Update app.py

app.py

@@ -54,31 +54,44 @@ def process_csv(file):
 
     return homorepeats, sequence_data
 
-# Function to generate and download Excel workbook
-def create_excel(sequences_data, homorepeats):
+# Function to generate and download Excel workbook with file names as separators
+def create_excel(sequences_data, homorepeats, filenames):
     output = BytesIO()
     workbook = xlsxwriter.Workbook(output, {'in_memory': True})
     worksheet = workbook.add_worksheet()
 
-    # Write the header
-    worksheet.write(0, 0, "Entry ID")
-    worksheet.write(0, 1, "Protein Name")
-    col = 2
-    for repeat in sorted(homorepeats):
-        worksheet.write(0, col, repeat)
-        col += 1
-
-    # Write data for each sequence
-    row = 1
-    for entry_id, protein_name, freq in sequences_data:
-        worksheet.write(row, 0, entry_id)
-        worksheet.write(row, 1, protein_name)
+    row = 0
+
+    # Iterate through sequences data grouped by filenames
+    for file_index, file_data in enumerate(sequences_data):
+        filename = filenames[file_index]
+
+        # Write filename as a separator row
+        worksheet.write(row, 0, f"File: {filename}")
+        row += 1
+
+        # Write the header for the current file
+        worksheet.write(row, 0, "Entry ID")
+        worksheet.write(row, 1, "Protein Name")
         col = 2
         for repeat in sorted(homorepeats):
-            worksheet.write(row, col, freq.get(repeat, 0))
+            worksheet.write(row, col, repeat)
             col += 1
         row += 1
 
+        # Write data for each sequence in the current file
+        for entry_id, protein_name, freq in file_data:
+            worksheet.write(row, 0, entry_id)
+            worksheet.write(row, 1, protein_name)
+            col = 2
+            for repeat in sorted(homorepeats):
+                worksheet.write(row, col, freq.get(repeat, 0))
+                col += 1
+            row += 1
+
+        # Add an empty row as a separator between files
+        row += 1
+
     workbook.close()
     output.seek(0)
     return output
@@ -93,18 +106,20 @@ uploaded_files = st.file_uploader("Upload CSV files", accept_multiple_files=True
 if uploaded_files:
     all_homorepeats = set()
     all_sequences_data = []
+    filenames = []
 
     for file in uploaded_files:
         homorepeats, sequence_data = process_csv(file)
         if homorepeats is not None:
             all_homorepeats.update(homorepeats)
-            all_sequences_data.extend(sequence_data)
+            all_sequences_data.append(sequence_data)
+            filenames.append(file.name)
 
     if all_sequences_data:
         st.success(f"Processed {len(uploaded_files)} files successfully!")
 
         # Step 3: Generate and download the Excel report
-        excel_file = create_excel(all_sequences_data, all_homorepeats)
+        excel_file = create_excel(all_sequences_data, all_homorepeats, filenames)
 
         # Download the Excel file
         st.download_button(
@@ -118,10 +133,12 @@ if uploaded_files:
         if st.checkbox("Show Results Table"):
             # Convert the sequences data into a DataFrame for easy display
             rows = []
-            for entry_id, protein_name, freq in all_sequences_data:
-                row = {"Entry ID": entry_id, "Protein Name": protein_name}
-                row.update({repeat: freq.get(repeat, 0) for repeat in sorted(all_homorepeats)})
-                rows.append(row)
+            for file_index, file_data in enumerate(all_sequences_data):
+                filename = filenames[file_index]
+                for entry_id, protein_name, freq in file_data:
+                    row = {"Filename": filename, "Entry ID": entry_id, "Protein Name": protein_name}
+                    row.update({repeat: freq.get(repeat, 0) for repeat in sorted(all_homorepeats)})
+                    rows.append(row)
 
             result_df = pd.DataFrame(rows)
-            st.dataframe(result_df)
+            st.dataframe(result_df)