import os import psycopg2 from dotenv import load_dotenv # Load environment variables root_env = os.path.join(os.path.dirname(os.path.dirname(__file__)), '.env') load_dotenv(root_env) # Connect to database conn = psycopg2.connect( host=os.getenv('DB_HOST', '192.168.0.61'), port=os.getenv('DB_PORT', '55432'), dbname=os.getenv('DB_NAME', 'njts_acct'), user=os.getenv('DB_USER', 'njts_app'), password=os.getenv('DB_PASSWORD') ) cur = conn.cursor() print("保険率カラムを DECIMAL(5,3) に変更中...") # Alter insurance_rates table cur.execute(""" ALTER TABLE insurance_rates ALTER COLUMN employee_rate TYPE DECIMAL(5, 3), ALTER COLUMN employer_rate TYPE DECIMAL(5, 3) """) # Alter child_support_contribution_rates table cur.execute(""" ALTER TABLE child_support_contribution_rates ALTER COLUMN contribution_rate TYPE DECIMAL(5, 3) """) conn.commit() print("OK カラム変更完了") # Verify changes cur.execute(""" SELECT column_name, data_type, numeric_precision, numeric_scale FROM information_schema.columns WHERE table_name='insurance_rates' AND column_name IN ('employee_rate', 'employer_rate') ORDER BY column_name """) print("\n変更後の insurance_rates カラム:") for row in cur.fetchall(): print(f" {row[0]}: {row[1]}({row[2]},{row[3]})") cur.execute(""" SELECT column_name, data_type, numeric_precision, numeric_scale FROM information_schema.columns WHERE table_name='child_support_contribution_rates' AND column_name = 'contribution_rate' """) print("\n変更後の child_support_contribution_rates カラム:") for row in cur.fetchall(): print(f" {row[0]}: {row[1]}({row[2]},{row[3]})") # Check data cur.execute(""" SELECT rate_year, rate_type, calculation_target, prefecture, employee_rate, employer_rate FROM insurance_rates WHERE rate_year = 2025 AND rate_type = '健康保険' LIMIT 3 """) print("\n実際のデータ (2025年健康保険):") for row in cur.fetchall(): print(f" {row[0]} {row[1]} {row[2]} {row[3]}: 従業員={float(row[4]):.3f} 会社={float(row[5]):.3f}") cur.close() conn.close() print("\n完了!")