app.py

import gradio as gr
import pandas as pd
from clean import clean_data
from report import create_full_report, REPORT_DIR
import os
import tempfile

def clean_and_visualize(file, progress=gr.Progress()):
    # Load the data
    df = pd.read_csv(file.name)

    # Clean the data
    cleaned_df = None
    nonconforming_cells_before = None
    process_times = None
    removed_columns = None
    removed_rows = None

    for progress_value, status_text in clean_data(df):
        if isinstance(status_text, tuple):
            cleaned_df, nonconforming_cells_before, process_times, removed_columns, removed_rows = status_text
            progress(progress_value, desc="Cleaning completed")
        else:
            progress(progress_value, desc=status_text)

    # Generate full visualization report
    create_full_report(
        df,
        cleaned_df,
        nonconforming_cells_before,
        process_times,
        removed_columns,
        removed_rows
    )

    # Save cleaned DataFrame to a temporary CSV file
    with tempfile.NamedTemporaryFile(delete=False, suffix='.csv') as tmp_file:
        cleaned_df.to_csv(tmp_file.name, index=False)
        cleaned_csv_path = tmp_file.name

    # Collect all generated images
    image_files = [os.path.join(REPORT_DIR, f) for f in os.listdir(REPORT_DIR) if f.endswith('.png')]

    return cleaned_csv_path, image_files

def launch_app():
    with gr.Blocks() as app:
        gr.Markdown("# AI Data Cleaner")

        with gr.Row():
            file_input = gr.File(label="Upload CSV File")

        with gr.Row():
            clean_button = gr.Button("Start Cleaning")

        with gr.Row():
            progress_bar = gr.Progress()

        with gr.Row():
            cleaned_file_output = gr.File(label="Download Cleaned CSV", visible=False)

        with gr.Row():
            output_gallery = gr.Gallery(label="Visualization Results", show_label=True, elem_id="gallery", columns=[2],
                                        rows=[2], object_fit="contain", height="auto")

        def process_and_show_download(file):
            cleaned_csv_path, image_files = clean_and_visualize(file, progress=progress_bar)
            return gr.File.update(value=cleaned_csv_path, visible=True), image_files

        clean_button.click(
            fn=process_and_show_download,
            inputs=file_input,
            outputs=[cleaned_file_output, output_gallery]
        )

    app.launch()

if __name__ == "__main__":
    launch_app()