Open Census MCP Server

#!/usr/bin/env python3 """ Extract 10 test variables for config validation """ import json from pathlib import Path def extract_10_test_variables(): """Extract 10 diverse variables for testing""" # Try different possible paths for the complete variables file possible_paths = [ "../complete_2023_acs_variables/complete_variables.csv", "../coos_variables_extracted.json", "complete_variables.csv", "coos_variables_extracted.json" ] variables_data = None source_file = None # Try to find an existing variables file for path in possible_paths: if Path(path).exists(): source_file = path break if not source_file: print("❌ No variables file found. Please check paths:") for path in possible_paths: print(f" {path}") return print(f"📁 Loading variables from: {source_file}") # Load data based on file type if source_file.endswith('.json'): with open(source_file, 'r') as f: variables_data = json.load(f) elif source_file.endswith('.csv'): import pandas as pd df = pd.read_csv(source_file) # Convert to JSON format expected by enrichment script variables_data = {} for _, row in df.iterrows(): var_id = row.get('name', row.get('variable_id', 'unknown')) variables_data[var_id] = { 'label': row.get('label', 'Unknown'), 'concept': row.get('concept', 'Unknown'), 'universe': row.get('universe', 'Unknown') } if not variables_data: print("❌ Could not load variables data") return print(f"📊 Found {len(variables_data)} total variables") # Select 10 diverse test variables # Try to get different table families selected_vars = {} target_tables = ['B19', 'B25', 'B08', 'B17', 'B01', 'B15', 'B23', 'B02', 'B11', 'B20'] for table_prefix in target_tables: for var_id, var_data in variables_data.items(): if var_id.startswith(table_prefix) and var_id not in selected_vars: selected_vars[var_id] = var_data break if len(selected_vars) >= 10: break # If we don't have 10 yet, just take first available if len(selected_vars) < 10: remaining_needed = 10 - len(selected_vars) for var_id, var_data in variables_data.items(): if var_id not in selected_vars: selected_vars[var_id] = var_data remaining_needed -= 1 if remaining_needed == 0: break # Save test file output_file = "test_10_variables.json" with open(output_file, 'w') as f: json.dump(selected_vars, f, indent=2) print(f"\n✅ Test file created: {output_file}") print(f"📋 Selected {len(selected_vars)} test variables:") for var_id, var_data in selected_vars.items(): table_family = var_id[:3] if len(var_id) >= 3 else var_id label = var_data.get('label', 'Unknown')[:50] + "..." if len(var_data.get('label', '')) > 50 else var_data.get('label', 'Unknown') print(f" {var_id} ({table_family}): {label}") print(f"\n🧪 Ready to test with:") print(f" python enhanced_collaborative_enrichment.py \\") print(f" --input-file {output_file} \\") print(f" --output-file test_results.json \\") print(f" --config-file agent_config.yaml \\") print(f" --openai-api-key $OPENAI_API_KEY \\") print(f" --claude-api-key $CLAUDE_API_KEY \\") print(f" --max-variables 10") if __name__ == "__main__": extract_10_test_variables()