知微
fa45d8aa5f
- health_checklist.json: 192.168.1.122→node122
- ocr_client.py: docstring IP→node122
- docs/market-data-requirements.md: IP→node122
- 所有API调用通过ProxyHandler({})绕过系统代理
Privoxy对node122:18003返回500，直连正常
72 lines
2.3 KiB
Python
72 lines
2.3 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2026/1/20 15:00
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Desc: 上海证券交易所-ETF基金份额数据
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https://www.sse.com.cn/assortment/fund/etf/list/scale/
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"""
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import pandas as pd
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import requests
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def fund_etf_scale_sse(date: str = "20250115") -> pd.DataFrame:
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"""
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上海证券交易所-产品-基金产品-ETF产品-ETF产品列表-基金规模
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https://www.sse.com.cn/assortment/fund/etf/list/scale/
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:param date: 统计日期, 默认为空返回最新数据, 格式如 "20250115"
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:type date: str
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:return: ETF基金份额数据
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:rtype: pandas.DataFrame
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"""
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data_str = "-".join([date[:4], date[4:6], date[6:]])
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url = "https://query.sse.com.cn/commonQuery.do"
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params = {
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"isPagination": "true",
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"pageHelp.pageSize": "10000",
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"pageHelp.pageNo": "1",
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"pageHelp.beginPage": "1",
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"pageHelp.cacheSize": "1",
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"pageHelp.endPage": "1",
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"sqlId": "COMMON_SSE_ZQPZ_ETFZL_XXPL_ETFGM_SEARCH_L",
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"STAT_DATE": data_str,
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}
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headers = {
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"Referer": "https://www.sse.com.cn/",
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/88.0.4324.150 Safari/537.36",
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}
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r = requests.get(url, params=params, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["result"])
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temp_df.rename(
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columns={
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"NUM": "序号",
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"SEC_CODE": "基金代码",
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"SEC_NAME": "基金简称",
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"ETF_TYPE": "ETF类型",
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"STAT_DATE": "统计日期",
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"TOT_VOL": "基金份额",
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},
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inplace=True,
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)
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temp_df = temp_df[
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[
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"序号",
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"基金代码",
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"基金简称",
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"ETF类型",
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"统计日期",
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"基金份额",
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]
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]
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temp_df["序号"] = pd.to_numeric(temp_df["序号"], errors="coerce")
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temp_df["统计日期"] = pd.to_datetime(temp_df["统计日期"], errors="coerce").dt.date
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temp_df["基金份额"] = pd.to_numeric(temp_df["基金份额"], errors="coerce") * 10000
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return temp_df
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if __name__ == "__main__":
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fund_etf_scale_sse_df = fund_etf_scale_sse(date="20250115")
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print(fund_etf_scale_sse_df)
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