Update app.py

app.py

@@ -6,6 +6,7 @@ from plotly.subplots import make_subplots
 import numpy as np
 import ast
 from pagination import paginator
+import style as cs
 
 
 
@@ -264,9 +265,11 @@ with news_analysis:
     # Fill NaN values in the new columns with 0
     events['Positive_Impacts'].fillna("", inplace=True)
     events['Negative_Impacts'].fillna("", inplace=True)
+    plot_sub_pos = events[events['Positive_Impacts']!='']
+    plot_sub_neg = events[events['Negative_Impacts']!='']
     # Create the line trace for stock prices
     line_stock = go.Scatter(x=events['Date'], y=events['Price'], mode='lines', name='OGDCL Close Price',
-        line=dict(dash='solid', color='royalblue', width=2),
+        line=dict(dash='solid', color=cs.close_line_color, width=2),
         # text=events['Cleaned_Headline'],
         # hovertext=events['FeatureSentiment'],
         customdata=events['Feature'],
@@ -276,31 +279,31 @@ with news_analysis:
     )
     # Create dummy traces for the legend
     dummy_positive = go.Scatter(x=[None], y=[None], mode='lines', name='Positive Impacts',
-        marker=dict(color='green', size=15), showlegend=True,
+        marker=dict(color=cs.pos_impacts_color, size=15), showlegend=True,
         # visible='legendonly'
         )
     dummy_negative = go.Scatter(x=[None], y=[None], mode='lines', name='Negative Impacts',
-        marker=dict(color='red', size=15), showlegend=True,
+        marker=dict(color=cs.neg_impacts_color, size=15), showlegend=True,
         # visible='legendonly'
     )
 
     fontsize = 12
     annotations = []
     # Create annotations for the Positive points
-    for index, row in events.iterrows():
+    for index, row in plot_sub_pos.iterrows():
         annotation1 = dict(x=row['Date'], y=row['Price'], text = row['Positive_Impacts'],
                 showarrow=True, arrowhead=0, # arrowcolor='black',
                 ax=10, ay=-20,   # Dynamic offset
-                font=dict(size=fontsize, color='green'),
+                font=dict(size=fontsize, color=cs.pos_impacts_color),
             )
         annotations.append(annotation1)
 
     # Create annotations for the Negative points
-    for index, row in events.iterrows():
+    for index, row in plot_sub_neg.iterrows():
         annotation2 = dict(x=row['Date'], y=row['Price'], text = row['Negative_Impacts'],
-                showarrow=True, arrowhead=0, arrowcolor='blue',
+                showarrow=True, arrowhead=0, arrowcolor=cs.close_line_color,
                 ax=10, ay=-20,   # Dynamic offset
-                font=dict(size=fontsize, color='red'),
+                font=dict(size=fontsize, color=cs.neg_impacts_color),
             )
         annotations.append(annotation2)
 
@@ -382,7 +385,7 @@ with news_analysis:
     print(dates, len(dates))
     num_dates = len(dates)
     items_per_page = min(num_dates, 5)
-    for i, date in paginator("Select Page Number", dates,  items_per_page=items_per_page, on_sidebar=False):
+    for i, date in paginator("Select Page Number", dates,  items_per_page=items_per_page, on_sidebar=False, ukey='news_pages'):
         st.write(f'<span style="font-size: large;"><b>Date:</b> <u>{date}</u></span>', unsafe_allow_html=True)
         
 
@@ -415,7 +418,7 @@ with news_analysis:
             
 with trade_recs:
     st.header("Trading Recommendations")
-    line_color = 'blue'
+
      # Create the line trace for stock prices
     # Dropdown for selecting the indicator
     selected_indicator = st.selectbox("Indicator to Show", ['EMA 9', 'EMA 55', 'MACD', 'RSI'])
@@ -432,7 +435,7 @@ with trade_recs:
         column = 'RSI_Signals'
         hover_text = '%{x}<br>Close: %{y}<br> RSI_Signal: %{customdata}<br>'
     line_stock = go.Scatter(x=events['Date'], y=events['Price'], mode='lines', name='OGDCL Close Price',
-        line=dict(dash='solid',color=line_color, width=2),   # color='royalblue'
+        line=dict(dash='solid',color=cs.close_line_color, width=2),   # color='royalblue'
         text=[column],
         # hovertext=events['FeatureSentiment'],
         customdata=events[column],
@@ -442,31 +445,31 @@ with trade_recs:
     )
     # Create dummy traces for the legend
     dummy_positive = go.Scatter(x=[None], y=[None], mode='lines', name='Positive Impacts',
-        marker=dict(color='black', size=15), showlegend=True,
+        marker=dict(color=cs.pos_impacts_color, size=15), showlegend=True,
         # visible='legendonly'
         )
     dummy_negative = go.Scatter(x=[None], y=[None], mode='lines', name='Negative Impacts',
-        marker=dict(color='red', size=15), showlegend=True,
+        marker=dict(color=cs.neg_impacts_color, size=15), showlegend=True,
         # visible='legendonly'
     )
 
     fontsize = 12
     annotations = []
     # Create annotations for the Positive points
-    for index, row in events.iterrows():
+    for index, row in plot_sub_pos.iterrows():
         annotation1 = dict(x=row['Date'], y=row['Price'], text = row['Positive_Impacts'],
                 showarrow=True, arrowhead=0, # arrowcolor='black',
                 ax=10, ay=-20,   # Dynamic offset
-                font=dict(size=fontsize, color='green'),
+                font=dict(size=fontsize, color=cs.pos_impacts_color),
             )
         annotations.append(annotation1)
 
     # Create annotations for the Negative points
-    for index, row in events.iterrows():
+    for index, row in plot_sub_neg.iterrows():
         annotation2 = dict(x=row['Date'], y=row['Price'], text = row['Negative_Impacts'],
-                showarrow=True, arrowhead=0, arrowcolor=line_color,
+                showarrow=True, arrowhead=0, arrowcolor=cs.close_line_color,
                 ax=10, ay=-20,   # Dynamic offset
-                font=dict(size=fontsize, color='red'),
+                font=dict(size=fontsize, color=cs.neg_impacts_color),
             )
         annotations.append(annotation2)
 
@@ -531,7 +534,25 @@ with trade_recs:
     trade_recs = events[['Date', 'Trading_Recommendations']]
     # Extract date component from the datetime column
     trade_recs['Date'] = trade_recs['Date'].dt.date
-    st.write(trade_recs)
+    # Convert back to Dictionaries from strings
+    trade_recs['Trading_Recommendations'] = trade_recs['Trading_Recommendations'].apply(convert_str_to_list)
+    dates = list(trade_recs['Date'].unique())
+    dates = np.sort(dates)
+    # Reverse the array to have the latest date at index 0
+    dates = dates[::-1]
+    num_dates = len(dates)
+    items_per_page = min(num_dates, 5)
+    for i, date in paginator("Select Page Number", dates,  items_per_page=items_per_page, on_sidebar=False, ukey='trade_pages'):
+        st.write(f'<span style="font-size: large;"><b>Date:</b> <u>{date}</u></span>', unsafe_allow_html=True)
+        
+        filtered_trades = trade_recs[trade_recs['Date'] == date]
+        filtered_trades.reset_index(inplace=True)
+        rec = filtered_trades['Trading_Recommendations'][0]
+        print(type(rec), rec)
+        trade_container = st.container(border=False)
+        trade_container.write(rec)
+
+    # st.write(trade_recs)
     
 with chat:
     st.balloons()