sqlite3 db upload

app.py

@@ -1,4 +1,28 @@
 import streamlit as st
+import sqlite3
+import pandas as pd
+import streamlit as st
 
 x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+st.write(x, 'squared is', x * x)
+
+
+conn = sqlite3.connect('fin_data.db')
+c = conn.cursor()
+c.execute("""
+       select * from test
+""")
+
+rows = c.fetchall()
+
+# Extract column names from the cursor
+column_names = [description[0] for description in c.description]
+
+# Create a DataFrame
+df = pd.DataFrame(rows, columns=column_names)
+
+print(df)
+st.dataframe(df)
+
+conn.commit()
+conn.close()

fin_data_api.py

@@ -4,6 +4,7 @@ import json
 import requests
 import datetime
 import sqlite3
+import pandas as pd
 
 with open('secrets.json') as f:
     content = json.load(f)
@@ -53,14 +54,14 @@ def sentiment_analysis(headline:str) -> str:
 #print(res_sentiment['data'][0].keys())
 
 
-# put data in database after figuring out what data we want to store
-conn = sqlite3.connect('fin_data.db')
-c = conn.cursor()
-c.execute("""
-       select * from test
-""")
+# # put data in database after figuring out what data we want to store
+# conn = sqlite3.connect('fin_data.db')
+# c = conn.cursor()
+# c.execute("""
+#        insert into test values (2, 'test value two')
+# """)
 
-print(c.fetchall())
 
-conn.commit()
-conn.close()
+
+# conn.commit()
+# conn.close()

requirements.txt

@@ -16,4 +16,5 @@ pathos
 transformers
 requests
 datetime
-pysqlite3 == 0.5.2
+pysqlite3 == 0.5.2
+streamlit