知微
fa45d8aa5f
- health_checklist.json: 192.168.1.122→node122
- ocr_client.py: docstring IP→node122
- docs/market-data-requirements.md: IP→node122
- 所有API调用通过ProxyHandler({})绕过系统代理
Privoxy对node122:18003返回500，直连正常
345 lines
12 KiB
Python
345 lines
12 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2025/5/16 19:00
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Desc: 债券-集思录-可转债
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集思录：https://www.jisilu.cn/data/cbnew/#cb
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"""
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from io import StringIO
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import pandas as pd
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import requests
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import time
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from akshare.utils import demjson
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def bond_cb_index_jsl() -> pd.DataFrame:
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"""
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首页-可转债-集思录可转债等权指数
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https://www.jisilu.cn/web/data/cb/index
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:return: 集思录可转债等权指数
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:rtype: pandas.DataFrame
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"""
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url = "https://www.jisilu.cn/webapi/cb/index_history/"
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r = requests.get(url)
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data_dict = demjson.decode(r.text)["data"]
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temp_df = pd.DataFrame(data_dict)
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return temp_df
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def bond_cb_jsl(cookie: str = None) -> pd.DataFrame:
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"""
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集思录可转债
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https://www.jisilu.cn/data/cbnew/#cb
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:param cookie: 输入获取到的游览器 cookie
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:type cookie: str
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:return: 集思录可转债
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:rtype: pandas.DataFrame
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"""
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url = "https://www.jisilu.cn/data/cbnew/cb_list_new/"
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headers = {
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"accept": "application/json, text/javascript, */*; q=0.01",
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"accept-encoding": "gzip, deflate, br",
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"accept-language": "zh-CN,zh;q=0.9,en;q=0.8",
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"cache-control": "no-cache",
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"content-length": "220",
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"content-type": "application/x-www-form-urlencoded; charset=UTF-8",
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"cookie": cookie,
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"origin": "https://www.jisilu.cn",
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"pragma": "no-cache",
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"referer": "https://www.jisilu.cn/data/cbnew/",
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"sec-ch-ua": '" Not;A Brand";v="99", "Google Chrome";v="91", "Chromium";v="91"',
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"sec-ch-ua-mobile": "?0",
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"sec-fetch-dest": "empty",
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"sec-fetch-mode": "cors",
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"sec-fetch-site": "same-origin",
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"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/91.0.4472.164 Safari/537.36",
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"x-requested-with": "XMLHttpRequest",
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}
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params = {
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"___jsl": f"LST___t={int(time.time() * 1000)}",
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}
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payload = {
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"fprice": "",
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"tprice": "",
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"curr_iss_amt": "",
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"volume": "",
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"svolume": "",
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"premium_rt": "",
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"ytm_rt": "",
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"market": "",
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"rating_cd": "",
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"is_search": "N",
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"market_cd[]": "shmb", # noqa: F601
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"market_cd[]": "shkc", # noqa: F601
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"market_cd[]": "szmb", # noqa: F601
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"market_cd[]": "szcy", # noqa: F601
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"btype": "",
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"listed": "Y",
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"qflag": "N",
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"sw_cd": "",
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"bond_ids": "",
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"rp": "50",
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}
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r = requests.post(url, params=params, json=payload, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame([item["cell"] for item in data_json["rows"]])
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temp_df.rename(
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columns={
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"bond_id": "代码",
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"bond_nm": "转债名称",
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"price": "现价",
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"increase_rt": "涨跌幅",
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"stock_id": "正股代码",
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"stock_nm": "正股名称",
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"sprice": "正股价",
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"sincrease_rt": "正股涨跌",
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"pb": "正股PB",
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"convert_price": "转股价",
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"convert_value": "转股价值",
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"premium_rt": "转股溢价率",
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"dblow": "双低",
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"rating_cd": "债券评级",
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"put_convert_price": "回售触发价",
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"force_redeem_price": "强赎触发价",
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"convert_amt_ratio": "转债占比",
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"maturity_dt": "到期时间",
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"year_left": "剩余年限",
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"curr_iss_amt": "剩余规模",
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"volume": "成交额",
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"turnover_rt": "换手率",
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"ytm_rt": "到期税前收益",
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},
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inplace=True,
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)
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temp_df = temp_df[
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[
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"代码",
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"转债名称",
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"现价",
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"涨跌幅",
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"正股代码",
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"正股名称",
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"正股价",
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"正股涨跌",
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"正股PB",
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"转股价",
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"转股价值",
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"转股溢价率",
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"债券评级",
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"回售触发价",
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"强赎触发价",
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"转债占比",
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"到期时间",
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"剩余年限",
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"剩余规模",
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"成交额",
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"换手率",
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"到期税前收益",
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"双低",
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]
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]
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temp_df["到期时间"] = pd.to_datetime(temp_df["到期时间"], errors="coerce").dt.date
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temp_df["现价"] = pd.to_numeric(temp_df["现价"], errors="coerce")
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temp_df["涨跌幅"] = pd.to_numeric(temp_df["涨跌幅"], errors="coerce")
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temp_df["正股价"] = pd.to_numeric(temp_df["正股价"], errors="coerce")
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temp_df["正股涨跌"] = pd.to_numeric(temp_df["正股涨跌"], errors="coerce")
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temp_df["正股PB"] = pd.to_numeric(temp_df["正股PB"], errors="coerce")
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temp_df["转股价"] = pd.to_numeric(temp_df["转股价"], errors="coerce")
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temp_df["转股价值"] = pd.to_numeric(temp_df["转股价值"], errors="coerce")
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temp_df["转股溢价率"] = pd.to_numeric(temp_df["转股溢价率"], errors="coerce")
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temp_df["回售触发价"] = pd.to_numeric(temp_df["回售触发价"], errors="coerce")
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temp_df["强赎触发价"] = pd.to_numeric(temp_df["强赎触发价"], errors="coerce")
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temp_df["转债占比"] = pd.to_numeric(temp_df["转债占比"], errors="coerce")
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temp_df["剩余年限"] = pd.to_numeric(temp_df["剩余年限"], errors="coerce")
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temp_df["剩余规模"] = pd.to_numeric(temp_df["剩余规模"], errors="coerce")
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temp_df["成交额"] = pd.to_numeric(temp_df["成交额"], errors="coerce")
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temp_df["换手率"] = pd.to_numeric(temp_df["换手率"], errors="coerce")
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temp_df["到期税前收益"] = pd.to_numeric(temp_df["到期税前收益"], errors="coerce")
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return temp_df
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def bond_cb_redeem_jsl() -> pd.DataFrame:
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"""
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集思录可转债-强赎
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https://www.jisilu.cn/data/cbnew/#redeem
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:return: 集思录可转债-强赎
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:rtype: pandas.DataFrame
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"""
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url = "https://www.jisilu.cn/data/cbnew/redeem_list/"
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headers = {
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"Accept": "application/json, text/javascript, */*; q=0.01",
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"Accept-Encoding": "gzip, deflate, br",
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"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"Content-Length": "5",
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"Content-Type": "application/x-www-form-urlencoded; charset=UTF-8",
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"Host": "www.jisilu.cn",
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"Origin": "https://www.jisilu.cn",
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"Pragma": "no-cache",
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"Referer": "https://www.jisilu.cn/data/cbnew/",
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"sec-ch-ua": '" Not A;Brand";v="99", "Chromium";v="101", "Google Chrome";v="101"',
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"sec-ch-ua-mobile": "?0",
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"sec-ch-ua-platform": '"Windows"',
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"Sec-Fetch-Dest": "empty",
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"Sec-Fetch-Mode": "cors",
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"Sec-Fetch-Site": "same-origin",
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) "
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"Chrome/101.0.4951.67 Safari/537.36",
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"X-Requested-With": "XMLHttpRequest",
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}
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params = {
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"___jsl": "LST___t=1653394005966",
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}
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payload = {
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"rp": "50",
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}
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r = requests.post(url, params=params, json=payload, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame([item["cell"] for item in data_json["rows"]])
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temp_df.rename(
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columns={
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"bond_id": "代码",
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"bond_nm": "名称",
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"price": "现价",
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"stock_id": "正股代码",
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"stock_nm": "正股名称",
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"margin_flg": "-",
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"btype": "-",
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"orig_iss_amt": "规模",
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"curr_iss_amt": "剩余规模",
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"convert_dt": "转股起始日",
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"convert_price": "转股价",
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"next_put_dt": "-",
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"redeem_dt": "-",
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"force_redeem": "-",
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"redeem_flag": "-",
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"redeem_price": "-",
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"redeem_price_ratio": "强赎触发比",
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"real_force_redeem_price": "强赎价",
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"redeem_remain_days": "-",
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"redeem_real_days": "-",
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"redeem_total_days": "-",
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"recount_dt": "-",
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"redeem_count_days": "-",
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"redeem_tc": "强赎条款",
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"sprice": "正股价",
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"delist_dt": "最后交易日",
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"maturity_dt": "到期日",
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"redeem_icon": "强赎状态",
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"redeem_orders": "-",
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"at_maturity": "-",
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"redeem_count": "强赎天计数",
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"after_next_put_dt": "-",
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"force_redeem_price": "强赎触发价",
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},
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inplace=True,
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)
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temp_df = temp_df[
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[
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"代码",
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"名称",
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"现价",
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"正股代码",
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"正股名称",
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"规模",
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"剩余规模",
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"转股起始日",
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"最后交易日",
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"到期日",
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"转股价",
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"强赎触发比",
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"强赎触发价",
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"正股价",
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"强赎价",
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"强赎天计数",
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"强赎条款",
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"强赎状态",
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]
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]
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temp_df["现价"] = pd.to_numeric(temp_df["现价"], errors="coerce")
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temp_df["规模"] = pd.to_numeric(temp_df["规模"], errors="coerce")
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temp_df["剩余规模"] = pd.to_numeric(temp_df["剩余规模"], errors="coerce")
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temp_df["转股起始日"] = pd.to_datetime(
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temp_df["转股起始日"], errors="coerce"
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).dt.date
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temp_df["最后交易日"] = pd.to_datetime(
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temp_df["最后交易日"], errors="coerce"
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).dt.date
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temp_df["到期日"] = pd.to_datetime(temp_df["到期日"], errors="coerce").dt.date
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temp_df["转股价"] = pd.to_numeric(temp_df["转股价"], errors="coerce")
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temp_df["强赎触发比"] = pd.to_numeric(
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temp_df["强赎触发比"].str.strip("%"), errors="coerce"
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)
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temp_df["强赎触发价"] = pd.to_numeric(temp_df["强赎触发价"], errors="coerce")
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temp_df["正股价"] = pd.to_numeric(temp_df["正股价"], errors="coerce")
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temp_df["强赎价"] = pd.to_numeric(temp_df["强赎价"], errors="coerce")
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temp_df["强赎天计数"] = temp_df["强赎天计数"].replace(
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r"^.*?(\d{1,2}\/\d{1,2} \| \d{1,2}).*?$", r"\1", regex=True
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)
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temp_df["强赎状态"] = temp_df["强赎状态"].map(
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{
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"R": "已公告强赎",
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"O": "公告要强赎",
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"G": "公告不强赎",
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"B": "已满足强赎条件",
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"": "",
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}
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)
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return temp_df
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def bond_cb_adj_logs_jsl(symbol: str = "128013") -> pd.DataFrame:
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"""
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集思录-可转债转股价-调整记录
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https://www.jisilu.cn/data/cbnew/#cb
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:param symbol: 可转债代码
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:type symbol: str
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:return: 转股价调整记录
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:rtype: pandas.DataFrame
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"""
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url = f"https://www.jisilu.cn/data/cbnew/adj_logs/?bond_id={symbol}"
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r = requests.get(url)
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data_text = r.text
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if "</table>" not in data_text:
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# 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'
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# 2. 无效可转债代码，服务端返回 {"timestamp":1639565628,"isError":1,"msg":"无效代码格式"}
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# 以上两种情况，返回空的 DataFrame
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return pd.DataFrame()
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else:
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temp_df = pd.read_html(StringIO(data_text), parse_dates=True)[0]
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temp_df.columns = [item.replace(" ", "") for item in temp_df.columns]
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temp_df["下修前转股价"] = pd.to_numeric(
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temp_df["下修前转股价"], errors="coerce"
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)
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temp_df["下修后转股价"] = pd.to_numeric(
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temp_df["下修后转股价"], errors="coerce"
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)
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temp_df["下修底价"] = pd.to_numeric(temp_df["下修底价"], errors="coerce")
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temp_df["股东大会日"] = pd.to_datetime(
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temp_df["股东大会日"], format="%Y-%m-%d", errors="coerce"
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).dt.date
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temp_df["新转股价生效日期"] = pd.to_datetime(
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temp_df["新转股价生效日期"], format="%Y-%m-%d", errors="coerce"
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).dt.date
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return temp_df
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if __name__ == "__main__":
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bond_cb_index_jsl_df = bond_cb_index_jsl()
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print(bond_cb_index_jsl_df)
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bond_cb_jsl_df = bond_cb_jsl(cookie="")
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print(bond_cb_jsl_df)
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bond_cb_redeem_jsl_df = bond_cb_redeem_jsl()
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print(bond_cb_redeem_jsl_df)
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bond_cb_adj_logs_jsl_df = bond_cb_adj_logs_jsl(symbol="128013")
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print(bond_cb_adj_logs_jsl_df)
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