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
46 lines
1.5 KiB
Python
46 lines
1.5 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2025/3/31 18:00
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Desc: 国泰君安期货-交易日历数据表
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https://www.gtjaqh.com/pc/calendar.html
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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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def futures_rule(date: str = "20231205") -> pd.DataFrame:
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"""
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国泰君安期货-交易日历数据表
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https://www.gtjaqh.com/pc/calendar.html
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:param date: 需要指定为交易日, 且是近期的日期
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:type date: str
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:return: 交易日历数据
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:rtype: pandas.DataFrame
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"""
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import urllib3
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urllib3.disable_warnings()
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url = " https://www.gtjaqh.com/pc/calendar"
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params = {"date": f"{date}"}
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r = requests.get(url, params=params, verify=False)
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big_df = pd.read_html(StringIO(r.text), header=1)[0]
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big_df["交易保证金比例"] = big_df["交易保证金比例"].str.strip("%")
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big_df["交易保证金比例"] = pd.to_numeric(big_df["交易保证金比例"], errors="coerce")
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big_df["涨跌停板幅度"] = big_df["涨跌停板幅度"].str.strip("%")
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big_df["涨跌停板幅度"] = pd.to_numeric(big_df["涨跌停板幅度"], errors="coerce")
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big_df["合约乘数"] = pd.to_numeric(big_df["合约乘数"], errors="coerce")
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big_df["最小变动价位"] = pd.to_numeric(big_df["最小变动价位"], errors="coerce")
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big_df["限价单每笔最大下单手数"] = pd.to_numeric(
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big_df["限价单每笔最大下单手数"], errors="coerce"
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)
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return big_df
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if __name__ == "__main__":
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futures_rule_df = futures_rule(date="20250328")
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print(futures_rule_df)
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