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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()
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