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, 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

for file in uploaded_files:
    homorepeats, sequence_data = process_csv(file)
    if homorepeats is not None:
        all_homorepeats.update(homorepeats)
        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, filenames)

    # Download the Excel file
    st.download_button(
        label="Download Excel file",
        data=excel_file,
        file_name="protein_homorepeat_results.xlsx",
        mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
    )

    # Step 4: Display summary table
    if st.checkbox("Show Results Table"):
        # Convert the sequences data into a DataFrame for easy display
        rows = []
        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)