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| import gradio as gr | |
| import sys | |
| import subprocess | |
| import importlib | |
| import io | |
| import contextlib | |
| from pygments import highlight | |
| from pygments.lexers import PythonLexer | |
| from pygments.formatters import HtmlFormatter | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| import pandas as pd | |
| # Function to install packages dynamically | |
| def install_package(package): | |
| subprocess.check_call([sys.executable, "-m", "pip", "install", package]) | |
| # Function to execute user code with output capturing and visualization support | |
| def execute_code(code, libraries): | |
| # Install libraries | |
| for library in libraries.splitlines(): | |
| if library.strip(): | |
| install_package(library.strip()) | |
| # Prepare output capturing | |
| output = io.StringIO() | |
| error_output = io.StringIO() | |
| # Execute the code | |
| try: | |
| with contextlib.redirect_stdout(output), contextlib.redirect_stderr(error_output): | |
| exec_globals = { | |
| 'plt': plt, | |
| 'np': np, | |
| 'pd': pd, | |
| } | |
| exec(code, exec_globals) | |
| # Check if a plot was created | |
| if plt.get_fignums(): | |
| plt.savefig('plot.png') | |
| plt.close() | |
| return output.getvalue(), error_output.getvalue(), 'plot.png' | |
| else: | |
| return output.getvalue(), error_output.getvalue(), None | |
| except Exception as e: | |
| return "", str(e), None | |
| # Function to highlight Python code | |
| def highlight_code(code): | |
| return highlight(code, PythonLexer(), HtmlFormatter(style="monokai")) | |
| # Define the Gradio interface | |
| with gr.Blocks(css=".gradio-container {background-color: #f0f0f0;}") as demo: | |
| gr.Markdown("# Advanced Python Code Executor") | |
| with gr.Tabs(): | |
| with gr.TabItem("Code Execution"): | |
| with gr.Row(): | |
| with gr.Column(scale=2): | |
| code_input = gr.Code(label="Python Code", language="python", lines=10) | |
| libraries_input = gr.TextArea(label="Libraries (one per line)", placeholder="e.g.\nrequests\nscipy", lines=3) | |
| execute_button = gr.Button("Run Code", variant="primary") | |
| with gr.Column(scale=1): | |
| output = gr.Textbox(label="Standard Output", lines=10) | |
| error_output = gr.Textbox(label="Error Output", lines=5) | |
| plot_output = gr.Image(label="Plot Output") | |
| with gr.TabItem("Code Highlighting"): | |
| code_to_highlight = gr.Code(label="Enter Python code to highlight", language="python", lines=10) | |
| highlight_button = gr.Button("Highlight Code") | |
| highlighted_code = gr.HTML(label="Highlighted Code") | |
| execute_button.click( | |
| fn=execute_code, | |
| inputs=[code_input, libraries_input], | |
| outputs=[output, error_output, plot_output] | |
| ) | |
| highlight_button.click( | |
| fn=highlight_code, | |
| inputs=[code_to_highlight], | |
| outputs=[highlighted_code] | |
| ) | |
| gr.Markdown(""" | |
| ## Features: | |
| - Execute Python code with custom library imports | |
| - Capture and display standard output and error messages separately | |
| - Support for data visualization with matplotlib | |
| - Code highlighting for better readability | |
| - Tab-based interface for different functionalities | |
| ## Tips: | |
| - Use `plt` for matplotlib, `np` for numpy, and `pd` for pandas (pre-imported) | |
| - Your plot will automatically be displayed if you use `plt.plot()` or similar functions | |
| """) | |
| # Launch the interface | |
| demo.launch() |