Visum Thinker MCP Server

""" Export all visible tables from a Visum Global Layout (.lay) to CSV files Supports: - Simple attributes (NO, LENGTH, etc.) - Attributes with sub-attributes (VEHKMTRAVPRT_DSEG(C_CORRETTA_FERIALE,AP)) - Formula columns defined in layout - Multiple tables in one layout file Usage: python export-all-tables-from-layout.py Or via project_execute MCP tool """ import xml.etree.ElementTree as ET import os # Configuration layout_file = r'H:\go\reports\Input\tabelle_report.lay' output_dir = r'H:\go\reports\Input' project_name = 'S000009result' # Parse layout XML print(f"📖 Parsing layout: {layout_file}") tree = ET.parse(layout_file) root = tree.getroot() # Find all visible tables tables_info = [] for list_item in root.iter('listLayoutItem'): graphic = list_item.find('.//listGraphicParameterLayoutItems') if graphic is not None: net_obj_type = graphic.get('netObjectType') if net_obj_type: # Get table name table_name_elem = list_item.find('.//caption') table_name = table_name_elem.get('text', net_obj_type) if table_name_elem is not None else net_obj_type # Get all column definitions col_defs = [] for attr_def in list_item.iter('attributeDefinition'): col_defs.append(attr_def.attrib) tables_info.append({ 'name': table_name, 'type': net_obj_type, 'columns': col_defs }) print(f"\n✅ Found {len(tables_info)} tables:") for t in tables_info: print(f" - {t['name']} ({t['type']}): {len(t['columns'])} columns") # Map net object types to Visum collections type_to_collection = { 'LINK': 'visum.Net.Links', 'NODE': 'visum.Net.Nodes', 'ZONE': 'visum.Net.Zones', 'ODPAIR': 'visum.Net.ODPairs', 'LINE': 'visum.Net.Lines', 'LINEROUTE': 'visum.Net.LineRoutes', 'TIMEPROFILE': 'visum.Net.TimeProfiles', 'TIMEPROFILEITEM': 'visum.Net.TimeProfileItems', 'VEHJOURNEYSECTION': 'visum.Net.VehicleJourneySections', 'STOP': 'visum.Net.Stops', 'STOPPOINTAREA': 'visum.Net.StopPointAreas', 'CONNECTOR': 'visum.Net.Connectors' } # Export each table results = [] for table in tables_info: table_type = table['type'] table_name = table['name'] print(f"\n🔄 Processing: {table_name} ({table_type})") # Get collection collection_path = type_to_collection.get(table_type) if not collection_path: print(f" ⚠️ Unknown type {table_type}, skipping...") results.append({'table': table_name, 'status': 'SKIPPED', 'reason': 'Unknown type'}) continue try: collection = eval(collection_path) count = collection.Count print(f" 📊 {count} objects found") except Exception as e: print(f" ❌ Cannot access collection: {e}") results.append({'table': table_name, 'status': 'ERROR', 'reason': str(e)}) continue # Build attribute list with sub-attributes full_attrs = [] headers = [] for col in table['columns']: attr_id = col['attributeID'] sub1 = col.get('subAttributeID1', '') sub2 = col.get('subAttributeID2', '') sub3 = col.get('subAttributeID3', '') # Build full attribute name if sub1 or sub2 or sub3: subs = [s for s in [sub1, sub2, sub3] if s] full_attr = attr_id + '(' + ','.join(subs) + ')' # Create readable header header = attr_id + '_' + '_'.join(subs) else: full_attr = attr_id header = attr_id full_attrs.append(full_attr) headers.append(header) print(f" 📝 Columns: {len(full_attrs)}") print(f" First 5: {full_attrs[:5]}") # Get data try: print(f" ⏳ Retrieving data...") data = collection.GetMultipleAttributes(full_attrs) # Build CSV print(f" 📄 Building CSV...") lines = [';'.join(headers)] for row_tuple in data: lines.append(';'.join(str(v) for v in row_tuple)) # Write file safe_name = table_name.replace('/', '_').replace('\\', '_').replace(' ', '_') output_file = os.path.join(output_dir, f'{project_name}_{safe_name}.csv') text = '\n'.join(lines) with open(output_file, 'w', encoding='utf-8', newline='') as f: f.write(text) size_mb = os.path.getsize(output_file) / (1024 * 1024) print(f" ✅ Exported: {output_file}") print(f" Size: {size_mb:.2f} MB") print(f" Rows: {len(data):,} + header") results.append({ 'table': table_name, 'type': table_type, 'status': 'SUCCESS', 'file': output_file, 'rows': len(data), 'cols': len(full_attrs), 'size_mb': round(size_mb, 2) }) except Exception as e: print(f" ❌ Export failed: {e}") results.append({ 'table': table_name, 'status': 'ERROR', 'reason': str(e)[:100] }) # Summary print("\n" + "="*60) print("📊 EXPORT SUMMARY") print("="*60) success = [r for r in results if r['status'] == 'SUCCESS'] errors = [r for r in results if r['status'] == 'ERROR'] skipped = [r for r in results if r['status'] == 'SKIPPED'] print(f"\n✅ Successful: {len(success)}") for r in success: print(f" - {r['table']}: {r['rows']:,} rows × {r['cols']} cols = {r['size_mb']} MB") if errors: print(f"\n❌ Errors: {len(errors)}") for r in errors: print(f" - {r['table']}: {r['reason']}") if skipped: print(f"\n⚠️ Skipped: {len(skipped)}") for r in skipped: print(f" - {r['table']}: {r['reason']}") print(f"\n📁 Output directory: {output_dir}") print("\n✨ Export complete!") # Return results for MCP result = { 'total_tables': len(tables_info), 'successful': len(success), 'errors': len(errors), 'skipped': len(skipped), 'details': results }