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import duckdb |
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import pandas as pd |
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import gradio as gr |
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from datasets import load_dataset |
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import tempfile |
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from query import sql_query |
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max_rows = 20 |
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max_cols = None |
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df_display_kwargs = dict( |
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wrap = True, |
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row_count = 3, |
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col_count = 4, |
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) |
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dataset_choices = [ |
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"rotten_tomatoes", |
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"sciq", |
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] |
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def apply_sql(input_table, sql_query): |
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output_df = duckdb.query(sql_query).to_df() |
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return output_df |
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def display_dataset(dataset_id): |
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dataset = load_dataset(dataset_id, split="train") |
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df = dataset.to_pandas() |
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display_df = df.iloc[:max_rows, :max_cols] |
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return display_df, df |
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def upload_dataset(dataset_file): |
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if dataset_file is None: |
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return None, None |
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df = pd.read_csv(dataset_file.name).iloc[:max_rows, :max_cols] |
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display_df = df.iloc[:max_rows, :max_cols] |
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return display_df, df |
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def process_dataset(full_dataset, sql_query): |
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input_table = full_dataset |
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output_df = duckdb.query(sql_query).to_df() |
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with tempfile.NamedTemporaryFile(delete=False) as temp_file: |
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file_path = temp_file.name |
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output_df.to_csv(file_path) |
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return output_df, file_path |
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theme = gr.themes.Soft( |
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primary_hue="blue", |
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neutral_hue="slate", |
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) |
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with gr.Blocks(theme=theme) as demo: |
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full_dataset = gr.State() |
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with gr.Column(): |
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with gr.Row().style(equal_height=True): |
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with gr.Column(variant="panel"): |
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with gr.Row(): |
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dark_mode_btn = gr.Button("Dark Mode", variant="primary") |
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load_dataset_button = gr.Button("Load HF Dataset", variant="secondary") |
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dataset_selector = gr.Dropdown(label="HF Dataset", choices=dataset_choices, value=dataset_choices[0]) |
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with gr.Column(variant="compact"): |
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with gr.Row(): |
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sql_query_btn = gr.Button("Apply SQL Query", variant="secondary") |
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download_dataset_btn = gr.Button("Download Queried Dataset", variant="primary") |
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sql_query_comp = gr.Code(language=None, label="SQL Query", lines=3, value=sql_query) |
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with gr.Row().style(equal_height=True): |
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upload_dataset_comp = gr.File(label="Upload Dataset") |
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download_dataset_comp = gr.File(label="Download Dataset") |
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with gr.Column(variant="panel"): |
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input_df_display = gr.Dataframe(**df_display_kwargs, label=f"Input Dataframe (Truncated to first {max_rows} Rows)") |
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output_df_display = gr.Dataframe(**df_display_kwargs, label=f"Output Dataframe (Truncated to first {max_rows} Rows)") |
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load_dataset_button.click(fn=display_dataset, inputs=[dataset_selector], outputs=[input_df_display, full_dataset]) |
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upload_dataset_comp.change(fn=upload_dataset, inputs=[upload_dataset_comp], outputs=[input_df_display, full_dataset]) |
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sql_query_btn.click(fn=apply_sql, inputs=[input_df_display, sql_query_comp], outputs=[output_df_display]) |
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download_dataset_btn.click(fn=process_dataset, inputs=[full_dataset, sql_query_comp], outputs=[output_df_display, download_dataset_comp]) |
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toggle_dark_mode_args = dict( |
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fn=None, |
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inputs=None, |
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outputs=None, |
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_js="""() => { |
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if (document.querySelectorAll('.dark').length) { |
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document.querySelectorAll('.dark').forEach(el => el.classList.remove('dark')); |
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} else { |
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document.querySelector('body').classList.add('dark'); |
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} |
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}""", |
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) |
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demo.load(**toggle_dark_mode_args) |
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dark_mode_btn.click(**toggle_dark_mode_args) |
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if __name__ == "__main__": |
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demo.launch(server_name="0.0.0.0", server_port=7860) |