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<h1 align="center">
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  <a href="https://www.pythonsheets.com"><img src="docs/_static/logo.png" alt="pysheeet" width=200"></a>
</h1>
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Introduction

This project was started to bring together useful Python code snippets that make coding faster, easier, and more enjoyable. You can explore all the cheat sheets at Pysheeet <https://www.pythonsheets.com/>_. Contributions are always welcome—feel free to fork the repo and submit a pull request to help it grow!

Plugin

pysheeet is available as a Claude Code plugin. Once installed, Claude automatically uses the cheat sheets to answer Python questions — just ask naturally and the skill triggers based on context.

Installation

As a Claude Code plugin (recommended):

.. code-block:: bash

# Step 1: Add the marketplace
claude plugin marketplace add crazyguitar/pysheeet

# Step 2: Install the plugin
claude plugin install pysheeet@pysheeet

Local testing (single session only):

.. code-block:: bash

claude --plugin-dir /path/to/pysheeet

Manual installation (requires cloning the repo):

.. code-block:: bash

git clone https://github.com/crazyguitar/pysheeet.git
mkdir -p ~/.claude/skills
cp -r pysheeet/skills/py ~/.claude/skills/py

Python Interview Cheatsheet

Curated Python interview questions indexed by topic — each question links directly to the section of the cheat sheet that answers it. Use it for quick review before an interview, or to drill down on a specific area (GIL, asyncio, decorators, MRO, and more).

• Python Interview Cheatsheet <docs/notes/interview/index.rst>_

What's New In Python 3

This part only provides a quick glance at some important features in Python 3. If you're interested in all of the most important features, please read the official document, What’s New in Python <https://docs.python.org/3/whatsnew/index.html>_.

• New in Python3 <docs/notes/python-new-py3.rst>_

Cheat Sheet

Core Python fundamentals including data types, functions, classes, and commonly used patterns for everyday programming tasks.

• From Scratch <docs/notes/basic/python-basic.rst>_
• Future <docs/notes/basic/python-future.rst>_
• Typing <docs/notes/basic/python-typing.rst>_
• Class <docs/notes/basic/python-object.rst>_
• Function <docs/notes/basic/python-func.rst>_
• Unicode <docs/notes/basic/python-unicode.rst>_
• List <docs/notes/basic/python-list.rst>_
• Set <docs/notes/basic/python-set.rst>_
• Dictionary <docs/notes/basic/python-dict.rst>_
• Heap <docs/notes/basic/python-heap.rst>_
• Generator <docs/notes/basic/python-generator.rst>_
• Regular expression <docs/notes/basic/python-rexp.rst>_

System

Date/time handling, file I/O, and operating system interfaces.

• Datetime <docs/notes/os/python-date.rst>_ - Timestamps, formatting, parsing, timezones, timedelta
• Files and I/O <docs/notes/os/python-io.rst>_ - Reading, writing, pathlib, shutil, tempfile
• Operating System <docs/notes/os/python-os.rst>_ - Processes, environment, system calls

Concurrency

Threading, multiprocessing, and concurrent.futures for parallel execution. Covers synchronization primitives, process pools, and bypassing the GIL.

• Threading <docs/notes/concurrency/python-threading.rst>_ - Threads, locks, semaphores, events, conditions
• Multiprocessing <docs/notes/concurrency/python-multiprocessing.rst>_ - Processes, pools, shared memory, IPC
• concurrent.futures <docs/notes/concurrency/python-futures.rst>_ - Executors, futures, callbacks

Asyncio

Asynchronous programming with Python's asyncio module. Covers coroutines, event loops, tasks, networking, and advanced patterns.

• A Hitchhiker's Guide to Asynchronous Programming <docs/notes/asyncio/python-asyncio-guide.rst>_ - Design philosophy and evolution
• Asyncio Basics <docs/notes/asyncio/python-asyncio-basic.rst>_ - Coroutines, tasks, gather, timeouts
• Asyncio Networking <docs/notes/asyncio/python-asyncio-server.rst>_ - TCP/UDP servers, HTTP, SSL/TLS
• Asyncio Advanced <docs/notes/asyncio/python-asyncio-advanced.rst>_ - Synchronization, queues, subprocesses

C/C++ Extensions

Native extensions for performance-critical code. Covers modern pybind11 (used by PyTorch, TensorFlow), ctypes, cffi, Cython, and the traditional Python C API. Also includes a guide for Python developers learning modern C++ syntax.

• ctypes <docs/notes/extension/python-ctypes.rst>_ - Load shared libraries without compilation
• Python C API <docs/notes/extension/python-capi.rst>_ - Traditional C extension reference
• Modern C/C++ Extensions <docs/notes/extension/python-cext-modern.rst>_ - pybind11, Cython
• Learn C++ from Python <docs/notes/extension/cpp-from-python.rst>_ - Modern C++ for Python developers

Security

Modern cryptographic practices and common security vulnerabilities. Covers encryption, TLS/SSL, and why legacy patterns are dangerous.

• Modern Cryptography <docs/notes/security/python-crypto.rst>_ - AES-GCM, RSA-OAEP, Ed25519, Argon2
• TLS/SSL and Certificates <docs/notes/security/python-tls.rst>_ - HTTPS servers, certificate generation
• Common Vulnerabilities <docs/notes/security/python-vulnerability.rst>_ - Padding oracle, injection, timing attacks

Network

Low-level network programming with Python sockets. Covers TCP/UDP communication, server implementations, asynchronous I/O, SSL/TLS encryption, and packet analysis.

• Socket Basics <docs/notes/network/python-socket.rst>_
• Socket Servers <docs/notes/network/python-socket-server.rst>_
• Async Socket I/O <docs/notes/network/python-socket-async.rst>_
• SSL/TLS Sockets <docs/notes/network/python-socket-ssl.rst>_
• Packet Sniffing <docs/notes/network/python-socket-sniffer.rst>_
• SSH and Tunnels <docs/notes/network/python-ssh.rst>_

Database

Database access with SQLAlchemy, Python's most popular ORM. Covers connection management, raw SQL, object-relational mapping, and common query patterns.

• SQLAlchemy Basics <docs/notes/database/python-sqlalchemy.rst>_
• SQLAlchemy ORM <docs/notes/database/python-sqlalchemy-orm.rst>_
• SQLAlchemy Query Recipes <docs/notes/database/python-sqlalchemy-query.rst>_

LLM

Large Language Models (LLM) training, inference, and optimization. Covers PyTorch for model development, distributed training across GPUs, and vLLM/SGLang for high-performance LLM inference and serving.

• PyTorch <docs/notes/llm/pytorch.rst>_ - Tensors, autograd, neural networks, training loops
• Megatron <docs/notes/llm/megatron.rst>_ - NVIDIA Megatron training/fine-tuning framework with enroot/pyxis
• LLM Serving <docs/notes/llm/llm-serving.rst>_ - vLLM and SGLang for production inference with TP/PP/DP/EP
• LLM Benchmark <docs/notes/llm/llm-bench.rst>_ - Benchmark suite for measuring serving performance

HPC

High-Performance Computing tools for cluster management and job scheduling. Covers Slurm workload manager and Ray for distributed computing on GPU clusters.

• Slurm <docs/notes/hpc/slurm.rst>_
• Ray Cluster <docs/notes/hpc/ray.rst>_

Blog

Supplementary topics covering Python internals, debugging techniques, and language features that don't fit elsewhere.

• NVSHMEM Multi-NIC Support with AWS EFA <docs/notes/appendix/nvshmem-multi-nic.rst>_
• Is Disaggregated Prefill/Decode a Silver Bullet for LLM Serving? <docs/notes/appendix/disaggregated-prefill-decode.rst>_
• Monitoring EFA with NCCL GIN and Nsys <docs/notes/appendix/megatron-efa-monitoring.rst>_
• GPU-Initiated Networking for NCCL on AWS <docs/notes/appendix/nccl-gin.rst>_
• PEP 572 and the walrus operator <docs/notes/appendix/python-walrus.rst>_
• Python Interpreter in GNU Debugger <docs/notes/appendix/python-gdb.rst>_

PDF Version

pdf_

.. _pdf: https://media.readthedocs.org/pdf/pysheeet/latest/pysheeet.pdf

How to run the server

.. code-block:: bash

$ virtualenv venv
$ . venv/bin/activate
$ pip install -r requirements.txt
$ make
$ python app.py

# URL: localhost:5000