From pysheeet
Python programming reference covering syntax, concurrency, networking, databases, ML/LLM, HPC, and interview prep. Fetches examples from pythonsheets.com for code writing, debugging, and optimization.
How this skill is triggered — by the user, by Claude, or both
Slash command
/pysheeet:pyThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Help users write functional, correct Python code and answer Python questions by fetching proven patterns and examples from pythonsheets.com.
Help users write functional, correct Python code and answer Python questions by fetching proven patterns and examples from pythonsheets.com.
When a user asks a Python question or wants to write a Python script:
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.
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
npx claudepluginhub crazyguitar/pysheeet --plugin pysheeetActivates senior ML engineer mode with Leeroopedia KB (27k+ pages on vLLM, SGLang, DeepSpeed, Axolotl) enforcing lookups, citations, and grounding before code in ML/AI discussions.
Teaches Pythonic idioms, PEP 8 style, type hints, and best practices for writing readable, maintainable Python code. Useful when writing or reviewing Python code and designing packages.
Provides asyncio patterns and best practices for async Python: concurrency control, rate limiting, context managers in I/O-bound apps, APIs, WebSockets.