#!/usr/bin/env python # -*- coding:utf-8 -*- """ Date: 2025/5/16 19:00 Desc: 债券-集思录-可转债 集思录：https://www.jisilu.cn/data/cbnew/#cb """ from io import StringIO import pandas as pd import requests import time from akshare.utils import demjson def bond_cb_index_jsl() -> pd.DataFrame: """ 首页-可转债-集思录可转债等权指数 https://www.jisilu.cn/web/data/cb/index :return: 集思录可转债等权指数 :rtype: pandas.DataFrame """ url = "https://www.jisilu.cn/webapi/cb/index_history/" r = requests.get(url) data_dict = demjson.decode(r.text)["data"] temp_df = pd.DataFrame(data_dict) return temp_df def bond_cb_jsl(cookie: str = None) -> pd.DataFrame: """ 集思录可转债 https://www.jisilu.cn/data/cbnew/#cb :param cookie: 输入获取到的游览器 cookie :type cookie: str :return: 集思录可转债 :rtype: pandas.DataFrame """ url = "https://www.jisilu.cn/data/cbnew/cb_list_new/" headers = { "accept": "application/json, text/javascript, */*; q=0.01", "accept-encoding": "gzip, deflate, br", "accept-language": "zh-CN,zh;q=0.9,en;q=0.8", "cache-control": "no-cache", "content-length": "220", "content-type": "application/x-www-form-urlencoded; charset=UTF-8", "cookie": cookie, "origin": "https://www.jisilu.cn", "pragma": "no-cache", "referer": "https://www.jisilu.cn/data/cbnew/", "sec-ch-ua": '" Not;A Brand";v="99", "Google Chrome";v="91", "Chromium";v="91"', "sec-ch-ua-mobile": "?0", "sec-fetch-dest": "empty", "sec-fetch-mode": "cors", "sec-fetch-site": "same-origin", "user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/91.0.4472.164 Safari/537.36", "x-requested-with": "XMLHttpRequest", } params = { "___jsl": f"LST___t={int(time.time() * 1000)}", } payload = { "fprice": "", "tprice": "", "curr_iss_amt": "", "volume": "", "svolume": "", "premium_rt": "", "ytm_rt": "", "market": "", "rating_cd": "", "is_search": "N", "market_cd[]": "shmb", # noqa: F601 "market_cd[]": "shkc", # noqa: F601 "market_cd[]": "szmb", # noqa: F601 "market_cd[]": "szcy", # noqa: F601 "btype": "", "listed": "Y", "qflag": "N", "sw_cd": "", "bond_ids": "", "rp": "50", } r = requests.post(url, params=params, json=payload, headers=headers) data_json = r.json() temp_df = pd.DataFrame([item["cell"] for item in data_json["rows"]]) temp_df.rename( columns={ "bond_id": "代码", "bond_nm": "转债名称", "price": "现价", "increase_rt": "涨跌幅", "stock_id": "正股代码", "stock_nm": "正股名称", "sprice": "正股价", "sincrease_rt": "正股涨跌", "pb": "正股PB", "convert_price": "转股价", "convert_value": "转股价值", "premium_rt": "转股溢价率", "dblow": "双低", "rating_cd": "债券评级", "put_convert_price": "回售触发价", "force_redeem_price": "强赎触发价", "convert_amt_ratio": "转债占比", "maturity_dt": "到期时间", "year_left": "剩余年限", "curr_iss_amt": "剩余规模", "volume": "成交额", "turnover_rt": "换手率", "ytm_rt": "到期税前收益", }, inplace=True, ) temp_df = temp_df[ [ "代码", "转债名称", "现价", "涨跌幅", "正股代码", "正股名称", "正股价", "正股涨跌", "正股PB", "转股价", "转股价值", "转股溢价率", "债券评级", "回售触发价", "强赎触发价", "转债占比", "到期时间", "剩余年限", "剩余规模", "成交额", "换手率", "到期税前收益", "双低", ] ] temp_df["到期时间"] = pd.to_datetime(temp_df["到期时间"], errors="coerce").dt.date temp_df["现价"] = pd.to_numeric(temp_df["现价"], errors="coerce") temp_df["涨跌幅"] = pd.to_numeric(temp_df["涨跌幅"], errors="coerce") temp_df["正股价"] = pd.to_numeric(temp_df["正股价"], errors="coerce") temp_df["正股涨跌"] = pd.to_numeric(temp_df["正股涨跌"], errors="coerce") temp_df["正股PB"] = pd.to_numeric(temp_df["正股PB"], errors="coerce") temp_df["转股价"] = pd.to_numeric(temp_df["转股价"], errors="coerce") temp_df["转股价值"] = pd.to_numeric(temp_df["转股价值"], errors="coerce") temp_df["转股溢价率"] = pd.to_numeric(temp_df["转股溢价率"], errors="coerce") temp_df["回售触发价"] = pd.to_numeric(temp_df["回售触发价"], errors="coerce") temp_df["强赎触发价"] = pd.to_numeric(temp_df["强赎触发价"], errors="coerce") temp_df["转债占比"] = pd.to_numeric(temp_df["转债占比"], errors="coerce") temp_df["剩余年限"] = pd.to_numeric(temp_df["剩余年限"], errors="coerce") temp_df["剩余规模"] = pd.to_numeric(temp_df["剩余规模"], errors="coerce") temp_df["成交额"] = pd.to_numeric(temp_df["成交额"], errors="coerce") temp_df["换手率"] = pd.to_numeric(temp_df["换手率"], errors="coerce") temp_df["到期税前收益"] = pd.to_numeric(temp_df["到期税前收益"], errors="coerce") return temp_df def bond_cb_redeem_jsl() -> pd.DataFrame: """ 集思录可转债-强赎 https://www.jisilu.cn/data/cbnew/#redeem :return: 集思录可转债-强赎 :rtype: pandas.DataFrame """ url = "https://www.jisilu.cn/data/cbnew/redeem_list/" headers = { "Accept": "application/json, text/javascript, */*; q=0.01", "Accept-Encoding": "gzip, deflate, br", "Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8", "Cache-Control": "no-cache", "Connection": "keep-alive", "Content-Length": "5", "Content-Type": "application/x-www-form-urlencoded; charset=UTF-8", "Host": "www.jisilu.cn", "Origin": "https://www.jisilu.cn", "Pragma": "no-cache", "Referer": "https://www.jisilu.cn/data/cbnew/", "sec-ch-ua": '" Not A;Brand";v="99", "Chromium";v="101", "Google Chrome";v="101"', "sec-ch-ua-mobile": "?0", "sec-ch-ua-platform": '"Windows"', "Sec-Fetch-Dest": "empty", "Sec-Fetch-Mode": "cors", "Sec-Fetch-Site": "same-origin", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) " "Chrome/101.0.4951.67 Safari/537.36", "X-Requested-With": "XMLHttpRequest", } params = { "___jsl": "LST___t=1653394005966", } payload = { "rp": "50", } r = requests.post(url, params=params, json=payload, headers=headers) data_json = r.json() temp_df = pd.DataFrame([item["cell"] for item in data_json["rows"]]) temp_df.rename( columns={ "bond_id": "代码", "bond_nm": "名称", "price": "现价", "stock_id": "正股代码", "stock_nm": "正股名称", "margin_flg": "-", "btype": "-", "orig_iss_amt": "规模", "curr_iss_amt": "剩余规模", "convert_dt": "转股起始日", "convert_price": "转股价", "next_put_dt": "-", "redeem_dt": "-", "force_redeem": "-", "redeem_flag": "-", "redeem_price": "-", "redeem_price_ratio": "强赎触发比", "real_force_redeem_price": "强赎价", "redeem_remain_days": "-", "redeem_real_days": "-", "redeem_total_days": "-", "recount_dt": "-", "redeem_count_days": "-", "redeem_tc": "强赎条款", "sprice": "正股价", "delist_dt": "最后交易日", "maturity_dt": "到期日", "redeem_icon": "强赎状态", "redeem_orders": "-", "at_maturity": "-", "redeem_count": "强赎天计数", "after_next_put_dt": "-", "force_redeem_price": "强赎触发价", }, inplace=True, ) temp_df = temp_df[ [ "代码", "名称", "现价", "正股代码", "正股名称", "规模", "剩余规模", "转股起始日", "最后交易日", "到期日", "转股价", "强赎触发比", "强赎触发价", "正股价", "强赎价", "强赎天计数", "强赎条款", "强赎状态", ] ] temp_df["现价"] = pd.to_numeric(temp_df["现价"], errors="coerce") temp_df["规模"] = pd.to_numeric(temp_df["规模"], errors="coerce") temp_df["剩余规模"] = pd.to_numeric(temp_df["剩余规模"], errors="coerce") temp_df["转股起始日"] = pd.to_datetime( temp_df["转股起始日"], errors="coerce" ).dt.date temp_df["最后交易日"] = pd.to_datetime( temp_df["最后交易日"], errors="coerce" ).dt.date temp_df["到期日"] = pd.to_datetime(temp_df["到期日"], errors="coerce").dt.date temp_df["转股价"] = pd.to_numeric(temp_df["转股价"], errors="coerce") temp_df["强赎触发比"] = pd.to_numeric( temp_df["强赎触发比"].str.strip("%"), errors="coerce" ) temp_df["强赎触发价"] = pd.to_numeric(temp_df["强赎触发价"], errors="coerce") temp_df["正股价"] = pd.to_numeric(temp_df["正股价"], errors="coerce") temp_df["强赎价"] = pd.to_numeric(temp_df["强赎价"], errors="coerce") temp_df["强赎天计数"] = temp_df["强赎天计数"].replace( r"^.*?(\d{1,2}\/\d{1,2} \| \d{1,2}).*?$", r"\1", regex=True ) temp_df["强赎状态"] = temp_df["强赎状态"].map( { "R": "已公告强赎", "O": "公告要强赎", "G": "公告不强赎", "B": "已满足强赎条件", "": "", } ) return temp_df def bond_cb_adj_logs_jsl(symbol: str = "128013") -> pd.DataFrame: """ 集思录-可转债转股价-调整记录 https://www.jisilu.cn/data/cbnew/#cb :param symbol: 可转债代码 :type symbol: str :return: 转股价调整记录 :rtype: pandas.DataFrame """ url = f"https://www.jisilu.cn/data/cbnew/adj_logs/?bond_id={symbol}" r = requests.get(url) data_text = r.text if "" not in data_text: # 1. 该可转债没有转股价调整记录，服务端返回文本 '暂无数据' # 2. 无效可转债代码，服务端返回 {"timestamp":1639565628,"isError":1,"msg":"无效代码格式"} # 以上两种情况，返回空的 DataFrame return pd.DataFrame() else: temp_df = pd.read_html(StringIO(data_text), parse_dates=True)[0] temp_df.columns = [item.replace(" ", "") for item in temp_df.columns] temp_df["下修前转股价"] = pd.to_numeric( temp_df["下修前转股价"], errors="coerce" ) temp_df["下修后转股价"] = pd.to_numeric( temp_df["下修后转股价"], errors="coerce" ) temp_df["下修底价"] = pd.to_numeric(temp_df["下修底价"], errors="coerce") temp_df["股东大会日"] = pd.to_datetime( temp_df["股东大会日"], format="%Y-%m-%d", errors="coerce" ).dt.date temp_df["新转股价生效日期"] = pd.to_datetime( temp_df["新转股价生效日期"], format="%Y-%m-%d", errors="coerce" ).dt.date return temp_df if __name__ == "__main__": bond_cb_index_jsl_df = bond_cb_index_jsl() print(bond_cb_index_jsl_df) bond_cb_jsl_df = bond_cb_jsl(cookie="") print(bond_cb_jsl_df) bond_cb_redeem_jsl_df = bond_cb_redeem_jsl() print(bond_cb_redeem_jsl_df) bond_cb_adj_logs_jsl_df = bond_cb_adj_logs_jsl(symbol="128013") print(bond_cb_adj_logs_jsl_df)