issue:4091669 PDR plugin is not isolate based on LinkDownedCounter measurements

plugins/pdr_deterministic_plugin/ufm_sim_web_service/pdr_algorithm.py

@@ -24,7 +24,7 @@ class PortData:
     """
     Represents the port data.
     """
-    #pylint: disable=too-many-arguments
+    #pylint: disable=too-many-positional-arguments,too-many-arguments
     def __init__(self, port_name=None, port_num=None, peer=None, node_type=None, active_speed=None, port_width=None, port_guid=None):
         """
         Initialize a new instance of the PortData class.
@@ -470,7 +470,7 @@ def check_deisolation_conditions(self, isolated_port):
 
         return True
 
-    #pylint: disable=too-many-arguments,too-many-locals
+    #pylint: disable=too-many-positional-arguments,too-many-arguments,too-many-locals
     def calc_symbol_ber_rate(self, port_name, port_speed, port_width, col_name, time_delta):
         """
         calculate the symbol BER rate for a given port given the time delta

plugins/pdr_deterministic_plugin/ufm_sim_web_service/telemetry_collector.py

@@ -23,34 +23,48 @@ def get_telemetry(self):
         get the telemetry from secondary telemetry, if it in test mode it get from the simulation
         return DataFrame of the telemetry
         """
+        # get telemetry data
         if self.test_mode:
             url = "http://127.0.0.1:9090/csv/xcset/simulated_telemetry"
         else:
             url = f"http://127.0.0.1:{self.SECONDARY_TELEMETRY_PORT}/csv/xcset/{self.SECONDARY_INSTANCE}"
         try:
-            self.logger.info(f"collecting telemetry from {url}.")
+            self.logger.info(f"Collecting telemetry from {url}.")
             telemetry_data = pd.read_csv(url)
         except (pd.errors.ParserError, pd.errors.EmptyDataError, urllib.error.URLError) as connection_error:
-            self.logger.error("failed to get telemetry data from UFM, fetched url=%s. Error: %s",url,connection_error)
+            self.logger.error("Failed to get telemetry data from UFM, fetched url=%s. Error: %s",url,connection_error)
             telemetry_data = None
-        if self.previous_telemetry_data is not None and telemetry_data is not None:
-            delta = self._get_delta(self.previous_telemetry_data,telemetry_data)
-            # when we want to keep only delta
-            if len(delta) > 0:
-                self.data_store.save(delta,self.data_store.get_filename_delta())
-        elif telemetry_data is not None:
-            # when we want to keep the abs
+
+        # store telemetry data
+        try:
+            if self.previous_telemetry_data is not None and telemetry_data is not None:
+                delta = self._get_delta(self.previous_telemetry_data,telemetry_data)
+                # when we want to keep only delta
+                if len(delta) > 0:
+                    self.data_store.save(delta,self.data_store.get_filename_delta())
+            elif telemetry_data is not None:
+                # when we want to keep the abs
+                self.data_store.save(telemetry_data,self.data_store.get_filename_abs())
+        except Exception as exception_error: # pylint: disable=broad-exception-caught
+            self.logger.error(f"Failed to store telemetry data with error {exception_error}")
+
+        # update previous telemetry data
+        if telemetry_data is not None:
             self.previous_telemetry_data = telemetry_data
-            self.data_store.save(telemetry_data,self.data_store.get_filename_abs())
         return telemetry_data
 
     def _get_delta(self, first_df: pd.DataFrame, second_df:pd.DataFrame):
         merged_df = pd.merge(second_df, first_df, on=self.BASED_COLUMNS, how='inner', suffixes=('', '_x'))
         delta_dataframe = pd.DataFrame()
-        for index,col in enumerate(second_df.columns):
-            if col not in self.KEY and not isinstance(merged_df.iat[0,index],str):
-                col_x = col + "_x"
-                delta_dataframe[col] = merged_df[col] - merged_df[col_x]
+        for _,col in enumerate(second_df.columns):
+            col_x = col + "_x"
+            if col not in self.KEY \
+                    and merged_df[col].dtype != 'object' \
+                    and merged_df[col_x].dtype != 'object':
+                try:
+                    delta_dataframe[col] = merged_df[col] - merged_df[col_x]
+                except TypeError:
+                    delta_dataframe[col] = second_df[col]
             else:
                 delta_dataframe[col] = second_df[col]
         return delta_dataframe