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pysheeet
Python

Python Cheat Sheet

Last updated Jul 8, 2026
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README

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pysheeet

Build Status Coverage License MIT DOI

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 welcomeβ€”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 β€” 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 β€” 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 _ - Design philosophy and evolution
  • Asyncio Basics _ - Coroutines, tasks, gather, timeouts
  • Asyncio Networking _ - TCP/UDP servers, HTTP, SSL/TLS
  • Asyncio Advanced _ - 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 _ - Load shared libraries without compilation
  • Python C API _ - Traditional C extension reference
  • Modern C/C++ Extensions _ - pybind11, Cython
  • Learn C++ from Python _ - 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 _ - AES-GCM, RSA-OAEP, Ed25519, Argon2
  • TLS/SSL and Certificates _ - HTTPS servers, certificate generation
  • Common Vulnerabilities _ - 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 _
  • Socket Servers _
  • Async Socket I/O _
  • SSL/TLS Sockets _
  • Packet Sniffing _
  • SSH and Tunnels _

Database ========

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

  • SQLAlchemy Basics _
  • SQLAlchemy ORM _
  • SQLAlchemy Query Recipes _

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 _ - Tensors, autograd, neural networks, training loops
  • Megatron _ - NVIDIA Megatron training/fine-tuning framework with enroot/pyxis
  • LLM Serving _ - vLLM and SGLang for production inference with TP/PP/DP/EP
  • LLM Benchmark _ - 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 _
  • Ray Cluster _

Blog ====

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

  • NVSHMEM Multi-NIC Support with AWS EFA _
  • Is Disaggregated Prefill/Decode a Silver Bullet for LLM Serving? _
  • Monitoring EFA with NCCL GIN and Nsys _
  • GPU-Initiated Networking for NCCL on AWS _
  • PEP 572 and the walrus operator _
  • Python Interpreter in GNU Debugger _
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

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