app.py

import gradio as gr
import ast
import traceback

def optimize_and_debug(code):
    """Attempts to optimize and debug the given Python code."""
    try:
        tree = ast.parse(code)
        #  Rudimentary optimization:  This is a placeholder.  Real optimization is complex.
        #  Here we just check for unnecessary nested loops (a very simple example).
        nested_loops = False
        for node in ast.walk(tree):
            if isinstance(node, ast.For) and any(isinstance(subnode, ast.For) for subnode in ast.walk(node)):
                nested_loops = True
                break
        optimization_suggestions = []
        if nested_loops:
            optimization_suggestions.append("Consider optimizing nested loops.  They can significantly impact performance.")


        # Execution and error handling
        exec(code, {})  # Execute the code (Caution: security implications for untrusted input)
        return "Code executed successfully.", optimization_suggestions, ""

    except Exception as e:
        error_message = traceback.format_exc()
        return "Code execution failed.", [], error_message


iface = gr.Interface(
    fn=optimize_and_debug,
    inputs=gr.Textbox(lines=10, label="Enter your Python code here:"),
    outputs=[
        gr.Textbox(label="Result"),
        gr.Textbox(label="Optimization Suggestions"),
        gr.Textbox(label="Error Messages (if any)"),
    ],
    title="Python Code Optimizer & Debugger (Simplified)",
    description="Paste your Python code below.  This tool provides basic optimization suggestions and error reporting.  Note:  This is a simplified demonstration and does not replace a full debugger.",
)

iface.launch()