db_create.py 5.4 KB

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  1. import pandas as pd
  2. from sqlalchemy import create_engine, inspect
  3. csv_file = 'CARLO.csv'
  4. clients = {'1': 'M und S Fahrzeughandel GmbH'}
  5. client_db = '1'
  6. date_filter = "'2018-01-01'"
  7. source_dsn = {'user': 'sa', 'pass': 'Mffu3011#', 'server': 'GC-SERVER1\\GLOBALCUBE', 'database': 'DE0017'}
  8. source_schema = 'dbo'
  9. target_dsn = {'user': 'sa', 'pass': 'Mffu3011#', 'server': 'GC-SERVER1\\GLOBALCUBE', 'database': 'CARLO2'}
  10. target_schema = 'import'
  11. # stage_dir = "\\\\gc-server1\Austausch\\stage"
  12. stage_dir = 'C:\\GlobalCube\\System\\CARLO\\Export\\stage'
  13. def db_import(select_query, source_db, current_table, target_db, target_schema):
  14. pd.read_sql(select_query, source_db).to_sql(current_table['target'], target_db, schema=target_schema, index=False, if_exists='append')
  15. def conn_string(dsn):
  16. return f"mssql+pyodbc://{dsn['user']}:{dsn['pass']}@{dsn['server']}/{dsn['database']}?driver=SQL+Server+Native+Client+11.0"
  17. def conn_params(dsn):
  18. return f"-S {dsn['server']} -d {dsn['database']} -U {dsn['user']} -P {dsn['pass']}"
  19. df = pd.read_csv(csv_file, sep=';', encoding='ansi')
  20. config = df[df['target'].notnull()]
  21. print(config.head())
  22. source_db = create_engine(conn_string(source_dsn))
  23. source_insp = inspect(source_db)
  24. source_tables = source_insp.get_table_names(schema=source_schema)
  25. source_tables_prefix = set([t.split('$')[0] for t in source_tables if '$' in t])
  26. print(source_tables_prefix)
  27. target_db = create_engine(conn_string(target_dsn))
  28. target_insp = inspect(target_db)
  29. target_tables = target_insp.get_table_names(schema=target_schema)
  30. for index, current_table in config.iterrows():
  31. with open(stage_dir + "\\batch\\" + current_table['target'] + '.bat', 'w', encoding='cp850') as f:
  32. f.write('@echo off \n')
  33. f.write('rem ==' + current_table['target'] + '==\n')
  34. if not current_table['target'] in target_tables:
  35. f.write(f"echo Ziel-Tabelle '{current_table['target']}' existiert nicht!\n")
  36. continue
  37. f.write(f"del {stage_dir}\\{current_table['target']}*.* /Q /F >nul 2>nul \n")
  38. f.write(f"sqlcmd.exe {conn_params(target_dsn)} -p -Q \"TRUNCATE TABLE [{target_schema}].[{current_table['target']}]\" \n")
  39. target_insp_cols = target_insp.get_columns(current_table['target'], schema=target_schema)
  40. target_columns_list = [col['name'] for col in target_insp_cols]
  41. target_columns = set(target_columns_list)
  42. for client_db, prefix in clients.items():
  43. source_table = current_table['source'].format(prefix)
  44. if source_table not in source_tables:
  45. f.write(f"echo Quell-Tabelle '{source_table}' existiert nicht!\n")
  46. continue
  47. stage_csv = f"{stage_dir}\\{current_table['target']}_{client_db}.csv"
  48. if not pd.isnull(current_table['query']):
  49. select_query = current_table['query'].format(prefix, date_filter)
  50. else:
  51. select_query = f"SELECT T1.* FROM [{source_schema}].[{source_table}] T1 "
  52. if not pd.isnull(current_table['filter']):
  53. select_query += " WHERE " + current_table['filter'].format("", date_filter)
  54. source_insp_cols = source_insp.get_columns(source_table)
  55. source_columns = set([col['name'] for col in source_insp_cols])
  56. intersect = source_columns.intersection(target_columns)
  57. # print("Auf beiden Seiten: " + ";".join(intersect))
  58. diff1 = source_columns.difference(target_columns)
  59. if len(diff1) > 0:
  60. f.write("rem Nur in Quelle: " + ";".join(diff1) + "\n")
  61. diff2 = target_columns.difference(source_columns)
  62. if 'Client_DB' not in diff2:
  63. f.write("echo Spalte 'Client_DB' fehlt!\n")
  64. continue
  65. diff2.remove('Client_DB')
  66. if len(diff2) > 0:
  67. f.write("rem Nur in Ziel: " + ";".join(diff2) + "\n")
  68. # select_columns = "T1.[" + "], T1.[".join(intersect) + "],"
  69. select_columns = ''
  70. for col in target_columns_list:
  71. if col in intersect:
  72. select_columns += "T1.[" + col + "], "
  73. elif col == 'Client_DB':
  74. select_columns += "'" + client_db + "' as \\\"Client_DB\\\", "
  75. else:
  76. select_columns += "'' as \\\"" + col + "\\\", "
  77. select_query = select_query.replace("T1.*", select_columns[:-2])
  78. select_query = select_query.replace("%", "%%") # batch-Problem
  79. # print(select_query)
  80. f.write(f"bcp \"{select_query}\" queryout \"{stage_csv}\" {conn_params(source_dsn)} -c -C 65001 -e \"{stage_csv[:-4]}.queryout.log\" > \"{stage_csv[:-4]}.bcp1.log\" \n")
  81. f.write(f"type \"{stage_csv[:-4]}.bcp1.log\" | findstr -v \"1000\" \n")
  82. f.write(f"bcp [{target_schema}].[{current_table['target']}] in \"{stage_csv}\" {conn_params(target_dsn)} -c -C 65001 -e \"{stage_csv[:-4]}.in.log\" > \"{stage_csv[:-4]}.bcp2.log\" \n")
  83. f.write(f"type \"{stage_csv[:-4]}.bcp2.log\" | findstr -v \"1000\" \n")
  84. with open(stage_dir + "\\batch\\_all.bat", "w", encoding="cp850") as f:
  85. f.write("@echo off & cd /d %~dp0 \n")
  86. f.write(f"del {stage_dir}\\*.* /Q /F >nul 2>nul \n\n")
  87. for index, current_table in config.iterrows():
  88. f.write("echo ==" + current_table['target'] + "==\n")
  89. f.write("echo " + current_table['target'] + " >CON \n")
  90. f.write("call " + current_table['target'] + ".bat\n\n")