diff --git a/video_prediction_tools/main_scripts/main_preprocess_data_step2.py b/video_prediction_tools/main_scripts/main_preprocess_data_step2.py
index 8d755d1526a45ceb55aee6b05a4aa0b749f58676..1a16e4e723bda40baafdfada3f9012b51b61016a 100644
--- a/video_prediction_tools/main_scripts/main_preprocess_data_step2.py
+++ b/video_prediction_tools/main_scripts/main_preprocess_data_step2.py
@@ -16,6 +16,9 @@ import warnings
 
 
 def main():
+
+    method="main_preprocess_data_step2"
+
     parser = argparse.ArgumentParser()
     parser.add_argument("-source_dir", type=str)
     parser.add_argument("-dest_dir", type=str)
@@ -25,8 +28,8 @@ def main():
     input_dir = args.source_dir
     ins = ERA5Pkl2Tfrecords(input_dir=input_dir,
                             dest_dir=args.dest_dir,
-                             sequence_length = args.sequence_length,
-                             sequences_per_file=args.sequences_per_file)
+                            sequence_length = args.sequence_length,
+                            sequences_per_file=args.sequences_per_file)
     
     years, months,years_months = ins.get_years_months()
     # ini. MPI
@@ -34,19 +37,19 @@ def main():
     my_rank = comm.Get_rank()  # rank of the node
     p = comm.Get_size()  # number of assigned nodes
     if p < 2:
-        raise ValueError("Preprocessing step 2 must be assigned to at least two tasks.")
+        raise ValueError("%{0}: Preprocessing step 2 must be assigned to at least two tasks.".format(method))
   
     if my_rank == 0:
         # retrieve final statistics first (not parallelized!)
         # some preparatory steps
         stat_dir = os.path.dirname(input_dir)
-        varnames        = ins.vars_in
+        varnames = ins.vars_in
     
         vars_uni, varsind, nvars = get_unique_vars(varnames)
         stat_obj = Calc_data_stat(nvars)                            # init statistic-instance
     
         # loop over whole data set (training, dev and test set) to collect the intermediate statistics
-        print("Start collecting statistics from the whole dataset to be processed...")
+        print("%{0}: Start collecting statistics from the whole dataset to be processed...".format(method))
        
         for year in years:
             file_dir = os.path.join(input_dir, year)
@@ -55,7 +58,7 @@ def main():
                     # process stat-file:
                     stat_obj.acc_stat_master(file_dir, int(month))  # process monthly statistic-file
                 else:
-                    warnings.warn("The stat file for year {} month {} does not exist".format(year, month))
+                    warnings.warn("%{0}: The statistic file for year {1}, month {2} does not exist".format(method, year, month))
         # finalize statistics and write to json-file
         stat_obj.finalize_stat_master(vars_uni)
         stat_obj.write_stat_json(stat_dir)
@@ -77,12 +80,11 @@ def main():
         while message_counter <= p-1:
             message_in = comm.recv()
             message_counter = message_counter + 1 
-            print("Message in from slave: ", message_in)
+            print("%{0}: Message in from worker: {1} ".format(method, message_in))
  
     else:
         message_in = comm.recv()
-        print("My rank,", my_rank)
-        print("message_in", message_in)
+        print("%{0}: Message from master to rank {1}: {2} ".format(method, my_rank, message_in))
         
         years = list(message_in[0])
         real_years_months = message_in[1] 
@@ -97,11 +99,11 @@ def main():
                                          sequences_per_file=args.sequences_per_file)
                 # create the tfrecords-files
                 ins2.read_pkl_and_save_tfrecords(year=year, month=my_rank)
-                print("Year {} finished", year)
+                print("%{0}: Year {1} finished".format(method, year))
             else:
-                print(year_rank + " is not in the datasplit_dic, will skip the process")
+                print("%{0}: {1} is not in the datasplit_dic, will skip the process".format(method, year_rank))
         message_out = ("Node:", str(my_rank), "finished", "", "\r\n")
-        print("Message out for slaves:", message_out)
+        print("%{0}: Message out for worker: {1}".format(method, message_out))
         comm.send(message_out, dest=0)
 
     MPI.Finalize()