app.py

import pandas as pd
import streamlit as st
import csv
import io
import matplotlib.pyplot as plt
import numpy as np
from second import double_main
from pre import preprocess_csv, load_data, fill_missing_data




def single_main(uploaded_file):  
    # st.title('Single CSV Analyzer')

    # uploaded_file = st.file_uploader("Upload CSV file", type="csv")

    if uploaded_file is not None:
       # Process the csv files with header
        filet = uploaded_file.read()
        processed_output = preprocess_csv(filet)
        processed_file = io.StringIO(processed_output.getvalue())
        data = load_data(processed_file)

        data = fill_missing_data(data, 4, 0)
        data['Start datetime'] = pd.to_datetime(data['Start datetime'], errors='coerce')
        data['End datetime'] = pd.to_datetime(data['End datetime'], errors='coerce')
        data['Time spent'] = (data['End datetime'] - data['Start datetime']).dt.total_seconds()

        # st.write(data)

       # Display scenarios with status "failed" grouped by functional area
        failed_scenarios = data[data['Status'] == 'FAILED']
        passed_scenarios = data[data['Status'] == 'PASSED']
        # selected_status = st.selectbox("Select a status", ['Failed', 'Passed'])
         # Use radio buttons for selecting status
        selected_status = st.radio("Select a status", ['Failed', 'Passed'])

        # Determine which scenarios to display based on selected status
        if selected_status == 'Failed':
            unique_areas = np.append(failed_scenarios['Functional area'].unique(), "All")
            selected_scenarios = failed_scenarios
            selected_functional_area = st.selectbox("Select a functional area", unique_areas, index=len(unique_areas)-1)        
        elif selected_status == 'Passed':
            unique_areas = np.append(passed_scenarios['Functional area'].unique(), "All")
            selected_scenarios = passed_scenarios
            selected_functional_area = st.selectbox("Select a functional area", unique_areas, index=len(unique_areas)-1)        
        else:  
            selected_scenarios = None
        
        if selected_scenarios is not None:
            # st.write(f"Scenarios with status '{selected_status}' grouped by functional area:")
            st.markdown(f"### Scenarios with status '{selected_status}' grouped by functional area:")
            
            # Handle the "All" option
           # Filter scenarios based on selected functional area
            if selected_functional_area != "All":
                filtered_scenarios = selected_scenarios[selected_scenarios['Functional area'] == selected_functional_area]
            else:
                filtered_scenarios = selected_scenarios

             # Calculate the average time spent for each functional area
            average_time_spent_seconds = filtered_scenarios.groupby('Functional area')['Time spent'].mean().reset_index()

            # Convert average time spent from seconds to minutes and seconds format
            average_time_spent_seconds['Time spent'] = pd.to_datetime(average_time_spent_seconds['Time spent'], unit='s').dt.strftime('%M:%S')

            # Group by functional area and get the start datetime for sorting
            start_datetime_group = filtered_scenarios.groupby('Functional area')['Start datetime'].min().reset_index()

            # Merge average_time_spent_seconds and start_datetime_group
            average_time_spent_seconds = average_time_spent_seconds.merge(start_datetime_group, on='Functional area')

            # Filter scenarios based on selected functional area
            
            grouped_filtered_failed_scenarios = filtered_scenarios.groupby('Functional area')[['Scenario name', 'Error message']].apply(lambda x: x.reset_index(drop=True))
            st.dataframe(grouped_filtered_failed_scenarios)
        
        
         # Display total count of failures
            fail_count = len(failed_scenarios)
            st.write(f"Failing scenarios Count: {fail_count}")
        # Display total count of Passing
            pass_count = len(passed_scenarios)
            st.write(f"Passing scenarios Count: {pass_count}")

            # Sort the average time spent table by start datetime
            average_time_spent_seconds = average_time_spent_seconds.sort_values(by='Start datetime')

           # Display average time spent on each functional area in a table
            st.markdown("### Average Time Spent on Each Functional Area")
            st.dataframe(average_time_spent_seconds)

        # Create and display bar graph of errors by functional area
            st.write("### Bar graph showing number of failures in each functional area:")
            error_counts = failed_scenarios['Functional area'].value_counts()
            plt.figure(figsize=(10, 6))
            plt.bar(error_counts.index, error_counts.values)
            plt.xlabel('Functional Area')
            plt.ylabel('Number of Errors')
            plt.title('Number of Errors by Functional Area')
            plt.xticks(rotation=45, ha='right')
            plt.tight_layout()  # Add this line to adjust layout
            st.pyplot(plt)

        else:
            st.write("### No scenarios with status 'failed' found.")  
    pass

def main():
    st.title('Batch Run CSV Analyser')

    # Initially we are in single file processing mode
    if "mode" not in st.session_state:
        st.session_state["mode"] = "single"

    mode_display = f'## Current mode: {st.session_state["mode"].title()} mode'
    st.sidebar.markdown(mode_display)

    # Add a button to switch between modes
    btn_label = "Switch to Compare mode" if st.session_state["mode"] == "single" else "Switch to Single mode"
    if st.sidebar.button(btn_label):
        if st.session_state["mode"] == "single":
            st.session_state["mode"] = "compare"
        else:
            st.session_state["mode"] = "single"

    # Only show the second file uploader in compare mode
    if st.session_state["mode"] == "single":
        uploaded_file_1 = st.sidebar.file_uploader("Upload CSV file", type="csv")
        if uploaded_file_1 is not None:
            single_main(uploaded_file_1)
    else:
        uploaded_file_1 = st.sidebar.file_uploader("Upload CSV file 1", type="csv")
        uploaded_file_2 = st.sidebar.file_uploader("Upload CSV file 2", type="csv")
        if uploaded_file_1 is not None and uploaded_file_2 is not None:
            double_main(uploaded_file_1, uploaded_file_2)

if __name__ == "__main__":
    main()