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| import gradio as gr | |
| import pandas as pd | |
| import pyarrow as pa | |
| import pyarrow.parquet as pq | |
| import tempfile | |
| css = ''' | |
| .gradio-container{max-width: 950px !important} | |
| h1{text-align:center} | |
| ''' | |
| DESCRIPTIONz= """## CSV to Parquet π | |
| """ | |
| def csv_to_parquet(file): | |
| df = pd.read_csv(file.name) | |
| table = pa.Table.from_pandas(df) | |
| with tempfile.NamedTemporaryFile(delete=False, suffix=".parquet") as tmp_file: | |
| pq.write_table(table, tmp_file) | |
| parquet_file_path = tmp_file.name | |
| return parquet_file_path | |
| with gr.Blocks(css=css, theme="Nymbo/Nymbo_Theme") as demo: | |
| gr.Markdown(DESCRIPTIONz) | |
| with gr.Row(): | |
| csv_input = gr.File(label="Upload CSV File", type="filepath", file_types=["text/csv"]) | |
| download_button = gr.File(label="Download Parquet File", interactive=False) | |
| convert_button = gr.Button("Convert CSV to Parquet") | |
| convert_button.click(fn=csv_to_parquet, inputs=[csv_input], outputs=[download_button]) | |
| gr.Markdown("π The speed of converting a CSV file to a .parquet file depends on the size and complexity of the CSV file.") | |
| demo.launch() |