#!/usr/bin/env python # -*- coding:utf-8 -*- """ Date: 2024/10/22 15:00 Desc: 巨潮资讯-数据浏览器-筹资指标-公司配股实施方案 https://webapi.cninfo.com.cn/#/dataBrowse """ import pandas as pd import py_mini_racer import requests from akshare.datasets import get_ths_js def _get_file_content_cninfo(file: str = "cninfo.js") -> str: """ 获取 JS 文件的内容 :param file: JS 文件名 :type file: str :return: 文件内容 :rtype: str """ setting_file_path = get_ths_js(file) with open(setting_file_path, encoding="utf-8") as f: file_data = f.read() return file_data def stock_allotment_cninfo( symbol: str = "600030", start_date: str = "19700101", end_date: str = "22220222" ) -> pd.DataFrame: """ 巨潮资讯-个股-配股实施方案 https://webapi.cninfo.com.cn/#/dataBrowse :param symbol: 股票代码 :type symbol: str :param start_date: 开始查询的日期 :type symbol: str :param end_date: 结束查询的日期 :type symbol: str :return: 配股实施方案 :rtype: pandas.DataFrame """ url = "https://webapi.cninfo.com.cn/api/stock/p_stock2232" params = { "scode": symbol, "sdate": start_date if not start_date else f"{start_date[0:4]}-{start_date[4:6]}-{start_date[6:8]}", "edate": end_date if not end_date else f"{end_date[0:4]}-{end_date[4:6]}-{end_date[6:8]}", } js_code = py_mini_racer.MiniRacer() js_content = _get_file_content_cninfo("cninfo.js") js_code.eval(js_content) mcode = js_code.call("getResCode1") headers = { "Accept": "*/*", "Accept-Enckey": mcode, "Accept-Encoding": "gzip, deflate", "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8", "Cache-Control": "no-cache", "Content-Length": "0", "Host": "webapi.cninfo.com.cn", "Origin": "https://webapi.cninfo.com.cn", "Pragma": "no-cache", "Proxy-Connection": "keep-alive", "Referer": "https://webapi.cninfo.com.cn/", "X-Requested-With": "XMLHttpRequest", } r = requests.post(url, params=params, headers=headers) data_json = r.json() columns = [ "记录标识", "证券简称", "停牌起始日", "上市公告日期", "配股缴款起始日", "可转配股数量", "停牌截止日", "实际配股数量", "配股价格", "配股比例", "配股前总股本", "每股配权转让费(元)", "法人股实配数量", "实际募资净额", "大股东认购方式", "其他配售简称", "发行方式", "配股失败，退还申购款日期", "除权基准日", "预计发行费用", "配股发行结果公告日", "证券代码", "配股权证交易截止日", "其他股份实配数量", "国家股实配数量", "委托单位", "公众获转配数量", "其他配售代码", "配售对象", "配股权证交易起始日", "资金到账日", "机构名称", "股权登记日", "实际募资总额", "预计募集资金", "大股东认购数量", "公众股实配数量", "转配股实配数量", "承销费用", "法人获转配数量", "配股后流通股本", "股票类别", "公众配售简称", "发行方式编码", "承销方式", "公告日期", "配股上市日", "配股缴款截止日", "承销余额(股)", "预计配股数量", "配股后总股本", "职工股实配数量", "承销方式编码", "发行费用总额", "配股前流通股本", "股票类别编码", "公众配售代码", ] if data_json["records"]: # 有配股记录 temp_df = pd.DataFrame(data_json["records"]) temp_df.columns = columns dates = ( "停牌起始日", "上市公告日期", "配股失败，退还申购款日期", "配股缴款起始日", "停牌截止日", "除权基准日", "配股发行结果公告日", "配股权证交易截止日", "配股权证交易起始日", "资金到账日", "股权登记日", "公告日期", "配股上市日", "配股缴款截止日", ) for s in dates: temp_df[s] = pd.to_datetime(temp_df[s], errors="coerce").dt.date nums = ( "可转配股数量", "实际配股数量", "配股价格", "配股比例", "配股前总股本", "每股配权转让费(元)", "法人股实配数量", "实际募资净额", "预计发行费用", "其他股份实配数量", "国家股实配数量", "公众获转配数量", "实际募资总额", "预计募集资金", "大股东认购数量", "公众股实配数量", "转配股实配数量", "承销费用", "法人获转配数量", "配股后流通股本", "承销余额(股)", "预计配股数量", "配股后总股本", "职工股实配数量", "发行费用总额", "配股前流通股本", ) for s in nums: temp_df[s] = pd.to_numeric(temp_df[s], errors="coerce") else: # 没有配股数据 temp_df = pd.DataFrame(columns=columns) return temp_df if __name__ == "__main__": stock_allotment_cninfo_df = stock_allotment_cninfo( symbol="600030", start_date="19900101", end_date="20241022" ) print(stock_allotment_cninfo_df)