missed to include the changes

mlair/run_modules/pre_processing.py

@@ -215,16 +215,24 @@ class PreProcessing(RunEnvironment):
         valid_stations = []
         kwargs = self.data_store.create_args_dict(data_handler.requirements(), scope=set_name)
 
-        logging.info("-------start parallel loop------")
-        pool = multiprocessing.Pool(4)
-        output = [pool.apply_async(f_proc, args=(data_handler, station, set_name, store_processed_data), kwds=kwargs)
+        if os.cpu_count() > 1:  # parallel solution
+            logging.info("use parallel validate station approach")
+            pool = multiprocessing.Pool()
+            output = [
+                pool.apply_async(f_proc, args=(data_handler, station, set_name, store_processed_data), kwds=kwargs)
                 for station in set_stations]
-
             for p in output:
                 dh, s = p.get()
                 if dh is not None:
                     collection.add(dh)
                     valid_stations.append(s)
+        else:  # serial solution
+            logging.info("use serial validate station approach")
+            for station in set_stations:
+                dh, s = f_proc(data_handler, station, set_name, store_processed_data, **kwargs)
+                if dh is not None:
+                    collection.add(dh)
+                    valid_stations.append(s)
 
         logging.info(f"run for {t_outer} to check {len(set_stations)} station(s). Found {len(collection)}/"
                      f"{len(set_stations)} valid stations.")
@@ -271,6 +279,11 @@ class PreProcessing(RunEnvironment):
 
 
 def f_proc(data_handler, station, name_affix, store, **kwargs):
+    """
+    Try to create a data handler for given arguments. If build fails, this station does not fulfil all requirements and
+    therefore f_proc will return None as indication. On a successfull build, f_proc returns the built data handler and
+    the station that was used. This function must be implemented globally to work together with multiprocessing.
+    """
     try:
         res = data_handler.build(station, name_affix=name_affix, store_processed_data=store,
                                  **kwargs)