Create read_predictions_from_db.py

read_predictions_from_db.py

@@ -0,0 +1,55 @@
+import pymongo
+import os
+import pandas as pd
+import logging
+
+
+class PredictionDBRead:
+    def __init__(self):
+        self.url = os.getenv('PREDICTION_DB_URL')
+        self.database = "indian_news_predictions_db"
+        self.collection = "indian_news_predictions_coll"
+        self.__client = None
+        self.__error = 0
+
+    def __connect(self):
+        try:
+            self.__client = pymongo.MongoClient(self.url)
+            _ = self.__client.list_database_names()
+        except Exception as conn_exception:
+            self.__error = 1
+            self.__client = None
+
+
+    def __read(self):
+        try:
+            db = self.__client[self.database]
+            coll = db[self.collection]
+            docs = []
+            for doc in coll.find():
+                docs.append(doc)
+            rss_df = pd.DataFrame(docs)
+        except Exception as insert_err:
+            self.__error = 1
+            rss_df = None
+        return rss_df
+
+    
+    def __close_connection(self):
+        if self.__client is not None:
+            self.__client.close()
+            self.__client = None
+
+    
+    def read_predictions_from_db(self):
+        rss_df = None
+        if self.url is not None:
+            if self.__error == 0:
+                self.__connect()
+            if self.__error == 0:
+                rss_df = self.__read()
+            if self.__error == 0:
+                logging.info("Prediction Data Read Successful")
+            if self.__client is not None:
+                self.__close_connection()
+        return rss_df