add schema for stocks_price table

appComponents.py

@@ -38,7 +38,7 @@ def create_portfolio_overview(df_list):
     ip_eval_df = p_eval_df.interactive()
     isector_eval_df = sector_eval_df.interactive()
 
-    # TODO convert below to a class
+    
     ranged_ip_eval_df = ip_eval_df[ip_eval_df.date.between(
         range_slider.param.value_start, range_slider.param.value_end)]
     ranged_isector_eval_df = isector_eval_df[isector_eval_df.date.between(
@@ -425,7 +425,6 @@ class DrawDownCard(Viewer):
     def calculate_drawdown(self):
         df = self.eval_df.copy()
         # rolling max return
-        # TODO: consider adding this to the processing code
         df['rolling_max_return_p'] = df['portfolio_return_p'].rolling(
             window=len(df), min_periods=1).max()
         # calculate drawdown

portfolioEditingPage.py

@@ -3,8 +3,6 @@
 import panel as pn
 from utils import create_stocks_entry_from_excel, style_number, create_share_changes_report
 import datetime as dt
-import pytz
-import io
 from bokeh.models.widgets.tables import CheckboxEditor, NumberEditor, SelectEditor
 from utils import time_in_beijing
 import api
@@ -307,10 +305,9 @@ def app():
             floating_windows.append(floatpanel)
 
     def handle_sync_to_db(e):
-        # TODO: change to use profile df instead, because tabulator might not contain all entry
+        # TODO: change to use profile df instead, because tabulator might not contain all entry (currently have no problem)
         '''sync selected entry to db'''
         new_portfolio = portfolio_tabulator.value
-        # TODO when initially df is empty, there is a 0 row in df as place holder
         # only update selected row to db
         selected_portfolio = new_portfolio[new_portfolio['sync_to_db']]
         successed = update_portfolio_profile_to_db(selected_portfolio)

script/processing.py

@@ -151,7 +151,7 @@ def get_portfolio_evaluation(portfolio_stock, benchmark_stock, profile_df):
     return merged_df
 
 
-# TODO convert below to funciton
+
 
 def get_portfolio_sector_evaluation(portfolio_stock, benchmark_df):
     # aggregate on sector and day

table_schema.py

@@ -26,3 +26,15 @@ STOCKS_DETAILS_TABLE_SCHEMA = {
     'sector': str,
     'aggregate_sector': str
 }
+
+STOCKS_PRICE_TABLE = 'stocks_price'
+STOCKS_PRICE_TABLE = {
+    'time': 'datetime64[ns]',
+    'ticker': str,
+    'open': float,
+    'close': float,
+    'high': float,
+    'low': float,
+    'volume': int,
+    'money': float,
+}