#!/usr/bin/env python """ Date: 2024/6/21 18:00 Desc: 新浪财经-股票期权 https://stock.finance.sina.com.cn/option/quotes.html 期权-中金所-沪深 300 指数 https://stock.finance.sina.com.cn/futures/view/optionsCffexDP.php 期权-上交所-50ETF 期权-上交所-300ETF 期权-上交所-500ETF https://stock.finance.sina.com.cn/option/quotes.html """ import datetime import json from functools import lru_cache from typing import Dict, List, Tuple import pandas as pd import requests from bs4 import BeautifulSoup from akshare.option.option_em import option_current_em from akshare.utils.func import set_df_columns # 期权-中金所-上证50指数 def option_cffex_sz50_list_sina() -> Dict[str, List[str]]: """ 新浪财经-中金所-上证 50 指数-所有合约, 返回的第一个合约为主力合约 目前新浪财经-中金所有上证 50 指数，沪深 300 指数和中证 1000 指数 :return: 中金所-上证 50 指数-所有合约 :rtype: dict """ url = "https://stock.finance.sina.com.cn/futures/view/optionsCffexDP.php/ho/cffex" r = requests.get(url) soup = BeautifulSoup(r.text, features="lxml") symbol = soup.find(attrs={"id": "option_symbol"}).find_all("li")[0].text temp_attr = soup.find(attrs={"id": "option_suffix"}).find_all("li") contract = [item.text for item in temp_attr] return {symbol: contract} # 期权-中金所-沪深300指数 def option_cffex_hs300_list_sina() -> Dict[str, List[str]]: """ 新浪财经-中金所-沪深 300 指数-所有合约, 返回的第一个合约为主力合约 目前新浪财经-中金所有沪深 300 指数和中证 1000 指数 :return: 中金所-沪深300指数-所有合约 :rtype: dict """ url = "https://stock.finance.sina.com.cn/futures/view/optionsCffexDP.php" r = requests.get(url) soup = BeautifulSoup(r.text, features="lxml") symbol = soup.find(attrs={"id": "option_symbol"}).find_all("li")[1].text temp_attr = soup.find(attrs={"id": "option_suffix"}).find_all("li") contract = [item.text for item in temp_attr] return {symbol: contract} def option_cffex_zz1000_list_sina() -> Dict[str, List[str]]: """ 新浪财经-中金所-中证 1000 指数-所有合约, 返回的第一个合约为主力合约 目前新浪财经-中金所有沪深 300 指数和中证 1000 指数 :return: 中金所-中证 1000 指数-所有合约 :rtype: dict """ url = "https://stock.finance.sina.com.cn/futures/view/optionsCffexDP.php/mo/cffex" r = requests.get(url) soup = BeautifulSoup(r.text, features="lxml") symbol = soup.find(attrs={"id": "option_symbol"}).find_all("li")[2].text temp_attr = soup.find(attrs={"id": "option_suffix"}).find_all("li") contract = [item.text for item in temp_attr] return {symbol: contract} def option_cffex_sz50_spot_sina(symbol: str = "ho2303") -> pd.DataFrame: """ 中金所-上证 50 指数-指定合约-实时行情 https://stock.finance.sina.com.cn/futures/view/optionsCffexDP.php/ho/cffex :param symbol: 合约代码; 用 ak.option_cffex_sz300_list_sina() 函数查看 :type symbol: str :return: 中金所-上证 50 指数-指定合约-看涨看跌实时行情 :rtype: pandas.DataFrame """ url = "https://stock.finance.sina.com.cn/futures/api/openapi.php/OptionService.getOptionData" params = { "type": "futures", "product": "ho", "exchange": "cffex", "pinzhong": symbol, } r = requests.get(url, params=params) data_text = r.text data_json = json.loads(data_text[data_text.find("{") : data_text.rfind("}") + 1]) option_call_df = pd.DataFrame( data_json["result"]["data"]["up"], columns=[ "看涨合约-买量", "看涨合约-买价", "看涨合约-最新价", "看涨合约-卖价", "看涨合约-卖量", "看涨合约-持仓量", "看涨合约-涨跌", "行权价", "看涨合约-标识", ], ) option_put_df = pd.DataFrame( data_json["result"]["data"]["down"], columns=[ "看跌合约-买量", "看跌合约-买价", "看跌合约-最新价", "看跌合约-卖价", "看跌合约-卖量", "看跌合约-持仓量", "看跌合约-涨跌", "看跌合约-标识", ], ) data_df = pd.concat(objs=[option_call_df, option_put_df], axis=1) data_df["看涨合约-买量"] = pd.to_numeric(data_df["看涨合约-买量"], errors="coerce") data_df["看涨合约-买价"] = pd.to_numeric(data_df["看涨合约-买价"], errors="coerce") data_df["看涨合约-最新价"] = pd.to_numeric( data_df["看涨合约-最新价"], errors="coerce" ) data_df["看涨合约-卖价"] = pd.to_numeric(data_df["看涨合约-卖价"], errors="coerce") data_df["看涨合约-卖量"] = pd.to_numeric(data_df["看涨合约-卖量"], errors="coerce") data_df["看涨合约-持仓量"] = pd.to_numeric( data_df["看涨合约-持仓量"], errors="coerce" ) data_df["看涨合约-涨跌"] = pd.to_numeric(data_df["看涨合约-涨跌"], errors="coerce") data_df["行权价"] = pd.to_numeric(data_df["行权价"], errors="coerce") data_df["看跌合约-买量"] = pd.to_numeric(data_df["看跌合约-买量"], errors="coerce") data_df["看跌合约-买价"] = pd.to_numeric(data_df["看跌合约-买价"], errors="coerce") data_df["看跌合约-最新价"] = pd.to_numeric( data_df["看跌合约-最新价"], errors="coerce" ) data_df["看跌合约-卖价"] = pd.to_numeric(data_df["看跌合约-卖价"], errors="coerce") data_df["看跌合约-卖量"] = pd.to_numeric(data_df["看跌合约-卖量"], errors="coerce") data_df["看跌合约-持仓量"] = pd.to_numeric( data_df["看跌合约-持仓量"], errors="coerce" ) data_df["看跌合约-涨跌"] = pd.to_numeric(data_df["看跌合约-涨跌"], errors="coerce") return data_df def option_cffex_hs300_spot_sina(symbol: str = "io2204") -> pd.DataFrame: """ 中金所-沪深 300 指数-指定合约-实时行情 https://stock.finance.sina.com.cn/futures/view/optionsCffexDP.php :param symbol: 合约代码; 用 option_cffex_hs300_list_sina 函数查看 :type symbol: str :return: 中金所-沪深300指数-指定合约-看涨看跌实时行情 :rtype: pandas.DataFrame """ url = "https://stock.finance.sina.com.cn/futures/api/openapi.php/OptionService.getOptionData" params = { "type": "futures", "product": "io", "exchange": "cffex", "pinzhong": symbol, } r = requests.get(url, params=params) data_text = r.text data_json = json.loads(data_text[data_text.find("{") : data_text.rfind("}") + 1]) option_call_df = pd.DataFrame( data_json["result"]["data"]["up"], columns=[ "看涨合约-买量", "看涨合约-买价", "看涨合约-最新价", "看涨合约-卖价", "看涨合约-卖量", "看涨合约-持仓量", "看涨合约-涨跌", "行权价", "看涨合约-标识", ], ) option_put_df = pd.DataFrame( data_json["result"]["data"]["down"], columns=[ "看跌合约-买量", "看跌合约-买价", "看跌合约-最新价", "看跌合约-卖价", "看跌合约-卖量", "看跌合约-持仓量", "看跌合约-涨跌", "看跌合约-标识", ], ) data_df = pd.concat(objs=[option_call_df, option_put_df], axis=1) data_df["看涨合约-买量"] = pd.to_numeric(data_df["看涨合约-买量"], errors="coerce") data_df["看涨合约-买价"] = pd.to_numeric(data_df["看涨合约-买价"], errors="coerce") data_df["看涨合约-最新价"] = pd.to_numeric( data_df["看涨合约-最新价"], errors="coerce" ) data_df["看涨合约-卖价"] = pd.to_numeric(data_df["看涨合约-卖价"], errors="coerce") data_df["看涨合约-卖量"] = pd.to_numeric(data_df["看涨合约-卖量"], errors="coerce") data_df["看涨合约-持仓量"] = pd.to_numeric( data_df["看涨合约-持仓量"], errors="coerce" ) data_df["看涨合约-涨跌"] = pd.to_numeric(data_df["看涨合约-涨跌"], errors="coerce") data_df["行权价"] = pd.to_numeric(data_df["行权价"], errors="coerce") data_df["看跌合约-买量"] = pd.to_numeric(data_df["看跌合约-买量"], errors="coerce") data_df["看跌合约-买价"] = pd.to_numeric(data_df["看跌合约-买价"], errors="coerce") data_df["看跌合约-最新价"] = pd.to_numeric( data_df["看跌合约-最新价"], errors="coerce" ) data_df["看跌合约-卖价"] = pd.to_numeric(data_df["看跌合约-卖价"], errors="coerce") data_df["看跌合约-卖量"] = pd.to_numeric(data_df["看跌合约-卖量"], errors="coerce") data_df["看跌合约-持仓量"] = pd.to_numeric( data_df["看跌合约-持仓量"], errors="coerce" ) data_df["看跌合约-涨跌"] = pd.to_numeric(data_df["看跌合约-涨跌"], errors="coerce") return data_df def option_cffex_zz1000_spot_sina(symbol: str = "mo2208") -> pd.DataFrame: """ 中金所-中证 1000 指数-指定合约-实时行情 https://stock.finance.sina.com.cn/futures/view/optionsCffexDP.php :param symbol: 合约代码; 用 option_cffex_zz1000_list_sina 函数查看 :type symbol: str :return: 中金所-中证 1000 指数-指定合约-看涨看跌实时行情 :rtype: pandas.DataFrame """ url = "https://stock.finance.sina.com.cn/futures/api/openapi.php/OptionService.getOptionData" params = { "type": "futures", "product": "mo", "exchange": "cffex", "pinzhong": symbol, } r = requests.get(url, params=params) data_text = r.text data_json = json.loads(data_text[data_text.find("{") : data_text.rfind("}") + 1]) option_call_df = pd.DataFrame( data_json["result"]["data"]["up"], columns=[ "看涨合约-买量", "看涨合约-买价", "看涨合约-最新价", "看涨合约-卖价", "看涨合约-卖量", "看涨合约-持仓量", "看涨合约-涨跌", "行权价", "看涨合约-标识", ], ) option_put_df = pd.DataFrame( data_json["result"]["data"]["down"], columns=[ "看跌合约-买量", "看跌合约-买价", "看跌合约-最新价", "看跌合约-卖价", "看跌合约-卖量", "看跌合约-持仓量", "看跌合约-涨跌", "看跌合约-标识", ], ) data_df = pd.concat(objs=[option_call_df, option_put_df], axis=1) data_df["看涨合约-买量"] = pd.to_numeric(data_df["看涨合约-买量"], errors="coerce") data_df["看涨合约-买价"] = pd.to_numeric(data_df["看涨合约-买价"], errors="coerce") data_df["看涨合约-最新价"] = pd.to_numeric( data_df["看涨合约-最新价"], errors="coerce" ) data_df["看涨合约-卖价"] = pd.to_numeric(data_df["看涨合约-卖价"], errors="coerce") data_df["看涨合约-卖量"] = pd.to_numeric(data_df["看涨合约-卖量"], errors="coerce") data_df["看涨合约-持仓量"] = pd.to_numeric( data_df["看涨合约-持仓量"], errors="coerce" ) data_df["看涨合约-涨跌"] = pd.to_numeric(data_df["看涨合约-涨跌"], errors="coerce") data_df["行权价"] = pd.to_numeric(data_df["行权价"], errors="coerce") data_df["看跌合约-买量"] = pd.to_numeric(data_df["看跌合约-买量"], errors="coerce") data_df["看跌合约-买价"] = pd.to_numeric(data_df["看跌合约-买价"], errors="coerce") data_df["看跌合约-最新价"] = pd.to_numeric( data_df["看跌合约-最新价"], errors="coerce" ) data_df["看跌合约-卖价"] = pd.to_numeric(data_df["看跌合约-卖价"], errors="coerce") data_df["看跌合约-卖量"] = pd.to_numeric(data_df["看跌合约-卖量"], errors="coerce") data_df["看跌合约-持仓量"] = pd.to_numeric( data_df["看跌合约-持仓量"], errors="coerce" ) data_df["看跌合约-涨跌"] = pd.to_numeric(data_df["看跌合约-涨跌"], errors="coerce") return data_df def option_cffex_sz50_daily_sina(symbol: str = "ho2303P2350") -> pd.DataFrame: """ 新浪财经-中金所-上证 50 指数-指定合约-日频行情 :param symbol: 具体合约代码(包括看涨和看跌标识), 可以通过 ak.option_cffex_sz50_spot_sina 中的 call-标识 获取 :type symbol: str :return: 日频率数据 :rtype: pandas.DataFrame """ year = datetime.datetime.now().year month = datetime.datetime.now().month day = datetime.datetime.now().day url = ( f"https://stock.finance.sina.com.cn/futures/api/jsonp.php/var%20_{symbol}{year}_{month}_{day}" f"=/FutureOptionAllService.getOptionDayline" ) params = {"symbol": symbol} r = requests.get(url, params=params) data_text = r.text data_df = pd.DataFrame( eval(data_text[data_text.find("[") : data_text.rfind("]") + 1]) ) data_df.columns = ["open", "high", "low", "close", "volume", "date"] data_df = data_df[ [ "date", "open", "high", "low", "close", "volume", ] ] data_df["date"] = pd.to_datetime(data_df["date"], errors="coerce").dt.date data_df["open"] = pd.to_numeric(data_df["open"], errors="coerce") data_df["high"] = pd.to_numeric(data_df["high"], errors="coerce") data_df["low"] = pd.to_numeric(data_df["low"], errors="coerce") data_df["close"] = pd.to_numeric(data_df["close"], errors="coerce") data_df["volume"] = pd.to_numeric(data_df["volume"], errors="coerce") return data_df def option_cffex_hs300_daily_sina(symbol: str = "io2202P4350") -> pd.DataFrame: """ 新浪财经-中金所-沪深300指数-指定合约-日频行情 :param symbol: 具体合约代码(包括看涨和看跌标识), 可以通过 ak.option_cffex_hs300_spot_sina 中的 call-标识 获取 :type symbol: str :return: 日频率数据 :rtype: pandas.DataFrame """ year = datetime.datetime.now().year month = datetime.datetime.now().month day = datetime.datetime.now().day url = ( f"https://stock.finance.sina.com.cn/futures/api/jsonp.php/var%20_{symbol}{year}_{month}_{day}" f"=/FutureOptionAllService.getOptionDayline" ) params = {"symbol": symbol} r = requests.get(url, params=params) data_text = r.text data_df = pd.DataFrame( eval(data_text[data_text.find("[") : data_text.rfind("]") + 1]) ) data_df.columns = ["open", "high", "low", "close", "volume", "date"] data_df = data_df[ [ "date", "open", "high", "low", "close", "volume", ] ] data_df["date"] = pd.to_datetime(data_df["date"], errors="coerce").dt.date data_df["open"] = pd.to_numeric(data_df["open"], errors="coerce") data_df["high"] = pd.to_numeric(data_df["high"], errors="coerce") data_df["low"] = pd.to_numeric(data_df["low"], errors="coerce") data_df["close"] = pd.to_numeric(data_df["close"], errors="coerce") data_df["volume"] = pd.to_numeric(data_df["volume"], errors="coerce") return data_df def option_cffex_zz1000_daily_sina( symbol: str = "mo2208P6200", ) -> pd.DataFrame: """ 新浪财经-中金所-中证 1000 指数-指定合约-日频行情 :param symbol: 具体合约代码(包括看涨和看跌标识), 可以通过 ak.option_cffex_zz1000_spot_sina 中的 call-标识 获取 :type symbol: str :return: 日频率数据 :rtype: pandas.DataFrame """ year = datetime.datetime.now().year month = datetime.datetime.now().month day = datetime.datetime.now().day url = ( f"https://stock.finance.sina.com.cn/futures/api/jsonp.php/var%20_{symbol}{year}_{month}_{day}" f"=/FutureOptionAllService.getOptionDayline" ) params = {"symbol": symbol} r = requests.get(url, params=params) data_text = r.text data_df = pd.DataFrame( eval(data_text[data_text.find("[") : data_text.rfind("]") + 1]) ) data_df.columns = ["open", "high", "low", "close", "volume", "date"] data_df = data_df[ [ "date", "open", "high", "low", "close", "volume", ] ] data_df["date"] = pd.to_datetime(data_df["date"], errors="coerce").dt.date data_df["open"] = pd.to_numeric(data_df["open"], errors="coerce") data_df["high"] = pd.to_numeric(data_df["high"], errors="coerce") data_df["low"] = pd.to_numeric(data_df["low"], errors="coerce") data_df["close"] = pd.to_numeric(data_df["close"], errors="coerce") data_df["volume"] = pd.to_numeric(data_df["volume"], errors="coerce") return data_df # 期权-上交所-50ETF def option_sse_list_sina(symbol: str = "50ETF", exchange: str = "null") -> List[str]: """ 新浪财经-期权-上交所-50ETF-合约到期月份列表 https://stock.finance.sina.com.cn/option/quotes.html :param symbol: 50ETF or 300ETF :type symbol: str :param exchange: null :type exchange: str :return: 合约到期时间 :rtype: list """ url = "https://stock.finance.sina.com.cn/futures/api/openapi.php/StockOptionService.getStockName" params = {"exchange": f"{exchange}", "cate": f"{symbol}"} r = requests.get(url, params=params) data_json = r.json() date_list = data_json["result"]["data"]["contractMonth"] return ["".join(i.split("-")) for i in date_list][1:] def option_sse_expire_day_sina( trade_date: str = "202102", symbol: str = "50ETF", exchange: str = "null" ) -> Tuple[str, int]: """ 指定到期月份指定品种的剩余到期时间 :param trade_date: 到期月份: 202002, 20203, 20206, 20209 :type trade_date: str :param symbol: 50ETF or 300ETF :type symbol: str :param exchange: null :type exchange: str :return: (到期时间, 剩余时间) :rtype: tuple """ url = "https://stock.finance.sina.com.cn/futures/api/openapi.php/StockOptionService.getRemainderDay" params = { "exchange": f"{exchange}", "cate": f"{symbol}", "date": f"{trade_date[:4]}-{trade_date[4:]}", } r = requests.get(url, params=params) data_json = r.json() data = data_json["result"]["data"] if int(data["remainderDays"]) < 0: url = "https://stock.finance.sina.com.cn/futures/api/openapi.php/StockOptionService.getRemainderDay" params = { "exchange": f"{exchange}", "cate": f"{'XD' + symbol}", "date": f"{trade_date[:4]}-{trade_date[4:]}", } r = requests.get(url, params=params) data_json = r.json() data = data_json["result"]["data"] return data["expireDay"], int(data["remainderDays"]) def option_sse_codes_sina( symbol: str = "看涨期权", trade_date: str = "202202", underlying: str = "510050", ) -> pd.DataFrame: """ 上海证券交易所-所有看涨和看跌合约的代码 :param symbol: choice of {"看涨期权", "看跌期权"} :type symbol: str :param trade_date: 期权到期月份 :type trade_date: "202002" :param underlying: 标的产品代码 华夏上证 50ETF: 510050 or 华泰柏瑞沪深 300ETF: 510300 :type underlying: str :return: 看涨看跌合约的代码 :rtype: Tuple[List, List] """ if symbol == "看涨期权": url = "".join( [ "https://hq.sinajs.cn/list=OP_UP_", underlying, str(trade_date)[-4:], ] ) else: url = "".join( [ "https://hq.sinajs.cn/list=OP_DOWN_", underlying, str(trade_date)[-4:], ] ) headers = { "Accept": "*/*", "Accept-Encoding": "gzip, deflate, br", "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8", "Cache-Control": "no-cache", "Connection": "keep-alive", "Host": "hq.sinajs.cn", "Pragma": "no-cache", "Referer": "https://stock.finance.sina.com.cn/", "sec-ch-ua": '" Not;A Brand";v="99", "Google Chrome";v="97", "Chromium";v="97"', "sec-ch-ua-mobile": "?0", "sec-ch-ua-platform": '"Windows"', "Sec-Fetch-Dest": "script", "Sec-Fetch-Mode": "no-cors", "Sec-Fetch-Site": "cross-site", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/97.0.4692.71 Safari/537.36", } r = requests.get(url, headers=headers) data_text = r.text data_temp = data_text.replace('"', ",").split(",") temp_list = [i[7:] for i in data_temp if i.startswith("CON_OP_")] temp_df = pd.DataFrame(temp_list) temp_df.reset_index(inplace=True) temp_df["index"] = temp_df.index + 1 temp_df.columns = [ "序号", "期权代码", ] return temp_df def option_sse_spot_price_sina(symbol: str = "10003720") -> pd.DataFrame: """ 新浪财经-期权-期权实时数据 :param symbol: 期权代码 :type symbol: str :return: 期权量价数据 :rtype: pandas.DataFrame """ url = f"https://hq.sinajs.cn/list=CON_OP_{symbol}" headers = { "Accept": "*/*", "Accept-Encoding": "gzip, deflate, br", "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8", "Cache-Control": "no-cache", "Connection": "keep-alive", "Host": "hq.sinajs.cn", "Pragma": "no-cache", "Referer": "https://stock.finance.sina.com.cn/", "sec-ch-ua": '" Not;A Brand";v="99", "Google Chrome";v="97", "Chromium";v="97"', "sec-ch-ua-mobile": "?0", "sec-ch-ua-platform": '"Windows"', "Sec-Fetch-Dest": "script", "Sec-Fetch-Mode": "no-cors", "Sec-Fetch-Site": "cross-site", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/97.0.4692.71 Safari/537.36", } r = requests.get(url, headers=headers) data_text = r.text data_list = data_text[data_text.find('"') + 1 : data_text.rfind('"')].split(",") field_list = [ "买量", "买价", "最新价", "卖价", "卖量", "持仓量", "涨幅", "行权价", "昨收价", "开盘价", "涨停价", "跌停价", "申卖价五", "申卖量五", "申卖价四", "申卖量四", "申卖价三", "申卖量三", "申卖价二", "申卖量二", "申卖价一", "申卖量一", "申买价一", "申买量一 ", "申买价二", "申买量二", "申买价三", "申买量三", "申买价四", "申买量四", "申买价五", "申买量五", "行情时间", "主力合约标识", "状态码", "标的证券类型", "标的股票", "期权合约简称", "振幅", "最高价", "最低价", "成交量", "成交额", ] data_df = pd.DataFrame(list(zip(field_list, data_list)), columns=["字段", "值"]) return data_df def option_sse_underlying_spot_price_sina( symbol: str = "sh510300", ) -> pd.DataFrame: """ 期权标的物的实时数据 :param symbol: sh510050 or sh510300 :type symbol: str :return: 期权标的物的信息 :rtype: pandas.DataFrame """ url = f"https://hq.sinajs.cn/list={symbol}" headers = { "Accept": "*/*", "Accept-Encoding": "gzip, deflate", "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8", "Cache-Control": "no-cache", "Host": "hq.sinajs.cn", "Pragma": "no-cache", "Proxy-Connection": "keep-alive", "Referer": "https://vip.stock.finance.sina.com.cn/", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/97.0.4692.71 Safari/537.36", } r = requests.get(url, headers=headers) data_text = r.text data_list = data_text[data_text.find('"') + 1 : data_text.rfind('"')].split(",") field_list = [ "证券简称", "今日开盘价", "昨日收盘价", "最近成交价", "最高成交价", "最低成交价", "买入价", "卖出价", "成交数量", "成交金额", "买数量一", "买价位一", "买数量二", "买价位二", "买数量三", "买价位三", "买数量四", "买价位四", "买数量五", "买价位五", "卖数量一", "卖价位一", "卖数量二", "卖价位二", "卖数量三", "卖价位三", "卖数量四", "卖价位四", "卖数量五", "卖价位五", "行情日期", "行情时间", "停牌状态", ] data_df = pd.DataFrame(list(zip(field_list, data_list)), columns=["字段", "值"]) return data_df def option_sse_greeks_sina(symbol: str = "10003045") -> pd.DataFrame: """ 期权基本信息表 :param symbol: 合约代码 :type symbol: str :return: 期权基本信息表 :rtype: pandas.DataFrame """ url = f"https://hq.sinajs.cn/list=CON_SO_{symbol}" headers = { "Accept": "*/*", "Accept-Encoding": "gzip, deflate", "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8", "Cache-Control": "no-cache", "Host": "hq.sinajs.cn", "Pragma": "no-cache", "Proxy-Connection": "keep-alive", "Referer": "https://vip.stock.finance.sina.com.cn/", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/97.0.4692.71 Safari/537.36", } r = requests.get(url, headers=headers) data_text = r.text data_list = data_text[data_text.find('"') + 1 : data_text.rfind('"')].split(",") field_list = [ "期权合约简称", "成交量", "Delta", "Gamma", "Theta", "Vega", "隐含波动率", "最高价", "最低价", "交易代码", "行权价", "最新价", "理论价值", ] data_df = pd.DataFrame( list(zip(field_list, [data_list[0]] + data_list[4:])), columns=["字段", "值"], ) return data_df def option_sse_minute_sina(symbol: str = "10003720") -> pd.DataFrame: """ 指定期权品种在当前交易日的分钟数据, 只能获取当前交易日的数据, 不能获取历史分钟数据 https://stock.finance.sina.com.cn/option/quotes.html :param symbol: 期权代码 :type symbol: str :return: 指定期权的当前交易日的分钟数据 :rtype: pandas.DataFrame """ url = "https://stock.finance.sina.com.cn/futures/api/openapi.php/StockOptionDaylineService.getOptionMinline" params = {"symbol": f"CON_OP_{symbol}"} headers = { "accept": "*/*", "accept-encoding": "gzip, deflate, br", "accept-language": "zh-CN,zh;q=0.9,en;q=0.8", "cache-control": "no-cache", "pragma": "no-cache", "referer": "https://stock.finance.sina.com.cn/option/quotes.html", "sec-ch-ua": '" Not;A Brand";v="99", "Google Chrome";v="97", "Chromium";v="97"', "sec-ch-ua-mobile": "?0", "sec-ch-ua-platform": '"Windows"', "sec-fetch-dest": "script", "sec-fetch-mode": "no-cors", "sec-fetch-site": "same-origin", "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/97.0.4692.71 Safari/537.36", } r = requests.get(url, params=params, headers=headers) data_json = r.json() temp_df = data_json["result"]["data"] data_df = pd.DataFrame(temp_df) data_df = set_df_columns( df=data_df, cols=["时间", "价格", "成交", "持仓", "均价", "日期"] ) data_df = data_df[["日期", "时间", "价格", "成交", "持仓", "均价"]] data_df["日期"] = pd.to_datetime(data_df["日期"], errors="coerce").dt.date data_df["日期"] = data_df["日期"].ffill() data_df["价格"] = pd.to_numeric(data_df["价格"], errors="coerce") data_df["成交"] = pd.to_numeric(data_df["成交"], errors="coerce") data_df["持仓"] = pd.to_numeric(data_df["持仓"], errors="coerce") data_df["均价"] = pd.to_numeric(data_df["均价"], errors="coerce") return data_df def option_sse_daily_sina(symbol: str = "10003889") -> pd.DataFrame: """ 指定期权的日频率数据 :param symbol: 期权代码 :type symbol: str :return: 指定期权的所有日频率历史数据 :rtype: pandas.DataFrame """ url = "https://stock.finance.sina.com.cn/futures/api/jsonp_v2.php//StockOptionDaylineService.getSymbolInfo" params = {"symbol": f"CON_OP_{symbol}"} headers = { "accept": "*/*", "accept-encoding": "gzip, deflate, br", "accept-language": "zh-CN,zh;q=0.9,en;q=0.8", "cache-control": "no-cache", "pragma": "no-cache", "referer": "https://stock.finance.sina.com.cn/option/quotes.html", "sec-ch-ua": '" Not;A Brand";v="99", "Google Chrome";v="97", "Chromium";v="97"', "sec-ch-ua-mobile": "?0", "sec-ch-ua-platform": '"Windows"', "sec-fetch-dest": "script", "sec-fetch-mode": "no-cors", "sec-fetch-site": "same-origin", "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/97.0.4692.71 Safari/537.36", } r = requests.get(url, params=params, headers=headers) data_text = r.text data_json = json.loads(data_text[data_text.find("(") + 1 : data_text.rfind(")")]) temp_df = pd.DataFrame(data_json) temp_df.columns = ["日期", "开盘", "最高", "最低", "收盘", "成交量"] temp_df["日期"] = pd.to_datetime(temp_df["日期"], errors="coerce").dt.date temp_df["开盘"] = pd.to_numeric(temp_df["开盘"], errors="coerce") temp_df["最高"] = pd.to_numeric(temp_df["最高"], errors="coerce") temp_df["最低"] = pd.to_numeric(temp_df["最低"], errors="coerce") temp_df["收盘"] = pd.to_numeric(temp_df["收盘"], errors="coerce") temp_df["成交量"] = pd.to_numeric(temp_df["成交量"], errors="coerce") return temp_df def option_finance_minute_sina(symbol: str = "10002530") -> pd.DataFrame: """ 指定期权的分钟频率数据 https://stock.finance.sina.com.cn/option/quotes.html :param symbol: 期权代码 :type symbol: str :return: 指定期权的分钟频率数据 :rtype: pandas.DataFrame """ url = "https://stock.finance.sina.com.cn/futures/api/openapi.php/StockOptionDaylineService.getFiveDayLine" params = { "symbol": f"CON_OP_{symbol}", } headers = { "accept": "*/*", "accept-encoding": "gzip, deflate, br", "accept-language": "zh-CN,zh;q=0.9,en;q=0.8", "cache-control": "no-cache", "pragma": "no-cache", "referer": "https://stock.finance.sina.com.cn/option/quotes.html", "sec-ch-ua": '" Not;A Brand";v="99", "Google Chrome";v="97", "Chromium";v="97"', "sec-ch-ua-mobile": "?0", "sec-ch-ua-platform": '"Windows"', "sec-fetch-dest": "script", "sec-fetch-mode": "no-cors", "sec-fetch-site": "same-origin", "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/97.0.4692.71 Safari/537.36", } r = requests.get(url, params=params, headers=headers) data_text = r.json() temp_df = pd.DataFrame() for item in data_text["result"]["data"]: temp_df = pd.concat(objs=[temp_df, pd.DataFrame(item)], ignore_index=True) temp_df.ffill(inplace=True) temp_df.columns = ["time", "price", "volume", "_", "average_price", "date"] temp_df = temp_df[["date", "time", "price", "average_price", "volume"]] temp_df["price"] = pd.to_numeric(temp_df["price"], errors="coerce") temp_df["average_price"] = pd.to_numeric(temp_df["average_price"], errors="coerce") temp_df["volume"] = pd.to_numeric(temp_df["volume"], errors="coerce") return temp_df @lru_cache() def __option_current_em() -> pd.DataFrame: inner_option_current_em_df = option_current_em() return inner_option_current_em_df def option_minute_em(symbol: str = "MO2404-P-4450") -> pd.DataFrame: """ 东方财富网-行情中心-期权市场-分时行情 https://wap.eastmoney.com/quote/stock/151.cu2404P61000.html :param symbol: 期权代码; 通过调用 ak.option_current_em() 获取 :type symbol: str :return: 指定期权的分钟频率数据 :rtype: pandas.DataFrame """ inner_option_current_em_df = __option_current_em() inner_option_current_em_df["标识"] = ( inner_option_current_em_df["市场标识"].astype(str) + "." + inner_option_current_em_df["代码"] ) id_ = inner_option_current_em_df[inner_option_current_em_df["代码"] == symbol][ "标识" ].values[0] url = "https://push2.eastmoney.com/api/qt/stock/trends2/get" params = { "secid": id_, "fields1": "f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f11,f12,f13,f14,f17", "fields2": "f51,f53,f54,f55,f56,f57,f58", "iscr": "0", "iscca": "0", "ut": "f057cbcbce2a86e2866ab8877db1d059", "ndays": "1", "cb": "quotepushdata1", } r = requests.get(url, params=params) data_text = r.text data_json = json.loads(data_text[data_text.find("(") + 1 : data_text.rfind(")")]) temp_df = pd.DataFrame([item.split(",") for item in data_json["data"]["trends"]]) temp_df.columns = ["time", "close", "high", "low", "volume", "amount", "-"] temp_df = temp_df[["time", "close", "high", "low", "volume", "amount"]] temp_df["close"] = pd.to_numeric(temp_df["close"], errors="coerce") temp_df["high"] = pd.to_numeric(temp_df["high"], errors="coerce") temp_df["low"] = pd.to_numeric(temp_df["low"], errors="coerce") temp_df["volume"] = pd.to_numeric(temp_df["volume"], errors="coerce") temp_df["amount"] = pd.to_numeric(temp_df["amount"], errors="coerce") return temp_df if __name__ == "__main__": option_cffex_sz50_list_sina_df = option_cffex_sz50_list_sina() print(option_cffex_sz50_list_sina_df) # 期权-中金所-沪深300指数 option_cffex_hs300_list_sina_df = option_cffex_hs300_list_sina() print(option_cffex_hs300_list_sina_df) option_cffex_zz1000_list_sina_df = option_cffex_zz1000_list_sina() print(option_cffex_zz1000_list_sina_df) option_cffex_sz50_spot_sina_df = option_cffex_sz50_spot_sina(symbol="ho2303") print(option_cffex_sz50_spot_sina_df) option_cffex_hs300_spot_sina_df = option_cffex_hs300_spot_sina(symbol="io2209") print(option_cffex_hs300_spot_sina_df) option_cffex_zz1000_spot_sina_df = option_cffex_zz1000_spot_sina(symbol="mo2209") print(option_cffex_zz1000_spot_sina_df) option_cffex_sz50_daily_sina_df = option_cffex_sz50_daily_sina(symbol="ho2303P2350") print(option_cffex_sz50_daily_sina_df) option_cffex_hs300_daily_sina_df = option_cffex_hs300_daily_sina( symbol="io2202P4350" ) print(option_cffex_hs300_daily_sina_df) option_cffex_zz1000_daily_sina_df = option_cffex_zz1000_daily_sina( symbol="mo2208P6200" ) print(option_cffex_zz1000_daily_sina_df) # 期权-上交所-50ETF option_sse_list_sina_df = option_sse_list_sina(symbol="50ETF", exchange="null") print(option_sse_list_sina_df) option_sse_expire_day_sina_df = option_sse_expire_day_sina( trade_date="202308", symbol="50ETF", exchange="null" ) print(option_sse_expire_day_sina_df) option_sse_codes_sina_df = option_sse_codes_sina( symbol="看跌期权", trade_date="202209", underlying="510050" ) print(option_sse_codes_sina_df) option_sse_spot_price_sina_df = option_sse_spot_price_sina(symbol="10003686") print(option_sse_spot_price_sina_df) option_sse_underlying_spot_price_sina_df = option_sse_underlying_spot_price_sina( symbol="sh510300" ) print(option_sse_underlying_spot_price_sina_df) option_sse_greeks_sina_df = option_sse_greeks_sina(symbol="10004023") print(option_sse_greeks_sina_df) option_sse_minute_sina_df = option_sse_minute_sina(symbol="10004023") print(option_sse_minute_sina_df) option_sse_daily_sina_df = option_sse_daily_sina(symbol="10004023") print(option_sse_daily_sina_df) option_finance_minute_sina_df = option_finance_minute_sina(symbol="10004023") print(option_finance_minute_sina_df) option_current_em_df = option_current_em() print(option_current_em_df) option_minute_em_df = option_minute_em(symbol="10008594") print(option_minute_em_df)