app.py

# Import necessary libraries
import gradio as gr
from typing import Dict, Any
from data_loader import read_dask_data, read_polars_data, read_another_dask_data

# Function to handle the data loading and processing logic
def load_and_process_data(dataset_choice: str, num_rows: int) -> Dict[str, Any]:
    try:
        # Load and process datasets based on user choice
        if dataset_choice == "Dask Data":
            data = read_dask_data()
            processed_data = data.head(num_rows)
        elif dataset_choice == "Polars Data":
            data = read_polars_data()
            processed_data = data.head(num_rows)
        elif dataset_choice == "Another Dask Data":
            data = read_another_dask_data()
            processed_data = data.head(num_rows)
        else:
            return {"error": "Invalid dataset choice."}

        # Optionally, include more complex data processing here

        # Return the processed data
        return {
            "Processed Data": processed_data
        }
    except Exception as e:
        # Log the exception
        print(f"Error processing data: {str(e)}")
        return {"error": "Unable to process data. Please check the logs for details."}

# Create a Gradio interface with more features
def create_interface():
    # Interface inputs
    dataset_choice = gr.inputs.Dropdown(["Dask Data", "Polars Data", "Another Dask Data"], label="Select Dataset")
    num_rows = gr.inputs.Slider(minimum=1, maximum=100, default=5, label="Number of Rows to Display")

    # Interface definition
    demo = gr.Interface(
        fn=load_and_process_data,
        inputs=[dataset_choice, num_rows],  # User can select dataset and number of rows
        outputs="json",  # Display output as JSON
        title="Enhanced Dataset Loader Demo",
        description="Interact with various datasets and select the amount of data to display.",
        allow_flagging="never"  # Disable flagging if not needed
    )

    demo.launch()

if __name__ == "__main__":
    create_interface()