python-executor

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass, no license.

Audit 0.4.1 · source sha 4599ef28a2a7 · 31 Oct 2026Report an issue or request a re-scan

• Publisherqu-skills GitHub organizationOwner of the repository this skill is read from
• Source folderqu-skills/skills/tools/utilities/python-executorThe exact folder we audited
• LicenceNot declaredAs the repository states it
• Commit pinned for this verdict4599ef28a2a7A new audit runs when the source changes
• Repository statusNot archivedLast push 16 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh,…

---
name: python-executor
description: "Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib"
allowed-tools: Bash(belt *)
---

> **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.

![Python Code Executor](https://cloud.inference.sh/u/33sqbmzt3mrg2xxphnhw5g5ear/01k8d8b4mckh6z89dhtxh72dsz.png)

## Quick Start

> Requires inference.sh CLI (`belt`). [Install instructions](https://raw.githubusercontent.com/inference-sh/skills/refs/heads/main/cli-install.md)

```bash
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

```json
{
  "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

```bash
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

```bash
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

```bash
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

```bash
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

```bash
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

```bash
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:

```python
# 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

```bash
# 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

```bash
# 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
```

## Documentation

- [Running Apps](https://inference.sh/docs/apps/running) - How to run apps via CLI
- [App Code](https://inferen

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

npx skills add inference-sh/skills@ai-image-generation
npx skills add inference-sh/skills@ai-video-generation
npx skills add inference-sh/skills@llm-models

git clone https://github.com/qu-skills/skills
git -C skills checkout 4599ef28a2a7

Works in

1. 2026-10-31
   ✓SAFE B 89 / 100

   first audit · source 4599ef28a2a7

Questions about python-executor

• github.com/qu-skills/skills/tree/main/tools/utilities/python-exe — the audited source at commit 4599ef28a2a7 and every finding aboveObserved · 31 Oct 2026

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