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
171 lines
5.6 KiB
Python
171 lines
5.6 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2024/7/25 14:30
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Desc: 巨潮资讯-数据中心-新股数据
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https://webapi.cninfo.com.cn/#/xinguList
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"""
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import pandas as pd
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import py_mini_racer
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import requests
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from akshare.datasets import get_ths_js
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def _get_file_content_cninfo(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_new_gh_cninfo() -> pd.DataFrame:
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"""
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巨潮资讯-数据中心-新股数据-新股过会
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https://webapi.cninfo.com.cn/#/xinguList
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:return: 新股过会
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:rtype: pandas.DataFrame
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"""
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url = "https://webapi.cninfo.com.cn/api/sysapi/p_sysapi1098"
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js_code = py_mini_racer.MiniRacer()
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js_content = _get_file_content_cninfo("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-Enckey": mcode,
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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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"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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r = requests.post(url, headers=headers)
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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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"公司名称",
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"上会日期",
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"审核类型",
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"审议内容",
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"审核结果",
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"审核公告日",
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]
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temp_df["上会日期"] = pd.to_datetime(temp_df["上会日期"], errors="coerce").dt.date
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temp_df["审核公告日"] = pd.to_datetime(
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temp_df["审核公告日"], errors="coerce"
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).dt.date
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return temp_df
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def stock_new_ipo_cninfo() -> pd.DataFrame:
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"""
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巨潮资讯-数据中心-新股数据-新股发行
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https://webapi.cninfo.com.cn/#/xinguList
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:return: 新股发行
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:rtype: pandas.DataFrame
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"""
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url = "https://webapi.cninfo.com.cn/api/sysapi/p_sysapi1097"
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js_code = py_mini_racer.MiniRacer()
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js_content = _get_file_content_cninfo("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-Enckey": mcode,
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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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"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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"timetype": "36",
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"market": "ALL",
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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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"摇号结果公告日",
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"中签公告日",
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"证券简称",
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"上市日期",
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"中签缴款日",
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"申购日期",
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"发行价",
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"证劵代码",
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"上网发行中签率",
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"总发行数量",
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"发行市盈率",
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"上网发行数量",
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"网上申购上限",
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]
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temp_df = temp_df[
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[
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"证劵代码",
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"证券简称",
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"上市日期",
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"申购日期",
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"发行价",
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"总发行数量",
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"发行市盈率",
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"上网发行中签率",
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"摇号结果公告日",
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"中签公告日",
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"中签缴款日",
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"网上申购上限",
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"上网发行数量",
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]
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]
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temp_df["摇号结果公告日"] = pd.to_datetime(
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temp_df["摇号结果公告日"], errors="coerce"
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).dt.date
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temp_df["中签公告日"] = pd.to_datetime(
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temp_df["中签公告日"], errors="coerce"
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).dt.date
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temp_df["上市日期"] = pd.to_datetime(temp_df["上市日期"], errors="coerce").dt.date
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temp_df["中签缴款日"] = pd.to_datetime(
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temp_df["中签缴款日"], errors="coerce"
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).dt.date
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temp_df["申购日期"] = pd.to_datetime(temp_df["申购日期"], errors="coerce").dt.date
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temp_df["发行价"] = pd.to_numeric(temp_df["发行价"], errors="coerce")
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temp_df["上网发行中签率"] = pd.to_numeric(
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temp_df["上网发行中签率"], errors="coerce"
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)
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temp_df["总发行数量"] = pd.to_numeric(temp_df["总发行数量"], errors="coerce")
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temp_df["发行市盈率"] = pd.to_numeric(temp_df["发行市盈率"], errors="coerce")
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temp_df["上网发行数量"] = pd.to_numeric(temp_df["上网发行数量"], errors="coerce")
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temp_df["网上申购上限"] = pd.to_numeric(temp_df["网上申购上限"], errors="coerce")
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return temp_df
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if __name__ == "__main__":
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stock_new_gh_cninfo_df = stock_new_gh_cninfo()
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print(stock_new_gh_cninfo_df)
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stock_new_ipo_cninfo_df = stock_new_ipo_cninfo()
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print(stock_new_ipo_cninfo_df)
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