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
513 lines
16 KiB
Python
513 lines
16 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2024/5/27 15:30
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Desc: 股票基本信息
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"""
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import json
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import warnings
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from functools import lru_cache
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from io import BytesIO
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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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from akshare.utils.tqdm import get_tqdm
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@lru_cache()
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def stock_info_sz_name_code(symbol: str = "A股列表") -> pd.DataFrame:
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"""
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深圳证券交易所-股票列表
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https://www.szse.cn/market/product/stock/list/index.html
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:param symbol: choice of {"A股列表", "B股列表", "CDR列表", "AB股列表"}
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:type symbol: str
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:return: 指定 indicator 的数据
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:rtype: pandas.DataFrame
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"""
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url = "https://www.szse.cn/api/report/ShowReport"
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indicator_map = {
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"A股列表": "tab1",
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"B股列表": "tab2",
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"CDR列表": "tab3",
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"AB股列表": "tab4",
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}
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params = {
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"SHOWTYPE": "xlsx",
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"CATALOGID": "1110",
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"TABKEY": indicator_map[symbol],
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"random": "0.6935816432433362",
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}
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r = requests.get(url, params=params, timeout=15)
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with warnings.catch_warnings(record=True):
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warnings.simplefilter("always")
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temp_df = pd.read_excel(BytesIO(r.content))
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if len(temp_df) > 10:
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if symbol == "A股列表":
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temp_df["A股代码"] = (
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temp_df["A股代码"]
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.astype(str)
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.str.split(".", expand=True)
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.iloc[:, 0]
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.str.zfill(6)
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.str.replace("000nan", "")
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)
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temp_df = temp_df[
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[
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"板块",
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"A股代码",
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"A股简称",
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"A股上市日期",
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"A股总股本",
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"A股流通股本",
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"所属行业",
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]
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]
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elif symbol == "B股列表":
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temp_df["B股代码"] = (
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temp_df["B股代码"]
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.astype(str)
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.str.split(".", expand=True)
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.iloc[:, 0]
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.str.zfill(6)
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.str.replace("000nan", "")
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)
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temp_df = temp_df[
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[
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"板块",
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"B股代码",
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"B股简称",
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"B股上市日期",
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"B股总股本",
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"B股流通股本",
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"所属行业",
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]
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]
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elif symbol == "AB股列表":
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temp_df["A股代码"] = (
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temp_df["A股代码"]
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.astype(str)
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.str.split(".", expand=True)
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.iloc[:, 0]
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.str.zfill(6)
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.str.replace("000nan", "")
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)
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temp_df["B股代码"] = (
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temp_df["B股代码"]
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.astype(str)
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.str.split(".", expand=True)
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.iloc[:, 0]
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.str.zfill(6)
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.str.replace("000nan", "")
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)
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temp_df = temp_df[
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[
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"板块",
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"A股代码",
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"A股简称",
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"A股上市日期",
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"B股代码",
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"B股简称",
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"B股上市日期",
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"所属行业",
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]
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]
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return temp_df
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else:
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return temp_df
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@lru_cache()
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def stock_info_sh_name_code(symbol: str = "主板A股") -> pd.DataFrame:
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"""
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上海证券交易所-股票列表
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https://www.sse.com.cn/assortment/stock/list/share/
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:param symbol: choice of {"主板A股": "1", "主板B股": "2", "科创板": "8"}
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:type symbol: str
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:return: 指定 indicator 的数据
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:rtype: pandas.DataFrame
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"""
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indicator_map = {"主板A股": "1", "主板B股": "2", "科创板": "8"}
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url = "https://query.sse.com.cn/sseQuery/commonQuery.do"
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headers = {
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"Host": "query.sse.com.cn",
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"Pragma": "no-cache",
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"Referer": "https://www.sse.com.cn/assortment/stock/list/share/",
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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/81.0.4044.138 Safari/537.36",
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}
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params = {
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"STOCK_TYPE": indicator_map[symbol],
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"REG_PROVINCE": "",
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"CSRC_CODE": "",
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"STOCK_CODE": "",
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"sqlId": "COMMON_SSE_CP_GPJCTPZ_GPLB_GP_L",
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"COMPANY_STATUS": "2,4,5,7,8",
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"type": "inParams",
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"isPagination": "true",
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"pageHelp.cacheSize": "1",
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"pageHelp.beginPage": "1",
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"pageHelp.pageSize": "10000",
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"pageHelp.pageNo": "1",
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"pageHelp.endPage": "1",
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}
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r = requests.get(url, params=params, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["result"])
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col_stock_code = "B_STOCK_CODE" if symbol == "主板B股" else "A_STOCK_CODE"
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temp_df.rename(
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columns={
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col_stock_code: "证券代码",
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"SEC_NAME_CN": "证券简称",
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"SEC_NAME_FULL": "证券全称",
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"COMPANY_ABBR": "公司简称",
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"FULL_NAME": "公司全称",
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"LIST_DATE": "上市日期",
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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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"证券代码",
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"证券简称",
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"证券全称",
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"公司简称",
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"公司全称",
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"上市日期",
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]
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]
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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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return temp_df
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@lru_cache()
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def stock_info_bj_name_code() -> pd.DataFrame:
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"""
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北京证券交易所-股票列表
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https://www.bse.cn/nq/listedcompany.html
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:return: 股票列表
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:rtype: pandas.DataFrame
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"""
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url = "https://www.bse.cn/nqxxController/nqxxCnzq.do"
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payload = {
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"page": "0",
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"typejb": "T",
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"xxfcbj[]": "2",
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"xxzqdm": "",
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"sortfield": "xxzqdm",
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"sorttype": "asc",
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}
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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/110.0.0.0 Safari/537.36"
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}
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r = requests.post(url, data=payload, headers=headers)
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data_text = r.text
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data_json = json.loads(data_text[data_text.find("[") : -1])
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total_page = data_json[0]["totalPages"]
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big_df = pd.DataFrame()
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tqdm = get_tqdm()
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for page in tqdm(range(total_page), leave=False):
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payload.update({"page": page})
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r = requests.post(url, data=payload, headers=headers)
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data_text = r.text
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data_json = json.loads(data_text[data_text.find("[") : -1])
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temp_df = data_json[0]["content"]
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temp_df = pd.DataFrame(temp_df)
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big_df = pd.concat([big_df, temp_df], ignore_index=True)
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big_df.columns = [
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"上市日期",
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"-",
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"-",
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"-",
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"-",
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"-",
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"-",
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"-",
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"-",
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"-",
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"-",
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"流通股本",
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"-",
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"-",
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"-",
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"-",
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"-",
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"所属行业",
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"-",
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"-",
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"-",
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"-",
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"报告日期",
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"-",
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"-",
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"-",
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"-",
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"-",
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"-",
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"地区",
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"-",
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"-",
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"-",
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"-",
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"-",
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"券商",
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"总股本",
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"-",
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"证券代码",
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"-",
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"证券简称",
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"-",
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"-",
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"-",
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"-",
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"-",
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"-",
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"-",
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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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"总股本",
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"流通股本",
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"上市日期",
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"所属行业",
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"地区",
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"报告日期",
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]
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]
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big_df["报告日期"] = pd.to_datetime(big_df["报告日期"], errors="coerce").dt.date
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big_df["上市日期"] = pd.to_datetime(big_df["上市日期"], errors="coerce").dt.date
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return big_df
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def stock_info_sh_delist(symbol: str = "全部") -> pd.DataFrame:
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"""
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上海证券交易所-终止上市公司
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https://www.sse.com.cn/assortment/stock/list/delisting/
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:param symbol: choice of {"全部", "沪市", "科创板"}
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:type symbol: str
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:return: 终止上市公司
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:rtype: pandas.DataFrame
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"""
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symbol_map = {
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"全部": "1,2,8",
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"沪市": "1,2",
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"科创板": "8",
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}
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url = "https://query.sse.com.cn/commonQuery.do"
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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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"Connection": "keep-alive",
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"Host": "query.sse.com.cn",
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"Pragma": "no-cache",
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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/97.0.4692.71 Safari/537.36",
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}
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params = {
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"sqlId": "COMMON_SSE_CP_GPJCTPZ_GPLB_GP_L",
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"isPagination": "true",
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"STOCK_CODE": "",
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"CSRC_CODE": "",
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"REG_PROVINCE": "",
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"STOCK_TYPE": symbol_map[symbol],
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"COMPANY_STATUS": "3",
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"type": "inParams",
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"pageHelp.cacheSize": "1",
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"pageHelp.beginPage": "1",
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"pageHelp.pageSize": "500",
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"pageHelp.pageNo": "1",
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"pageHelp.endPage": "1",
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}
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r = requests.get(url, params=params, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["result"])
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temp_df.rename(
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columns={
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"COMPANY_ABBR": "公司简称",
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"DELIST_DATE": "暂停上市日期",
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"LIST_DATE": "上市日期",
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"COMPANY_CODE": "公司代码",
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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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"公司代码",
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"公司简称",
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"上市日期",
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"暂停上市日期",
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]
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]
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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["暂停上市日期"] = pd.to_datetime(
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temp_df["暂停上市日期"], errors="coerce"
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).dt.date
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return temp_df
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def stock_info_sz_delist(symbol: str = "终止上市公司") -> pd.DataFrame:
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"""
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深证证券交易所-暂停上市公司-终止上市公司
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https://www.szse.cn/market/stock/suspend/index.html
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:param symbol: choice of {"暂停上市公司", "终止上市公司"}
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:type symbol: str
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:return: 暂停上市公司 or 终止上市公司 的数据
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:rtype: pandas.DataFrame
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"""
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indicator_map = {"暂停上市公司": "tab1", "终止上市公司": "tab2"}
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url = "https://www.szse.cn/api/report/ShowReport"
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params = {
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"SHOWTYPE": "xlsx",
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"CATALOGID": "1793_ssgs",
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"TABKEY": indicator_map[symbol],
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"random": "0.6935816432433362",
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}
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r = requests.get(url, params=params)
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with warnings.catch_warnings(record=True):
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warnings.simplefilter("always")
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temp_df = pd.read_excel(BytesIO(r.content))
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if temp_df.empty:
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return pd.DataFrame()
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temp_df["证券代码"] = temp_df["证券代码"].astype("str").str.zfill(6)
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temp_df["上市日期"] = pd.to_datetime(temp_df["上市日期"]).dt.date
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temp_df["终止上市日期"] = pd.to_datetime(temp_df["终止上市日期"]).dt.date
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return temp_df
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def stock_info_sz_change_name(symbol: str = "全称变更") -> pd.DataFrame:
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"""
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深证证券交易所-市场数据-股票数据-名称变更
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https://www.szse.cn/www/market/stock/changename/index.html
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:param symbol: choice of {"全称变更": "tab1", "简称变更": "tab2"}
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:type symbol: str
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:return: 名称变更数据
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:rtype: pandas.DataFrame
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"""
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indicator_map = {"全称变更": "tab1", "简称变更": "tab2"}
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url = "https://www.szse.cn/api/report/ShowReport"
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params = {
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"SHOWTYPE": "xlsx",
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"CATALOGID": "SSGSGMXX",
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"TABKEY": indicator_map[symbol],
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"random": "0.6935816432433362",
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}
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r = requests.get(url, params=params)
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with warnings.catch_warnings(record=True):
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warnings.simplefilter("always")
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temp_df = pd.read_excel(BytesIO(r.content))
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temp_df["证券代码"] = temp_df["证券代码"].astype("str").str.zfill(6)
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temp_df["变更日期"] = pd.to_datetime(temp_df["变更日期"]).dt.date
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temp_df.sort_values(["变更日期"], inplace=True, ignore_index=True)
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return temp_df
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def stock_info_change_name(symbol: str = "000503") -> pd.DataFrame:
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"""
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新浪财经-股票曾用名
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https://vip.stock.finance.sina.com.cn/corp/go.php/vCI_CorpInfo/stockid/300378.phtml
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:param symbol: 股票代码
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:type symbol: str
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:return: 股票曾用名
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:rtype: list
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"""
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url = f"https://vip.stock.finance.sina.com.cn/corp/go.php/vCI_CorpInfo/stockid/{symbol}.phtml"
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r = requests.get(url)
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temp_df = pd.read_html(StringIO(r.text))[3].iloc[:, :2]
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temp_df.dropna(inplace=True)
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temp_df.columns = ["item", "value"]
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temp_df["item"] = temp_df["item"].str.split("：", expand=True)[0]
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try:
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name_list = (
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temp_df[temp_df["item"] == "证券简称更名历史"].value.tolist()[0].split(" ")
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)
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big_df = pd.DataFrame(name_list)
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big_df.reset_index(inplace=True)
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big_df["index"] = big_df.index + 1
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big_df.columns = ["index", "name"]
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return big_df
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except IndexError:
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return pd.DataFrame()
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@lru_cache()
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def stock_info_a_code_name() -> pd.DataFrame:
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"""
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沪深京 A 股列表
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:return: 沪深京 A 股数据
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:rtype: pandas.DataFrame
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"""
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big_df = pd.DataFrame()
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stock_sh = stock_info_sh_name_code(symbol="主板A股")
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stock_sh = stock_sh[["证券代码", "证券简称"]]
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stock_sz = stock_info_sz_name_code(symbol="A股列表")
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stock_sz["A股代码"] = stock_sz["A股代码"].astype(str).str.zfill(6)
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big_df = pd.concat(
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objs=[big_df, stock_sz[["A股代码", "A股简称"]]], ignore_index=True
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)
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big_df.columns = ["证券代码", "证券简称"]
|
||
|
||
stock_kcb = stock_info_sh_name_code(symbol="科创板")
|
||
stock_kcb = stock_kcb[["证券代码", "证券简称"]]
|
||
|
||
stock_bse = stock_info_bj_name_code()
|
||
stock_bse = stock_bse[["证券代码", "证券简称"]]
|
||
stock_bse.columns = ["证券代码", "证券简称"]
|
||
|
||
big_df = pd.concat(objs=[big_df, stock_sh], ignore_index=True)
|
||
big_df = pd.concat(objs=[big_df, stock_kcb], ignore_index=True)
|
||
big_df = pd.concat(objs=[big_df, stock_bse], ignore_index=True)
|
||
big_df.columns = ["code", "name"]
|
||
return big_df
|
||
|
||
|
||
if __name__ == "__main__":
|
||
stock_info_sh_name_code_df = stock_info_sh_name_code(symbol="主板A股")
|
||
print(stock_info_sh_name_code_df)
|
||
|
||
stock_info_sh_name_code_df = stock_info_sh_name_code(symbol="主板B股")
|
||
print(stock_info_sh_name_code_df)
|
||
|
||
stock_info_sh_name_code_df = stock_info_sh_name_code(symbol="科创板")
|
||
print(stock_info_sh_name_code_df)
|
||
|
||
stock_info_sz_name_code_df = stock_info_sz_name_code(symbol="A股列表")
|
||
print(stock_info_sz_name_code_df)
|
||
|
||
stock_info_sz_df = stock_info_sz_name_code(symbol="B股列表")
|
||
print(stock_info_sz_df)
|
||
|
||
stock_info_sz_df = stock_info_sz_name_code(symbol="AB股列表")
|
||
print(stock_info_sz_df)
|
||
|
||
stock_info_sz_df = stock_info_sz_name_code(symbol="CDR列表")
|
||
print(stock_info_sz_df)
|
||
|
||
stock_info_sh_delist_df = stock_info_sh_delist()
|
||
print(stock_info_sh_delist_df)
|
||
|
||
stock_info_sz_change_name_df = stock_info_sz_change_name(symbol="全称变更")
|
||
print(stock_info_sz_change_name_df)
|
||
|
||
stock_info_change_name_df = stock_info_change_name(symbol="000503")
|
||
print(stock_info_change_name_df)
|
||
|
||
stock_info_a_code_name_df = stock_info_a_code_name()
|
||
print(stock_info_a_code_name_df)
|
||
|
||
stock_info_bj_name_code_df = stock_info_bj_name_code()
|
||
print(stock_info_bj_name_code_df)
|
||
|
||
stock_info_sz_delist_df = stock_info_sz_delist(symbol="终止上市公司")
|
||
print(stock_info_sz_delist_df)
|
||
|
||
stock_info_sz_delist_df = stock_info_sz_delist(symbol="暂停上市公司")
|
||
print(stock_info_sz_delist_df)
|