Update app.py

app.py

@@ -1,37 +1,63 @@
 import pandas as pd
-import random
 import gradio as gr
-import os
 
-def group_names(file, members_per_group):
+def group_names(file, members_per_group, fixed_groups_input):
     # Read the CSV file
     df = pd.read_csv(file.name, encoding='utf-8')
     
-    # Shuffle the DataFrame
-    df = df.sample(frac=1).reset_index(drop=True)
+    # Parse fixed groups input
+    fixed_groups = [group.strip() for group in fixed_groups_input.split(';') if group.strip()]
+    fixed_groups_df_list = []
+    remaining_df = df.copy()
+
+    # Process fixed groups and create a list for additional members to be added
+    for group in fixed_groups:
+        group_names = [name.strip() for name in group.split(',') if name.strip()]
+        # Find these names in the DataFrame
+        matched_rows = remaining_df[remaining_df['Names'].isin(group_names)]
+        fixed_groups_df_list.append(matched_rows)
+        # Remove these names from the pool of remaining names
+        remaining_df = remaining_df[~remaining_df['Names'].isin(group_names)]
+
+    # Shuffle the remaining DataFrame
+    remaining_df = remaining_df.sample(frac=1).reset_index(drop=True)
     
-    # Grouping
-    groups = []
-    for i in range(0, len(df), members_per_group):
-        groups.append(df[i:i + members_per_group])
+    # Adjusting fixed groups to include additional members if they're under the specified group size
+    for i, group_df in enumerate(fixed_groups_df_list):
+        while len(group_df) < members_per_group and not remaining_df.empty:
+            group_df = pd.concat([group_df, remaining_df.iloc[[0]]])
+            remaining_df = remaining_df.iloc[1:].reset_index(drop=True)
+        fixed_groups_df_list[i] = group_df  # Update the group with added members
+
+    # Grouping the remaining names
+    groups = fixed_groups_df_list  # Start with adjusted fixed groups
+    for i in range(0, len(remaining_df), members_per_group):
+        groups.append(remaining_df[i:i + members_per_group])
 
     # Creating a new DataFrame for grouped data
-    grouped_df = pd.DataFrame({'Group': [f'Group {i+1}' for i, group in enumerate(groups)],
-                               'Names': [', '.join(group['Names'].tolist()) for group in groups]})
+    grouped_data = []
+    for i, group in enumerate(groups):
+        group_name = f'Group {i+1}'
+        names = ', '.join(group['Names'].tolist())
+        grouped_data.append({'Group': group_name, 'Members': names})
+    grouped_df = pd.DataFrame(grouped_data)
     
     return grouped_df
 
-def main_interface(file, members_per_group):
-    grouped_df = group_names(file, members_per_group)
+def main_interface(file, members_per_group, fixed_groups_input):
+    grouped_df = group_names(file, members_per_group, fixed_groups_input)
     # Save the DataFrame to a CSV file with UTF-8 encoding
     output_filename = '/tmp/grouped_names.csv'
     grouped_df.to_csv(output_filename, index=False, encoding='utf-8-sig')
-    # Return both the DataFrame for display and the file path for downloading
     return grouped_df, output_filename
 
 iface = gr.Interface(
     fn=main_interface,
-    inputs=[gr.File(label="Upload CSV File"), gr.Number(label="Members per Group", value=5)],
+    inputs=[
+        gr.File(label="Upload CSV File"),
+        gr.Number(label="Members per Group", value=4),
+        gr.Textbox(label="Fixed Groups (separated by semicolon)", placeholder="Name1, Name2; Name3, Name4", value=""),
+    ],
     outputs=[gr.Dataframe(label="Grouped Names"), gr.File(label="Download Grouped Names CSV")],
     allow_flagging="never"
 )