48 lines
1.7 KiB
Python
48 lines
1.7 KiB
Python
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()
|