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
168 lines
5.8 KiB
Python
168 lines
5.8 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2025/3/7 17:00
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Desc: 东方财富网-行情中心-全球指数
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https://quote.eastmoney.com/center/gridlist.html#global_qtzs
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"""
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import pandas as pd
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import requests
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from akshare.index.cons import index_global_em_symbol_map
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def index_global_spot_em() -> pd.DataFrame:
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"""
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东方财富网-行情中心-全球指数-实时行情数据
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https://quote.eastmoney.com/center/gridlist.html#global_qtzs
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:return: 实时行情数据
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:rtype: pandas.DataFrame
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"""
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url = "https://push2.eastmoney.com/api/qt/clist/get"
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params = {
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"np": "2",
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"fltt": "1",
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"invt": "2",
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"fs": "i:1.000001,i:0.399001,i:0.399005,i:0.399006,i:1.000300,i:100.HSI,i:100.HSCEI,i:124.HSCCI,"
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"i:100.TWII,i:100.N225,i:100.KOSPI200,i:100.KS11,i:100.STI,i:100.SENSEX,i:100.KLSE,i:100.SET,"
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"i:100.PSI,i:100.KSE100,i:100.VNINDEX,i:100.JKSE,i:100.CSEALL,i:100.SX5E,i:100.FTSE,i:100.MCX,"
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"i:100.AXX,i:100.FCHI,i:100.GDAXI,i:100.RTS,i:100.IBEX,i:100.PSI20,i:100.OMXC20,i:100.BFX,"
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"i:100.AEX,i:100.WIG,i:100.OMXSPI,i:100.SSMI,i:100.HEX,i:100.OSEBX,i:100.ATX,i:100.MIB,"
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"i:100.ASE,i:100.ICEXI,i:100.PX,i:100.ISEQ,i:100.DJIA,i:100.SPX,i:100.NDX,i:100.TSX,"
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"i:100.BVSP,i:100.MXX,i:100.AS51,i:100.AORD,i:100.NZ50,i:100.UDI,i:100.BDI,i:100.CRB",
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"fields": "f12,f13,f14,f292,f1,f2,f4,f3,f152,f17,f18,f15,f16,f7,f124",
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"fid": "f3",
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"pn": "1",
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"pz": "200",
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"po": "1",
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"dect": "1",
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"wbp2u": "|0|0|0|web",
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}
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r = requests.get(url=url, params=params)
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data_json = r.json()
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temp_df = pd.DataFrame(data_json["data"]["diff"]).T
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temp_df.reset_index(inplace=True)
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temp_df["index"] = temp_df["index"].astype(int) + 1
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temp_df.rename(
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columns={
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"index": "序号",
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"f12": "代码",
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"f14": "名称",
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"f17": "开盘价",
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"f4": "涨跌额",
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"f3": "涨跌幅",
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"f2": "最新价",
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"f15": "最高价",
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"f16": "最低价",
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"f18": "昨收价",
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"f7": "振幅",
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"f124": "最新行情时间",
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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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"序号",
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"代码",
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"名称",
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"最新价",
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"涨跌额",
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"涨跌幅",
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"开盘价",
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"最高价",
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"最低价",
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"昨收价",
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"振幅",
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"最新行情时间",
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]
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]
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temp_df["最新行情时间"] = pd.to_datetime(
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temp_df["最新行情时间"], unit="s", utc=True, errors="coerce"
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).dt.tz_convert("Asia/Shanghai")
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temp_df["最新行情时间"] = temp_df["最新行情时间"].dt.strftime("%Y-%m-%d %H:%M:%S")
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temp_df["最新价"] = pd.to_numeric(temp_df["最新价"], errors="coerce") / 100
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temp_df["涨跌额"] = pd.to_numeric(temp_df["涨跌额"], errors="coerce") / 100
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temp_df["涨跌幅"] = pd.to_numeric(temp_df["涨跌幅"], errors="coerce") / 100
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temp_df["开盘价"] = pd.to_numeric(temp_df["开盘价"], errors="coerce") / 100
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temp_df["最高价"] = pd.to_numeric(temp_df["最高价"], errors="coerce") / 100
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temp_df["最低价"] = pd.to_numeric(temp_df["最低价"], errors="coerce") / 100
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temp_df["昨收价"] = pd.to_numeric(temp_df["昨收价"], errors="coerce") / 100
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temp_df["振幅"] = pd.to_numeric(temp_df["振幅"], errors="coerce") / 100
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return temp_df
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def index_global_hist_em(symbol: str = "美元指数") -> pd.DataFrame:
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"""
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东方财富网-行情中心-全球指数-历史行情数据
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https://quote.eastmoney.com/gb/zsUDI.html
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:param symbol: 指数名称；可以通过 ak.index_global_spot_em() 获取
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:type symbol: str
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:return: 历史行情数据
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:rtype: pandas.DataFrame
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"""
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url = "https://push2his.eastmoney.com/api/qt/stock/kline/get"
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params = {
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"secid": f"{index_global_em_symbol_map[symbol]['market']}.{index_global_em_symbol_map[symbol]['code']}",
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"klt": "101",
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"fqt": "1",
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"lmt": "50000",
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"end": "20500000",
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"iscca": "1",
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"fields1": "f1,f2,f3,f4,f5,f6,f7,f8",
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"fields2": "f51,f52,f53,f54,f55,f56,f57,f58,f59,f60,f61,f62,f63,f64",
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"ut": "f057cbcbce2a86e2866ab8877db1d059",
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"forcect": "1",
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}
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r = requests.get(url=url, params=params)
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data_json = r.json()
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temp_df = pd.DataFrame([item.split(",") for item in data_json["data"]["klines"]])
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temp_df["code"] = data_json["data"]["code"]
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temp_df["name"] = data_json["data"]["name"]
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temp_df.columns = [
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"日期",
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"今开",
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"最新价",
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"最高",
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"最低",
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"-",
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"-",
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"振幅",
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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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"代码",
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"名称",
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]
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temp_df = temp_df[
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[
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"日期",
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"代码",
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"名称",
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"今开",
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"最新价",
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"最高",
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"最低",
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"振幅",
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]
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]
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temp_df["日期"] = pd.to_datetime(temp_df["日期"], errors="coerce").dt.date
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temp_df["今开"] = pd.to_numeric(temp_df["今开"], errors="coerce")
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temp_df["最新价"] = pd.to_numeric(temp_df["最新价"], errors="coerce")
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temp_df["最高"] = pd.to_numeric(temp_df["最高"], errors="coerce")
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temp_df["最低"] = pd.to_numeric(temp_df["最低"], errors="coerce")
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temp_df["振幅"] = pd.to_numeric(temp_df["振幅"], errors="coerce")
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return temp_df
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if __name__ == "__main__":
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index_global_spot_em_df = index_global_spot_em()
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print(index_global_spot_em_df)
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index_global_hist_em_df = index_global_hist_em(symbol="美元指数")
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print(index_global_hist_em_df)
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