py

name	py
description	Comprehensive Python programming reference covering syntax, concurrency, networking, databases, ML/LLM development, and HPC. Use for: Python questions, Python interview preparation, debugging, performance optimization, async patterns, library examples, code review, best practices, MLOps workflows, distributed computing, security implementations, and any Python development tasks.

Python Cheat Sheets (/py)

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

• "What should I review for a Python interview?" → Fetch https://www.pythonsheets.com/notes/interview/index.html and walk the reader through the topic groups
• "Common Python interview questions on the GIL" → Fetch https://www.pythonsheets.com/notes/interview/index.html and then drill into https://www.pythonsheets.com/notes/concurrency/python-threading.html for detailed answers
• "How does asyncio work?" → Fetch https://www.pythonsheets.com/notes/asyncio/python-asyncio-guide.html and explain with the site's examples
• "Write a socket server" → Fetch https://www.pythonsheets.com/notes/network/python-socket-server.html, use the patterns to write a working server
• "What's the walrus operator?" → Fetch https://www.pythonsheets.com/notes/appendix/python-walrus.html and explain with practical examples
• "Set up Megatron distributed training" → Fetch https://www.pythonsheets.com/notes/llm/megatron.html, use the patterns to write a correct training script