Python - Resources

Official Python Resources

• The Python Standard Library
  • [[main — Top-level code environment]]
    • On sys.exit(main()): “Since the call to main is wrapped in sys.exit(), the expectation is that your function will return some value acceptable as an input to sys.exit(); typically, an integer or None (which is implicitly returned if your function does not have a return statement).”
    • “__main__.py will be executed when the package itself is invoked directly from the command line using the -m flag.”. Example: python -m bandclass
    • You can import __main__ to do useful things like thing in dir(__main__) checks. There’s special handling in the import system as described in Special considerations for main
  • zlib — Compression compatible with gzip
  • contextlib — Utilities for with-statement contexts
• The Python Language Reference
  • ✨ 3. Data model - the Python data model methods as referred to by James Powell a.k.a. Don’t Use This Code
    • object.new(cls[, …])
  • 6. Expressions - lots of useful stuff here like evaluation order, operator precedence, displays (when list, set and dictionary displays compute elements via a set of looping and filtering instructions, this is called a comprehension)
• Python HOWTOs
  • Functional Programming HOWTO
  • Socket Programming HOWTO
  • Logging HOWTO - When to use logging - Python Docs - specifically the section on When to use logging since this table is very clear and useful
• The Python Tutorial - the official Python 3 tutorialbeginnerfriendly - under this point I include non-trivial standard library modules (i.e. packages or modules like json csv respectively are omitted as I use them so frequently, so am familiar with them)
  • • The module pickletools contains tools for analyzing data streams generated by pickle. pickletools source code has extensive comments about opcodes used by pickle protocols.
  • Data Compression: Common data archiving and compression formats are directly supported by modules including zlib, gzip, bz2, lzma, zipfile and tarfile
  • The email package is a library for managing email messages, including MIME and other RFC 2822-based message documents. Unlike smtplib and poplib which actually send and receive messages, the email package has a complete toolset for building or decoding complex message structures (including attachments) and for implementing internet encoding and header protocols.
  • The smtplib module defines an SMTP client session object that can be used to send mail to any internet machine with an SMTP or ESMTP listener daemon.
  • XML processing is supported by the xml.etree.ElementTree, xml.dom and xml.sax packages. Together, these modules and packages greatly simplify data interchange between Python applications and other tools.
  • The sqlite3 module is a wrapper for the SQLite database library, providing a persistent database that can be updated and accessed using slightly nonstandard SQL syntax.
  • Internationalization is supported by a number of modules including gettext, locale, and the codecs package.
  • 11. Brief Tour of the Standard Library — Part II
• Python/C API Reference Manual
  • Memory Management

3rd Party Python Resources

• Dive Into Python 3 - IMHO the best place to start learning Pythonbeginnerfriendly
  • Classes & Iterators - Dive Into Python 3
  • Closures & Generators - Dive Into Python 3
• Python Data Science Handbook by Jake VanderPlas - helped me a lot when I was starting outbeginnerfriendly
• A Whirlwind Tour of Python - Jake VanderPlas -beginnerfriendly
• The Hitchhiker’s Guide to Python -beginnerfriendly
• Intermediate Python
• Hyperpolyglot Numerical Analysis & Statistics: MATLAB, R, NumPy, Julia - a side-by-side reference sheet
• Python Object Graphs — objgraph 3.6.2 documentation
• [[Why you should use python -m pip]] - not sure about this but saved for reference/to check later
• What Are Python Wheels and Why Should You Care?
• pip documentation
  • Requirements File Format
• Python Packaging User Guide
  • Writing your pyproject.toml - Python Packaging User Guide
  • Package Formats - Python Packaging User Guide
  • Glossary - Python Packaging User Guide
  • Entry points specification - Python Packaging User Guide - describes the design of entrypoints in Python distributions (source distns or wheels) via the group-name-object reference model
    • Note: the advice here does not mention the [project.scripts] group under which I provide an entrypoint in the arxivbot package for the obsidian-import CLI facility allowing import of papers from arXiv
      • question is this specification out of date?
• Learning Resources for pytest The PyCharm Blog - pytest
• File IO With Memory Mapping Using Python mmap - Real Python
• Python Wheels || Python Wheels- useful to gain an idea of what the most popular packages are
• Awesome Python - find the best - Hand-picked awesome Python libraries, organised by category 🐍 -

PEPs

Interesting or useful PEPs.

• PEP 544 – Protocols Structural subtyping (static duck typing) peps.python.org

Python Implementations

• PyPy

Articles

• CHARMING PYTHON B26 Python Elegance, Python Warts, Part 2 — Properties, attributes, methods and custom access — - recommended in Dive Into Python 3
• 🔥 Read Inside The Python Virtual Machine $\leftarrow$ this looks absolutely amazing; added to READUS
• Polars vs. pandas What’s the Difference? The PyCharm Blog
• Python’s new t-strings - davepeck.org
• Python Closures Common Use Cases and Examples
• Use Ruff, Pyright, typos, and gitlint to Help You Write Better Python Code (Python Linting) - YouTube

Tools & Packages

• ty
  • ty Astral’s New Python Type Checker Released
• Ruff
  • Ruff || astral-sh/ruff - An extremely fast Python linter and code formatter, written in Rust.
• uv
  • uv - An extremely fast Python package and project manager, written in Rust
    • Managing Python Projects With uv An All-in-One Solution
  • Running scripts uv (clipped: Running scripts uv)
• Typing
  • Introduction Pyrefly
  • Pyre Pyre || facebook/pyre-check
  • Beartype - Beartype enforces type hints across your entire app in two lines of runtime code with no runtime overhead
• Package management
  • pipx — Install and Run Python Applications in Isolated Environments
    • pipx - main (first) docs page
• Linting and Formatting
  • Ruff moved to section above
• Logging
  • Loguru || Delgan/loguru - Python logging made (stupidly) simple; “a library which aims to bring enjoyable logging in Python”
• System interaction
  • psutil: giampaolopsutil Cross-platform lib for process and system monitoring in Python
• Data & Databases
  • Psycopg 3 - Psycopg 3 is the new implementation of the most used, reliable and feature-rich PostgreSQL adapter for Python
    • Psycopg 3 docs
    • psycopg/psycopg - New generation PostgreSQL database adapter for the Python programming language
    • the Psycopg features, which also compares versions 2 and 3 and notes that Psycopg is a wrapper around the libpq library, the official PostgreSQL client library
  • Polars: Index - Polars user guide
• Synthetic Data
  • Creating Synthetic Data with Python Faker Tutorial
• Serialisation
  • dill package documentation — dill 0.4.1.dev0 documentation
• NVIDIA, Triton, Hardware and High Performance Computing (HPC)
  • pyNVML - Python bindings to the NVIDIA Management Library - per PyPI: pip install nvidia-ml-py
• Scientific computing
  • SciPy
• CLIs + Applications
  • google/python-fire || The Python Fire Guide || The Python Fire Guide - Python Fire 👈 quick primer on Fire usage (main, automatic CLI, python -m fire ... without import) - used in kyutai-labs/moshi-finetune
  • lebrice/SimpleParsing - Simple, Elegant, Typed Argument Parsing with argparse - used in kyutai-labs/moshi-finetune