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import gradio as gr
import pandas as pd
import os
from datetime import datetime
from clean import clean_data, get_numeric_columns
from report import create_full_report, REPORT_DIR
def clean_and_visualize(file, primary_key_column, progress=gr.Progress()):
# Read the CSV file
progress(0.05, desc="Reading CSV file")
df = pd.read_csv(file.name)
# Clean the data
progress(0.1, desc="Starting data cleaning")
cleaned_df, nonconforming_cells_before, process_times = clean_data(df, primary_key_column, progress)
progress(0.8, desc="Data cleaning completed")
# Calculate removed columns and rows
removed_columns = len(df.columns) - len(cleaned_df.columns)
removed_rows = len(df) - len(cleaned_df)
# Generate full visualization report
progress(0.9, desc="Generating report")
create_full_report(
df,
cleaned_df,
nonconforming_cells_before,
process_times,
removed_columns,
removed_rows,
primary_key_column
)
# Save cleaned data as CSV
progress(0.95, desc="Saving cleaned data")
current_time = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
cleaned_csv_path = os.path.join(f"cleaned_data_{current_time}.csv")
cleaned_df.to_csv(cleaned_csv_path, index=False)
# Collect all generated images
image_files = [os.path.join(REPORT_DIR, f) for f in os.listdir(REPORT_DIR) if f.endswith('.png')]
progress(1.0, desc="Process completed")
return cleaned_csv_path, image_files
def launch_app():
with gr.Blocks() as app:
gr.Markdown("# 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 None:
return gr.Dropdown(choices=[])
df = pd.read_csv(file.name)
numeric_columns = get_numeric_columns(df)
return gr.Dropdown(choices=numeric_columns)
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() |