Alle Skills / BANKAI-SKILLS

bankai-skills/superpowers

python-executor

Execute Python code in a safe sandboxed environment via inference.sh.

Quelltext ansehen

Verwendung

Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.

npx skills add https://github.com/bankai-skills/superpowers --skill python-executor

Vor dem Start

Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.

Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

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

Quick Start

Requires inference.sh CLI (belt). Install instructions

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

Verwandte Aufgaben

aus demselben Repository

Weitere Skills

ai-avatar-video

Create AI avatar and talking head videos via inference.sh CLI. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also: OmniHuman, Fabric, PixVerse. Audio: Inworld TTS-2 (100+ languages, emotion steering for characters), ElevenLabs, Kokoro. Capabilities: audio-driven avatars, text-to-avatar, lipsync videos, talking head generation, virtual presenters, UGC content. Use for: AI presenters, explainer videos, virtual influencers, dubbing, marketing videos, UGC ads, gaming avatars, NPC di

Installationen: 387.143
GitHub Stars: 0
Aktualisiert: 31. Aug.

Skill-Details ansehen →

ai-image-generation

Generate AI images with GPT-Image-2, FLUX, Gemini, Grok, Seedream, Reve and 50+ models via inference.sh CLI. Models: GPT-Image-2, FLUX Dev LoRA, FLUX.2 Klein LoRA, Gemini 3 Pro Image, Grok Imagine, Seedream 4.5, Reve, ImagineArt. Capabilities: text-to-image, image-to-image, inpainting, LoRA, image editing, upscaling, text rendering. Use for: AI art, product mockups, concept art, social media graphics, marketing visuals, illustrations. Triggers: flux, image generation, ai image, text to image, st

Installationen: 387.193
GitHub Stars: 0
Aktualisiert: 31. Aug.

Skill-Details ansehen →

ai-video-generation

Generate AI videos with Google Veo, Seedance 2.0, HappyHorse, Wan, Grok and 40+ models via inference.sh CLI. Models: Veo 3.1, Veo 3, Seedance 2.0, HappyHorse 1.0, Wan 2.5, Grok Imagine Video, OmniHuman, Fabric, HunyuanVideo. Capabilities: text-to-video, image-to-video, reference-to-video, video editing, lipsync, avatar animation, video upscaling, foley sound. Use for: social media videos, marketing content, explainer videos, product demos, AI avatars. Triggers: video generation, ai video, text t

Installationen: 387.081
GitHub Stars: 0
Aktualisiert: 31. Aug.

Skill-Details ansehen →

twitter-automation

Automate Twitter/X with posting, engagement, and user management via inference.sh CLI. Apps: x/post-tweet, x/post-create (with media), x/post-like, x/post-retweet, x/dm-send, x/user-follow. Capabilities: post tweets, schedule content, like posts, retweet, send DMs, follow users, get profiles. Use for: social media automation, content scheduling, engagement bots, audience growth, X API. Triggers: twitter api, x api, tweet automation, post to twitter, twitter bot, social media automation, x automa

Installationen: 387.074
GitHub Stars: 0
Aktualisiert: 31. Aug.

Skill-Details ansehen →