app/app.py

@@ -11,8 +11,8 @@ app.config['SESSION_TYPE'] = 'filesystem'
 app.config['SESSION_FILE_DIR'] = './.flask_session/'
 Session(app)
 
-STRIPE_STARTING_COLS = ['Type', 'ID', 'Created', 'Description', 'Amount', 'Currency', 'Converted Amount']
-RAISENOW_STARTING_COLS = ['Identifikationsnummer', 'Erstellt', 'UTC-Offset', 'Status', 'Betrag', 'Währung']
+STRIPE_STARTING_COLS = ['Type', 'ID', 'Created', 'Description', 'Amount', 'Currency', 'Converted Amount', 'Fees', 'Net', 'Converted Currency', 'Details']
+RAISENOW_STARTING_COLS = ['Identifikationsnummer', 'Erstellt', 'UTC-Offset', 'Status', 'Betrag', 'Währung', 'Übernommene Gebühren - Betrag', 'Übernommene Gebühren - Währung', 'Zahlungsmethode', 'Zahlungsanbieter', 'Nettobetrag', 'Auszahlungswährung']
 
 
 def get_dataframe(key):
@@ -36,7 +36,7 @@ def get_merged_df(table_name): # return table_name: str
       - no pandas merge suffixes at all
       - all original columns (including Raisenow's norm_zweck) preserved
     """
-    print('calculate DataFrame...')
+    print('calculated DataFrame')
     # --- load & normalize Stripe ---
     stripe_import = get_dataframe('stripe_import')
     
@@ -125,11 +125,10 @@ def get_merged_df(table_name): # return table_name: str
     )
     # additional assignment: build a mask of rows where norm_zweck is still empty/NaN
     mask = raisenow['norm_zweck'].isna() | (raisenow['norm_zweck'] == '')
-    if mask.any() and 'raisenow_parameters.product.source_url' in raisenow.columns:
-        raisenow.loc[mask, 'norm_zweck'] = (
-            raisenow.loc[mask, 'raisenow_parameters.product.source_url']
-                .str.extract(r'https?://[^/]+/([^/?#]+)')[0]
-        )
+    raisenow.loc[mask, 'norm_zweck'] = (
+        raisenow.loc[mask, 'raisenow_parameters.product.source_url']
+            .str.extract(r'https?://[^/]+/([^/?#]+)')[0]
+    )
 
     # --- return raw tables if requested ---
     if table_name == 'stripe_import':
@@ -344,10 +343,10 @@ def upload():
         raw = (
             pd.read_csv(f) if f.filename.lower().endswith('.csv') else pd.read_excel(f)
         )
-        raw = raw.dropna(how='all')
+        raw = raw.dropna(how='all').dropna(axis=1, how='all')
+        print('number of rows:', len(raw))
         raw = raw.astype(object).replace({np.nan: None})
         cols = list(raw.columns)
-
         if cols[:len(STRIPE_STARTING_COLS)] == STRIPE_STARTING_COLS:
             key = 'stripe_import'
             dedupe_col = 'ID'
@@ -355,12 +354,8 @@ def upload():
             key = 'raisenow_import'
             dedupe_col = 'Identifikationsnummer'
         else:
-            print('file does not match expected formats:', f.filename)
-            return jsonify({
-                "status": "error",
-                "message": f"File '{f.filename}' does not match expected formats."
-            }), 400
-        
+            continue
+
         existing = get_dataframe(key)
         combined = pd.concat([existing, raw], ignore_index=True)
         deduped = combined.drop_duplicates(subset=[dedupe_col], keep='first').reset_index(drop=True)

app/templates/index.html

@@ -176,21 +176,8 @@
           columns: cols,
         };
 
-        // add sum_amount to the footer using column calculations
-        // If you want to sum the "amount" column, add a bottomCalc to the column definition
-        cols.forEach(col => {
-          if (col.field === 'amount') {
-            col.bottomCalc = 'sum';
-            col.bottomCalcFormatter = cell => cell.getValue().toFixed(2);
-          }
-        });
-        // Recreate table with updated columns
         if (table) table.destroy();
-        table = new Tabulator('#table', {
-          ...opts,
-          columns: cols,
-        });
-
+        table = new Tabulator('#table', opts);
       } catch (err) {
         console.error(err); alert('Failed to load table data');
       } finally { hideLoading(); }