#!/usr/bin/env python # -*- coding:utf-8 -*- """ Date: 2024/6/7 20:00 Desc: 天天基金网-基金档案-投资组合 https://fundf10.eastmoney.com/ccmx_000001.html """ from io import StringIO import pandas as pd import requests from bs4 import BeautifulSoup from akshare.utils import demjson def fund_portfolio_hold_em(symbol: str = "000001", date: str = "2024") -> pd.DataFrame: """ 天天基金网-基金档案-投资组合-基金持仓 https://fundf10.eastmoney.com/ccmx_000001.html :param symbol: 基金代码 :type symbol: str :param date: 查询年份 :type date: str :return: 基金持仓 :rtype: pandas.DataFrame """ url = "https://fundf10.eastmoney.com/FundArchivesDatas.aspx" params = { "type": "jjcc", "code": symbol, "topline": "10000", "year": date, "month": "", "rt": "0.913877030254846", } r = requests.get(url, params=params) data_text = r.text data_json = demjson.decode(data_text[data_text.find("{") : -1]) soup = BeautifulSoup(data_json["content"], features="lxml") item_label = [ item.text.split("\xa0\xa0")[1] for item in soup.find_all(name="h4", attrs={"class": "t"}) ] column_name = [ "序号", "股票代码", "股票名称", "占净值比例", "持股数", "持仓市值", "季度", ] big_df = pd.DataFrame(columns=column_name) for item in range(len(item_label)): temp_df = pd.read_html( StringIO(data_json["content"]), converters={"股票代码": str} )[item] del temp_df["相关资讯"] temp_df.rename(columns={"占净值 比例": "占净值比例"}, inplace=True) temp_df["占净值比例"] = ( temp_df["占净值比例"].str.split("%", expand=True).iloc[:, 0] ) temp_df.rename( columns={"持股数（万股）": "持股数", "持仓市值（万元）": "持仓市值"}, inplace=True, ) temp_df.rename( columns={"持股数 （万股）": "持股数", "持仓市值 （万元）": "持仓市值"}, inplace=True, ) temp_df.rename( columns={"持股数（万股）": "持股数", "持仓市值（万元人民币）": "持仓市值"}, inplace=True, ) temp_df.rename( columns={ "持股数 （万股）": "持股数", "持仓市值 （万元人民币）": "持仓市值", }, inplace=True, ) temp_df["季度"] = item_label[item] temp_df = temp_df[column_name] big_df = ( pd.concat(objs=[temp_df, big_df], ignore_index=True) if not big_df.empty else temp_df ) if not big_df.empty: big_df["占净值比例"] = pd.to_numeric(big_df["占净值比例"], errors="coerce") big_df["持股数"] = pd.to_numeric(big_df["持股数"], errors="coerce") big_df["持仓市值"] = pd.to_numeric(big_df["持仓市值"], errors="coerce") del big_df["序号"] big_df.reset_index(inplace=True, drop=False) big_df["index"] = big_df["index"] + 1 big_df.rename(columns={"index": "序号"}, inplace=True) return big_df def fund_portfolio_bond_hold_em( symbol: str = "000001", date: str = "2023" ) -> pd.DataFrame: """ 天天基金网-基金档案-投资组合-债券持仓 https://fundf10.eastmoney.com/ccmx1_000001.html :param symbol: 基金代码 :type symbol: str :param date: 查询年份 :type date: str :return: 债券持仓 :rtype: pandas.DataFrame """ url = "https://fundf10.eastmoney.com/FundArchivesDatas.aspx" params = { "type": "zqcc", "code": symbol, "year": date, "rt": "0.913877030254846", } r = requests.get(url, params=params) data_text = r.text data_json = demjson.decode(data_text[data_text.find("{") : -1]) soup = BeautifulSoup(data_json["content"], features="lxml") item_label = [ item.text.split("\xa0\xa0")[1] for item in soup.find_all(name="h4", attrs={"class": "t"}) ] big_df = pd.DataFrame() for item in range(len(item_label)): temp_df = pd.read_html( StringIO(data_json["content"]), converters={"债券代码": str} )[item] temp_df["占净值比例"] = ( temp_df["占净值比例"].str.split("%", expand=True).iloc[:, 0] ) temp_df.rename(columns={"持仓市值（万元）": "持仓市值"}, inplace=True) temp_df["季度"] = item_label[item] temp_df = temp_df[ [ "序号", "债券代码", "债券名称", "占净值比例", "持仓市值", "季度", ] ] big_df = pd.concat(objs=[big_df, temp_df], ignore_index=True) big_df["占净值比例"] = pd.to_numeric(big_df["占净值比例"], errors="coerce") big_df["持仓市值"] = pd.to_numeric(big_df["持仓市值"], errors="coerce") big_df["序号"] = range(1, len(big_df) + 1) return big_df def fund_portfolio_industry_allocation_em( symbol: str = "000001", date: str = "2023" ) -> pd.DataFrame: """ 天天基金网-基金档案-投资组合-行业配置 https://fundf10.eastmoney.com/hytz_000001.html :param symbol: 基金代码 :type symbol: str :param date: 查询年份 :type date: str :return: 行业配置 :rtype: pandas.DataFrame """ url = "https://api.fund.eastmoney.com/f10/HYPZ/" headers = { "Accept": "*/*", "Accept-Encoding": "gzip, deflate", "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8", "Cache-Control": "no-cache", "Connection": "keep-alive", "Host": "api.fund.eastmoney.com", "Pragma": "no-cache", "Referer": "https://fundf10.eastmoney.com/", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/99.0.4844.82 Safari/537.36", } params = { "fundCode": symbol, "year": date, "callback": "jQuery183006997159478989867_1648016188499", } r = requests.get(url, params=params, headers=headers) data_text = r.text data_json = demjson.decode(data_text[data_text.find("{") : -1]) temp_list = [] for item in data_json["Data"]["QuarterInfos"]: temp_list.extend(item["HYPZInfo"]) temp_df = pd.DataFrame(temp_list) temp_df.reset_index(inplace=True) temp_df["index"] = temp_df.index + 1 temp_df.columns = [ "序号", "-", "截止时间", "-", "行业类别", "市值", "-", "占净值比例", "-", "-", "-", "-", "-", "-", "-", "-", "-", ] temp_df = temp_df[ [ "序号", "行业类别", "占净值比例", "市值", "截止时间", ] ] temp_df["市值"] = pd.to_numeric(temp_df["市值"], errors="coerce") temp_df["占净值比例"] = pd.to_numeric(temp_df["占净值比例"], errors="coerce") return temp_df def fund_portfolio_change_em( symbol: str = "003567", indicator: str = "累计买入", date: str = "2023" ) -> pd.DataFrame: """ 天天基金网-基金档案-投资组合-重大变动 https://fundf10.eastmoney.com/ccbd_000001.html :param symbol: 基金代码 :type symbol: str :param indicator: choice of {"累计买入", "累计卖出"} :type indicator: str :param date: 查询年份 :type date: str :return: 重大变动 :rtype: pandas.DataFrame """ indicator_map = { "累计买入": "1", "累计卖出": "2", } url = "https://fundf10.eastmoney.com/FundArchivesDatas.aspx" params = { "type": "zdbd", "code": symbol, "zdbd": indicator_map[indicator], "year": date, "rt": "0.913877030254846", } r = requests.get(url, params=params) data_text = r.text data_json = demjson.decode(data_text[data_text.find("{") : -1]) soup = BeautifulSoup(data_json["content"], features="lxml") item_label = [ item.text.split("\xa0\xa0")[1] for item in soup.find_all(name="h4", attrs={"class": "t"}) ] big_df = pd.DataFrame() for item in range(len(item_label)): temp_df = pd.read_html( StringIO(data_json["content"]), converters={"股票代码": str} )[item] del temp_df["相关资讯"] temp_df["占期初基金资产净值比例（%）"] = ( temp_df["占期初基金资产净值比例（%）"] .str.split("%", expand=True) .iloc[:, 0] ) temp_df["季度"] = item_label[item] temp_df.columns = [ "序号", "股票代码", "股票名称", "本期累计买入金额", "占期初基金资产净值比例", "季度", ] temp_df = temp_df[ [ "序号", "股票代码", "股票名称", "本期累计买入金额", "占期初基金资产净值比例", "季度", ] ] big_df = pd.concat(objs=[big_df, temp_df], ignore_index=True) del big_df["序号"] big_df.reset_index(inplace=True) big_df["index"] = big_df.index + 1 big_df.rename(columns={"index": "序号"}, inplace=True) big_df["本期累计买入金额"] = pd.to_numeric( big_df["本期累计买入金额"], errors="coerce" ) big_df["占期初基金资产净值比例"] = pd.to_numeric( big_df["占期初基金资产净值比例"], errors="coerce" ) return big_df if __name__ == "__main__": fund_portfolio_hold_em_df = fund_portfolio_hold_em(symbol="000001", date="2024") print(fund_portfolio_hold_em_df) fund_portfolio_bond_hold_em_df = fund_portfolio_bond_hold_em( symbol="000001", date="2023" ) print(fund_portfolio_bond_hold_em_df) fund_portfolio_industry_allocation_em_df = fund_portfolio_industry_allocation_em( symbol="000001", date="2023" ) print(fund_portfolio_industry_allocation_em_df) fund_portfolio_change_em_df = fund_portfolio_change_em( symbol="003567", indicator="累计买入", date="2023" ) print(fund_portfolio_change_em_df) fund_portfolio_change_em_df = fund_portfolio_change_em( symbol="003567", indicator="累计卖出", date="2023" ) print(fund_portfolio_change_em_df)