Refactor name matching logic in app.py: streamline the process of creating the name ID mapping and matching player names, improving efficiency and clarity in data handling.

app.py

@@ -145,47 +145,47 @@ with tab1:
             
             # Update projections_df with any new matches
             st.session_state['projections_df'] = find_name_mismatches(st.session_state['portfolio'], st.session_state['projections_df'])
-            if 'export_dict' not in st.session_state and csv_file is not None:
-                try:
-                    name_id_map = dict(zip(
-                        st.session_state['csv_file']['Name'], 
-                        st.session_state['csv_file']['Name + ID']
-                    ))
-                    print("Using Name + ID mapping")
-                except:
-                    name_id_map = dict(zip(
-                        st.session_state['csv_file']['Nickname'], 
-                        st.session_state['csv_file']['Id']
-                    ))
-                    print("Using Nickname + Id mapping")
-                
-                # Get all names at once
-                names = projections['player_names'].tolist()
-                choices = list(name_id_map.keys())
-                
-                # Create a dictionary to store matches
-                match_dict = {}
-                
-                # Process each name individually but more efficiently
-                for name in names:
-                    # Use extractOne with score_cutoff for efficiency
-                    match = process.extractOne(
-                        name,
-                        choices,
-                        score_cutoff=85
-                    )
-                    
-                    if match:
-                        match_dict[name] = name_id_map[match[0]]
-                    else:
-                        match_dict[name] = name
+            try:
+                name_id_map = dict(zip(
+                    st.session_state['csv_file']['Name'], 
+                    st.session_state['csv_file']['Name + ID']
+                ))
+                print("Using Name + ID mapping")
+            except:
+                name_id_map = dict(zip(
+                    st.session_state['csv_file']['Nickname'], 
+                    st.session_state['csv_file']['Id']
+                ))
+                print("Using Nickname + Id mapping")
+            
+            # Get all names at once
+            names = projections['player_names'].tolist()
+            choices = list(name_id_map.keys())
+            
+            # Create a dictionary to store matches
+            match_dict = {}
+            
+            # Process each name individually but more efficiently
+            for name in names:
+                # Use extractOne with score_cutoff for efficiency
+                match = process.extractOne(
+                    name,
+                    choices,
+                    score_cutoff=85
+                )
                 
-                print(f"Number of entries in match_dict: {len(match_dict)}")
-                print("Sample of match_dict:", list(match_dict.items())[:3])
+                if match:
+                    match_dict[name] = name_id_map[match[0]]
+                else:
+                    match_dict[name] = name
+            
+            print(f"Number of entries in match_dict: {len(match_dict)}")
+            print("Sample of match_dict:", list(match_dict.items())[:3])
 
-                # Apply the matches
-                projections['upload_match'] = projections['player_names'].map(match_dict)
-                st.session_state['export_dict'] = match_dict
+            # Apply the matches
+            projections['upload_match'] = projections['player_names'].map(match_dict)
+            st.session_state['export_dict'] = match_dict
+                
                 
             st.write(st.session_state['export_dict'])
             st.session_state['origin_portfolio'] = st.session_state['portfolio'].copy()