📡 Python radar - December 2022

A personal selection of Python-related news and projects that caught my attention this month (note: leading emojis are mine).

⚠️ It’s time to stop using Python 3.7 (pythonspeed.com)
Support for version 3.7 ends in June 2023! It's high time to migrate if you haven’t already. [EDIT 2025-01-20: original link broken, replaced by an Internet Archive link]

🌱 mlco2/codecarbon: Track emissions from Compute (github.com)
A nice find that allows you to evaluate and track the carbon footprint of your running Python code, a good tool to integrate eco-design into your development practice?

📊 PyArrow and the future of data analytics (youtube.com)
An informative presentation of the capabilities of PyArrow, the "Swiss knife of data," compatible with various technologies including Numpy and Pandas.

🛡️ DataDog/guarddog: GuardDog is a CLI tool to Identify malicious PyPI packages (github.com)
Continuing the recent updates on malicious PyPI packages, here’s a tool to help protect against them.

⚡ PyTorch 2.0 (pytorch.org)
A detailed review of this major new version of PyTorch, which promises speed, dynamism, and pythonicity (I just invented that word).

📚 Natural Language Processing Demystified (nlpdemystified.org)
A complete and truly free course (no signup) to understand the fundamentals of NLP.

🖼️ comet-ml/kangas: 🦘 Explore multimedia datasets at scale (github.com)
A new tool in beta for exploring and analyzing large multimedia datasets (images, sound, videos).

🚀 exaloop/codon: A high-performance, zero-overhead, extensible Python compiler using LLVM (github.com)
A Python code compiler with support for OpenMP and Nvidia GPUs. Note the BSL license, which allows non-commercial use only but transitions to Apache 2.0 after 3 years.

🔐 Has your password been pwned? Or, how I almost failed to search a 37 GB text file in under 1 millisecond (death.andgravity.com)
A post presenting the results of a progressive optimization exercise, quite technical but informative.

⭐ vinta/awesome-python: A curated list of awesome Python frameworks, libraries, software and resources (github.com)
The famous "awesome-python" where you’ll find hundreds of useful Python packages in all sorts of domains.