Update app.py

app.py

@@ -17,28 +17,52 @@ def fetch_binance_data(symbol, timeframe, limit=2000):
     df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
     return df
 
+# def fetch_yfinance_data(pair: str, period: str, interval: str) -> pd.DataFrame:
+#     """
+#     pair: e.g. "BCH/USDT" or "BTC/USDT"
+#     period: e.g. "100d"
+#     interval: e.g. "1d", "60m", "90m", "1h"
+#     """
+#     # Yahoo uses e.g. "BCH-USD" for BCH/USDT
+#     ticker = pair.replace("/USDT", "-USD")
+#     df = yf.download(ticker, period=period, interval=interval)
+#     df = df.reset_index().rename(columns={
+#         'Datetime':  'timestamp',
+#         'Date':      'timestamp',
+#         'Open':      'open',
+#         'High':      'high',
+#         'Low':       'low',
+#         'Close':     'close',
+#         'Volume':    'volume'
+#     })
+#     # ensure we have a timestamp column in datetime
+#     df['timestamp'] = pd.to_datetime(df['timestamp'])
+#     return df
+
 def fetch_yfinance_data(pair: str, period: str, interval: str) -> pd.DataFrame:
     """
-    pair: e.g. "BCH/USDT" or "BTC/USDT"
+    pair: e.g. "BCH/USDT"
     period: e.g. "100d"
-    interval: e.g. "1d", "60m", "90m", "1h"
+    interval: e.g. "1d", "1h", "4h"
     """
-    # Yahoo uses e.g. "BCH-USD" for BCH/USDT
     ticker = pair.replace("/USDT", "-USD")
     df = yf.download(ticker, period=period, interval=interval)
-    df = df.reset_index().rename(columns={
-        'Datetime':  'timestamp',
-        'Date':      'timestamp',
-        'Open':      'open',
-        'High':      'high',
-        'Low':       'low',
-        'Close':     'close',
-        'Volume':    'volume'
-    })
-    # ensure we have a timestamp column in datetime
-    df['timestamp'] = pd.to_datetime(df['timestamp'])
-    return df
 
+    # bring the DateTimeIndex into a column, whatever its name was
+    df = df.reset_index()
+    df.rename(columns={df.columns[0]: 'timestamp'}, inplace=True)
+
+    # standardize OHLCV
+    df.rename(columns={
+        'Open':   'open',
+        'High':   'high',
+        'Low':    'low',
+        'Close':  'close',
+        'Volume': 'volume'
+    }, inplace=True)
+
+    return df
+    
 # Rolling Window Normalizer
 class RollingWindowNormalizer:
     def __init__(self, window=24):