app.py

import gradio as gr
import pandas as pd
import requests
from io import BytesIO

def convert_parquet_to_csv(parquet_file=None, parquet_url=None):
    # Read the Parquet file either from an upload or a URL
    if parquet_file is not None:
        df = pd.read_parquet(parquet_file.name)
    elif parquet_url is not None:
        response = requests.get(parquet_url)
        response.raise_for_status()  # Check that the request was successful
        df = pd.read_parquet(BytesIO(response.content))
    else:
        raise ValueError("Either parquet_file or parquet_url must be provided")
    
    # Clean string columns to handle any invalid UTF-8 sequences
    for col in df.select_dtypes(include=["object"]).columns:
        df[col] = df[col].apply(
            lambda x: x.encode("utf-8", errors="replace").decode("utf-8", errors="replace") 
            if isinstance(x, str) else x
        )
    
    # Convert the DataFrame to CSV format
    csv_data = df.to_csv(index=False)
    
    # Save the CSV data to a file
    output_file_path = "output.csv"
    with open(output_file_path, "w", encoding="utf-8") as f:
        f.write(csv_data)
    
    return output_file_path

demo = gr.Interface(
    fn=convert_parquet_to_csv,
    inputs=[gr.File(label="Parquet File"), gr.Textbox(label="Parquet File URL")],
    outputs=[gr.File(label="CSV Output")],
    title="Parquet to CSV Converter",
    description="Convert a Parquet file to CSV format from a downloadable link or file upload"
)

if __name__ == "__main__":
    demo.launch()