base version only KD indicator with jpm, ft yahoo as sources

import.py

@@ -0,0 +1,41 @@
+import pandas as pd
+import os
+
+def import_history(source_file, symbol):
+    """
+    source_file: path to your historical data (Excel or CSV)
+    symbol: The symbol name matching your instruments.csv (e.g., 'AGI_USD')
+    """
+    cache_dir = "data_cache"
+    os.makedirs(cache_dir, exist_ok=True)
+    target_path = os.path.join(cache_dir, f"{symbol}.csv")
+
+    try:
+        # Load your data
+        if source_file.endswith('.xlsx'):
+            df = pd.read_excel(source_file)
+        else:
+            df = pd.read_csv(source_file)
+
+        # 1. Standardize columns: We need 'date' and 'close'
+        # Adjust these strings if your Excel uses different names like 'Price' or 'Date'
+        df.columns = [c.lower().strip() for c in df.columns]
+        
+        # If your Excel has columns named 'nav' or 'price', rename them
+        rename_map = {'price': 'close', 'nav': 'close', 'valuation date': 'date'}
+        df = df.rename(columns=rename_map)
+
+        # 2. Convert to proper format
+        df['date'] = pd.to_datetime(df['date']).dt.strftime('%Y-%m-%d')
+        df = df[['date', 'close']].dropna().sort_values('date')
+
+        # 3. Save to the cache folder
+        df.to_csv(target_path, index=False)
+        print(f"✅ Successfully created cache for {symbol} at {target_path}")
+        print(f"📊 Rows imported: {len(df)}")
+
+    except Exception as e:
+        print(f"❌ Error importing {symbol}: {e}")
+
+# EXAMPLE USAGE:
+# import_history('my_old_data.xlsx', 'AGI_USD')