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
298 lines
11 KiB
Python
298 lines
11 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2024/11/8 17:00
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Desc: 董监高及相关人员持股变动
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北京证券交易所-信息披露-监管信息-董监高及相关人员持股变动
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https://www.bse.cn/disclosure/djg_sharehold_change.html
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深圳证券交易所-信息披露-监管信息公开-董监高人员股份变动
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https://www.szse.cn/disclosure/supervision/change/index.html
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上海证券交易所-披露-监管信息公开-公司监管-董董监高人员股份变动
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https://www.sse.com.cn/disclosure/credibility/supervision/change/
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"""
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import json
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import pandas as pd
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import requests
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from tqdm import tqdm
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def stock_share_hold_change_sse(symbol: str = "600000") -> pd.DataFrame:
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"""
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上海证券交易所-披露-监管信息公开-公司监管-董董监高人员股份变动
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https://www.sse.com.cn/disclosure/credibility/supervision/change/
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:param symbol: choice of {"全部", "具体股票代码"}
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:type symbol: str
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:return: 董监高人员股份变动
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:rtype: pandas.DataFrame
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"""
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url = "https://query.sse.com.cn/commonQuery.do"
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params = {
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"isPagination": "true",
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"pageHelp.pageSize": "100",
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"pageHelp.pageNo": "1",
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"pageHelp.beginPage": "1",
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"pageHelp.cacheSize": "1",
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"pageHelp.endPage": "1",
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"sqlId": "COMMON_SSE_XXPL_CXJL_SSGSGFBDQK_S",
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"COMPANY_CODE": "",
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"NAME": "",
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"BEGIN_DATE": "1990-01-01",
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"END_DATE": "2050-01-01",
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"BOARDTYPE": "",
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}
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params if symbol == "全部" else params.update({"COMPANY_CODE": symbol})
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headers = {
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"Host": "query.sse.com.cn",
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"Referer": "https://www.sse.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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}
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r = requests.get(url, headers=headers, params=params)
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data_json = r.json()
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total_page = data_json["pageHelp"]["pageCount"]
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big_df = pd.DataFrame()
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for page in tqdm(range(1, total_page + 1), leave=False):
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params.update(
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{
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"pageHelp.pageNo": page,
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"pageHelp.beginPage": page,
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"pageHelp.endPage": page,
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}
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)
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r = requests.get(url, headers=headers, params=params)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["result"])
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big_df = pd.concat(objs=[big_df, temp_df], axis=0, ignore_index=True)
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big_df.rename(
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columns={
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"STOCK_TYPE": "股票种类",
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"COMPANY_ABBR": "公司名称",
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"NUM": "-",
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"CURRENT_AVG_PRICE": "本次变动平均价格",
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"CHANGE_DATE": "变动日期",
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"HOLDSTOCK_NUM": "变动后持股数",
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"NAME": "姓名",
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"CHANGE_REASON": "变动原因",
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"DUTY": "职务",
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"CURRENCY_TYPE": "货币种类",
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"COMPANY_CODE": "公司代码",
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"FORM_DATE": "填报日期",
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"CHANGE_NUM": "变动数",
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"CURRENT_NUM": "本次变动前持股数",
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},
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inplace=True,
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)
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big_df = big_df[
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[
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"公司代码",
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"公司名称",
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"姓名",
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"职务",
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"股票种类",
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"货币种类",
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"本次变动前持股数",
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"变动数",
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"本次变动平均价格",
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"变动后持股数",
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"变动原因",
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"变动日期",
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"填报日期",
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]
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]
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big_df["变动日期"] = pd.to_datetime(big_df["变动日期"], errors="coerce").dt.date
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big_df["填报日期"] = pd.to_datetime(big_df["填报日期"], errors="coerce").dt.date
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big_df["本次变动前持股数"] = pd.to_numeric(
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big_df["本次变动前持股数"], errors="coerce"
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)
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big_df["变动数"] = pd.to_numeric(big_df["变动数"], errors="coerce")
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big_df["本次变动平均价格"] = pd.to_numeric(
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big_df["本次变动平均价格"], errors="coerce"
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)
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big_df["变动后持股数"] = pd.to_numeric(big_df["变动后持股数"], errors="coerce")
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return big_df
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def stock_share_hold_change_szse(symbol: str = "全部") -> pd.DataFrame:
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"""
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深圳证券交易所-信息披露-监管信息公开-董监高人员股份变动
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https://www.szse.cn/disclosure/supervision/change/index.html
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:param symbol: choice of {"全部", "具体股票代码"}
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:type symbol: str
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:return: 董监高人员股份变动
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:rtype: pandas.DataFrame
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"""
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url = "https://www.szse.cn/api/report/ShowReport/data"
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headers = {
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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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}
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params = {
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"SHOWTYPE": "JSON",
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"CATALOGID": "1801_cxda",
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"TABKEY": "tab1",
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"PAGENO": "1",
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"random": "0.7874198771222201",
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}
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params if symbol == "全部" else params.update({"txtDMorJC": symbol})
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r = requests.get(url, headers=headers, params=params)
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data_json = r.json()
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total_page = data_json[0]["metadata"]["pagecount"]
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big_df = pd.DataFrame()
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for page in tqdm(range(1, total_page + 1), leave=False):
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params.update(
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{
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"PAGENO": page,
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}
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)
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r = requests.get(url, headers=headers, params=params)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json[0]["data"])
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big_df = pd.concat(objs=[big_df, temp_df], axis=0, ignore_index=True)
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big_df.rename(
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columns={
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"zqdm": "证券代码",
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"zqjc": "证券简称",
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"ggxm": "董监高姓名",
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"jyrq": "变动日期",
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"bdgs": "变动股份数量",
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"bdjj": "成交均价",
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"bdyy": "变动原因",
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"cgbdbl": "变动比例",
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"cgzs": "当日结存股数",
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"gdxm": "股份变动人姓名",
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"zw": "职务",
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"gxlb": "变动人与董监高的关系",
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},
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inplace=True,
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)
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big_df = big_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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"董监高姓名",
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"变动日期",
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"变动股份数量",
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"成交均价",
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"变动原因",
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"变动比例",
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"当日结存股数",
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"股份变动人姓名",
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"职务",
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"变动人与董监高的关系",
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]
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]
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big_df["变动日期"] = pd.to_datetime(big_df["变动日期"], errors="coerce").dt.date
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big_df["变动股份数量"] = pd.to_numeric(big_df["变动股份数量"], errors="coerce")
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big_df["成交均价"] = pd.to_numeric(big_df["成交均价"], errors="coerce")
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big_df["变动比例"] = pd.to_numeric(big_df["变动比例"], errors="coerce")
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big_df["当日结存股数"] = big_df["当日结存股数"].str.replace(",", "")
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big_df["当日结存股数"] = pd.to_numeric(big_df["当日结存股数"], errors="coerce")
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return big_df
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def stock_share_hold_change_bse(symbol: str = "430489") -> pd.DataFrame:
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"""
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北京证券交易所-信息披露-监管信息-董监高及相关人员持股变动
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https://www.bse.cn/disclosure/djg_sharehold_change.html
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:param symbol: choice of {"全部", "具体股票代码"}
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:type symbol: str
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:return: 董监高及相关人员持股变动
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:rtype: pandas.DataFrame
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"""
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symbol = symbol if symbol != "全部" else ""
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params = {
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"page": "0",
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"startTime": "",
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"endTime": "",
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"stockCode": symbol,
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"djgName": "",
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"ssgs": "1",
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"sortfield": "bean.change_date desc, bean.stock_code asc, bean.change_amount desc, bean.price",
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"sorttype": "desc",
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}
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url = "https://www.bse.cn/djgCgbdController/getDjgCgbdList.do"
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headers = {
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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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}
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r = requests.get(url, headers=headers, params=params)
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data_text = r.text
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data_text = data_text.strip("null(").strip(")")
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data_json = json.loads(data_text)
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total_page = data_json[0]["result"]["totalPages"]
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big_df = pd.DataFrame()
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for page in tqdm(range(0, total_page), leave=False):
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params.update(
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{
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"page": page,
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}
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)
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r = requests.get(url, headers=headers, params=params)
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data_text = r.text
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data_text = data_text.strip("null(").strip(")")
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data_json = json.loads(data_text)
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temp_df = pd.DataFrame(data_json[0]["result"]["content"])
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big_df = pd.concat(objs=[big_df, temp_df], axis=0, ignore_index=True)
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big_df.rename(
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columns={
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"changeAmount": "变动股数",
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"changeDate": "变动日期",
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"createTime": "-",
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"djgName": "姓名",
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"duty": "职务",
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"id": "-",
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"infoId": "-",
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"newAmount": "变动后持股数",
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"preAmount": "变动前持股数",
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"price": "变动均价",
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"reason": "变动原因",
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"ssgs": "-",
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"stockCode": "代码",
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"stockName": "简称",
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},
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inplace=True,
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)
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big_df = big_df[
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[
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"代码",
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"简称",
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"姓名",
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"职务",
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"变动日期",
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"变动股数",
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"变动前持股数",
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"变动后持股数",
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"变动均价",
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"变动原因",
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]
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]
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big_df["变动日期"] = pd.to_datetime(big_df["变动日期"], errors="coerce").dt.date
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big_df["变动股数"] = pd.to_numeric(big_df["变动股数"], errors="coerce")
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big_df["变动前持股数"] = pd.to_numeric(big_df["变动前持股数"], errors="coerce")
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big_df["变动后持股数"] = pd.to_numeric(big_df["变动后持股数"], errors="coerce")
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big_df["变动均价"] = pd.to_numeric(big_df["变动均价"], errors="coerce")
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return big_df
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if __name__ == "__main__":
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stock_share_hold_change_sse_df = stock_share_hold_change_sse(symbol="600000")
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print(stock_share_hold_change_sse_df)
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stock_share_hold_change_sse_df = stock_share_hold_change_sse(symbol="全部")
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print(stock_share_hold_change_sse_df)
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stock_share_hold_change_szse_df = stock_share_hold_change_szse(symbol="001308")
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print(stock_share_hold_change_szse_df)
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stock_share_hold_change_szse_df = stock_share_hold_change_szse(symbol="全部")
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print(stock_share_hold_change_szse_df)
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stock_share_hold_change_bse_df = stock_share_hold_change_bse(symbol="430489")
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print(stock_share_hold_change_bse_df)
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stock_share_hold_change_bse_df = stock_share_hold_change_bse(symbol="全部")
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print(stock_share_hold_change_bse_df)
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