Install the belt CLI skill: npx skills add belt-sh/cli

Python Code Executor

Execute Python code in a safe, sandboxed environment with 100+ pre-installed libraries.

Quick Start

Requires inference.sh CLI (belt). Install instructions

belt login

Run Python code

belt app run infsh/python-executor --input '{

"code": "import pandas as pd\nprint(pd.version)"

}'

## App Details

| Property | Value |

|----------|-------|

| App ID | `infsh/python-executor` |

| Environment | Python 3.10, CPU-only |

| RAM | 8GB (default) / 16GB (high_memory) |

| Timeout | 1-300 seconds (default: 30) |

## Input Schema

{

"code": "print('Hello World!')",

"timeout": 30,

"capture_output": true,

"working_dir": null

}

## Pre-installed Libraries

### Web Scraping & HTTP

- `requests`, `httpx`, `aiohttp` - HTTP clients

- `beautifulsoup4`, `lxml` - HTML/XML parsing

- `selenium`, `playwright` - Browser automation

- `scrapy` - Web scraping framework

### Data Processing

- `numpy`, `pandas`, `scipy` - Numerical computing

- `matplotlib`, `seaborn`, `plotly` - Visualization

### Image Processing

- `pillow`, `opencv-python-headless` - Image manipulation

- `scikit-image`, `imageio` - Image algorithms

### Video & Audio

- `moviepy` - Video editing

- `av` (PyAV), `ffmpeg-python` - Video processing

- `pydub` - Audio manipulation

### 3D Processing

- `trimesh`, `open3d` - 3D mesh processing

- `numpy-stl`, `meshio`, `pyvista` - 3D file formats

### Documents & Graphics

- `svgwrite`, `cairosvg` - SVG creation

- `reportlab`, `pypdf2` - PDF generation

## Examples

### Web Scraping

belt app run infsh/python-executor --input '{

"code": "import requests\nfrom bs4 import BeautifulSoup\n\nresponse = requests.get(\"https://example.com\")\nsoup = BeautifulSoup(response.content, \"html.parser\")\nprint(soup.find(\"title\").text)"

}'

### Data Analysis with Visualization

belt app run infsh/python-executor --input '{

"code": "import pandas as pd\nimport matplotlib.pyplot as plt\n\ndata = {\"name\": [\"Alice\", \"Bob\"], \"sales\": [100, 150]}\ndf = pd.DataFrame(data)\n\nplt.bar(df[\"name\"], df[\"sales\"])\nplt.savefig(\"outputs/chart.png\")\nprint(\"Chart saved!\")"

}'

### Image Processing

belt app run infsh/python-executor --input '{

"code": "from PIL import Image\nimport numpy as np\n\n# Create gradient image\narr = np.linspace(0, 255, 256*256, dtype=np.uint8).reshape(256, 256)\nimg = Image.fromarray(arr, mode=\"L\")\nimg.save(\"outputs/gradient.png\")\nprint(\"Image created!\")"

}'

### Video Creation

belt app run infsh/python-executor --input '{

"code": "from moviepy.editor import ColorClip, TextClip, CompositeVideoClip\n\nclip = ColorClip(size=(640, 480), color=(0, 100, 200), duration=3)\ntxt = TextClip(\"Hello!\", fontsize=70, color=\"white\").set_position(\"center\").set_duration(3)\nvideo = CompositeVideoClip([clip, txt])\nvideo.write_videofile(\"outputs/hello.mp4\", fps=24)\nprint(\"Video created!\")",

"timeout": 120

}'

### 3D Model Processing

belt app run infsh/python-executor --input '{

"code": "import trimesh\n\nsphere = trimesh.creation.icosphere(subdivisions=3, radius=1.0)\nsphere.export(\"outputs/sphere.stl\")\nprint(f\"Created sphere with {len(sphere.vertices)} vertices\")"

}'

### API Calls

belt app run infsh/python-executor --input '{

"code": "import requests\nimport json\n\nresponse = requests.get(\"https://api.github.com/users/octocat\")\ndata = response.json()\nprint(json.dumps(data, indent=2))"

}'

## File Output

Files saved to `outputs/` are automatically returned:

These files will be in the response

plt.savefig('outputs/chart.png')

df.to_csv('outputs/data.csv')

video.write_videofile('outputs/video.mp4')

mesh.export('outputs/model.stl')

## Variants

Default (8GB RAM)

belt app run infsh/python-executor --input input.json

High memory (16GB RAM) for large datasets

belt app run infsh/python-executor@high_memory --input input.json

## Use Cases

- **Web scraping** - Extract data from websites

- **Data analysis** - Process and visualize datasets

- **Image manipulation** - Resize, crop, composite images

- **Video creation** - Generate videos with text overlays

- **3D processing** - Load, transform, export 3D models

- **API integration** - Call external APIs

- **PDF generation** - Create reports and documents

- **Automation** - Run any Python script

## Important Notes

- **CPU-only** - No GPU/ML libraries (use dedicated AI apps for that)

- **Safe execution** - Runs in isolated subprocess

- **Non-interactive** - Use `plt.savefig()` not `plt.show()`

- **File detection** - Output files are auto-detected and returned

## Related Skills

AI image generation (for ML-based images)

npx skills add inference-sh/skills@ai-image-generation

AI video generation (for ML-based videos)

npx skills add inference-sh/skills@ai-video-generation

LLM models (for text generation)

npx skills add inference-sh/skills@llm-models