diff --git a/chart.py b/chart.py
index 6314f02..cffd920 100644
--- a/chart.py
+++ b/chart.py
@@ -1,5 +1,5 @@
 import pandas as pd
-from db_config import DatabaseManager, DatabaseConfig
+
 from loguru import logger
 import talib as ta
 import numpy as np
@@ -30,7 +30,7 @@ def get_fixed_color_based_on_period(period):
 
 
 def add_ema(df, chart, period: int = 50):
-    name = f"EMA {period}"
+    name = f"EMA_{period}"
     df[name] = ta.EMA(df["close"], timeperiod=period)
     color = get_fixed_color_based_on_period(period)
     line = chart.create_line(
@@ -206,29 +206,6 @@ def add_buy_sell_signal_markers(df, chart):
     chart.marker_list(markers)
 
 
-def get_kline(code: str) -> list:
-    """
-    获取所有指数代码
-    :return:
-    """
-    env = "online"
-    env = "daily"
-    db_config = DatabaseConfig(env=env)
-    logger.info(f"数据库连接: {db_config.connection_string}")
-
-    db_manager = DatabaseManager(db_config)
-    sql = f"SELECT date as time, open, high, low, close, volume FROM public.index_kline where code='{code}' order by date;"
-    res = db_manager.execute_query(sql)
-    data_list = [dict(item) for item in res]
-    df = pd.DataFrame(data_list)
-    df["time"] = pd.to_datetime(df["time"])
-    num_cols = ["open", "high", "low", "close", "volume"]
-    for col in num_cols:
-        if col in df.columns:
-            df[col] = pd.to_numeric(df[col], errors="coerce").astype(float)
-    return df
-
-
 def resample_data(df: pd.DataFrame, timeframe: str) -> pd.DataFrame:
     """
     对日线数据进行重采样
@@ -372,10 +349,10 @@ def plot_chart(df, symbol: str, name: str, timeframe: str):
 
     chart.set(df)
     chart.events.range_change += on_range_change_poc
-    add_ema(df, chart, period=10)
-    add_ema(df, chart, period=20)
+    # add_ema(df, chart, period=10)
+    # add_ema(df, chart, period=20)
     add_ema(df, chart, period=30)
-    add_ema(df, chart, period=60)
+    # add_ema(df, chart, period=60)
     add_macd(df, chart)
     add_cci(df, chart, period=14)
     add_TD(df, chart)
@@ -385,17 +362,4 @@ def plot_chart(df, symbol: str, name: str, timeframe: str):
 
 
 if __name__ == "__main__":
-    symbol = "399998"
-    timeframe = "1W"
-
-    df = pd.read_csv(
-        "/Users/aszer/Documents/vscode/etf/data/index_all_stock.csv",
-        encoding="utf-8-sig",
-    )
-    name = df.loc[df["代码"] == symbol, "名称"].values[0]
-
-    df = get_kline(code=symbol)
-    df = resample_data(df, timeframe)
-    # df['buy'] = df['time'].apply(lambda x: 1 if pd.to_datetime(x).day % 2 == 1 else 0)
-    # df['sell'] = df['time'].apply(lambda x: 1 if pd.to_datetime(x).day % 2 == 0 else 0)
-    plot_chart(df=df, symbol=symbol, name=name, timeframe=timeframe)
+    ...