|
sql_query='''SELECT * FROM input_table |
|
WHERE text LIKE '%curls%';'''; |
|
import duckdb |
|
import pandas as pd |
|
import gradio as gr |
|
from datasets import load_dataset |
|
import tempfile |
|
import re |
|
|
|
|
|
max_rows = 20 |
|
df_display_kwargs = dict( |
|
wrap = True, |
|
max_rows = max_rows, |
|
type = "pandas", |
|
row_count = 3, |
|
col_count = 4, |
|
) |
|
|
|
dataset_choices = [ |
|
"rotten_tomatoes", |
|
"sciq", |
|
] |
|
|
|
def apply_sql(input_table, sql_query): |
|
|
|
|
|
match = re.search(r"\bFROM\s+(\w+)", sql_query, re.IGNORECASE) |
|
if match: |
|
table_name = match.group(1) |
|
|
|
sql_query = sql_query.replace(table_name, "input_table") |
|
|
|
output_df = duckdb.query(sql_query).to_df() |
|
|
|
return output_df |
|
|
|
def display_dataset(dataset_id): |
|
|
|
dataset = load_dataset(dataset_id, split="train") |
|
df = dataset.to_pandas() |
|
return df, df |
|
|
|
def upload_dataset(dataset_file): |
|
|
|
if dataset_file is None: |
|
return None, None |
|
|
|
print(dataset_file.name) |
|
|
|
df = pd.read_csv(dataset_file.name) |
|
|
|
return df, df |
|
|
|
|
|
def process_dataset(full_dataset, sql_query): |
|
input_table = full_dataset |
|
output_df = duckdb.query(sql_query).to_df() |
|
|
|
with tempfile.NamedTemporaryFile(delete=False) as temp_file: |
|
file_path = temp_file.name |
|
output_df.to_csv(file_path) |
|
|
|
return output_df, file_path |
|
|
|
|
|
theme = gr.themes.Soft( |
|
primary_hue="blue", |
|
neutral_hue="slate", |
|
) |
|
|
|
|
|
with gr.Blocks(analytics_enabled=False, theme=theme) as demo: |
|
full_dataset = gr.State() |
|
|
|
with gr.Column(): |
|
with gr.Row().style(equal_height=True): |
|
|
|
with gr.Column(variant="panel"): |
|
|
|
with gr.Row(): |
|
dark_mode_btn = gr.Button("Dark Mode", variant="primary") |
|
load_dataset_button = gr.Button("Load HF Dataset", variant="secondary") |
|
|
|
dataset_selector = gr.Dropdown(label="HF Dataset", choices=dataset_choices, value=dataset_choices[0]) |
|
|
|
|
|
with gr.Column(variant="compact"): |
|
|
|
with gr.Row(): |
|
sql_query_btn = gr.Button("Apply SQL Query", variant="secondary") |
|
download_dataset_btn = gr.Button("Download Queried Dataset", variant="primary") |
|
|
|
sql_query_comp = gr.Code(language=None, label="SQL Query", lines=3, value=sql_query) |
|
|
|
with gr.Row().style(equal_height=True): |
|
upload_dataset_comp = gr.File(label="Upload Dataset") |
|
download_dataset_comp = gr.File(label="Download Dataset") |
|
|
|
with gr.Column(variant="panel"): |
|
input_df_display = gr.Dataframe(**df_display_kwargs, label=f"Input Dataframe (Truncated to first {max_rows} Rows)") |
|
|
|
output_df_display = gr.Dataframe(**df_display_kwargs, label=f"Output Dataframe (Truncated to first {max_rows} Rows)") |
|
|
|
load_dataset_button.click(fn=display_dataset, inputs=[dataset_selector], outputs=[input_df_display, full_dataset]) |
|
upload_dataset_comp.change(fn=upload_dataset, inputs=[upload_dataset_comp], outputs=[input_df_display, full_dataset]) |
|
|
|
sql_query_btn.click(fn=apply_sql, inputs=[input_df_display, sql_query_comp], outputs=[output_df_display]) |
|
|
|
download_dataset_btn.click(fn=process_dataset, inputs=[full_dataset, sql_query_comp], outputs=[output_df_display, download_dataset_comp]) |
|
|
|
toggle_dark_mode_args = dict( |
|
fn=None, |
|
inputs=None, |
|
outputs=None, |
|
_js="""() => { |
|
if (document.querySelectorAll('.dark').length) { |
|
document.querySelectorAll('.dark').forEach(el => el.classList.remove('dark')); |
|
} else { |
|
document.querySelector('body').classList.add('dark'); |
|
} |
|
}""", |
|
) |
|
demo.load(**toggle_dark_mode_args) |
|
dark_mode_btn.click(**toggle_dark_mode_args) |
|
|