{"skill":{"slug":"python-executor","displayName":"Python Executor","summary":"Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSo...","description":"---\nname: python-executor\ndescription: \"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\"\nallowed-tools: Bash(infsh *)\n---\n\n# Python Code Executor\n\nExecute Python code in a safe, sandboxed environment with 100+ pre-installed libraries.\n\n![Python Code Executor](https://cloud.inference.sh/u/33sqbmzt3mrg2xxphnhw5g5ear/01k8d8b4mckh6z89dhtxh72dsz.png)\n\n## Quick Start\n\n```bash\ncurl -fsSL https://cli.inference.sh | sh && infsh login\n\n# Run Python code\ninfsh app run infsh/python-executor --input '{\n  \"code\": \"import pandas as pd\\nprint(pd.__version__)\"\n}'\n```\n\n> **Install note:** The [install script](https://cli.inference.sh) only detects your OS/architecture, downloads the matching binary from `dist.inference.sh`, and verifies its SHA-256 checksum. No elevated permissions or background processes. [Manual install & verification](https://dist.inference.sh/cli/checksums.txt) available.\n\n## App Details\n\n| Property | Value |\n|----------|-------|\n| App ID | `infsh/python-executor` |\n| Environment | Python 3.10, CPU-only |\n| RAM | 8GB (default) / 16GB (high_memory) |\n| Timeout | 1-300 seconds (default: 30) |\n\n## Input Schema\n\n```json\n{\n  \"code\": \"print('Hello World!')\",\n  \"timeout\": 30,\n  \"capture_output\": true,\n  \"working_dir\": null\n}\n```\n\n## Pre-installed Libraries\n\n### Web Scraping & HTTP\n- `requests`, `httpx`, `aiohttp` - HTTP clients\n- `beautifulsoup4`, `lxml` - HTML/XML parsing\n- `selenium`, `playwright` - Browser automation\n- `scrapy` - Web scraping framework\n\n### Data Processing\n- `numpy`, `pandas`, `scipy` - Numerical computing\n- `matplotlib`, `seaborn`, `plotly` - Visualization\n\n### Image Processing\n- `pillow`, `opencv-python-headless` - Image manipulation\n- `scikit-image`, `imageio` - Image algorithms\n\n### Video & Audio\n- `moviepy` - Video editing\n- `av` (PyAV), `ffmpeg-python` - Video processing\n- `pydub` - Audio manipulation\n\n### 3D Processing\n- `trimesh`, `open3d` - 3D mesh processing\n- `numpy-stl`, `meshio`, `pyvista` - 3D file formats\n\n### Documents & Graphics\n- `svgwrite`, `cairosvg` - SVG creation\n- `reportlab`, `pypdf2` - PDF generation\n\n## Examples\n\n### Web Scraping\n\n```bash\ninfsh app run infsh/python-executor --input '{\n  \"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)\"\n}'\n```\n\n### Data Analysis with Visualization\n\n```bash\ninfsh app run infsh/python-executor --input '{\n  \"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!\\\")\"\n}'\n```\n\n### Image Processing\n\n```bash\ninfsh app run infsh/python-executor --input '{\n  \"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!\\\")\"\n}'\n```\n\n### Video Creation\n\n```bash\ninfsh app run infsh/python-executor --input '{\n  \"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!\\\")\",\n  \"timeout\": 120\n}'\n```\n\n### 3D Model Processing\n\n```bash\ninfsh app run infsh/python-executor --input '{\n  \"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\\\")\"\n}'\n```\n\n### API Calls\n\n```bash\ninfsh app run infsh/python-executor --input '{\n  \"code\": \"import requests\\nimport json\\n\\nresponse = requests.get(\\\"https://api.github.com/users/octocat\\\")\\ndata = response.json()\\nprint(json.dumps(data, indent=2))\"\n}'\n```\n\n## File Output\n\nFiles saved to `outputs/` are automatically returned:\n\n```python\n# These files will be in the response\nplt.savefig('outputs/chart.png')\ndf.to_csv('outputs/data.csv')\nvideo.write_videofile('outputs/video.mp4')\nmesh.export('outputs/model.stl')\n```\n\n## Variants\n\n```bash\n# Default (8GB RAM)\ninfsh app run infsh/python-executor --input input.json\n\n# High memory (16GB RAM) for large datasets\ninfsh app run infsh/python-executor@high_memory --input input.json\n```\n\n## Use Cases\n\n- **Web scraping** - Extract data from websites\n- **Data analysis** - Process and visualize datasets\n- **Image manipulation** - Resize, crop, composite images\n- **Video creation** - Generate videos with text overlays\n- **3D processing** - Load, transform, export 3D models\n- **API integration** - Call external APIs\n- **PDF generation** - Create reports and documents\n- **Automation** - Run any Python script\n\n## Important Notes\n\n- **CPU-only** - No GPU/ML libraries (use dedicated AI apps for that)\n- **Safe execution** - Runs in isolated subprocess\n- **Non-interactive** - Use `plt.savefig()` not `plt.show()`\n- **File detection** - Output files are auto-detected and returned\n\n## Related Skills\n\n```bash\n# AI image generation (for ML-based images)\nnpx skills add inference-sh/skills@ai-image-generation\n\n# AI video generation (for ML-based videos)\nnpx skills add inference-sh/skills@ai-video-generation\n\n# LLM models (for text generation)\nnpx skills add inference-sh/skills@llm-models\n```\n\n## Documentation\n\n- [Running Apps](https://inference.sh/docs/apps/running) - How to run apps via CLI\n- [App Code](https://inference.sh/docs/extend/app-code) - Understanding app execution\n- [Sandboxed Code Execution](https://inference.sh/blog/tools/sandboxed-execution) - Safe code execution for agents\n","tags":{"latest":"0.1.5"},"stats":{"comments":0,"downloads":8851,"installsAllTime":309,"installsCurrent":97,"stars":3,"versions":2},"createdAt":1770363446663,"updatedAt":1778988665268},"latestVersion":{"version":"0.1.5","createdAt":1771403346215,"changelog":"- Added detailed documentation in SKILL.md, including usage examples, input schema, and pre-installed library list.\n- Clarified environment specs, supported triggers, and output file handling.\n- Listed practical use cases for web scraping, data analysis, image/video/3D processing, API calls, PDF generation, and automation.\n- Provided quick start instructions and links to related skills and official documentation.","license":null},"metadata":null,"owner":{"handle":"okaris","userId":"s1737xapsjy8k5qnagtfyf5nrx85t72x","displayName":"Ömer Karışman","image":"https://avatars.githubusercontent.com/u/1448702?v=4"},"moderation":null}