#!/usr/bin/env python # -*- coding:utf-8 -*- """ Date: 2026/1/20 17:00 Desc: 东方财富网站-天天基金网-基金数据-开放式基金净值 https://fund.eastmoney.com/manager/default.html#dt14;mcreturnjson;ftall;pn20;pi1;scabbname;stasc 1.基金经理基本数据, 建议包含:基金经理代码,基金经理姓名,从业起始日期,现任基金公司,管理资产总规模,上述数据可在"基金经理列表: https://fund.eastmoney.com/manager/default.html#dt14;mcreturnjson;ftall;pn20;pi1;scabbname;stasc 和 "基金经理理档案如:https://fund.eastmoney.com/manager/30040164.html 获取. 2.基金经理任职数据:可调取全部或特定经理,管理的基金数据,建议包含:基金经理代码,基金经理姓名,基金代码,基金简称, 经理位次(在当前基金的经理中排第几位),起始任职时间,截止任职时间,任职回报.在特定基金的经理信息中可以获取如: https://fundf10.eastmoney.com/jjjl_001810.html 3.在接口：fund_basic"公募基金列表"增加数据"基金经理代码"(或第一基金经理代码), "基金经理姓名"(或第一基金经理姓名),"当前基金经理人数","当前经理任职起始时间". 用户ID:269993 """ import json import math import time from io import StringIO import pandas as pd import py_mini_racer import requests from akshare.utils import demjson from akshare.utils.cons import headers from akshare.utils.tqdm import get_tqdm def fund_purchase_em() -> pd.DataFrame: """ 东方财富网站-天天基金网-基金数据-基金申购状态 https://fund.eastmoney.com/Fund_sgzt_bzdm.html#fcode,asc_1 :return: 基金申购状态 :rtype: pandas.DataFrame """ url = "https://fund.eastmoney.com/Data/Fund_JJJZ_Data.aspx" params = { "t": "8", "page": "1,50000", "js": "reData", "sort": "fcode,asc", } r = requests.get(url, params=params, headers=headers) data_text = r.text data_json = demjson.decode(data_text.strip("var reData=")) temp_df = pd.DataFrame(data_json["datas"]) temp_df.reset_index(inplace=True) temp_df["index"] = temp_df.index + 1 temp_df.columns = [ "序号", "基金代码", "基金简称", "基金类型", "最新净值/万份收益", "最新净值/万份收益-报告时间", "申购状态", "赎回状态", "下一开放日", "购买起点", "日累计限定金额", "-", "-", "手续费", ] temp_df = temp_df[ [ "序号", "基金代码", "基金简称", "基金类型", "最新净值/万份收益", "最新净值/万份收益-报告时间", "申购状态", "赎回状态", "下一开放日", "购买起点", "日累计限定金额", "手续费", ] ] temp_df["下一开放日"] = pd.to_datetime( temp_df["下一开放日"], errors="coerce" ).dt.date temp_df["最新净值/万份收益"] = pd.to_numeric( temp_df["最新净值/万份收益"], errors="coerce" ) temp_df["购买起点"] = pd.to_numeric(temp_df["购买起点"], errors="coerce") temp_df["日累计限定金额"] = pd.to_numeric( temp_df["日累计限定金额"], errors="coerce" ) temp_df["手续费"] = temp_df["手续费"].str.strip("%") temp_df["手续费"] = pd.to_numeric(temp_df["手续费"], errors="coerce") return temp_df def fund_name_em() -> pd.DataFrame: """ 东方财富网站-天天基金网-基金数据-所有基金的名称和类型 https://fund.eastmoney.com/manager/default.html#dt14;mcreturnjson;ftall;pn20;pi1;scabbname;stasc :return: 所有基金的名称和类型 :rtype: pandas.DataFrame """ url = "https://fund.eastmoney.com/js/fundcode_search.js" r = requests.get(url, headers=headers) text_data = r.text data_json = demjson.decode(text_data.strip("var r = ")[:-1]) temp_df = pd.DataFrame(data_json) temp_df.columns = ["基金代码", "拼音缩写", "基金简称", "基金类型", "拼音全称"] return temp_df def fund_info_index_em( symbol: str = "沪深指数", indicator: str = "被动指数型" ) -> pd.DataFrame: """ 东方财富网站-天天基金网-基金数据-基金信息-指数型 https://fund.eastmoney.com/trade/zs.html :param symbol: choice of {"全部", "沪深指数", "行业主题", "大盘指数", "中盘指数", "小盘指数", "股票指数", "债券指数"} :type symbol: str :param indicator: choice of {"全部", "被动指数型", "增强指数型"} :type indicator: str :return: 基金信息-指数型 :rtype: pandas.DataFrame """ symbol_map = { "全部": "", "沪深指数": "053", "行业主题": "054", "大盘指数": "01", "中盘指数": "02", "小盘指数": "03", "股票指数": "050|001", "债券指数": "050|003", } indicator_map = { "全部": "", "被动指数型": "051", "增强指数型": "052", } url = "https://api.fund.eastmoney.com/FundTradeRank/GetRankList" if symbol in {"股票指数", "债券指数"}: params = { "ft": "zs", "sc": "1n", "st": "desc", "pi": "1", "pn": "10000", "cp": "", "ct": "", "cd": "", "ms": "", "fr": symbol_map[symbol].split("|")[0], "plevel": "", "fst": "", "ftype": symbol_map[symbol].split("|")[1], "fr1": indicator_map[indicator], "fl": "0", "isab": "1", } else: params = { "ft": "zs", "sc": "1n", "st": "desc", "pi": "1", "pn": "10000", "cp": "", "ct": "", "cd": "", "ms": "", "fr": symbol_map[symbol].split("|")[0], "plevel": "", "fst": "", "ftype": "", "fr1": indicator_map[indicator], "fl": "0", "isab": "1", } headers = { "Accept": "*/*", "Accept-Encoding": "gzip, deflate", "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8", "Cache-Control": "no-cache", "Host": "api.fund.eastmoney.com", "Pragma": "no-cache", "Proxy-Connection": "keep-alive", "Referer": "https://fund.eastmoney.com/", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/103.0.0.0 Safari/537.36", } r = requests.get(url, params=params, headers=headers) data_json = r.json() data_json = json.loads(data_json["Data"]) temp_df = pd.DataFrame([item.split("|") for item in data_json["datas"]]) temp_df.columns = [ "基金代码", "基金名称", "-", "日期", "单位净值", "日增长率", "近1周", "近1月", "近3月", "近6月", "近1年", "近2年", "近3年", "今年来", "成立来", "-", "-", "-", "手续费", "-", "-", "-", "-", "-", "起购金额", "-", "-", "-", "-", ] temp_df = temp_df[ [ "基金代码", "基金名称", "单位净值", "日期", "日增长率", "近1周", "近1月", "近3月", "近6月", "近1年", "近2年", "近3年", "今年来", "成立来", "手续费", "起购金额", ] ] temp_df["跟踪标的"] = symbol temp_df["跟踪方式"] = indicator temp_df["单位净值"] = pd.to_numeric(temp_df["单位净值"], errors="coerce") temp_df["日增长率"] = pd.to_numeric(temp_df["日增长率"], errors="coerce") temp_df["近1周"] = pd.to_numeric(temp_df["近1周"], errors="coerce") temp_df["近1月"] = pd.to_numeric(temp_df["近1月"], errors="coerce") temp_df["近3月"] = pd.to_numeric(temp_df["近3月"], errors="coerce") temp_df["近6月"] = pd.to_numeric(temp_df["近6月"], errors="coerce") temp_df["近1年"] = pd.to_numeric(temp_df["近1年"], errors="coerce") temp_df["近2年"] = pd.to_numeric(temp_df["近2年"], errors="coerce") temp_df["近3年"] = pd.to_numeric(temp_df["近3年"], errors="coerce") temp_df["今年来"] = pd.to_numeric(temp_df["今年来"], errors="coerce") temp_df["成立来"] = pd.to_numeric(temp_df["成立来"], errors="coerce") temp_df["手续费"] = pd.to_numeric(temp_df["手续费"], errors="coerce") return temp_df def fund_open_fund_daily_em() -> pd.DataFrame: """ 东方财富网-天天基金网-基金数据-开放式基金净值 https://fund.eastmoney.com/fund.html#os_0;isall_0;ft_;pt_1 :return: 当前交易日的所有开放式基金净值数据 :rtype: pandas.DataFrame """ url = "https://fund.eastmoney.com/Data/Fund_JJJZ_Data.aspx" params = { "t": "1", "lx": "1", "letter": "", "gsid": "", "text": "", "sort": "zdf,desc", "page": "1,50000", "dt": "1580914040623", "atfc": "", "onlySale": "0", } res = requests.get(url, params=params, headers=headers) text_data = res.text data_json = demjson.decode(text_data.strip("var db=")) temp_df = pd.DataFrame(data_json["datas"]) show_day = data_json["showday"] temp_df.columns = [ "基金代码", "基金简称", "-", f"{show_day[0]}-单位净值", f"{show_day[0]}-累计净值", f"{show_day[1]}-单位净值", f"{show_day[1]}-累计净值", "日增长值", "日增长率", "申购状态", "赎回状态", "-", "-", "-", "-", "-", "-", "手续费", "-", "-", "-", ] data_df = temp_df[ [ "基金代码", "基金简称", f"{show_day[0]}-单位净值", f"{show_day[0]}-累计净值", f"{show_day[1]}-单位净值", f"{show_day[1]}-累计净值", "日增长值", "日增长率", "申购状态", "赎回状态", "手续费", ] ] return data_df def fund_open_fund_info_em( symbol: str = "710001", indicator: str = "单位净值走势", period: str = "成立来" ) -> pd.DataFrame: """ 东方财富网-天天基金网-基金数据-开放式基金净值 https://fund.eastmoney.com/fund.html :param symbol: 基金代码; 可以通过调用 ak.fund_open_fund_daily_em() 获取所有开放式基金代码 :type symbol: str :param indicator: 需要获取的指标 :type indicator: str :param period: "成立来"; choice of {"1月", "3月", "6月", "1年", "3年", "5年", "今年来", "成立来"} :type period: str :return: 指定基金指定指标的数据 :rtype: pandas.DataFrame """ from akshare.utils.cons import headers url = f"https://fund.eastmoney.com/pingzhongdata/{symbol}.js" # 各类数据都在里面 r = requests.get(url, headers=headers) data_text = r.text js_code = py_mini_racer.MiniRacer() js_code.eval(data_text) # 单位净值走势 if indicator == "单位净值走势": data_json = js_code.execute("Data_netWorthTrend") temp_df = pd.DataFrame(data_json) if temp_df.empty: return pd.DataFrame() temp_df["x"] = pd.to_datetime(temp_df["x"], unit="ms", utc=True).dt.tz_convert( "Asia/Shanghai" ) temp_df["x"] = temp_df["x"].dt.date temp_df.columns = [ "净值日期", "单位净值", "日增长率", "_", ] temp_df = temp_df[ [ "净值日期", "单位净值", "日增长率", ] ] temp_df["净值日期"] = pd.to_datetime( temp_df["净值日期"], errors="coerce" ).dt.date temp_df["单位净值"] = pd.to_numeric(temp_df["单位净值"], errors="coerce") temp_df["日增长率"] = pd.to_numeric(temp_df["日增长率"], errors="coerce") return temp_df # 累计净值走势 if indicator == "累计净值走势": data_json = js_code.execute("Data_ACWorthTrend") temp_df = pd.DataFrame(data_json) if temp_df.empty: return pd.DataFrame() temp_df.columns = ["x", "y"] temp_df["x"] = pd.to_datetime(temp_df["x"], unit="ms", utc=True).dt.tz_convert( "Asia/Shanghai" ) temp_df["x"] = temp_df["x"].dt.date temp_df.columns = [ "净值日期", "累计净值", ] temp_df = temp_df[ [ "净值日期", "累计净值", ] ] temp_df["净值日期"] = pd.to_datetime( temp_df["净值日期"], errors="coerce" ).dt.date temp_df["累计净值"] = pd.to_numeric(temp_df["累计净值"], errors="coerce") return temp_df # 每万份收益 if indicator == "每万份收益": data_json = js_code.execute("Data_millionCopiesIncome") temp_df = pd.DataFrame(data_json) if temp_df.empty: return pd.DataFrame() temp_df.columns = ["x", "y"] temp_df["x"] = pd.to_datetime(temp_df["x"], unit="ms", utc=True).dt.tz_convert( "Asia/Shanghai" ) temp_df["x"] = temp_df["x"].dt.date temp_df.columns = [ "净值日期", "每万份收益", ] temp_df = temp_df[ [ "净值日期", "每万份收益", ] ] temp_df["净值日期"] = pd.to_datetime( temp_df["净值日期"], errors="coerce" ).dt.date temp_df["每万份收益"] = pd.to_numeric(temp_df["每万份收益"], errors="coerce") return temp_df # 7日年化收益率 if indicator == "7日年化收益率": data_json = js_code.execute("Data_sevenDaysYearIncome") temp_df = pd.DataFrame(data_json) if temp_df.empty: return pd.DataFrame() temp_df.columns = ["x", "y"] temp_df["x"] = pd.to_datetime(temp_df["x"], unit="ms", utc=True).dt.tz_convert( "Asia/Shanghai" ) temp_df["x"] = temp_df["x"].dt.date temp_df.columns = [ "净值日期", "7日年化收益率", ] temp_df = temp_df[ [ "净值日期", "7日年化收益率", ] ] temp_df["净值日期"] = pd.to_datetime( temp_df["净值日期"], errors="coerce" ).dt.date temp_df["7日年化收益率"] = pd.to_numeric( temp_df["7日年化收益率"], errors="coerce" ) return temp_df # 累计收益率走势 if indicator == "累计收益率走势": url = "https://api.fund.eastmoney.com/pinzhong/LJSYLZS" headers = {"Referer": "https://fund.eastmoney.com/"} period_map = { "1月": "m", "3月": "q", "6月": "hy", "1年": "y", "3年": "try", "5年": "fiy", "今年来": "sy", "成立来": "se", } params = { "fundCode": symbol, "indexcode": "000300", "type": period_map[period], } r = requests.get(url, params=params, headers=headers) data_json = r.json() temp_df = pd.DataFrame(data_json["Data"][0]["data"]) temp_df.columns = ["日期", "累计收益率"] temp_df["日期"] = pd.to_datetime( temp_df["日期"], unit="ms", utc=True ).dt.tz_convert("Asia/Shanghai") temp_df["日期"] = pd.to_datetime(temp_df["日期"], errors="coerce").dt.date temp_df["累计收益率"] = pd.to_numeric(temp_df["累计收益率"], errors="coerce") return temp_df # 同类排名走势 if indicator == "同类排名走势": data_json = js_code.execute("Data_rateInSimilarType") temp_df = pd.DataFrame(data_json) temp_df["x"] = pd.to_datetime(temp_df["x"], unit="ms", utc=True).dt.tz_convert( "Asia/Shanghai" ) temp_df["x"] = temp_df["x"].dt.date temp_df.columns = [ "报告日期", "同类型排名-每日近三月排名", "总排名-每日近三月排名", ] temp_df = temp_df[ [ "报告日期", "同类型排名-每日近三月排名", "总排名-每日近三月排名", ] ] temp_df["报告日期"] = pd.to_datetime( temp_df["报告日期"], errors="coerce" ).dt.date temp_df["同类型排名-每日近三月排名"] = pd.to_numeric( temp_df["同类型排名-每日近三月排名"], errors="coerce" ) temp_df["总排名-每日近三月排名"] = pd.to_numeric( temp_df["总排名-每日近三月排名"], errors="coerce" ) return temp_df # 同类排名百分比 if indicator == "同类排名百分比": data_json = js_code.execute("Data_rateInSimilarPersent") temp_df = pd.DataFrame(data_json) temp_df.columns = ["x", "y"] temp_df["x"] = pd.to_datetime(temp_df["x"], unit="ms", utc=True).dt.tz_convert( "Asia/Shanghai" ) temp_df["x"] = temp_df["x"].dt.date temp_df.columns = [ "报告日期", "同类型排名-每日近3月收益排名百分比", ] temp_df = temp_df[ [ "报告日期", "同类型排名-每日近3月收益排名百分比", ] ] temp_df["报告日期"] = pd.to_datetime( temp_df["报告日期"], errors="coerce" ).dt.date temp_df["同类型排名-每日近3月收益排名百分比"] = pd.to_numeric( temp_df["同类型排名-每日近3月收益排名百分比"], errors="coerce" ) return temp_df # 分红送配详情 if indicator == "分红送配详情": url = f"https://fundf10.eastmoney.com/fhsp_{symbol}.html" r = requests.get(url, headers=headers) table_num = len(pd.read_html(StringIO(r.text))) if table_num == 3: temp_df = pd.read_html(StringIO(r.text))[1] else: temp_df = pd.read_html(StringIO(r.text))[0] if temp_df.iloc[0, 1] == "暂无分红信息!": return pd.DataFrame() else: return temp_df # 拆分详情 if indicator == "拆分详情": url = f"https://fundf10.eastmoney.com/fhsp_{symbol}.html" r = requests.get(url, headers=headers) table_num = len(pd.read_html(StringIO(r.text))) if table_num == 3: temp_df = pd.read_html(StringIO(r.text))[2] else: temp_df = pd.read_html(StringIO(r.text))[1] if temp_df.iloc[0, 1] == "暂无拆分信息!": return pd.DataFrame() else: return temp_df return pd.DataFrame() def fund_money_fund_daily_em() -> pd.DataFrame: """ 东方财富网-天天基金网-基金数据-货币型基金收益 https://fund.eastmoney.com/HBJJ_pjsyl.html :return: 当前交易日的所有货币型基金收益数据 :rtype: pandas.DataFrame """ url = "https://fund.eastmoney.com/HBJJ_pjsyl.html" r = requests.get(url, headers=headers) r.encoding = "gb2312" show_day = pd.read_html(StringIO(r.text))[1].iloc[0, 5:11].tolist() temp_df = pd.read_html(StringIO(r.text))[1].iloc[1:, 2:] temp_df_columns = temp_df.iloc[0, :].tolist()[1:] temp_df = temp_df.iloc[1:, 1:] temp_df.columns = temp_df_columns temp_df["基金简称"] = temp_df["基金简称"].str.strip("基金吧档案") temp_df.columns = [ "基金代码", "基金简称", f"{show_day[0]}-万份收益", f"{show_day[1]}-7日年化%", f"{show_day[2]}-单位净值", f"{show_day[3]}-万份收益", f"{show_day[4]}-7日年化%", f"{show_day[5]}-单位净值", "日涨幅", "成立日期", "基金经理", "手续费", "可购全部", ] return temp_df def fund_money_fund_info_em(symbol: str = "000009") -> pd.DataFrame: """ 东方财富网-天天基金网-基金数据-货币型基金收益-历史净值数据 https://fundf10.eastmoney.com/jjjz_004186.html :param symbol: 货币型基金代码, 可以通过 fund_money_fund_daily_em 来获取 :type symbol: str :return: 东方财富网站-天天基金网-基金数据-货币型基金收益-历史净值数据 :rtype: pandas.DataFrame """ url = "https://api.fund.eastmoney.com/f10/lsjz" headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/80.0.3987.149 Safari/537.36", "Referer": f"https://fundf10.eastmoney.com/jjjz_{symbol}.html", "Host": "api.fund.eastmoney.com", } params = { "fundCode": symbol, "pageIndex": "1", "pageSize": "20", "startDate": "", "endDate": "", "_": round(time.time() * 1000), } r = requests.get(url, params=params, headers=headers) data_json = r.json() total_page = math.ceil(int(data_json["TotalCount"]) / 20) tqdm = get_tqdm() big_list = [] for page in tqdm(range(1, total_page + 1), leave=False): params.update({"pageIndex": page}) r = requests.get(url, params=params, headers=headers) data_json = r.json() temp_df = pd.DataFrame(data_json["Data"]["LSJZList"]) big_list.append(temp_df) big_df = pd.concat(big_list, ignore_index=True) big_df.columns = [ "净值日期", "每万份收益", "7日年化收益率", "_", "_", "_", "_", "申购状态", "赎回状态", "_", "_", "_", "_", ] big_df.sort_values(by=["净值日期"], inplace=True, ignore_index=True) big_df = big_df[["净值日期", "每万份收益", "7日年化收益率", "申购状态", "赎回状态"]] big_df["净值日期"] = pd.to_datetime(big_df["净值日期"], errors="coerce").dt.date big_df["每万份收益"] = pd.to_numeric(big_df["每万份收益"], errors="coerce") big_df["7日年化收益率"] = pd.to_numeric(big_df["7日年化收益率"], errors="coerce") return big_df def fund_financial_fund_daily_em() -> pd.DataFrame: """ 东方财富网站-天天基金网-基金数据-理财型基金收益 # 该接口暂无数据 https://fund.eastmoney.com/lcjj.html#1_1__0__ljjz,desc_1_os1 :return: 当前交易日的所有理财型基金收益 :rtype: pandas.DataFrame """ url = "https://api.fund.eastmoney.com/FundNetValue/GetLCJJJZ" headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/80.0.3987.149 Safari/537.36", "Referer": "https://fund.eastmoney.com/lcjj.html", } params = { "letter": "", "jjgsid": "0", "searchtext": "", "sort": "ljjz,desc", "page": "1,100", "AttentionCodes": "", "cycle": "", "OnlySale": "1", } r = requests.get(url, params=params, headers=headers) data_json = r.json() temp_df = pd.DataFrame(data_json["Data"]["List"]) if temp_df.empty: return pd.DataFrame() show_day = data_json["Data"]["showday"] data_df = temp_df[ [ "Id", "actualsyi", "cycle", "fcode", "kfr", "mui", "shortname", "syi", "zrmui", "zrsyi", ] ] data_df.columns = [ "序号", "上一期年化收益率", "封闭期", "基金代码", "申购状态", f"{show_day[0]}-万份收益", "基金简称", f"{show_day[0]}-7日年华", f"{show_day[1]}-万份收益", f"{show_day[1]}-7日年华", ] data_df = data_df[ [ "序号", "基金代码", "基金简称", "上一期年化收益率", f"{show_day[0]}-万份收益", f"{show_day[0]}-7日年华", f"{show_day[1]}-万份收益", f"{show_day[1]}-7日年华", "封闭期", "申购状态", ] ] return data_df def fund_financial_fund_info_em(symbol: str = "000134") -> pd.DataFrame: """ 东方财富网站-天天基金网-基金数据-理财型基金收益-历史净值明细 https://fundf10.eastmoney.com/jjjz_000791.html :param symbol: 理财型基金代码, 可以通过 ak.fund_financial_fund_daily_em() 来获取 :type symbol: str :return: 东方财富网站-天天基金网-基金数据-理财型基金收益-历史净值明细 :rtype: pandas.DataFrame """ url = "https://api.fund.eastmoney.com/f10/lsjz" headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/80.0.3987.149 Safari/537.36", "Referer": f"https://fundf10.eastmoney.com/jjjz_{symbol}.html", } params = { "callback": "jQuery18307915911837995662_1588249228826", "fundCode": symbol, "pageIndex": "1", "pageSize": "10000", "startDate": "", "endDate": "", "_": round(time.time() * 1000), } r = requests.get(url, params=params, headers=headers) text_data = r.text data_json = demjson.decode(text_data[text_data.find("{") : -1]) temp_df = pd.DataFrame(data_json["Data"]["LSJZList"]) temp_df.columns = [ "净值日期", "单位净值", "累计净值", "_", "_", "_", "日增长率", "申购状态", "赎回状态", "_", "_", "_", "分红送配", ] temp_df = temp_df[ [ "净值日期", "单位净值", "累计净值", "日增长率", "申购状态", "赎回状态", "分红送配", ] ] temp_df.sort_values(["净值日期"], inplace=True, ignore_index=True) temp_df["净值日期"] = pd.to_datetime(temp_df["净值日期"]).dt.date temp_df["单位净值"] = pd.to_numeric(temp_df["单位净值"], errors="coerce") temp_df["累计净值"] = pd.to_numeric(temp_df["累计净值"], errors="coerce") temp_df["日增长率"] = pd.to_numeric(temp_df["日增长率"], errors="coerce") return temp_df def fund_graded_fund_daily_em() -> pd.DataFrame: """ 东方财富网站-天天基金网-基金数据-分级基金净值 https://fund.eastmoney.com/fjjj.html#1_1__0__zdf,desc_1 :return: 当前交易日的所有分级基金净值 :rtype: pandas.DataFrame """ url = "https://fund.eastmoney.com/Data/Fund_JJJZ_Data.aspx" headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/80.0.3987.149 Safari/537.36", "Referer": "https://fund.eastmoney.com/fjjj.html", } params = { "t": "1", "lx": "9", "letter": "", "gsid": "0", "text": "", "sort": "zdf,desc", "page": "1,10000", "dt": "1580914040623", "atfc": "", } res = requests.get(url, params=params, headers=headers) text_data = res.text data_json = demjson.decode(text_data.strip("var db=")) temp_df = pd.DataFrame(data_json["datas"]) show_day = data_json["showday"] temp_df.columns = [ "基金代码", "基金简称", "-", f"{show_day[0]}-单位净值", f"{show_day[0]}-累计净值", f"{show_day[1]}--单位净值", f"{show_day[1]}--累计净值", "日增长值", "日增长率", "市价", "折价率", "-", "-", "-", "-", "-", "-", "-", "-", "手续费", ] data_df = temp_df[ [ "基金代码", "基金简称", f"{show_day[0]}-单位净值", f"{show_day[0]}-累计净值", f"{show_day[1]}--单位净值", f"{show_day[1]}--累计净值", "日增长值", "日增长率", "市价", "折价率", "手续费", ] ] return data_df def fund_graded_fund_info_em(symbol: str = "150232") -> pd.DataFrame: """ 东方财富网站-天天基金网-基金数据-分级基金净值-历史净值明细 https://fundf10.eastmoney.com/jjjz_150232.html :param symbol: 分级基金代码, 可以通过 ak.fund_money_fund_daily_em() 来获取 :type symbol: str :return: 东方财富网站-天天基金网-基金数据-分级基金净值-历史净值明细 :rtype: pandas.DataFrame """ url = "https://api.fund.eastmoney.com/f10/lsjz" headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/80.0.3987.149 Safari/537.36", "Referer": f"https://fundf10.eastmoney.com/jjjz_{symbol}.html", } params = { "fundCode": symbol, "pageIndex": "1", "pageSize": "20", "startDate": "", "endDate": "", "_": round(time.time() * 1000), } r = requests.get(url, params=params, headers=headers) data_json = r.json() total_page = math.ceil(int(data_json["TotalCount"]) / 20) tqdm = get_tqdm() big_list = [] for page in tqdm(range(1, total_page + 1), leave=False): params.update({"pageIndex": page}) r = requests.get(url, params=params, headers=headers) data_json = r.json() temp_df = pd.DataFrame(data_json["Data"]["LSJZList"]) big_list.append(temp_df) big_df = pd.concat(big_list, ignore_index=True) big_df.columns = [ "净值日期", "单位净值", "累计净值", "_", "_", "_", "日增长率", "申购状态", "赎回状态", "_", "_", "_", "_", ] big_df.sort_values(by=["净值日期"], inplace=True, ignore_index=True) big_df = big_df[ ["净值日期", "单位净值", "累计净值", "日增长率", "申购状态", "赎回状态"] ] big_df["净值日期"] = pd.to_datetime(big_df["净值日期"], errors="coerce").dt.date big_df["单位净值"] = pd.to_numeric(big_df["单位净值"], errors="coerce") big_df["累计净值"] = pd.to_numeric(big_df["累计净值"], errors="coerce") big_df["日增长率"] = pd.to_numeric(big_df["日增长率"], errors="coerce") return big_df def fund_etf_fund_daily_em() -> pd.DataFrame: """ 东方财富网-天天基金网-基金数据-场内交易基金 https://fund.eastmoney.com/cnjy_dwjz.html :return: 当前交易日的所有场内交易基金数据 :rtype: pandas.DataFrame """ url = "https://fund.eastmoney.com/cnjy_dwjz.html" r = requests.get(url, headers=headers) r.encoding = "gb2312" show_day = pd.read_html(StringIO(r.text))[1].iloc[0, 6:10].tolist() temp_df = pd.read_html(StringIO(r.text))[1].iloc[1:, 2:] temp_df_columns = temp_df.iloc[0, :].tolist()[1:] temp_df = temp_df.iloc[1:, 1:] temp_df.columns = temp_df_columns temp_df["基金简称"] = temp_df["基金简称"].str.replace("行情吧档案", "") temp_df.reset_index(inplace=True, drop=True) temp_df.columns = [ "基金代码", "基金简称", "类型", f"{show_day[0]}-单位净值", f"{show_day[0]}-累计净值", f"{show_day[2]}-单位净值", f"{show_day[2]}-累计净值", "增长值", "增长率", "市价", "折价率", ] return temp_df def fund_etf_fund_info_em( fund: str = "511280", start_date: str = "20000101", end_date: str = "20500101", ) -> pd.DataFrame: """ 东方财富网站-天天基金网-基金数据-场内交易基金-历史净值明细 https://fundf10.eastmoney.com/jjjz_511280.html :param fund: 场内交易基金代码, 可以通过 fund_etf_fund_daily_em 来获取 :type fund: str :param start_date: 开始统计时间 :type start_date: str :param end_date: 结束统计时间 :type end_date: str :return: 东方财富网站-天天基金网-基金数据-场内交易基金-历史净值明细 :rtype: pandas.DataFrame """ url = "https://api.fund.eastmoney.com/f10/lsjz" headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/80.0.3987.149 Safari/537.36", "Referer": f"https://fundf10.eastmoney.com/jjjz_{fund}.html", } params = { "fundCode": fund, "pageIndex": "1", "pageSize": "20", "startDate": "-".join([start_date[:4], start_date[4:6], start_date[6:]]), "endDate": "-".join([end_date[:4], end_date[4:6], end_date[6:]]), "_": round(time.time() * 1000), } r = requests.get(url, params=params, headers=headers) data_json = r.json() total_page = math.ceil(data_json["TotalCount"] / 20) df_list = [] tqdm = get_tqdm() for page in tqdm(range(1, total_page + 1), leave=False): params.update({"pageIndex": page}) r = requests.get(url, params=params, headers=headers) data_json = r.json() temp_df = pd.DataFrame(data_json["Data"]["LSJZList"]) df_list.append(temp_df) big_df = pd.concat(df_list) big_df.columns = [ "净值日期", "单位净值", "累计净值", "_", "_", "_", "日增长率", "申购状态", "赎回状态", "_", "_", "_", "_", ] big_df = big_df[ ["净值日期", "单位净值", "累计净值", "日增长率", "申购状态", "赎回状态"] ] big_df["净值日期"] = pd.to_datetime(big_df["净值日期"], errors="coerce").dt.date big_df["单位净值"] = pd.to_numeric(big_df["单位净值"], errors="coerce") big_df["累计净值"] = pd.to_numeric(big_df["累计净值"], errors="coerce") big_df["日增长率"] = pd.to_numeric(big_df["日增长率"], errors="coerce") big_df.sort_values(["净值日期"], inplace=True, ignore_index=True) return big_df def fund_value_estimation_em(symbol: str = "全部") -> pd.DataFrame: """ 东方财富网-数据中心-净值估算 https://fund.eastmoney.com/fundguzhi.html :param symbol: choice of {'全部', '股票型', '混合型', '债券型', '指数型', 'QDII', 'ETF联接', 'LOF', '场内交易基金'} :type symbol: str :return: 近期净值估算数据 :rtype: pandas.DataFrame """ symbol_map = { "全部": 1, "股票型": 2, "混合型": 3, "债券型": 4, "指数型": 5, "QDII": 6, "ETF联接": 7, "LOF": 8, "场内交易基金": 9, } url = "https://api.fund.eastmoney.com/FundGuZhi/GetFundGZList" headers = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/81.0.4044.138 Safari/537.36", "Referer": "https://fund.eastmoney.com/", } params = { "type": symbol_map[symbol], "sort": "3", "orderType": "desc", "canbuy": "0", "pageIndex": "1", "pageSize": "20000", "_": int(time.time() * 1000), } r = requests.get(url, params=params, headers=headers) json_data = r.json() temp_df = pd.DataFrame(json_data["Data"]["list"]) value_day = json_data["Data"]["gzrq"] cal_day = json_data["Data"]["gxrq"] temp_df.columns = [ "基金代码", "-", "-", "-", "-", "-", "基金类型", "-", "-", "-", "-", "估算日期", "-", "-", "-", "-", "_", "-", "-", "估算偏差", f"{cal_day}-估算数据-估算值", f"{cal_day}-估算数据-估算增长率", f"{cal_day}-公布数据-日增长率", f"{value_day}-单位净值", f"{cal_day}-公布数据-单位净值", "-", "基金名称", "-", "-", "-", ] temp_df = temp_df[ [ "基金代码", "基金名称", f"{cal_day}-估算数据-估算值", f"{cal_day}-估算数据-估算增长率", f"{cal_day}-公布数据-单位净值", f"{cal_day}-公布数据-日增长率", "估算偏差", f"{value_day}-单位净值", ] ] temp_df.reset_index(inplace=True) temp_df["index"] = range(1, len(temp_df) + 1) temp_df.rename(columns={"index": "序号"}, inplace=True) return temp_df def fund_hk_fund_hist_em( code: str = "1002200683", symbol: str = "历史净值明细" ) -> pd.DataFrame: """ 东方财富网-天天基金网-基金数据-香港基金-历史净值明细(分红送配详情) https://overseas.1234567.com.cn/f10/FundJz/968092#FHPS :param code: 通过 ak.fund_em_hk_rank() 获取 :type code: str :param symbol: choice of {"历史净值明细", "分红送配详情"} :type symbol: str :return: 香港基金-历史净值明细(分红送配详情) :rtype: pandas.DataFrame """ url = "https://overseas.1234567.com.cn/overseasapi/OpenApiHander.ashx" if symbol == "历史净值明细": params = { "api": "HKFDApi", "m": "MethodJZ", "hkfcode": f"{code}", "action": "2", "pageindex": "0", "pagesize": "1000", "date1": "", "date2": "", } r = requests.get(url, params=params, headers=headers) data_json = r.json() temp_one_df = pd.DataFrame(data_json["Data"]) temp_one_df.columns = [ "_", "_", "_", "净值日期", "单位净值", "_", "日增长值", "日增长率", "_", "单位", "_", ] temp_one_df = temp_one_df[ [ "净值日期", "单位净值", "日增长值", "日增长率", "单位", ] ] else: params = { "api": "HKFDApi", "m": "MethodJZ", "hkfcode": f"{code}", "action": "3", "pageindex": "0", "pagesize": "1000", "date1": "", "date2": "", } r = requests.get(url, params=params, headers=headers) data_json = r.json() temp_one_df = pd.DataFrame(data_json["Data"]) temp_one_df.columns = [ "_", "_", "_", "_", "_", "年份", "分红金额", "除息日", "权益登记日", "分红发放日", "_", "单位", "_", "_", ] temp_one_df = temp_one_df[ [ "年份", "权益登记日", "除息日", "分红发放日", "分红金额", "单位", ] ] return temp_one_df if __name__ == "__main__": fund_purchase_em_df = fund_purchase_em() print(fund_purchase_em_df) fund_name_em_df = fund_name_em() print(fund_name_em_df) fund_info_index_em_df = fund_info_index_em(symbol="债券指数", indicator="全部") print(fund_info_index_em_df) fund_open_fund_daily_em_df = fund_open_fund_daily_em() print(fund_open_fund_daily_em_df) time.sleep(3) fund_open_fund_info_em_df = fund_open_fund_info_em( symbol="710001", indicator="单位净值走势" ) print(fund_open_fund_info_em_df) time.sleep(3) fund_open_fund_info_em_df = fund_open_fund_info_em( symbol="502010", indicator="累计净值走势", period="成立来" ) print(fund_open_fund_info_em_df) time.sleep(3) fund_open_fund_info_em_df = fund_open_fund_info_em( symbol="710001", indicator="累计收益率走势", period="成立来" ) print(fund_open_fund_info_em_df) time.sleep(3) fund_open_fund_info_em_df = fund_open_fund_info_em( symbol="710001", indicator="同类排名走势" ) print(fund_open_fund_info_em_df) time.sleep(3) fund_open_fund_info_em_df = fund_open_fund_info_em( symbol="710001", indicator="同类排名百分比" ) print(fund_open_fund_info_em_df) time.sleep(3) fund_open_fund_info_em_df = fund_open_fund_info_em( symbol="014164", indicator="分红送配详情" ) print(fund_open_fund_info_em_df) time.sleep(3) fund_open_fund_info_em_df = fund_open_fund_info_em( symbol="005561", indicator="拆分详情" ) print(fund_open_fund_info_em_df) fund_money_fund_daily_em_df = fund_money_fund_daily_em() print(fund_money_fund_daily_em_df) fund_money_fund_info_em_df = fund_money_fund_info_em(symbol="000009") print(fund_money_fund_info_em_df) fund_financial_fund_daily_em_df = fund_financial_fund_daily_em() print(fund_financial_fund_daily_em_df) fund_financial_fund_info_em_df = fund_financial_fund_info_em(symbol="000134") print(fund_financial_fund_info_em_df) fund_graded_fund_daily_em_df = fund_graded_fund_daily_em() print(fund_graded_fund_daily_em_df) fund_graded_fund_info_em_df = fund_graded_fund_info_em(symbol="150232") print(fund_graded_fund_info_em_df) fund_etf_fund_daily_em_df = fund_etf_fund_daily_em() print(fund_etf_fund_daily_em_df) fund_etf_fund_info_em_df = fund_etf_fund_info_em( fund="511280", start_date="20000101", end_date="20500101" ) print(fund_etf_fund_info_em_df) fund_value_estimation_em_df = fund_value_estimation_em(symbol="混合型") print(fund_value_estimation_em_df) fund_hk_fund_hist_em_df = fund_hk_fund_hist_em( code="1002200683", symbol="历史净值明细" ) print(fund_hk_fund_hist_em_df) fund_hk_fund_hist_em_df = fund_hk_fund_hist_em( code="1002200683", symbol="分红送配详情" ) print(fund_hk_fund_hist_em_df)