# -*- coding:utf-8 -*- # !/usr/bin/env python """ Date: 2024/7/24 23:30 Desc: 巨潮资讯-数据中心-专题统计-基金报表 https://webapi.cninfo.com.cn/#/thematicStatistics """ 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 fund_report_stock_cninfo(date: str = "20210630") -> pd.DataFrame: """ 巨潮资讯-数据中心-专题统计-基金报表-基金重仓股 https://webapi.cninfo.com.cn/#/thematicStatistics :param date: 报告时间; choice of {"XXXX0331", "XXXX0630", "XXXX0930", "XXXX1231"} :type date: str :return: 基金重仓股 :rtype: pandas.DataFrame """ url = "https://webapi.cninfo.com.cn/api/sysapi/p_sysapi1112" 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/", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/93.0.4577.63 Safari/537.36", "X-Requested-With": "XMLHttpRequest", } params = { "rdate": "-".join([date[:4], date[4:6], date[6:]]), } r = requests.post(url, headers=headers, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["records"]) temp_df.rename( columns={ "F003N": "持股总市值", "F002N": "持股总数", "F001N": "基金覆盖家数", "SECNAME": "股票简称", "ID": "序号", "SECCODE": "股票代码", "ENDDATE": "报告期", }, inplace=True, ) temp_df = temp_df[ [ "序号", "股票代码", "股票简称", "报告期", "基金覆盖家数", "持股总数", "持股总市值", ] ] temp_df["报告期"] = pd.to_datetime(temp_df["报告期"], errors="coerce").dt.date temp_df["持股总数"] = pd.to_numeric(temp_df["持股总数"], errors="coerce") temp_df["持股总市值"] = pd.to_numeric(temp_df["持股总市值"], errors="coerce") temp_df["基金覆盖家数"] = pd.to_numeric(temp_df["基金覆盖家数"], errors="coerce") temp_df["序号"] = range(1, len(temp_df) + 1) return temp_df def fund_report_industry_allocation_cninfo(date: str = "20210630") -> pd.DataFrame: """ 巨潮资讯-数据中心-专题统计-基金报表-基金行业配置 https://webapi.cninfo.com.cn/#/thematicStatistics :param date: 报告时间; choice of {"XXXX0331", "XXXX0630", "XXXX0930", "XXXX1231"}, 从 2017 年开始 :type date: str :return: 基金行业配置 :rtype: pandas.DataFrame """ url = "https://webapi.cninfo.com.cn/api/sysapi/p_sysapi1113" 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/", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/93.0.4577.63 Safari/537.36", "X-Requested-With": "XMLHttpRequest", } params = { "rdate": "-".join([date[:4], date[4:6], date[6:]]), } r = requests.post(url, headers=headers, params=params) data_json = r.json() temp_df = pd.DataFrame(data_json["records"]) temp_df.rename( columns={ "F004N": "行业规模", "F003N": "基金覆盖家数", "F002V": "证监会行业名称", "F001V": "行业编码", "ENDDATE": "报告期", "F005N": "占净资产比例", }, inplace=True, ) temp_df = temp_df[ [ "行业编码", "证监会行业名称", "报告期", "基金覆盖家数", "行业规模", "占净资产比例", ] ] temp_df["报告期"] = pd.to_datetime(temp_df["报告期"], errors="coerce").dt.date temp_df["基金覆盖家数"] = pd.to_numeric(temp_df["基金覆盖家数"], errors="coerce") temp_df["行业规模"] = pd.to_numeric(temp_df["行业规模"], errors="coerce") temp_df["占净资产比例"] = pd.to_numeric(temp_df["占净资产比例"], errors="coerce") return temp_df def fund_report_asset_allocation_cninfo() -> pd.DataFrame: """ 巨潮资讯-数据中心-专题统计-基金报表-基金资产配置 https://webapi.cninfo.com.cn/#/thematicStatistics :return: 基金资产配置 :rtype: pandas.DataFrame """ url = "https://webapi.cninfo.com.cn/api/sysapi/p_sysapi1114" 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/", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/93.0.4577.63 Safari/537.36", "X-Requested-With": "XMLHttpRequest", } r = requests.post(url, headers=headers) data_json = r.json() temp_df = pd.DataFrame(data_json["records"]) temp_df.rename( columns={ "F001N": "基金覆盖家数", "F008N": "现金货币类占净资产比例", "F007N": "债券固定收益类占净资产比例", "F006N": "股票权益类占净资产比例", "ENDDATE": "报告期", "F005N": "基金市场净资产规模", }, inplace=True, ) temp_df = temp_df[ [ "报告期", "基金覆盖家数", "股票权益类占净资产比例", "债券固定收益类占净资产比例", "现金货币类占净资产比例", "基金市场净资产规模", ] ] temp_df["报告期"] = pd.to_datetime(temp_df["报告期"], errors="coerce").dt.date temp_df["基金覆盖家数"] = pd.to_numeric(temp_df["基金覆盖家数"], errors="coerce") temp_df["股票权益类占净资产比例"] = pd.to_numeric( temp_df["股票权益类占净资产比例"], errors="coerce" ) temp_df["债券固定收益类占净资产比例"] = pd.to_numeric( temp_df["债券固定收益类占净资产比例"], errors="coerce" ) temp_df["现金货币类占净资产比例"] = pd.to_numeric( temp_df["现金货币类占净资产比例"], errors="coerce" ) temp_df["基金市场净资产规模"] = pd.to_numeric( temp_df["基金市场净资产规模"], errors="coerce" ) return temp_df if __name__ == "__main__": fund_report_stock_cninfo_df = fund_report_stock_cninfo(date="20210630") print(fund_report_stock_cninfo_df) fund_report_industry_allocation_cninfo_df = fund_report_industry_allocation_cninfo( date="20210930" ) print(fund_report_industry_allocation_cninfo_df) fund_report_asset_allocation_cninfo_df = fund_report_asset_allocation_cninfo() print(fund_report_asset_allocation_cninfo_df)