Update app.py

app.py

@@ -226,14 +226,17 @@ def validate_csv(df):
     Validate that the CSV has the required columns.
     Returns True if valid, False otherwise with an error message.
     """
+    # Strip whitespace from column names
+    df.columns = df.columns.str.strip()
     required_columns = ['device_id', 'usage_hours', 'amc_date', 'status']
     missing_columns = [col for col in required_columns if col not in df.columns]
     if missing_columns:
-        return False, f"Missing required columns: {', '.join(missing_columns)}"
+        return False, f"Missing required columns: {', '.join(missing_columns)}. Found columns: {', '.join(df.columns)}"
     # Validate data types
     try:
         df['usage_hours'] = pd.to_numeric(df['usage_hours'], errors='raise')
-        df['amc_date'] = pd.to_datetime(df['amc_date'], errors='raise')
+        # Parse amc_date with specified format
+        df['amc_date'] = pd.to_datetime(df['amc_date'], format='%d-%m-%Y', errors='raise')
         # Handle 'downtime' if present
         if 'downtime' in df.columns:
             df['downtime'] = pd.to_numeric(df['downtime'], errors='raise')
@@ -370,8 +373,10 @@ def process_files(uploaded_files):
     # Load and combine CSV files
     for file in valid_files:
         try:
-            df = pd.read_csv(file.name)
-            logging.info(f"Loaded {len(df)} records from {file.name}")
+            # Read CSV with explicit delimiter and strip whitespace
+            df = pd.read_csv(file.name, delimiter=',', skipinitialspace=True)
+            # Log the columns for debugging
+            logging.info(f"Columns in {file.name}: {', '.join(df.columns)}")
             # Rename columns to match expected names
             df = df.rename(columns={
                 'device_id': 'equipment',