Implement button for export matching in app.py: add a button to initiate the creation of a name-to-ID mapping and apply best match logic, enhancing user interaction and functionality during the export process.

app.py

@@ -147,28 +147,29 @@ with tab1:
             st.write('starting name matching')
             st.session_state['projections_df'] = find_name_mismatches(st.session_state['portfolio'], st.session_state['projections_df'])
             if csv_file is not None and 'export_dict' not in st.session_state:
-                    # Create a dictionary of Name to Name+ID from csv_file
-                    try:
-                        name_id_map = dict(zip(
-                            st.session_state['csv_file']['Name'], 
-                            st.session_state['csv_file']['Name + ID']
-                        ))
-                    except:
-                        name_id_map = dict(zip(
-                            st.session_state['csv_file']['Nickname'], 
-                            st.session_state['csv_file']['Id']
-                        ))
-                    
-                    # Function to find best match
-                    def find_best_match(name):
-                        best_match = process.extractOne(name, name_id_map.keys())
-                        if best_match and best_match[1] >= 85:  # 85% match threshold
-                            return name_id_map[best_match[0]]
-                        return name  # Return original name if no good match found
-                    
-                    # Apply the matching
-                    projections['upload_match'] = projections['player_names'].apply(find_best_match)
-                    st.session_state['export_dict'] = dict(zip(projections['player_names'], projections['upload_match']))
+                    if st.button('Prepare export matching'):
+                        # Create a dictionary of Name to Name+ID from csv_file
+                        try:
+                            name_id_map = dict(zip(
+                                st.session_state['csv_file']['Name'], 
+                                st.session_state['csv_file']['Name + ID']
+                            ))
+                        except:
+                            name_id_map = dict(zip(
+                                st.session_state['csv_file']['Nickname'], 
+                                st.session_state['csv_file']['Id']
+                            ))
+                        
+                        # Function to find best match
+                        def find_best_match(name):
+                            best_match = process.extractOne(name, name_id_map.keys())
+                            if best_match and best_match[1] >= 85:  # 85% match threshold
+                                return name_id_map[best_match[0]]
+                            return name  # Return original name if no good match found
+                        
+                        # Apply the matching
+                        projections['upload_match'] = projections['player_names'].apply(find_best_match)
+                        st.session_state['export_dict'] = dict(zip(projections['player_names'], projections['upload_match']))
             
             st.session_state['origin_portfolio'] = st.session_state['portfolio'].copy()
             st.write('name matching complete')