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
152 lines
4.9 KiB
Python
152 lines
4.9 KiB
Python
#!/usr/bin/env python
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# -*- coding:utf-8 -*-
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"""
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Date: 2025/3/9 23:00
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Desc: 东方财富网-行情中心-沪深港通
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https://quote.eastmoney.com/center/gridlist.html#ah_comparison
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"""
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import pandas as pd
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from akshare.utils.func import fetch_paginated_data
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def stock_zh_ah_spot_em() -> pd.DataFrame:
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"""
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东方财富网-行情中心-沪深港通-AH股比价-实时行情
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https://quote.eastmoney.com/center/gridlist.html#ah_comparison
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:return: 东方财富网-行情中心-沪深港通-AH股比价-实时行情
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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": "1",
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"fltt": "1",
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"invt": "2",
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"fs": "b:DLMK0101",
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"fields": "f193,f191,f192,f12,f13,f14,f1,f2,f4,f3,f152,f186,f190,f187,f189,f188",
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"fid": "f3",
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"pn": "1",
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"pz": "100",
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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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temp_df = fetch_paginated_data(url, params)
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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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"f193": "名称",
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"f12": "H股代码",
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"f2": "最新价-HKD",
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"f3": "H股-涨跌幅",
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"f191": "A股代码",
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"f186": "最新价-RMB",
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"f187": "A股-涨跌幅",
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"f189": "比价",
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"f188": "溢价",
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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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"名称",
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"H股代码",
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"最新价-HKD",
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"H股-涨跌幅",
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"A股代码",
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"最新价-RMB",
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"A股-涨跌幅",
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"比价",
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"溢价",
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]
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]
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temp_df["最新价-HKD"] = pd.to_numeric(temp_df["最新价-HKD"], errors="coerce") / 1000
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temp_df["H股-涨跌幅"] = pd.to_numeric(temp_df["H股-涨跌幅"], errors="coerce") / 100
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temp_df["最新价-RMB"] = pd.to_numeric(temp_df["最新价-RMB"], errors="coerce") / 100
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temp_df["A股-涨跌幅"] = pd.to_numeric(temp_df["A股-涨跌幅"], errors="coerce") / 100
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temp_df["比价"] = pd.to_numeric(temp_df["比价"], errors="coerce") / 100
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temp_df["溢价"] = pd.to_numeric(temp_df["溢价"], errors="coerce") / 100
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return temp_df
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def stock_hsgt_sh_hk_spot_em() -> pd.DataFrame:
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"""
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东方财富网-行情中心-沪深港通-港股通(沪>港)-股票
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https://quote.eastmoney.com/center/gridlist.html#hk_sh_stocks
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:return: 东方财富网-行情中心-沪深港通-港股通(沪>港)-股票
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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": "1",
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"fltt": "1",
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"invt": "2",
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"fs": "b:DLMK0144",
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"fields": "f12,f13,f14,f19,f1,f2,f4,f3,f152,f17,f18,f15,f16,f5,f6",
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"fid": "f12",
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"pn": "1",
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"pz": "100",
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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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temp_df = fetch_paginated_data(url, params)
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temp_df.rename(
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columns={
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"f12": "代码",
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"f14": "名称",
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"f2": "最新价",
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"f4": "涨跌额",
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"f3": "涨跌幅",
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"f17": "今开",
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"f15": "最高",
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"f16": "最低",
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"f18": "昨收",
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"f5": "成交量",
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"f6": "成交额",
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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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"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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"今开",
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"最高",
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"最低",
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"昨收",
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"成交量",
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"成交额",
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]
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]
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temp_df["最新价"] = pd.to_numeric(temp_df["最新价"], errors="coerce") / 1000
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temp_df["涨跌额"] = pd.to_numeric(temp_df["涨跌额"], errors="coerce") / 1000
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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["今开"] = pd.to_numeric(temp_df["今开"], errors="coerce") / 1000
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temp_df["最高"] = pd.to_numeric(temp_df["最高"], errors="coerce") / 1000
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temp_df["最低"] = pd.to_numeric(temp_df["最低"], errors="coerce") / 1000
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temp_df["昨收"] = pd.to_numeric(temp_df["昨收"], errors="coerce") / 1000
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temp_df["成交量"] = pd.to_numeric(temp_df["成交量"], errors="coerce") / 100000000
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temp_df["成交额"] = pd.to_numeric(temp_df["成交额"], errors="coerce") / 100000000
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temp_df.sort_values(["代码"], ignore_index=True, inplace=True)
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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(columns={"index": "序号"}, inplace=True)
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return temp_df
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if __name__ == "__main__":
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stock_zh_ah_spot_em_df = stock_zh_ah_spot_em()
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print(stock_zh_ah_spot_em_df)
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stock_hsgt_sh_hk_spot_em_df = stock_hsgt_sh_hk_spot_em()
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print(stock_hsgt_sh_hk_spot_em_df)
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