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
117 lines
3.8 KiB
Python
117 lines
3.8 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2024/5/19 18:34
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Desc: 巨潮资讯-数据中心-专题统计-公司治理-对外担保
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https://webapi.cninfo.com.cn/#/thematicStatistics
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"""
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import pandas as pd
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import requests
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import py_mini_racer
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from akshare.datasets import get_ths_js
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def _get_file_content_ths(file: str = "cninfo.js") -> str:
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"""
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获取 JS 文件的内容
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:param file: JS 文件名
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:type file: str
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:return: 文件内容
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:rtype: str
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"""
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setting_file_path = get_ths_js(file)
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with open(setting_file_path, encoding="utf-8") as f:
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file_data = f.read()
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return file_data
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def stock_cg_guarantee_cninfo(
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symbol: str = "全部", start_date: str = "20180630", end_date: str = "20210927"
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) -> pd.DataFrame:
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"""
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巨潮资讯-数据中心-专题统计-公司治理-对外担保
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https://webapi.cninfo.com.cn/#/thematicStatistics
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:param symbol: choice of {"全部", "深市主板", "沪市", "创业板", "科创板"}
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:type symbol: str
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:param start_date: 开始统计时间
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:type start_date: str
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:param end_date: 结束统计时间
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:type end_date: str
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:return: 对外担保
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:rtype: pandas.DataFrame
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"""
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symbol_map = {
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"全部": "",
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"深市主板": "012002",
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"沪市": "012001",
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"创业板": "012015",
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"科创板": "012029",
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}
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url = "https://webapi.cninfo.com.cn/api/sysapi/p_sysapi1054"
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js_code = py_mini_racer.MiniRacer()
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js_content = _get_file_content_ths("cninfo.js")
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js_code.eval(js_content)
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mcode = js_code.call("getResCode1")
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headers = {
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"Accept": "*/*",
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"Accept-Encoding": "gzip, deflate",
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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": "0",
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"Host": "webapi.cninfo.com.cn",
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"Accept-Enckey": mcode,
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"Origin": "https://webapi.cninfo.com.cn",
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"Pragma": "no-cache",
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"Proxy-Connection": "keep-alive",
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"Referer": "https://webapi.cninfo.com.cn/",
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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/93.0.4577.63 Safari/537.36",
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"X-Requested-With": "XMLHttpRequest",
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}
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params = {
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"sdate": "-".join([start_date[:4], start_date[4:6], start_date[6:]]),
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"edate": "-".join([end_date[:4], end_date[4:6], end_date[6:]]),
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"market": symbol_map[symbol],
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}
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r = requests.post(url, headers=headers, params=params)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["records"])
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temp_df.columns = [
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"公告统计区间",
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"担保金融占净资产比例",
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"担保金额",
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"担保笔数",
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"证券简称",
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"证券代码",
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"归属于母公司所有者权益",
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]
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temp_df = temp_df[
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[
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"证券代码",
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"证券简称",
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"公告统计区间",
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"担保笔数",
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"担保金额",
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"归属于母公司所有者权益",
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"担保金融占净资产比例",
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]
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]
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temp_df["担保笔数"] = pd.to_numeric(temp_df["担保笔数"], errors="coerce")
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temp_df["担保金额"] = pd.to_numeric(temp_df["担保金额"], errors="coerce")
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temp_df["归属于母公司所有者权益"] = pd.to_numeric(
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temp_df["归属于母公司所有者权益"], errors="coerce"
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)
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temp_df["担保金融占净资产比例"] = pd.to_numeric(
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temp_df["担保金融占净资产比例"], errors="coerce"
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)
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return temp_df
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if __name__ == "__main__":
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stock_corporate_governance_guarantee_df = stock_cg_guarantee_cninfo(
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symbol="全部", start_date="20180928", end_date="20210927"
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)
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print(stock_corporate_governance_guarantee_df)
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