# -*- coding:utf-8 -*- # !/usr/bin/env python """ Date: 2026/2/22 13:00 Desc: 天天基金网-基金数据-分红送配 https://fund.eastmoney.com/data/fundfenhong.html """ import pandas as pd import requests from akshare.utils.tqdm import get_tqdm def fund_fh_em( year: str = "2025", typ: str = "", rank: str = "BZDM", sort: str = "asc", page: int = -1, ) -> pd.DataFrame: """ 天天基金网-基金数据-分红送配-基金分红 https://fund.eastmoney.com/data/fundfenhong.html#DJR,desc,1,,, :param year: 查询年份 :type year: str :param typ: 基金类型；空串表示全部; choice of {"指数型-其他", "指数型-海外股票", "指数型-固收", "指数型-股票", "债券型-中短债", "债券型-长债", "债券型-理财", "债券型-混合债", "债券型-混合一级", "债券型-混合二级", "货币型-普通货币", "货币型-浮动净值", "混合型-平衡", "混合型-偏债", "混合型-偏股", "混合型-灵活", "混合型-绝对收益", "股票型", "REITs", "Reits", "QDII-商品", "QDII-普通股票", "QDII-混合债", "QDII-混合偏股", "QDII-纯债", "QDII-REITs", "FOF"} :type typ: str :param rank: 排序字段；choice of {"BZDM", "ABBNAME", "DJR", "FSRQ", "FHFCZ", "FFR"}; "BZDM": 基金代码, "ABBNAME": 基金简称, "DJR": 权益登记日, "FSRQ": 除息日期, "FHFCZ": 分红(元/份), "FFR": 分红发放日 :type rank: str :param sort: 排序方向；排序方式; choice of {"asc", "desc"} :type sort: str :param page: 查询页数；请求第page页数据; -1 表示全部页面 :type page: int :return: 基金分红 :rtype: pandas.DataFrame """ def get_df_from_response(response): text = response.text return pd.DataFrame(eval(text[text.find("[["): text.find(";var jjfh_jjgs")])) url = "https://fund.eastmoney.com/Data/funddataIndex_Interface.aspx" params = { "dt": "8", "page": "1" if page == -1 else str(page), "rank": rank, "sort": sort, "gs": "", "ftype": typ, "year": year, } r = requests.get(url, params=params) data_list = [get_df_from_response(r)] if page == -1: data_text = r.text total_page = eval(data_text[data_text.find("=") + 1: data_text.find(";")])[0] tqdm = get_tqdm() for p in tqdm(range(2, total_page + 1), leave=False): params.update({"page": str(p)}) r = requests.get(url, params=params) data_list.append(get_df_from_response(r)) big_df = pd.concat(objs=data_list, ignore_index=True) big_df.reset_index(inplace=True) big_df["index"] = big_df.index + 1 # 处理空数据时报错的问题 if big_df.empty: big_df = big_df.reindex( columns=[ "序号", "基金代码", "基金简称", "权益登记日", "除息日期", "分红", "分红发放日", "-", ] ) big_df.columns = [ "序号", "基金代码", "基金简称", "权益登记日", "除息日期", "分红", "分红发放日", "-", ] big_df = big_df[ ["序号", "基金代码", "基金简称", "权益登记日", "除息日期", "分红", "分红发放日"] ] big_df["权益登记日"] = pd.to_datetime(big_df["权益登记日"]).dt.date big_df["除息日期"] = pd.to_datetime(big_df["除息日期"]).dt.date big_df["分红发放日"] = pd.to_datetime(big_df["分红发放日"]).dt.date big_df["分红"] = pd.to_numeric(big_df["分红"]) return big_df def fund_cf_em( year: str = "2025", typ: str = "", rank: str = "FSRQ", sort: str = "desc", page: int = -1, ) -> pd.DataFrame: """ 天天基金网-基金数据-分红送配-基金拆分 https://fund.eastmoney.com/data/fundchaifen.html#FSRQ,desc,1,,, :param year: 查询年份 :type year: str :param typ: 基金类型；空串表示全部; choice of {"", "指数型-其他", "指数型-海外股票", "指数型-固收", "指数型-股票", "债券型-中短债", "债券型-长债", "债券型-可转债", "债券型-混合债", "债券型-混合一级", "债券型-混合二级", "商品（不含QDII）", "货币型", "混合型-平衡", "混合型-偏债", "混合型-偏股", "混合型-灵活", "股票型", "QDII", "FOF"} :type typ: str :param rank: 排序字段；choice of {"BZDM", "ABBNAME", "FSRQ", "FHFCZ"}; "BZDM": 基金代码, "ABBNAME": 基金简称, "FSRQ": 拆分折算日, "FHFCZ": 拆分折算(每份) :type rank: str :param sort: 排序方向；choice of {"asc", "desc"} :type sort: str :param page: 查询页数；请求第page页数据; -1 表示全部页面 :type page: int :return: 基金拆分 :rtype: pandas.DataFrame """ def get_df_from_response(response): text = response.text code = text[text.find("[["): text.find(";var jjcf_jjgs")] if code: return pd.DataFrame(eval(code)) return pd.DataFrame() url = "https://fund.eastmoney.com/Data/funddataIndex_Interface.aspx" params = { "dt": "9", "page": "1" if page == -1 else str(page), "rank": rank, "sort": sort, "gs": "", "ftype": typ, "year": year, } r = requests.get(url, params=params) data_list = [get_df_from_response(r)] if page == -1: data_text = r.text total_page = eval(data_text[data_text.find("=") + 1: data_text.find(";")])[0] tqdm = get_tqdm() for p in tqdm(range(2, total_page + 1), leave=False): params.update({"page": str(p)}) r = requests.get(url, params=params) data_list.append(get_df_from_response(r)) big_df = pd.concat(objs=data_list, ignore_index=True) big_df.reset_index(inplace=True) big_df.loc[:, "index"] = big_df["index"] + 1 # 处理空数据时报错的问题 if big_df.empty: big_df = big_df.reindex( columns=[ "序号", "基金代码", "基金简称", "拆分折算日", "拆分类型", "拆分折算", "-", ] ) big_df.columns = [ "序号", "基金代码", "基金简称", "拆分折算日", "拆分类型", "拆分折算", "-", ] big_df = big_df[ ["序号", "基金代码", "基金简称", "拆分折算日", "拆分类型", "拆分折算"] ] big_df["拆分折算日"] = pd.to_datetime(big_df["拆分折算日"]).dt.date big_df["拆分折算"] = pd.to_numeric(big_df["拆分折算"], errors="coerce") return big_df def fund_fh_rank_em() -> pd.DataFrame: """ 天天基金网-基金数据-分红送配-基金分红排行 https://fund.eastmoney.com/data/fundleijifenhong.html :return: 基金分红排行 :rtype: pandas.DataFrame """ url = "https://fund.eastmoney.com/Data/funddataIndex_Interface.aspx" params = { "dt": "10", "page": "1", "rank": "FHFCZ", "sort": "desc", "gs": "", "ftype": "", } r = requests.get(url, params=params) data_text = r.text total_page = eval(data_text[data_text.find("=") + 1: data_text.find(";")])[0] big_df = pd.DataFrame() tqdm = get_tqdm() for page in tqdm(range(1, total_page + 1), leave=False): params.update({"page": str(page)}) r = requests.get(url, params=params) data_text = r.text temp_list = eval( data_text[data_text.find("[["): data_text.find(";var fhph_jjgs")] ) temp_df = pd.DataFrame(temp_list) big_df = pd.concat(objs=[big_df, temp_df], ignore_index=True) big_df.reset_index(inplace=True) big_df["index"] = big_df.index + 1 # 处理空数据时报错的问题 if big_df.empty: big_df = big_df.reindex( columns=[ "序号", "基金代码", "基金简称", "累计分红", "累计次数", "成立日期", "-", ] ) big_df.columns = [ "序号", "基金代码", "基金简称", "累计分红", "累计次数", "成立日期", "-", ] big_df = big_df[ ["序号", "基金代码", "基金简称", "累计分红", "累计次数", "成立日期"] ] big_df["成立日期"] = pd.to_datetime(big_df["成立日期"]).dt.date big_df["累计分红"] = pd.to_numeric(big_df["累计分红"], errors="coerce") big_df["累计次数"] = pd.to_numeric(big_df["累计次数"], errors="coerce") return big_df if __name__ == "__main__": fund_fh_em_df = fund_fh_em(year="2025") print(fund_fh_em_df) fund_cf_em_df = fund_cf_em(year="2025") print(fund_cf_em_df) fund_fh_rank_em_df = fund_fh_rank_em() print(fund_fh_rank_em_df)