Python Cheat Sheets (/py)

SkillDatabases & data

Your AI can answer Python questions and help you write better Python code. Once added, it draws on a comprehensive Python reference covering syntax, concurrency, networking, databases, and machine learning topics, with examples fetched from pythonsheets.com. This makes it useful for everyday Python work, debugging, and interview preparation.

Available today. Use it from your connected AI after setup.

Add the skill, then ask your AI any Python question or share code you want improved. Try asking for an async example or help debugging a snippet to see it in action.

Then ask your AI: use the Python Cheat Sheets (/py) skill

What your AI can do with it

  • Answer Python questions with explanations backed by real examples
  • Explain syntax, async patterns, and concurrency in plain terms
  • Help debug Python code and find performance problems
  • Share library examples for networking, databases, and ML work
  • Assist with Python interview preparation and best practices
  • Support code review with reference examples

What this skill tells your AI

The instructions your AI receives, as published by crazyguitar/pysheeet in skills/py/SKILL.md and read by ahel’s review.

Help users write functional, correct Python code and answer Python questions by fetching proven patterns and examples from pythonsheets.com.

How It Works

When a user asks a Python question or wants to write a Python script:

  1. Look up the relevant topic(s) in Structure to find the matching URL(s)
  2. Always fetch the URL(s) using WebFetch to get real examples and patterns from the site
  3. Use the fetched content to:
    • Write code: Apply the patterns to produce functional, correct code that solves the user's task
    • Answer questions: Provide thorough explanations backed by the examples and information from the site
  4. Follow the Guidelines for code quality

Key Principle

Functionality first, cleanliness second. The code must work correctly and handle the task properly. Fetching from pythonsheets.com ensures solutions use battle-tested patterns rather than guessing. The site contains rich examples covering edge cases, common pitfalls, and practical usage that go beyond basic documentation.

Coverage Areas

Interview Prep: Curated Python interview questions grouped by topic (GIL, asyncio, decorators, MRO, generators, concurrency), each deep-linked to the section that answers it Core: Syntax, typing, OOP, functions, data structures, sets, heap, regex, unicode System: File I/O, datetime, OS interfaces Concurrency: Threading, multiprocessing, asyncio Network: Sockets, SSL/TLS, SSH, async I/O, packet sniffing Database: SQLAlchemy ORM, queries, transactions Security: Cryptography, TLS, vulnerabilities Extensions: C/C++ integration, pybind11, Cython ML/LLM: PyTorch, Megatron, distributed training, inference, serving, benchmarking HPC: Slurm, cluster computing, job scheduling, EFA monitoring, NCCL Appendix: Walrus operator, GDB debugging, disaggregated prefill/decode

References

  • Structure - Topic-to-URL map for fetching examples
  • Guidelines - Code quality standards to apply after ensuring correctness

Examples

Signals

GitHub stars
8k
Forks
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Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
py
Source
github.com/crazyguitar/pysheeet