Create indicater.py

indicater.py

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+# indicater.py
+import pandas as pd
+import numpy as np
+import talib as ta
+
+# -------------------------------
+# CUSTOM INDICATOR FUNCTIONS
+# -------------------------------
+
+def supertrend(df, period=10, multiplier=3):
+    """
+    Simple SuperTrend calculation.
+    Returns a Series aligned with df.index
+    """
+    atr = ta.ATR(df['High'], df['Low'], df['Close'], timeperiod=period)
+    hl2 = (df['High'] + df['Low']) / 2
+    final_upperband = hl2 + multiplier * atr
+    final_lowerband = hl2 - multiplier * atr
+
+    st = pd.Series(index=df.index, dtype=float)
+    trend = True
+    for i in range(1, len(df)):
+        if df['Close'].iloc[i] > final_upperband.iloc[i-1]:
+            trend = True
+        elif df['Close'].iloc[i] < final_lowerband.iloc[i-1]:
+            trend = False
+        st.iloc[i] = final_lowerband.iloc[i] if trend else final_upperband.iloc[i]
+    return st
+
+# -------------------------------
+# MAIN INDICATOR FUNCTION
+# -------------------------------
+
+def calculate_indicators(df):
+    """
+    df: DataFrame with columns ['Open','High','Low','Close','Volume']
+    Returns dict of indicator DataFrames or Series
+    """
+    indicators = {}
+
+    if 'Close' in df.columns:
+        # Moving averages on main chart
+        indicators['SMA20'] = ta.SMA(df['Close'], timeperiod=20)
+        indicators['SMA50'] = ta.SMA(df['Close'], timeperiod=50)
+        indicators['EMA20'] = ta.EMA(df['Close'], timeperiod=20)
+        indicators['EMA50'] = ta.EMA(df['Close'], timeperiod=50)
+
+        # MACD as sub-plot
+        macd, macdsignal, macdhist = ta.MACD(df['Close'], fastperiod=12, slowperiod=26, signalperiod=9)
+        indicators['MACD'] = pd.DataFrame({'MACD': macd, 'Signal': macdsignal, 'Hist': macdhist}, index=df.index)
+
+        # Bollinger Bands
+        upper, middle, lower = ta.BBANDS(df['Close'], timeperiod=20)
+        indicators['Bollinger'] = pd.DataFrame({'Upper': upper, 'Middle': middle, 'Lower': lower}, index=df.index)
+
+    # SuperTrend requires High, Low, Close
+    if all(x in df.columns for x in ['High', 'Low', 'Close']):
+        indicators['SuperTrend'] = supertrend(df)
+
+    return indicators