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
83 lines
2.4 KiB
Python
83 lines
2.4 KiB
Python
#!/usr/bin/env python
|
|
# -*- coding:utf-8 -*-
|
|
"""
|
|
Date: 2025/3/7 17:00
|
|
Desc: 新浪财经-行情中心-环球市场
|
|
https://finance.sina.com.cn/stock/globalindex/quotes/UKX
|
|
"""
|
|
|
|
import pandas as pd
|
|
import requests
|
|
|
|
from akshare.index.cons import index_global_sina_symbol_map
|
|
|
|
|
|
def index_global_name_table() -> pd.DataFrame:
|
|
"""
|
|
新浪财经-行情中心-环球市场-名称代码映射表
|
|
https://finance.sina.com.cn/stock/globalindex/quotes/UKX
|
|
:return: 名称代码映射表
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
temp_df = pd.DataFrame.from_dict(
|
|
index_global_sina_symbol_map, orient="index", columns=["代码"]
|
|
)
|
|
temp_df.index.name = "指数名称"
|
|
temp_df.reset_index(inplace=True)
|
|
return temp_df
|
|
|
|
|
|
def index_global_hist_sina(symbol: str = "OMX") -> pd.DataFrame:
|
|
"""
|
|
新浪财经-行情中心-环球市场-历史行情
|
|
https://finance.sina.com.cn/stock/globalindex/quotes/UKX
|
|
:param symbol: 指数名称；可以通过 ak.index_global_name_table() 获取
|
|
:type symbol: str
|
|
:return: 环球市场历史行情
|
|
:rtype: pandas.DataFrame
|
|
"""
|
|
url = "https://gi.finance.sina.com.cn/hq/daily"
|
|
params = {
|
|
"symbol": index_global_sina_symbol_map[symbol],
|
|
"num": "10000",
|
|
}
|
|
r = requests.get(url=url, params=params)
|
|
data_json = r.json()
|
|
temp_df = pd.DataFrame(data_json["result"]["data"])
|
|
temp_df.rename(
|
|
columns={
|
|
"d": "date",
|
|
"o": "open",
|
|
"h": "high",
|
|
"l": "low",
|
|
"c": "close",
|
|
"v": "volume",
|
|
},
|
|
inplace=True,
|
|
)
|
|
temp_df = temp_df[
|
|
[
|
|
"date",
|
|
"open",
|
|
"high",
|
|
"low",
|
|
"close",
|
|
"volume",
|
|
]
|
|
]
|
|
temp_df["date"] = pd.to_datetime(temp_df["date"], errors="coerce").dt.date
|
|
temp_df["open"] = pd.to_numeric(temp_df["open"], errors="coerce")
|
|
temp_df["high"] = pd.to_numeric(temp_df["high"], errors="coerce")
|
|
temp_df["low"] = pd.to_numeric(temp_df["low"], errors="coerce")
|
|
temp_df["close"] = pd.to_numeric(temp_df["close"], errors="coerce")
|
|
temp_df["volume"] = pd.to_numeric(temp_df["volume"], errors="coerce")
|
|
return temp_df
|
|
|
|
|
|
if __name__ == "__main__":
|
|
index_global_name_table_df = index_global_name_table()
|
|
print(index_global_name_table_df)
|
|
|
|
index_global_hist_sina_df = index_global_hist_sina(symbol="瑞士股票指数")
|
|
print(index_global_hist_sina_df)
|