create a new db function

db_operation.py

@@ -57,6 +57,11 @@ def _get_most_recent(table_name, ts_column='date'):
         # convert date to datetime object
         df[ts_column] = pd.to_datetime(df[ts_column])
         return df
+    
+def get_all_portfolio_profile():
+    df = _get_all_row(ts.PORTFOLIO_TABLE)
+    # df['date'] = pd.to_datetime(df['date'])
+    return df
 
 def get_most_recent_portfolio_profile():
     df = _get_most_recent(ts.PORTFOLIO_TABLE)
@@ -82,4 +87,25 @@ def append_to_stocks_price_table(df):
 def get_all_stocks():
     with create_engine(db_url).connect() as conn:
         all_stocks = pd.read_sql(ts.STOCKS_DETAILS_TABLE, con=conn)
-        return all_stocks
+        return all_stocks
+
+def _get_all_row(table_name):
+    with create_engine(db_url).connect() as conn:
+        df = pd.read_sql(table_name, con=conn)
+        return df
+
+def get_all_stocks_price():
+    '''
+    return all entries in stocks price table
+    '''
+    return _get_all_row(ts.STOCKS_PRICE_TABLE)
+
+def get_stocks_price(tickers: list[str]):
+    '''
+    return df of stock price within ticker in stocks price table
+    '''
+    query = f"SELECT * FROM {ts.STOCKS_PRICE_TABLE} WHERE ticker IN {tuple(tickers)}"
+    with create_engine(db_url).connect() as conn:
+        df = pd.read_sql(query, con=conn)
+        df.time = pd.to_datetime(df.time)
+        return df