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
69 lines
2.3 KiB
Python
69 lines
2.3 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2025/9/28 13:30
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Desc: 新浪财经-日内分时数据
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https://quote.eastmoney.com/f1.html?newcode=0.000001
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"""
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import math
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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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def stock_intraday_sina(
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symbol: str = "sz000001", date: str = "20240321"
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) -> pd.DataFrame:
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"""
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新浪财经-日内分时数据
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https://vip.stock.finance.sina.com.cn/quotes_service/view/cn_bill.php?symbol=sz000001
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:param symbol: 股票代码
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:type symbol: str
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:param date: 交易日
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:type date: str
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:return: 分时数据
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:rtype: pandas.DataFrame
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"""
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url = "https://vip.stock.finance.sina.com.cn/quotes_service/api/json_v2.php/CN_Bill.GetBillListCount"
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params = {
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"symbol": f"{symbol}",
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"num": "60",
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"page": "1",
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"sort": "ticktime",
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"asc": "0",
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"volume": "0",
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"amount": "0",
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"type": "0",
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"day": "-".join([date[:4], date[4:6], date[6:]]),
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}
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headers = {
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"Referer": f"https://vip.stock.finance.sina.com.cn/quotes_service/view/cn_bill.php?symbol={symbol}",
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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/107.0.0.0 Safari/537.36",
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}
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r = requests.get(url=url, params=params, headers=headers)
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data_json = r.json()
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total_page = math.ceil(int(data_json) / 60)
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url = "https://vip.stock.finance.sina.com.cn/quotes_service/api/json_v2.php/CN_Bill.GetBillList"
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big_df = pd.DataFrame()
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tqdm = get_tqdm()
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for page in tqdm(range(1, total_page + 1), leave=False):
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params.update({"page": page})
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r = requests.get(url=url, params=params, headers=headers)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json)
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big_df = pd.concat(objs=[big_df, temp_df], ignore_index=True)
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big_df.sort_values(by=["ticktime"], inplace=True, ignore_index=True)
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big_df["price"] = pd.to_numeric(big_df["price"], errors="coerce")
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big_df["volume"] = pd.to_numeric(big_df["volume"], errors="coerce")
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big_df["prev_price"] = pd.to_numeric(big_df["prev_price"], errors="coerce")
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return big_df
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if __name__ == "__main__":
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stock_intraday_sina_df = stock_intraday_sina(symbol="sz000001", date="20250926")
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print(stock_intraday_sina_df)
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