testing

src/streamlit_app.py

@@ -1316,38 +1316,24 @@ if selected_tab == 'Optimals':
                     )
         
     if site_var == 'Draftkings':
-        if 'working_seed' in st.session_state:
-            st.session_state.working_seed = st.session_state.working_seed
-            if player_var2 != []:
-                st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-            elif player_var2 == []:
-                st.session_state.working_seed = dk_lineups.copy()
-            st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
-        elif 'working_seed' not in st.session_state:
+        st.session_state.working_seed = dk_lineups.copy()
+        st.session_state.working_seed = st.session_state.working_seed
+        if player_var2 != []:
+            st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
+        elif player_var2 == []:
             st.session_state.working_seed = dk_lineups.copy()
-            st.session_state.working_seed = st.session_state.working_seed
-            if player_var2 != []:
-                st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-            elif player_var2 == []:
-                st.session_state.working_seed = dk_lineups.copy()
-            st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+        st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+            
         
     elif site_var == 'Fanduel':
-        if 'working_seed' in st.session_state:
-            st.session_state.working_seed = st.session_state.working_seed
-            if player_var2 != []:
-                st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-            elif player_var2 == []:
-                st.session_state.working_seed = fd_lineups.copy()
-            st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
-        elif 'working_seed' not in st.session_state:
+        st.session_state.working_seed = fd_lineups.copy()
+        st.session_state.working_seed = st.session_state.working_seed
+        if player_var2 != []:
+            st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
+        elif player_var2 == []:
             st.session_state.working_seed = fd_lineups.copy()
-            st.session_state.working_seed = st.session_state.working_seed
-            if player_var2 != []:
-                st.session_state.working_seed = st.session_state.working_seed[np.equal.outer(st.session_state.working_seed, player_var2).any(axis=1).all(axis=1)]
-            elif player_var2 == []:
-                st.session_state.working_seed = fd_lineups.copy()
-            st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+        st.session_state.data_export_display = pd.DataFrame(st.session_state.working_seed[0:lineup_num_var], columns=column_names)
+            
     st.session_state.data_export_display = st.session_state.data_export_display[st.session_state.data_export_display['salary'] >= salary_min_var]
     st.session_state.data_export_display = st.session_state.data_export_display[st.session_state.data_export_display['salary'] <= salary_max_var]
     st.session_state.data_export_display = st.session_state.data_export_display[st.session_state.data_export_display['Team_count'] >= min_stacks_var]
@@ -1373,7 +1359,6 @@ if selected_tab == 'Optimals':
             elif sport_var == 'WNBA':
                 map_columns = ['G1', 'G2', 'F1', 'F2', 'F3', 'UTIL']
             for col_idx in map_columns:
-                print(export_file[col_idx])
                 export_file[col_idx] = export_file[col_idx].map(fd_id_map)
         elif type_var == 'Showdown':
             map_columns = ['CPT', 'FLEX1', 'FLEX2', 'FLEX3', 'FLEX4', 'FLEX5']