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
114 lines
3.7 KiB
Python
114 lines
3.7 KiB
Python
# -*- coding:utf-8 -*-
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# !/usr/bin/env python
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"""
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Date: 2025/11/20 22:00
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Desc: 巨潮资讯-个股-历史分红
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https://webapi.cninfo.com.cn/#/company?companyid=600009
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"""
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import pandas as pd
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import py_mini_racer
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import requests
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from akshare.datasets import get_ths_js
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def _get_file_content_ths(file: str = "cninfo.js") -> str:
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"""
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获取 JS 文件的内容
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:param file: JS 文件名
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:type file: str
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:return: 文件内容
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:rtype: str
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"""
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setting_file_path = get_ths_js(file)
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with open(setting_file_path, encoding="utf-8") as f:
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file_data = f.read()
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return file_data
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def stock_dividend_cninfo(symbol: str = "600009") -> pd.DataFrame:
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"""
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巨潮资讯-个股-历史分红
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https://webapi.cninfo.com.cn/#/company?companyid=600009
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:param symbol: 股票代码
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:type symbol: str
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:return: 历史分红
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:rtype: pandas.DataFrame
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"""
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url = "https://webapi.cninfo.com.cn/api/sysapi/p_sysapi1139"
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params = {"scode": symbol}
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js_code = py_mini_racer.MiniRacer()
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js_content = _get_file_content_ths("cninfo.js")
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js_code.eval(js_content)
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mcode = js_code.call("getResCode1")
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headers = {
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"Accept": "*/*",
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"Accept-Enckey": mcode,
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"Accept-Encoding": "gzip, deflate",
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"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
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"Cache-Control": "no-cache",
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"Content-Length": "0",
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"Host": "webapi.cninfo.com.cn",
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"Origin": "http://webapi.cninfo.com.cn",
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"Pragma": "no-cache",
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"Proxy-Connection": "keep-alive",
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"Referer": "http://webapi.cninfo.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/93.0.4577.63 Safari/537.36",
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"X-Requested-With": "XMLHttpRequest",
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}
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r = requests.post(url, params=params, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["records"])
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temp_df.rename(
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columns={
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"F006D": "实施方案公告日期",
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"F044V": "分红类型",
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"F011N": "转增比例",
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"F010N": "送股比例",
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"F012N": "派息比例",
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"F018D": "股权登记日",
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"F020D": "除权日",
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"F023D": "派息日",
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"F025D": "股份到账日",
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"F007V": "实施方案分红说明",
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"F001V": "报告时间",
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},
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inplace=True,
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)
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temp_df["实施方案公告日期"] = pd.to_datetime(
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temp_df["实施方案公告日期"], errors="coerce"
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).dt.date
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temp_df["送股比例"] = pd.to_numeric(temp_df["送股比例"], errors="coerce")
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temp_df["转增比例"] = pd.to_numeric(temp_df["转增比例"], errors="coerce")
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temp_df["派息比例"] = pd.to_numeric(temp_df["派息比例"], errors="coerce")
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temp_df["股权登记日"] = pd.to_datetime(
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temp_df["股权登记日"], errors="coerce"
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).dt.date
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temp_df["除权日"] = pd.to_datetime(temp_df["除权日"], errors="coerce").dt.date
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temp_df["派息日"] = pd.to_datetime(temp_df["派息日"], errors="coerce").dt.date
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temp_df.sort_values(by="实施方案公告日期", ignore_index=True, inplace=True)
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temp_df = temp_df[
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[
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"实施方案公告日期",
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"分红类型",
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"送股比例",
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"转增比例",
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"派息比例",
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"股权登记日",
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"除权日",
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"派息日",
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"股份到账日",
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"实施方案分红说明",
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"报告时间",
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]
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]
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return temp_df
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if __name__ == "__main__":
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stock_dividend_cninfo_df = stock_dividend_cninfo(symbol="600009")
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print(stock_dividend_cninfo_df)
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