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
76 lines
2.3 KiB
Python
76 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: 2025/3/10 18:00
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Desc: 东财财富-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 json
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import pandas as pd
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import requests
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def __event_stream(url, params):
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# 使用 stream=True 参数来启用流式请求
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response = requests.get(url, params=params, stream=True)
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event_data = ""
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for line in response.iter_lines():
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# 过滤掉保持连接的空行
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if line:
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event_data += line.decode() + "\n"
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elif event_data:
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yield event_data
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event_data = ""
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def stock_intraday_em(symbol: str = "000001") -> pd.DataFrame:
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"""
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东方财富-分时数据
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https://quote.eastmoney.com/f1.html?newcode=0.000001
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:param symbol: 股票代码
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:type symbol: 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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market_code = 1 if symbol.startswith("6") else 0
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url = "https://70.push2.eastmoney.com/api/qt/stock/details/sse"
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params = {
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"fields1": "f1,f2,f3,f4",
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"fields2": "f51,f52,f53,f54,f55",
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"mpi": "2000",
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"ut": "bd1d9ddb04089700cf9c27f6f7426281",
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"fltt": "2",
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"pos": "-0",
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"secid": f"{market_code}.{symbol}",
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"wbp2u": "|0|0|0|web",
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}
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big_df = pd.DataFrame() # 创建一个空的 DataFrame
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for event in __event_stream(url, params):
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# 从每个事件的数据行中删除 "data: "，然后解析 JSON
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event_json = json.loads(event.replace("data: ", ""))
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# 将 JSON 数据转换为 DataFrame，然后添加到主 DataFrame 中
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temp_df = pd.DataFrame(
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[item.split(",") for item in event_json["data"]["details"]]
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)
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big_df = pd.concat(objs=[big_df, temp_df], ignore_index=True)
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break
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big_df.columns = ["时间", "成交价", "手数", "-", "买卖盘性质"]
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big_df["买卖盘性质"] = big_df["买卖盘性质"].map(
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{"2": "买盘", "1": "卖盘", "4": "中性盘"}
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)
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big_df = big_df[["时间", "成交价", "手数", "买卖盘性质"]]
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big_df["成交价"] = pd.to_numeric(big_df["成交价"], errors="coerce")
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big_df["手数"] = pd.to_numeric(big_df["手数"], errors="coerce")
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return big_df
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if __name__ == "__main__":
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stock_intraday_em_df = stock_intraday_em(symbol="000001")
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print(stock_intraday_em_df)
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