过滤当天更新的指数并计算天和周cci

em_browser_state.json

@@ -1 +0,0 @@
-{"cookies": [{"name": "fullscreengg", "value": "1", "domain": ".eastmoney.com", "path": "/", "expires": -1, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "fullscreengg2", "value": "1", "domain": ".eastmoney.com", "path": "/", "expires": -1, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "qgqp_b_id", "value": "3998be81d9d8e920bf1a47e9d7b68329", "domain": ".eastmoney.com", "path": "/", "expires": 1796311917.296861, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "st_nvi", "value": "pcDSsW8vzKoZZ2lzT5Z2i07df", "domain": ".eastmoney.com", "path": "/", "expires": 1793287917, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "st_si", "value": "92630991205653", "domain": ".eastmoney.com", "path": "/", "expires": -1, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "st_pvi", "value": "92887489601905", "domain": ".eastmoney.com", "path": "/", "expires": 1796311917.368717, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "st_sp", "value": "2025-10-29%2023%3A31%3A57", "domain": ".eastmoney.com", "path": "/", "expires": 1796311917.369031, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "st_inirUrl", "value": "", "domain": ".eastmoney.com", "path": "/", "expires": 1796311917.369443, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "st_sn", "value": "1", "domain": ".eastmoney.com", "path": "/", "expires": -1, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "st_psi", "value": "20251029233157369-113200313003-0751845929", "domain": ".eastmoney.com", "path": "/", "expires": -1, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "st_asi", "value": "delete", "domain": ".eastmoney.com", "path": "/", "expires": -1, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "nid", "value": "03decfaee3d761b8ded27f8ee073dc4b", "domain": ".eastmoney.com", "path": "/", "expires": 1769527917, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "nid_create_time", "value": "1761751917950", "domain": ".eastmoney.com", "path": "/", "expires": 1769527917, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "gvi", "value": "ppXpL14DB48utbjDwaDu6785e", "domain": ".eastmoney.com", "path": "/", "expires": 1769527917, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "gvi_create_time", "value": "1761751917950", "domain": ".eastmoney.com", "path": "/", "expires": 1769527917, "httpOnly": false, "secure": false, "sameSite": "Lax"}, {"name": "wsc_checkuser_ok", "value": "1", "domain": ".eastmoney.com", "path": "/", "expires": -1, "httpOnly": false, "secure": false, "sameSite": "Lax"}], "origins": [{"origin": "https://quote.eastmoney.com", "localStorage": [{"name": "st_inirUrl", "value": ""}, {"name": "st_pvi", "value": "92887489601905"}, {"name": "st_sp", "value": "2025-10-29 23:31:57"}]}]}

em_index_sport.py

@@ -1,121 +0,0 @@
-import time
-from playwright.sync_api import sync_playwright
-from loguru import logger
-import datetime
-import re
-import json
-import pandas as pd
-
-
-def index_data_scraper(index_code: str, data_file_path: str):
-
-    with sync_playwright() as p:
-
-        def on_response(response):
-            if "push2.eastmoney.com/api/qt/clist/get" in response.url:
-                try:
-                    if response.request.failure is None and response.status == 200:
-                        data = response.text()
-                        # logger.info(f"最新数据: \n{data}")
-
-                        # 保存响应数据
-                        with open(data_file_path, "a", encoding="utf-8") as f:
-                            f.write(data)
-                            f.write("\n")
-                except Exception as e:
-                    logger.error(f"处理响应数据失败: {e}")
-
-        browser_state_file_path = "./em_browser_state.json"
-        browser = p.chromium.launch(args=["--start-maximized"], headless=True)
-        context = browser.new_context(
-            storage_state=browser_state_file_path, no_viewport=True
-        )
-        page = context.new_page()
-        page.on("response", on_response)
-        url = f"https://quote.eastmoney.com/center/gridlist.html#{index_code}"
-        page.goto(url)
-        # page.pause()
-        for i in range(1, 500):
-            logger.info(f"第{i}次点击")
-            try:
-                page.get_by_role("link", name=">", exact=True).click(timeout=30000)
-            except Exception as e:
-                break
-            time.sleep(30)
-
-
-def get_state():
-    with sync_playwright() as p:
-        browser_state_file_path = "./em_browser_state.json"
-        browser = p.chromium.launch(args=["--start-maximized"], headless=False)
-        page = browser.new_page()
-        url = f"https://quote.eastmoney.com/center/gridlist.html#index_sh"
-        page.goto(url)
-        page.pause()
-        browser.contexts[0].storage_state(path=browser_state_file_path)
-
-
-
-def parse_data(data_file_path: str):
-    df_list = []
-    with open(data_file_path, "r", encoding="utf-8") as f:
-        for line in f:
-            match = re.search(r"\((\{.*\})\);?$", line)
-            json_str = match.group(1)
-            data = json.loads(json_str)
-            inner_temp_df = pd.DataFrame(data["data"]["diff"])
-            df_list.append(inner_temp_df)
-    temp_df = pd.concat(df_list, ignore_index=True)
-    temp_df["f3"] = pd.to_numeric(temp_df["f3"], errors="coerce")
-    temp_df.sort_values(by=["f3"], ascending=False, inplace=True, ignore_index=True)
-    temp_df.reset_index(inplace=True)
-    temp_df["index"] = temp_df["index"].astype(int) + 1
-    col_name_map = {
-        "f12": "代码",
-        "f14": "名称",
-        "f2": "最新价",
-        "f3": "涨跌幅",
-        "f4": "涨跌额",
-        "f5": "成交量",
-        "f6": "成交额",
-        "f7": "振幅",
-        "f15": "最高",
-        "f16": "最低",
-        "f17": "今开",
-        "f18": "昨收",
-        "f10": "量比",
-    }
-    temp_df.rename(
-        columns=col_name_map,
-        inplace=True,
-    )
-    new_cols = col_name_map.values()
-    temp_df = temp_df[new_cols]
-    for col in new_cols:
-        if col in [
-            "代码",
-            "名称",
-        ]:
-            continue
-        temp_df[col] = pd.to_numeric(temp_df[col], errors="coerce")
-    return temp_df
-
-
-def get_index_latest_data():
-    today = datetime.datetime.now().strftime("%Y%m%d")
-    data_file_path = f"./{today}.txt"
-    index_code = "index_sh"
-    index_code_list = ["index_sh", "index_sz", "index_components", "index_zzzs"]
-    for index_code in index_code_list:
-        logger.info(f"开始更新指数数据: {index_code}")
-        index_data_scraper(index_code=index_code, data_file_path=data_file_path)
-    df = parse_data(data_file_path)
-    return df
-
-
-if __name__ == "__main__":
-    # df = get_index_latest_data()
-    # code = "000001"
-    # df = df[df["代码"] == code]
-    # print(df)
-    get_state()

signal_calc.py

@@ -70,6 +70,10 @@ def main_calc_process():
             continue
         # 将 'date' 列转换为 datetime 类型，并设置为索引
         df["date"] = pd.to_datetime(df["date"])
+        # 判断最新日期是否为今天，如果不是则跳过
+        today_str = datetime.now().strftime("%Y-%m-%d")
+        if df["date"].max().strftime("%Y-%m-%d") != today_str:
+            continue
         df = df.sort_values("date")
         df.set_index("date", inplace=True)
 
@@ -93,23 +97,40 @@ def main_calc_process():
             timeperiod=14,
         )
         df_weekly = df_weekly.tail(1)
-        cci = df_weekly["cci"].values[0]
+        week_cci = df_weekly["cci"].values[0]
-        logger.info(f"{i}/{len(code_list)}: {code} cci: {cci}")
+
+        df["cci"] = ta.CCI(
+            high=df["high"],
+            low=df["low"],
+            close=df["close"],
+            timeperiod=14,
+        )
+        cci = df["cci"].tail(1).values[0]
+        logger.info(f"{i}/{len(code_list)}: {code} week_cci: {week_cci} day_cci: {cci}")
         if cci < -100:
             signal_list.append(
-                {"code": code, "name": code_info["指数名称"], "cci": cci}
+                {
+                    "code": code,
+                    "name": code_info["指数名称"],
+                    "天cci": cci,
+                    "周cci": week_cci,
+                }
             )
             # break
     signal_df = pd.DataFrame(signal_list)
     # dingtalk.send_markdown(
     #     f"CCI信号", signal_df.to_markdown(tablefmt="simple", index=False)
     # )
-    dingtalk.send_text(
+    if len(signal_list) > 0:
-        tabulate(signal_df, tablefmt="plain", headers="keys", showindex=False)
+        dingtalk.send_text(
-    )
+            tabulate(signal_df, tablefmt="plain", headers="keys", showindex=False)
+        )
+    else:
+        logger.info("无信号")
 
 
 if __name__ == "__main__":
+    # main_calc_process()
     ...
     # main()
     # logger.info(datetime.now())

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"
+    df = ak.stock_zh_index_spot_sina()
-    # )
-    # 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()
     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")
+    df["date"] = cur_date
-    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.dropna(how="any", inplace=True)
     # df.to_csv(f"aaaa.csv", index=False, encoding="utf-8-sig")
     return df