only stop time if time attr is still present

mlair/run_modules/run_environment.py

@@ -113,6 +113,7 @@ class RunEnvironment(object):
         not as inheritance from this class, log file is copied and data store is cleared.
         """
         if not self.del_by_exit:
+            if hasattr(self, "time"):
                 self.time.stop()
                 try:
                     logging.info(f"{self._name} finished after {self.time}")

test/test_run_modules/test_pre_processing.py

@@ -9,8 +9,6 @@ from mlair.helpers import PyTestRegex
 from mlair.run_modules.experiment_setup import ExperimentSetup
 from mlair.run_modules.pre_processing import PreProcessing
 from mlair.run_modules.run_environment import RunEnvironment
-import pandas as pd
-import numpy as np
 import multiprocessing
 
 
@@ -146,24 +144,3 @@ class TestPreProcessing:
         class data_preparation_no_trans: pass
 
         assert pre.transformation(data_preparation_no_trans, stations) is None
-
-    # @pytest.fixture
-    # def dummy_df(self):
-    #     data_dict = {'station_name': {'DEBW013': 'Stuttgart Bad Cannstatt', 'DEBW076': 'Baden-Baden',
-    #                                   'DEBW087': 'Schwäbische_Alb', 'DEBW107': 'Tübingen',
-    #                                   'DEBY081': 'Garmisch-Partenkirchen/Kreuzeckbahnstraße', '# Stations': np.nan,
-    #                                   '# Samples': np.nan},
-    #                  'station_lon': {'DEBW013': 9.2297, 'DEBW076': 8.2202, 'DEBW087': 9.2076, 'DEBW107': 9.0512,
-    #                                  'DEBY081': 11.0631, '# Stations': np.nan, '# Samples': np.nan},
-    #                  'station_lat': {'DEBW013': 48.8088, 'DEBW076': 48.7731, 'DEBW087': 48.3458, 'DEBW107': 48.5077,
-    #                                  'DEBY081': 47.4764, '# Stations': np.nan, '# Samples': np.nan},
-    #                  'station_alt': {'DEBW013': 235.0, 'DEBW076': 148.0, 'DEBW087': 798.0, 'DEBW107': 325.0,
-    #                                  'DEBY081': 735.0, '# Stations': np.nan, '# Samples': np.nan},
-    #                  'train': {'DEBW013': 1413, 'DEBW076': 3002, 'DEBW087': 3016, 'DEBW107': 1782, 'DEBY081': 2837,
-    #                            '# Stations': 6, '# Samples': 12050},
-    #                  'val': {'DEBW013': 698, 'DEBW076': 715, 'DEBW087': 700, 'DEBW107': 701, 'DEBY081': 456,
-    #                          '# Stations': 6, '# Samples': 3270},
-    #                  'test': {'DEBW013': 1066, 'DEBW076': 696, 'DEBW087': 1080, 'DEBW107': 1080, 'DEBY081': 700,
-    #                           '# Stations': 6, '# Samples': 4622}}
-    #     df = pd.DataFrame.from_dict(data_dict)
-    #     return df