+    json_str = re.search(r"\((.*)\)", r.text).group(1)
+    json_str = json_str.replace("'", '"')
+    data_json = json.loads(json_str)
+    temp_df = pd.DataFrame(data_json[0])
+    temp_df = temp_df[
+        [
+            "rzmre",
+            "rzye",
+            "rqmcl",
+            "rqyl",
+            "rqye",
+            "rzrqye",
+        ]
+    ]
+    temp_df.columns = [
+        "融资买入额",
+        "融资余额",
+        "融券卖出量",
+        "融券余量",
+        "融券余额",
+        "融资融券余额",
+    ]
+    temp_df["融资买入额"] = temp_df["融资买入额"].astype(str).str.replace(",", "")
+    temp_df["融资买入额"] = pd.to_numeric(temp_df["融资买入额"], errors="coerce")
+    temp_df["融资余额"] = temp_df["融资余额"].astype(str).str.replace(",", "")
+    temp_df["融资余额"] = pd.to_numeric(temp_df["融资余额"], errors="coerce")
+    temp_df["融券卖出量"] = temp_df["融券卖出量"].astype(str).str.replace(",", "")
+    temp_df["融券卖出量"] = pd.to_numeric(temp_df["融券卖出量"], errors="coerce")
+    temp_df["融券余量"] = temp_df["融券余量"].astype(str).str.replace(",", "")
+    temp_df["融券余量"] = pd.to_numeric(temp_df["融券余量"], errors="coerce")
+    temp_df["融券余额"] = temp_df["融券余额"].astype(str).str.replace(",", "")
+    temp_df["融券余额"] = pd.to_numeric(temp_df["融券余额"], errors="coerce")
+    temp_df["融资融券余额"] = temp_df["融资融券余额"].astype(str).str.replace(",", "")
+    temp_df["融资融券余额"] = pd.to_numeric(temp_df["融资融券余额"], errors="coerce")
+    return temp_df
+
+
+def stock_margin_detail_bse(date: str = "20260603") -> pd.DataFrame:
+    """
+    北京证券交易所-融资融券数据-融资融券交易明细
+    https://www.bseinfo.net/disclosure/rzrq_trans_list.html
+    :param date: 交易日期
+    :type date: str
+    :return: 融资融券明细
+    :rtype: pandas.DataFrame
+    """
+    url = "https://www.bseinfo.net/rzrqjyyexxController/exportDetail.do"
+    params = {
+        "transDateDetail": "-".join([date[:4], date[4:6], date[6:]]),
+    }
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
+        "Chrome/88.0.4324.150 Safari/537.36",
+    }
+    r = requests.get(url, params=params, headers=headers)
+    with warnings.catch_warnings(record=True):
+        warnings.simplefilter("always")
+        temp_df = pd.read_excel(BytesIO(r.content), engine="xlrd", dtype={"证券代码": str})
+    # 去掉最后一行的日期统计行
+    temp_df = temp_df[temp_df["证券代码"].str.match(r"^\d+$", na=False)]
+    temp_df.columns = [
+        "证券代码",
+        "证券简称",
+        "融资买入额",
+        "融资余额",
+        "融券卖出量",
+        "融券余量",
+        "融券余额",
+        "融资融券余额",
+    ]
+    temp_df["证券简称"] = temp_df["证券简称"].astype(str).str.replace(" ", "")
+    temp_df["融资买入额"] = temp_df["融资买入额"].astype(str).str.replace(",", "")
+    temp_df["融资买入额"] = pd.to_numeric(temp_df["融资买入额"], errors="coerce")
+    temp_df["融资余额"] = temp_df["融资余额"].astype(str).str.replace(",", "")
+    temp_df["融资余额"] = pd.to_numeric(temp_df["融资余额"], errors="coerce")
+    temp_df["融券卖出量"] = temp_df["融券卖出量"].astype(str).str.replace(",", "")
+    temp_df["融券卖出量"] = pd.to_numeric(temp_df["融券卖出量"], errors="coerce")
+    temp_df["融券余量"] = temp_df["融券余量"].astype(str).str.replace(",", "")
+    temp_df["融券余量"] = pd.to_numeric(temp_df["融券余量"], errors="coerce")
+    temp_df["融券余额"] = temp_df["融券余额"].astype(str).str.replace(",", "")
+    temp_df["融券余额"] = pd.to_numeric(temp_df["融券余额"], errors="coerce")
+    temp_df["融资融券余额"] = temp_df["融资融券余额"].astype(str).str.replace(",", "")
+    temp_df["融资融券余额"] = pd.to_numeric(temp_df["融资融券余额"], errors="coerce")
+    return temp_df
+
+
+if __name__ == "__main__":
+    stock_margin_underlying_info_bse_df = stock_margin_underlying_info_bse(date="20260605")
+    print(stock_margin_underlying_info_bse_df)
+
+    stock_margin_bse_df = stock_margin_bse(date="20260603")
+    print(stock_margin_bse_df)
+
+    stock_margin_detail_bse_df = stock_margin_detail_bse(date="20260604")
+    print(stock_margin_detail_bse_df)