# Updated exception clauses

app.py

@@ -199,6 +199,7 @@ def load_and_predict(df_grouped, index_no):
 
 
 def start_prediction(raw_path, viscosity_path, index_no, raw_skip_rows, viscosity_skip_rows):
+    try:
         logger.info(f"Starting prediction for {index_no}")
         logger.info("Reading raw file data")
         df = read_raw_data(raw_path, raw_skip_rows)
@@ -249,6 +250,9 @@ def start_prediction(raw_path, viscosity_path, index_no, raw_skip_rows, viscosit
 
         # load_and_predict(df_grouped, index_no)
         model_trainer(df_grouped, index_no)
+    except Exception as err:
+        logger.error(f"Exception in main prediction {str(err)}")
+        raise Exception(str(err))
 
 
 if __name__ == "__main__":
@@ -274,3 +278,4 @@ if __name__ == "__main__":
         start_prediction(raw_file_path, viscosity_file_path, index_number, raw_file_skip_rows, viscosity_file_skip_rows)
     except Exception as e:
         logger.exception(f"Module failed because of error {e}")
+        raise Exception(str(e))

main.py

@@ -293,7 +293,7 @@ def return_fy676a_pick_batch_no_df(raw_df, viscosity_df, bof_date_dict, bof_batc
         for each_day in dt_list:
             day_df = sorted_pick_df[sorted_pick_df['day'] == each_day]
             if day_df['length passed through.1'].max() - day_df['length passed through.1'].min() <= 0:
-                value = 0
+                raise Exception(f"Length passed through in pick up section for {each_day} is 0")
             else:
                 value = day_df['length passed through.1'].max() - day_df['length passed through.1'].min()
             day_length_dic[each_day] = value
@@ -423,7 +423,7 @@ def return_fy664g_pick_batch_no_df(raw_df, viscosity_df, bof_date_dict, index_no
             if minimum <= 0:
                 minimum = 0
             if day_df['length passed through.1'].max() - minimum <= 0:
-                value = 0
+                raise Exception(f"Length passed through in pick up section for {each_day} is 0")
             else:
                 value = day_df['length passed through.1'].max() - minimum
             day_length_dic[each_day] = value
@@ -538,6 +538,8 @@ def preprocess_pickup_section(raw_df, index_number, viscosity_df):
         for each_day in dt_list:
             day_df = sorted_pick_df[sorted_pick_df['day'] == each_day]
             day_length_dic[each_day] = day_df['length passed through.1'].max() - day_df['length passed through.1'].min()
+            if day_df['length passed through.1'].max() - day_df['length passed through.1'].min() <= 0:
+                raise Exception(f"Length passed through in pick up section for {each_day} is 0")
 
         ''' Reading viscosity file with skipping 2 rows '''
         viscosity_df['Mixing date'] = pd.to_datetime(viscosity_df['Mixing date'])
@@ -774,6 +776,7 @@ def preprocess_viscosity_section(viscosity_df, index_number):
 
 
 def mixer_section_start_end_time(raw_df, index_no):
+    try:
         mixer_cols = ['Time Stamp',
                       'Size No (INDEX No).3',
                       'Size name',
@@ -810,11 +813,13 @@ def mixer_section_start_end_time(raw_df, index_no):
             date_dict[each_bt] = {"start_time": str(list(df_nw['time_min'])[0]),
                                   'end_time': str(list(df_nw['time_max'])[0])}
         return date_dict
+    except Exception as err:
+        logger.error(f'Exception in mixer time fetch: {str(err)}')
+        raise Exception(str(err))
 
 
-def return_batch_no_df_1(
-        raw_df, viscosity_df, date_dict, bof_cols, additional_cols, index_no
-):
+def return_batch_no_df_1(raw_df, viscosity_df, date_dict, bof_cols, additional_cols, index_no):
+    try:
         raw_df = raw_df.sort_values(by='Time Stamp')
         raw_df['Time Stamp'] = pd.to_datetime(raw_df['Time Stamp'])
         raw_df["day"] = raw_df["Time Stamp"].dt.date
@@ -839,7 +844,7 @@ def return_batch_no_df_1(
         for each_day in dt_list:
             day_df = sorted_bof_df[sorted_bof_df["day"] == each_day]
             if day_df["discharge length"].max() - day_df["discharge length"].min() <= 0:
-            value = 0
+                raise Exception(f"Discharge length in extruder section for {each_day} is 0")
             else:
                 value = day_df["discharge length"].max() - day_df["discharge length"].min()
             day_length_dic[each_day] = value
@@ -974,9 +979,13 @@ def return_batch_no_df_1(
                 + test_df["day"].astype("str")
         )
         return test_df
+    except Exception as err:
+        logger.error(f'Exception in batch formation in extruder: {str(err)}')
+        raise Exception(str(err))
 
 
 def preprocess_extruder_section(df, index_number, vis_df):
+    try:
         extruder_cols = ExtruderConstants.extruder_cols
         additional_columns = ['Time Stamp']
         df_extruder = df[extruder_cols + additional_columns]
@@ -1023,7 +1032,9 @@ def preprocess_extruder_section(df, index_number, vis_df):
         df_extruder_grouped = df_extruder_grouped.fillna(df_extruder_grouped.mean())
         df_extruder_grouped = round(df_extruder_grouped, 6)
         return df_extruder_grouped
-
+    except Exception as err:
+        logger.error(f'Exception in extruder preprocess: {str(err)}')
+        raise Exception(str(err))
 
 
 def return_batch_no_df(raw_df, viscosity_df, date_dict, index_number):
@@ -1047,7 +1058,7 @@ def return_batch_no_df(raw_df, viscosity_df, date_dict, index_number):
         for each_day in dt_list:
             day_df = sorted_bof_df[sorted_bof_df['day'] == each_day]
             if (day_df['length passed through'].max() - day_df['length passed through'].min()) <= 0:
-                value = 0
+                raise Exception(f"Length passed through in bof section for {each_day} is 0")
             else:
                 value = day_df['length passed through'].max() - day_df['length passed through'].min()
             day_length_dic[each_day] = value
@@ -1856,6 +1867,7 @@ def load_and_predict(df_grouped, index_no, model_path):
 
 
 def start_prediction(raw_path, viscosity_path, index_no, raw_skip_rows, viscosity_skip_rows):
+    try:
         logger.info(f"Starting prediction for {index_no}")
         logger.info("Reading raw file data")
         df = read_raw_data(raw_path, raw_skip_rows)
@@ -1906,6 +1918,9 @@ def start_prediction(raw_path, viscosity_path, index_no, raw_skip_rows, viscosit
 
         # load_and_predict(df_grouped, index_no, model_path)
         model_trainer(df_grouped, index_no, model_path)
+    except Exception as er:
+        logger.error(f"Error in main prediction: {str(er)}")
+        raise Exception(str(er))
 
 
 if __name__ == "__main__":
@@ -1919,3 +1934,4 @@ if __name__ == "__main__":
         start_prediction(raw_file_path, viscosity_file_path, index_number, raw_file_skip_rows, viscosity_file_skip_rows)
     except Exception as e:
         logger.exception(f"Module failed because of error {e}")
+        raise Exception(str(e))

scripts/section_utils/bof_section.py

@@ -72,7 +72,7 @@ def return_batch_no_df(raw_df, viscosity_df, date_dict, index_number):
         for each_day in dt_list:
             day_df = sorted_bof_df[sorted_bof_df['day'] == each_day]
             if (day_df['length passed through'].max() - day_df['length passed through'].min()) <= 0:
-                value = 0
+                raise Exception(f"Length passed through in bof section for the day {each_day} is 0")
             else:
                 value = day_df['length passed through'].max() - day_df['length passed through'].min()
             day_length_dic[each_day] = value

scripts/section_utils/extruder_section.py

@@ -12,6 +12,7 @@ warnings.filterwarnings("ignore")
 
 
 def mixer_section_start_end_time(raw_df, index_no):
+    try:
         mixer_cols = ['Time Stamp',
                       'Size No (INDEX No).3',
                       'Size name',
@@ -48,11 +49,13 @@ def mixer_section_start_end_time(raw_df, index_no):
             date_dict[each_bt] = {"start_time": str(list(df_nw['time_min'])[0]),
                                   'end_time': str(list(df_nw['time_max'])[0])}
         return date_dict
+    except Exception as err:
+        logger.error(f'Exception in extruder mixer time fetch {str(err)}')
+        raise Exception(str(err))
 
 
-def return_batch_no_df(
-        raw_df, viscosity_df, date_dict, bof_cols, additional_cols, index_no
-):
+def return_batch_no_df(raw_df, viscosity_df, date_dict, bof_cols, additional_cols, index_no):
+    try:
         raw_df = raw_df.sort_values(by='Time Stamp')
         raw_df['Time Stamp'] = pd.to_datetime(raw_df['Time Stamp'])
         raw_df["day"] = raw_df["Time Stamp"].dt.date
@@ -77,7 +80,7 @@ def return_batch_no_df(
         for each_day in dt_list:
             day_df = sorted_bof_df[sorted_bof_df["day"] == each_day]
             if day_df["discharge length"].max() - day_df["discharge length"].min() <= 0:
-            value = 0
+                raise Exception(f"Discharge length in extruder section for the day {each_day} is 0")
             else:
                 value = day_df["discharge length"].max() - day_df["discharge length"].min()
             day_length_dic[each_day] = value
@@ -212,9 +215,13 @@ def return_batch_no_df(
                 + test_df["day"].astype("str")
         )
         return test_df
+    except Exception as err:
+        logger.error(f'Exception in generating extruder batch {str(err)}')
+        raise Exception(str(err))
 
 
 def preprocess_extruder_section(df, index_number, vis_df):
+    try:
         extruder_cols = ExtruderConstants.extruder_cols
         additional_columns = ['Time Stamp']
         df_extruder = df[extruder_cols + additional_columns]
@@ -261,3 +268,6 @@ def preprocess_extruder_section(df, index_number, vis_df):
         df_extruder_grouped = df_extruder_grouped.fillna(df_extruder_grouped.mean())
         df_extruder_grouped = round(df_extruder_grouped, 6)
         return df_extruder_grouped
+    except Exception as err:
+        logger.error(f"Exception in extruder preprocess {str(err)}")
+        raise Exception(str(err))

scripts/section_utils/pickup_section.py

@@ -505,6 +505,8 @@ def preprocess_pickup_section(raw_df, index_number, viscosity_df):
         for each_day in dt_list:
             day_df = sorted_pick_df[sorted_pick_df['day'] == each_day]
             day_length_dic[each_day] = day_df['length passed through.1'].max() - day_df['length passed through.1'].min()
+            if day_df['length passed through.1'].max() - day_df['length passed through.1'].min() <= 0:
+                raise Exception(f"Length passed through in pick up section for {each_day} is 0")
 
         ''' Reading viscosity file with skipping 2 rows '''
         viscosity_df['Mixing date'] = pd.to_datetime(viscosity_df['Mixing date'])