Create better log messages

Pipfile

@@ -6,7 +6,7 @@ verify_ssl = true
 [dev-packages]
 
 [packages]
-# cdplib = {editable = true,git = "https://readonly:readonly@intra.acdp.at/gogs/tanja/cdplib.git"}
+cdplib = {editable = true,git = "https://readonly:readonly@intra.acdp.at/gogs/tanja/cdplib.git"}
 pycodestyle = "*"
 ipykernel = "*"
 spyder-kernels = "==0.*"

cdplib/db_handlers/MongodbHandler.py

@@ -259,7 +259,7 @@ class MongodbHandler:
         except Exception as error:
             self._log.log_and_raise_error(('An error occured trying to query data from {}, with query {}: {}:{}. \nError:{}').format(collection_name, attribute_value, comparison_operator, attribute_value, error))
 
-        return self.convert_mongo_data_into_dataframe(data, index)
+        return self.convert_mongo_data_into_dataframe(data, index, collection_name)
 
     def aggregate_data_and_generate_dataframe(self, collection_name: str, aggregation_pipeline: list, index: str = None):
 
@@ -268,14 +268,17 @@ class MongodbHandler:
         except Exception as error:
             self._log.log_and_raise_error(('A problem occured when aggregating the collection {} with the pipeline {}. \nError: {}').format(collection_name, aggregation_pipeline, error))
 
-        return self.convert_mongo_data_into_dataframe(data, index)
+        return self.convert_mongo_data_into_dataframe(data, index, collection_name)
 
-    def convert_mongo_data_into_dataframe(self, data, index: str = None) -> pd.DataFrame():
+    def convert_mongo_data_into_dataframe(self, data, index: str = None, collection_name: str = None) -> pd.DataFrame():
 
         data = list(data)
         try:
             if len(data)> 0:
-                self._log.info(('{} rows were fetched from the database').format(len(data)))
+                if collection_name:
+                    self._log.info(('{} rows were fetched from the {} collection').format(len(data), collection_name))
+                else:
+                    self._log.info(('{} rows were fetched from the database').format(len(data)))
                 df = pd.DataFrame(data)
                 if index is not None:
                     df.set_index(index, inplace=True)