From f0205ec14669b36132ba37a080b8aa0dde22198b Mon Sep 17 00:00:00 2001
From: aszerW <aszer27937@gmail.com>
Date: Thu, 30 Oct 2025 21:55:14 +0800
Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E6=94=B9=E4=B8=BA=E4=BD=BF=E7=94=A8?=
 =?UTF-8?q?=E6=96=B0=E6=B5=AA=E8=B4=A2=E7=BB=8F=E6=95=B0=E6=8D=AE=20https:?=
 =?UTF-8?q?//vip.stock.finance.sina.com.cn/mkt/#hs=5Fs?=
MIME-Version: 1.0
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---
 update_data.py | 53 +++++---------------------------------------------
 1 file changed, 5 insertions(+), 48 deletions(-)

diff --git a/update_data.py b/update_data.py
index 875cd09..2aab544 100644
--- a/update_data.py
+++ b/update_data.py
@@ -3,8 +3,7 @@ from db_config import DatabaseManager, DatabaseConfig
 from loguru import logger
 from datetime import datetime
 import akshare as ak
-from index_downloader import get_all_stock_index
-from em_index_sport import get_index_latest_data
+
 import schedule
 import time
 import traceback
@@ -19,28 +18,10 @@ secret = "SEC43a0fa0b29717f98637a119b92a0bd5f7b2b6da671bdd2bd1279ed8323454d5e"
 dingtalk = DingTalkBot(webhook, secret)
 
 
-def set_proxy():
-    url = "http://v2.api.juliangip.com/company/postpay/getips?auto_white=1&num=1&pt=1&result_type=json&trade_no=6735165951220899&sign=bd763049a68b4b817608520dad35ea25"
-    r = requests.get(url)
-    data = r.json()
-    logger.info(data)
-    proxy = data["data"]["proxy_list"][0]
-    os.environ["https_proxy"] = f"http://{proxy}"
-    os.environ["http_proxy"] = f"http://{proxy}"
 
-
-@retry(tries=3, delay=10)
 def get_latest_index_kline_date():
-    # df = pd.read_csv(
-    #     "/Users/aszer/Documents/vscode/etf/index_all_stock.csv", encoding="utf-8-sig"
-    # )
-    # index_hist_df = pd.read_csv(
-    #     "/Users/aszer/Documents/vscode/etf/data/index_history_data/000001.csv",
-    #     encoding="utf-8-sig",
-    # )
-    set_proxy()
-    df = get_all_stock_index()
-    # df = get_index_latest_data()
+
+    df = ak.stock_zh_index_spot_sina()
     column_mapping = {
         "date": "date",
         "代码": "code",
@@ -50,37 +31,13 @@ def get_latest_index_kline_date():
         "最新价": "close",
         "成交量": "volume",
     }
-
     df["date"] = None
     df = df.rename(columns=column_mapping)
+    df['code'] = df['code'].str.extract(r'(\d+)')[0]
     df = df[column_mapping.values()]
     df = df.drop_duplicates(subset=["code"])
-
-    # 获取上证指数最近30天的数据
-    code = "000001"  # 用来获取当前最新k线数据的日期，参考 上证指数
-    latest = df[df["code"] == code].to_dict(orient="records")[0]
-    h, l, o, c = latest["high"], latest["low"], latest["open"], latest["close"]
     cur_date = datetime.now().strftime("%Y%m%d")
-    seven_days_ago = (datetime.now() - pd.Timedelta(days=30)).strftime("%Y%m%d")
-    index_hist_df = ak.index_zh_a_hist(
-        symbol=code,
-        period="daily",
-        start_date=seven_days_ago,
-        end_date=cur_date,
-    )
-
-    index_hist_df = index_hist_df.sort_values(
-        by="日期", ascending=False
-    )  # 按时间降序排列
-    index_hist_df = index_hist_df[
-        (index_hist_df["最高"] == h)
-        & (index_hist_df["最低"] == l)
-        & (index_hist_df["开盘"] == o)
-        & (index_hist_df["收盘"] == c)
-    ]
-    index_hist = index_hist_df.to_dict(orient="records")[0]
-    hist_date = index_hist["日期"]
-    df["date"] = hist_date
+    df["date"] = cur_date
     df.dropna(how="any", inplace=True)
     # df.to_csv(f"aaaa.csv", index=False, encoding="utf-8-sig")
     return df