app.py

import os
os.system("pip install streamlit pandas xlsxwriter openpyxl")

import streamlit as st
import pandas as pd
from io import BytesIO

st.set_page_config(page_title="Protein Repeat Comparator", layout="centered")
st.title("🧬 Protein Repeat Comparator")
st.write("Upload two Excel files with protein data. Frequency values should start from the second row.")

uploaded_file1 = st.file_uploader("Upload First Excel File", type=["xlsx"])
uploaded_file2 = st.file_uploader("Upload Second Excel File", type=["xlsx"])

if uploaded_file1 and uploaded_file2:
    try:
        df1 = pd.read_excel(uploaded_file1, header=0)
        df2 = pd.read_excel(uploaded_file2, header=0)

        df1.columns = df1.columns.astype(str)
        df2.columns = df2.columns.astype(str)

        id_col = df1.columns[0]
        name_col = df1.columns[1]
        repeat_columns = df1.columns[2:]

        differences = []

        for _, row1 in df1.iterrows():
            entry_id = row1[id_col]
            protein_name = row1[name_col]

            row2_match = df2[(df2[id_col] == entry_id) & (df2[name_col] == protein_name)]
            if row2_match.empty:
                continue

            row2 = row2_match.iloc[0]

            for repeat_col in repeat_columns:
                freq1 = row1[repeat_col]
                freq2 = row2[repeat_col]

                if pd.isna(freq1) or pd.isna(freq2) or freq1 == 0:
                    continue

                if freq1 != freq2:
                    diff = abs(freq1 - freq2)
                    pct_change = ((freq2 - freq1) / freq1) * 100
                    differences.append({
                        id_col: entry_id,
                        name_col: protein_name,
                        "Repeat": repeat_col,
                        "Frequency File 1": freq1,
                        "Frequency File 2": freq2,
                        "Difference": diff,
                        "%age Change": pct_change
                    })

        if differences:
            result_df = pd.DataFrame(differences)
            result_df = result_df.sort_values(by="Difference", ascending=False)

            # Style for Excel (green for +, red for -)
            def color_pct(val):
                if val > 0:
                    return 'color: green'
                elif val < 0:
                    return 'color: red'
                return ''

            styled_df = result_df.style.applymap(color_pct, subset=["%age Change"])

            output = BytesIO()
            with pd.ExcelWriter(output, engine='openpyxl') as writer:
                styled_df.to_excel(writer, index=False, sheet_name="Changed Repeats")
            output.seek(0)

            st.success("✅ Comparison complete. Showing only changed repeats.")
            st.download_button(
                label="📥 Download Excel",
                data=output,
                file_name="changed_repeats_with_percentage.xlsx",
                mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
            )
        else:
            st.info("No changes in repeat frequencies were found.")

    except Exception as e:
        st.error(f"⚠ Error: {e}")