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

 # Remove duplicates from the primary key column
 df = df.drop_duplicates(subset=[primary_key_column], keep='first')

 # 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, primary_key_column):
 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,
 primary_key_column
 )

 # 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", file_count="single", file_types=[".csv"])

 with gr.Row():
 primary_key_dropdown = gr.Dropdown(label="Select Primary Key Column", choices=[], interactive=True)

 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="Cleaned CSV", visible=True)

 with gr.Row():
 output_gallery = gr.Gallery(
 label="Visualization Results",
 show_label=True,
 elem_id="gallery",
 columns=[3],
 rows=[3],
 object_fit="contain",
 height="auto",
 visible=False
 )

 def update_primary_key_options(file):
 if file is not None:
 df = pd.read_csv(file.name)
 return gr.Dropdown(choices=df.columns.tolist())

 def process_and_show_results(file, primary_key_column):
 cleaned_csv_path, image_files = clean_and_visualize(file, primary_key_column, progress=progress_bar)
 return (
 cleaned_csv_path,
 gr.Gallery(visible=True, value=image_files)
 )

 file_input.change(
 fn=update_primary_key_options,
 inputs=file_input,
 outputs=primary_key_dropdown
 )

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

 app.launch()


if __name__ == "__main__":
 launch_app()