made hedonodon server ready

CRUDManager.py

@@ -1,48 +1,48 @@
-from DbSetup import engine, session, databaseUrl
-import pandas as pd
-from sqlalchemy import desc, select
-from Tables import Toots
-
-
-def calculateSentimentCount():
-    query = f'''SELECT DATE(datetime) as date, sentiment, COUNT(sentiment) as sentimentCount
-                FROM Toots
-                GROUP BY DATE(datetime),
-                sentiment
-                HAVING datetime >= DATE("now","-1 day")
-                AND datetime < DATE("now")'''
-    return pd.read_sql(
-        query,
-        databaseUrl,
-        parse_dates=["datetime"]
-    )
-
-def calculateSentimentMean(dataframe):
-    negativeSentimentSum = dataframe[dataframe['sentiment'] == 'negative']['sentimentCount'].sum() * -1
-    positiveSentimentSum = dataframe[dataframe['sentiment'] == 'positive']['sentimentCount'].sum()
-    sentimentSum = dataframe['sentimentCount'].sum()
-    sentimentMean = (negativeSentimentSum + positiveSentimentSum) / sentimentSum
-    sentimentDate = dataframe.loc[0]['date']
-    return pd.DataFrame.from_records(
-        [
-            {
-                'date': sentimentDate,
-                'sentimentsMean': sentimentMean
-            }
-        ]
-    )
-
-class CRUDManager():
-
-    def saveToDatabase(self, dataframe, table:str, useIndex=False):
-        try:
-            dataframe.to_sql(table, engine, index=useIndex, if_exists="append")
-        except:
-            print(f'Could not save data to {table}!')
-
-    def loadFromDatabase(self, table:str, indexColumn=None):
-        return pd.read_sql_table(table, databaseUrl, index_col=indexColumn)
-
-    def getLastToot(self):
-        stmt = select(Toots.tootId).order_by(desc('datetime'))
-        return session.scalars(stmt).first()
+from DbSetup import connection, engine, session, databaseUrl
+import pandas as pd
+from sqlalchemy import desc, select, sql
+from Tables import Toots
+
+
+def calculateSentimentCount():
+    query = f'''SELECT DATE(datetime) as date, sentiment, COUNT(sentiment) as sentimentCount
+                FROM Toots
+                GROUP BY DATE(datetime),
+                sentiment
+                HAVING datetime >= DATE("now","-1 day")
+                AND datetime < DATE("now")'''
+    return pd.read_sql(
+        sql.text(query),
+        connection,
+        parse_dates=["datetime"]
+    )
+
+def calculateSentimentMean(dataframe):
+    negativeSentimentSum = dataframe[dataframe['sentiment'] == 'negative']['sentimentCount'].sum() * -1
+    positiveSentimentSum = dataframe[dataframe['sentiment'] == 'positive']['sentimentCount'].sum()
+    sentimentSum = dataframe['sentimentCount'].sum()
+    sentimentMean = (negativeSentimentSum + positiveSentimentSum) / sentimentSum
+    sentimentDate = dataframe.loc[0]['date']
+    return pd.DataFrame.from_records(
+        [
+            {
+                'date': sentimentDate,
+                'sentimentsMean': sentimentMean
+            }
+        ]
+    )
+
+class CRUDManager():
+
+    def saveToDatabase(self, dataframe, table:str, useIndex=False):
+        try:
+            dataframe.to_sql(table, engine, index=useIndex, if_exists="append")
+        except:
+            print(f'Could not save data to {table}!')
+
+    def loadFromDatabase(self, table:str, indexColumn=None):
+        return pd.read_sql_table(table, connection, index_col=indexColumn)
+
+    def getLastToot(self):
+        stmt = select(Toots.tootId).order_by(desc('datetime'))
+        return session.scalars(stmt).first()