Update app.py

app.py

@@ -1,22 +1,26 @@
 import pandas as pd
+import openpyxl
 import gradio as gr
-import os
+import io
+import base64
 from datetime import datetime
 
-def convert_and_save_local(file_path, direction):
+def convert_schedule(file_path, direction):
     if file_path is None:
-        return pd.DataFrame({'Message': ['Please upload a file']}), "No file uploaded"
+        return pd.DataFrame({'Error': ['Please upload a file']}), None
         
     try:
-        # [Same conversion logic as before - truncated for brevity]
+        # 1. Load raw header rows to determine day labels
         raw = pd.read_excel(file_path, header=None)
         header1 = raw.iloc[0, 1:].astype(object)
         header2 = raw.iloc[1, 1:].astype(object)
 
+        # Decide which header row to use: prefer second if fully populated
         if header2.notna().all() and not header2.str.startswith('Unnamed').any():
             days = header2.tolist()
             data_start = 2
         else:
+            # Forward-fill merged first-row headers
             days = []
             last = None
             for val in header1:
@@ -27,79 +31,163 @@ def convert_and_save_local(file_path, direction):
                     days.append(last)
             data_start = 1
 
-        df = pd.read_excel(file_path, header=data_start, index_col=0, usecols=[0] + list(range(1, len(days) + 1)))
+        # 2. Load actual data using resolved day columns
+        df = pd.read_excel(
+            file_path,
+            header=data_start,
+            index_col=0,
+            usecols=[0] + list(range(1, len(days) + 1))
+        )
         df.columns = [str(day) for day in days]
+
+        # 3. Retain original day column order
         day_cols = list(df.columns)
 
+        # 4. Build assignment mapping via explicit iteration
         assignments = {}
         if direction == 'A to B':
+            # Models in rows → Texters as rows
             for model in df.index.astype(str):
                 for day in day_cols:
                     cell = df.at[model, day]
-                    if pd.isna(cell): continue
+                    if pd.isna(cell):
+                        continue
                     for texter in str(cell).split(','):
                         texter = texter.strip()
-                        if not texter or texter.lower() in ['nan', 'none', '']: continue
+                        if not texter or texter.lower() in ['nan', 'none', '']:
+                            continue
                         assignments.setdefault(texter, {d: [] for d in day_cols})
                         assignments[texter][day].append(model)
-            first_col_name = 'Texter'
+            
+            if not assignments:
+                result = pd.DataFrame(columns=day_cols)
+                first_col_name = 'Texter'
+            else:
+                index = sorted(assignments.keys())
+                result = pd.DataFrame(index=index, columns=day_cols)
+                first_col_name = 'Texter'
+                for texter, days_map in assignments.items():
+                    for day in day_cols:
+                        models = days_map.get(day, [])
+                        result.at[texter, day] = ', '.join(models) if models else 'OFF'
         else:
+            # Texters in rows → Models as rows
             for texter in df.index.astype(str):
                 for day in day_cols:
                     cell = df.at[texter, day]
-                    if pd.isna(cell): continue
+                    if pd.isna(cell):
+                        continue
                     for model in str(cell).split(','):
                         model = model.strip()
-                        if not model or model.lower() in ['nan', 'none', '']: continue
+                        if not model or model.lower() in ['nan', 'none', '']:
+                            continue
                         assignments.setdefault(model, {d: [] for d in day_cols})
                         assignments[model][day].append(texter)
-            first_col_name = 'Model'
-
-        if not assignments:
-            result = pd.DataFrame(columns=day_cols)
-        else:
-            index = sorted(assignments.keys())
-            result = pd.DataFrame(index=index, columns=day_cols)
-            for person, days_map in assignments.items():
-                for day in day_cols:
-                    items = days_map.get(day, [])
-                    result.at[person, day] = ', '.join(items) if items else 'OFF'
+            
+            if not assignments:
+                result = pd.DataFrame(columns=day_cols)
+                first_col_name = 'Model'
+            else:
+                index = sorted(assignments.keys())
+                result = pd.DataFrame(index=index, columns=day_cols)
+                first_col_name = 'Model'
+                for model, days_map in assignments.items():
+                    for day in day_cols:
+                        texters = days_map.get(day, [])
+                        result.at[model, day] = ', '.join(texters) if texters else 'OFF'
 
+        # 5. Cleanup axis names
         result.index.name = None
         result.columns.name = None
+
+        # For display, include index as a column
         display_df = result.reset_index().rename(columns={'index': first_col_name})
-        
-        # Save to local directory
-        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-        local_filename = f"converted_schedule_{timestamp}.csv"
-        local_path = os.path.join(os.getcwd(), local_filename)
-        
+
+        # 6. Create downloadable file using in-memory approach
         result_clean = result.copy().fillna('OFF')
+        
+        # Ensure all values are strings
+        for col in result_clean.columns:
+            result_clean[col] = result_clean[col].astype(str)
+
+        # Create CSV file in memory (more reliable than Excel)
         download_df = result_clean.reset_index().rename(columns={'index': first_col_name})
-        download_df.to_csv(local_path, index=False)
         
-        success_msg = f"✅ File saved successfully!\nLocation: {local_path}"
+        # Create CSV content
+        csv_buffer = io.StringIO()
+        download_df.to_csv(csv_buffer, index=False)
+        csv_content = csv_buffer.getvalue()
         
-        return display_df, success_msg
+        # Create filename with timestamp
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        filename = f"converted_schedule_{timestamp}.csv"
+        
+        # Return the CSV content for download
+        return display_df, (csv_content.encode('utf-8'), filename)
 
     except Exception as e:
-        error_df = pd.DataFrame({'Error': [f"Error: {str(e)}"]})
-        return error_df, f"❌ Error: {str(e)}"
+        error_msg = f"Error processing file: {str(e)}"
+        print(f"DEBUG: {error_msg}")
+        error_df = pd.DataFrame({'Error': [error_msg]})
+        return error_df, None
+
+# Wrapper function to handle the file download properly
+def process_and_download(file_path, direction):
+    display_result, download_data = convert_schedule(file_path, direction)
+    
+    if download_data is None:
+        return display_result, None
+    
+    # Create a temporary file that Gradio can serve
+    import tempfile
+    import os
+    
+    excel_content, filename = download_data
+    
+    # Save to a temporary file in the system temp directory
+    temp_dir = tempfile.gettempdir()
+    temp_path = os.path.join(temp_dir, filename)
+    
+    # Write CSV content
+    with open(temp_path, 'w', encoding='utf-8') as f:
+        f.write(excel_content.decode('utf-8'))
+    
+    return display_result, temp_path
 
+# Create the interface
 iface = gr.Interface(
-    fn=convert_and_save_local,
+    fn=process_and_download,
     inputs=[
-        gr.File(label='Upload Weekly Schedule (.xlsx)', file_types=['.xlsx', '.xls']),
-        gr.Radio(['A to B', 'B to A'], label='Convert Direction', value='A to B')
+        gr.File(
+            label='Upload Weekly Schedule (.xlsx)', 
+            file_count='single', 
+            file_types=['.xlsx', '.xls']
+        ),
+        gr.Radio(
+            ['A to B', 'B to A'], 
+            label='Convert Direction', 
+            value='A to B',
+            info='A to B: Models→Texters, B to A: Texters→Models'
+        )
     ],
     outputs=[
-        gr.Dataframe(label='Converted Schedule (Preview)'),
-        gr.Textbox(label='Save Status', lines=3)
+        gr.Dataframe(label='Converted Schedule (Preview)', wrap=True),
+        gr.File(label='Download Converted Schedule (.csv)')
     ],
-    title='🔄 Schedule Converter - Local Save',
-    description='Converts and saves the file directly to your current directory',
+    title='🔄 7-Day Schedule Converter',
+    description=(
+        '**How to use:**\n'
+        '1. Upload your Excel file with a 7-day schedule\n'
+        '2. Choose conversion direction\n'
+        '3. Preview the result and download the converted file\n\n'
+        '*Supports merged headers and handles Models ↔ Texters conversion*'
+    ),
     flagging_mode='never'
 )
 
 if __name__ == "__main__":
-    iface.launch(server_name='0.0.0.0', server_port=7860)
+    iface.launch(
+        server_name='0.0.0.0', 
+        server_port=7860,
+        share=False
+    )