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| # Import necessary libraries | |
| import pandas as pd | |
| import streamlit as st | |
| import csv | |
| import io | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| from pre import preprocess_uploaded_file | |
| import xlsxwriter | |
| # Main function to process 2 uploaded CSV files | |
| def double_main(uploaded_file1,uploaded_file2): | |
| # Check if both files are uploaded | |
| if uploaded_file1 is not None and uploaded_file2 is not None: | |
| # Preprocess the uploaded CSV files | |
| data_1 = preprocess_uploaded_file(uploaded_file1) | |
| data_2 = preprocess_uploaded_file(uploaded_file2) | |
| # Determine which file is older and newer | |
| if data_1['Start datetime'].min() < data_2['Start datetime'].min(): | |
| older_df = data_1 | |
| newer_df = data_2 | |
| else: | |
| older_df = data_2 | |
| newer_df = data_1 | |
| # Convert time columns to MM:SS format | |
| older_df['Time spent'] = pd.to_datetime(older_df['Time spent'], unit='s').dt.strftime('%M:%S') | |
| newer_df['Time spent'] = pd.to_datetime(newer_df['Time spent'], unit='s').dt.strftime('%M:%S') | |
| # Get start datetime of each file | |
| older_datetime = older_df['Start datetime'].min() | |
| newer_datetime = newer_df['Start datetime'].min() | |
| # Display start datetime of each file | |
| st.write(f"The older csv started on {older_datetime}") | |
| st.write(f"The newer csv started on {newer_datetime}") | |
| # Merge dataframes on 'scenario name' | |
| merged_df = pd.merge(older_df, newer_df, on=['Functional area', 'Scenario name'], suffixes=('_old', '_new')) | |
| # Filter scenarios that were failing and are still failing | |
| fail_to_fail_scenarios = merged_df[(merged_df['Status_old'] == 'FAILED') & (merged_df['Status_new'] == 'FAILED')] | |
| # Display Consistent Failures section | |
| st.markdown("### Consistent Failures(previously failing, now failing)") | |
| # Get failing scenarios count | |
| fail_count = len(fail_to_fail_scenarios) | |
| st.write(f"Failing scenarios Count: {fail_count}") | |
| # Display filtered dataframe | |
| columns_to_display1 = ['Functional area', 'Scenario name', 'Error message_old', 'Error message_new'] | |
| st.write(fail_to_fail_scenarios[columns_to_display1]) | |
| # Filter scenarios that were passing and now failing | |
| pass_to_fail_scenarios = merged_df[(merged_df['Status_old'] == 'PASSED') & (merged_df['Status_new'] == 'FAILED')] | |
| # Display New Failures section | |
| st.markdown("### New Failures(previously passing, now failing)") | |
| # Get failing scenarios count | |
| pass_fail_count = len(pass_to_fail_scenarios) | |
| st.write(f"Failing scenarios Count: {pass_fail_count}") | |
| # Display filtered dataframe | |
| columns_to_display2 = ['Functional area', 'Scenario name', 'Error message_new', 'Time spent_old','Time spent_new',] | |
| st.write(pass_to_fail_scenarios[columns_to_display2]) | |
| # Filter scenarios that were failing and now passing | |
| fail_to_pass_scenarios = merged_df[(merged_df['Status_old'] == 'FAILED') & (merged_df['Status_new'] == 'PASSED')] | |
| # Display New Passes section | |
| st.markdown("### New Passes(previously failing, now passing)") | |
| # Get passing scenarios count | |
| pass_count = len(fail_to_pass_scenarios) | |
| st.write(f"Passing scenarios Count: {pass_count}") | |
| # Display filtered dataframe | |
| columns_to_display3 = ['Functional area', 'Scenario name', 'Error message_old', 'Time spent_old','Time spent_new',] | |
| st.write(fail_to_pass_scenarios[columns_to_display3]) | |
| # Create a Pandas Excel writer using XlsxWriter as the engine | |
| excel_writer = pd.ExcelWriter('comparison_results.xlsx', engine='xlsxwriter') | |
| # Write each section to a separate sheet | |
| fail_to_fail_scenarios.loc[:, columns_to_display1].to_excel(excel_writer, sheet_name='Consistent Failures', index=False) | |
| pass_to_fail_scenarios.loc[:, columns_to_display2].to_excel(excel_writer, sheet_name='New Failures', index=False) | |
| fail_to_pass_scenarios.loc[:, columns_to_display3].to_excel(excel_writer, sheet_name='New Passes', index=False) | |
| # Add a sheet to store information about CSV versions | |
| csv_version_sheet = excel_writer.book.add_worksheet('CSV Details') | |
| # Write the CSV version information | |
| csv_version_sheet.write('A1', 'Older CSV:') | |
| csv_version_sheet.write('B1', 'Newer CSV:') | |
| csv_version_sheet.write('A2', older_df['Start datetime'].min().strftime('%Y-%m-%d %H:%M:%S')) | |
| csv_version_sheet.write('B2', newer_df['Start datetime'].min().strftime('%Y-%m-%d %H:%M:%S')) | |
| # Save the Excel file | |
| excel_writer.save() | |
| # Create a Download Excel button | |
| st.markdown("### Download Excel Report") | |
| st.markdown("Click below to download the comparison results in Excel format:") | |
| with open('comparison_results.xlsx', 'rb') as excel_file: | |
| excel_bytes = excel_file.read() | |
| st.download_button(label='Download Excel Report', data=excel_bytes, file_name='comparison_results.xlsx', key='excel-download') |