The State of Django 2026: Boring is so back

EVE Online moves to Python 3

Modern Django Deployments in 2026

A written guide to my talk on deploying Django and why 90% of it is the same.

SIMD in Pure Python

SIMD is Single Instruction, Multiple Data, an approach that does calculations with vectors of data sets. Python doesn’t support it natively, but libraries like NumPy allow you to code this way.

Numba in the Browser: Unlocking a New Scientific Python Stack in JupyterLite

Hydra for Python Configuration: Build Modular and Maintainable Pipelines

Hardcoded paths and parameters can quickly drift out of sync across a data science project’s scripts. This article shows how to move them into Hydra configuration files, access values with dot notation, override settings from the command line, swap entire configuration groups, and run experiment sweeps with a single multirun flag.

Django: introducing django-msgspec

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Spy on Function Calls With unittest.mock Wraps

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Scaling NumPy on Free-Threaded Python

A recap on the work done in NumPy and CPython to make multi-threaded NumPy workloads scale on the free-threaded build of CPython.

Python⇒Speed: Faster floating point math with Rust’s new API

Floating point math is often slower than integer math because the compiler is being conservative about how it optimizes your code. While some programming languages already had solutions of a sort, until now Rust did not have a good stable way to deal with this limitation. But now, starting in version 1.98, Rust will allow telling the compiler it can optimize your code further—but with extra control so that you can still write numeric algorithms with minimal rounding errors. 

Find All Instances of a Class With gc.get_objects()

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Running Gemma 4 in the Browser with Transformers.js and WebGPU

12K+ JPEGs From NASA’s Artemis II Mission

Mark writes articles on data analysis. This one is all about the images NASA released from the Artemis II mission. It includes step-by-step instructions that you can follow along.

Git for Data Scientists

A practical Git walkthrough for data scientists, focused on real workflows like branching for experiments, reverting mistakes, and keeping project history clean with small, focused commits. It also explains merge vs. rebase, why you should not rebase shared branches, and how to set up .gitignore for data-heavy projects.

What Every Dev Should Know About the CPython ABI

An introduction to the concept of the Application Binary Interface (ABI), the various CPython ABIs, and the new abi3t stable ABI in Python 3.15.

Best Django Redis configuration for speed and size

`lzma` compresses the most and `zlib` is about as fast as `zstd` in `django_redis` as compressor.

Gleam for Python Programmers

What Every Python Developer Should Know About the CPython ABI

Python 3.15’s Ultra-Low Overhead Interpreter Profiling Mode

Ken is one of the key contributors to the experimental JIT. This post talks about how Python 3.15’s interpreter profiling mode is helping them figure out what is working with the JIT and what isn’t.

itertools cheatsheet

Cheatsheet with visual diagrams that explain how the iterables from itertools work. This cheatsheet contains diagrams that explain how the iterables from the module itertools work in a visual way. Download this cheatsheet Download this cheatsheet