修改排版，加入up，down，flat，unknown显示

TF_DF.py

@@ -56,6 +56,10 @@ class TF_DF():
 				return None
 			return float(ema24_value)
 		return None
+	def get_current_klc(self):
+		if len(self.klc_list) > 0:
+			return self.klc_list[-2]
+		return None
 	def add_indicators(self, df):
 		fast = 12
 		slow = 26
@@ -93,14 +97,33 @@ class TF_DF():
 		df['macd'] = macd['macd']
 		df['macdsignal'] = macd['macdsignal']
 		df['macdhist'] = macd['macdhist']
-		df['ema5'] = ta.EMA(df, timeperiod=5)
-		df['ema10'] = ta.EMA(df, timeperiod=10)
-		df['ema24'] = ta.EMA(df, timeperiod=24)
-		df['ema26'] = ta.EMA(df, timeperiod=26)
-		df['ema52'] = ta.EMA(df, timeperiod=52)
+		df['ema5'] = self.cal_ema(df, 5)
+		df['ema10'] = self.cal_ema(df, 10)
+		df['ema24'] = self.cal_ema(df, 24)
+		df['ema26'] = self.cal_ema(df, 26)
+		df['ema52'] = self.cal_ema(df, 52)
 		df['rsi'] = ta.RSI(df, timeperiod=14)
 		df['volume_ratio'] = self.cal_volume_ratio(df)
 		return df
+	@staticmethod
+	def cal_ema(df, timeperiod):
+		"""
+		计算 EMA，优先使用 pandas ewm(adjust=False) 以贴近前端/TradingView 显示；
+		必要时回退到 TA-Lib（abstract）。
+		"""
+		try:
+			series = df['close'].astype(float) if isinstance(df, pd.DataFrame) else pd.Series(df).astype(float)
+			return series.ewm(span=int(timeperiod), adjust=False).mean()
+		except Exception:
+			try:
+				if isinstance(df, pd.DataFrame):
+					return ta.EMA(df, timeperiod=int(timeperiod))
+			except Exception:
+				pass
+			# 最后回退：返回同索引的 NaN 序列
+			if isinstance(df, pd.DataFrame) and 'close' in df:
+				return pd.Series(np.nan, index=df.index)
+			return pd.Series(dtype=float)
 	def check_fx(self, klc):
 		if klc.pre and klc.next:
 			if klc.high > klc.pre.high and klc.high > klc.next.high: