import pandas as pd from sqlalchemy import create_engine, inspect cfg = { 'csv_file': 'CARLO.csv', 'clients': {'1': 'M und S Fahrzeughandel GmbH'}, 'filter': {'01.01.2018', '2019-01-01'}, 'source_dsn': {'user': 'sa', 'pass': 'Mffu3011#', 'server': 'GC-SERVER1\\GLOBALCUBE', 'database': 'DE0017', 'schema': 'dbo'}, 'target_dsn': {'user': 'sa', 'pass': 'Mffu3011#', 'server': 'GC-SERVER1\\GLOBALCUBE', 'database': 'CARLO2', 'schema': 'import'}, 'stage_dir': 'C:\\GlobalCube\\System\\CARLO\\Export\\stage' } def db_import(select_query, source_db, current_table, target_db, target_schema): pd.read_sql(select_query, source_db).to_sql(current_table['target'], target_db, schema=target_schema, index=False, if_exists='append') def conn_string(dsn): return f"mssql+pyodbc://{dsn['user']}:{dsn['pass']}@{dsn['server']}/{dsn['database']}?driver=SQL+Server+Native+Client+11.0" def conn_params(dsn): return f"-S {dsn['server']} -d {dsn['database']} -U {dsn['user']} -P {dsn['pass']}" df = pd.read_csv(cfg['csv_file'], sep=';', encoding='latin-1') config = df[df['target'].notnull()] print(config.head()) source_db = create_engine(conn_string(cfg['source_dsn'])) source_insp = inspect(source_db) source_tables = source_insp.get_table_names(schema=cfg['source_dsn']['schema']) source_tables_prefix = set([t.split('$')[0] for t in source_tables if '$' in t]) print(source_tables_prefix) target_db = create_engine(conn_string(cfg['target_dsn'])) target_insp = inspect(target_db) target_tables = target_insp.get_table_names(schema=cfg['target_dsn']['schema']) for index, current_table in config.iterrows(): with open(cfg['stage_dir'] + "\\batch\\" + current_table['target'] + ".bat", "w", encoding="cp850") as f: f.write("@echo off \n") f.write("rem ==" + current_table['target'] + "==\n") if not current_table['target'] in target_tables: f.write(f"echo Ziel-Tabelle '{current_table['target']}' existiert nicht!\n") continue f.write(f"del {cfg['stage_dir']}\\{current_table['target']}*.* /Q /F >nul 2>nul \n") f.write(f"sqlcmd.exe {conn_params(cfg['target_dsn'])} -p " + f"-Q \"TRUNCATE TABLE [{cfg['target_dsn']['schema']}].[{current_table['target']}]\" \n") target_insp_cols = target_insp.get_columns(current_table['target'], schema=cfg['target_dsn']['schema']) target_columns_list = [col['name'] for col in target_insp_cols] target_columns = set(target_columns_list) for client_db, prefix in cfg['clients'].items(): source_table = current_table['source'].format(prefix) if source_table not in source_tables: f.write(f"echo Quell-Tabelle '{source_table}' existiert nicht!\n") continue stage_csv = f"{cfg['stage_dir']}\\{current_table['target']}_{client_db}.csv" if not pd.isnull(current_table['query']): select_query = current_table['query'].format(prefix, cfg['filter'][0], cfg['filter'][1]) else: select_query = f"SELECT T1.* FROM [{cfg['source_dsn']['schema']}].[{source_table}] T1 " if not pd.isnull(current_table['filter']): select_query += " WHERE " + current_table['filter'].format("", cfg['filter'][0], cfg['filter'][1]) source_insp_cols = source_insp.get_columns(source_table) source_columns = set([col['name'] for col in source_insp_cols]) intersect = source_columns.intersection(target_columns) # print("Auf beiden Seiten: " + ";".join(intersect)) diff1 = source_columns.difference(target_columns) if len(diff1) > 0: f.write("rem Nur in Quelle: " + ";".join(diff1) + "\n") diff2 = target_columns.difference(source_columns) if "Client_DB" not in diff2: f.write("echo Spalte 'Client_DB' fehlt!\n") continue diff2.remove("Client_DB") if len(diff2) > 0: f.write("rem Nur in Ziel: " + ";".join(diff2) + "\n") # select_columns = "T1.[" + "], T1.[".join(intersect) + "]," select_columns = "" for col in target_columns_list: if col in intersect: select_columns += "T1.[" + col + "], " elif col == "Client_DB": select_columns += "'" + client_db + "' as \\\"Client_DB\\\", " else: select_columns += "'' as \\\"" + col + "\\\", " select_query = select_query.replace("T1.*", select_columns[:-2]) select_query = select_query.replace("%", "%%") # batch-Problem # print(select_query) f.write(f"bcp \"{select_query}\" queryout \"{stage_csv}\" {conn_params(cfg['source_dsn'])} " + f"-c -C 65001 -e \"{stage_csv[:-4]}.queryout.log\" > \"{stage_csv[:-4]}.bcp1.log\" \n") f.write(f"type \"{stage_csv[:-4]}.bcp1.log\" | findstr -v \"1000\" \n") f.write(f"bcp [{cfg['target_dsn']['schema']}].[{current_table['target']}] in \"{stage_csv}\" " + f"-c -C 65001 {conn_params(cfg['target_dsn'])} -e \"{stage_csv[:-4]}.in.log\" > \"{stage_csv[:-4]}.bcp2.log\" \n") f.write(f"type \"{stage_csv[:-4]}.bcp2.log\" | findstr -v \"1000\" \n") with open(cfg['stage_dir'] + "\\batch\\_all.bat", "w", encoding="cp850") as f: f.write("@echo off & cd /d %~dp0 \n") f.write(f"del {cfg['stage_dir']}\\*.* /Q /F >nul 2>nul \n\n") for index, current_table in config.iterrows(): f.write("echo ==" + current_table['target'] + "==\n") f.write("echo " + current_table['target'] + " >CON \n") f.write("call " + current_table['target'] + ".bat\n\n")