CPython 3.15 (JIT) Performance Showdown

How We Built an Async-Aware Python Profiler

Learn how Datadog made Python profiling async-aware while reducing profiler overhead and preserving context across asyncio tasks.

Django: set up its test suite with uv

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How fast is Python 3.15?

Monte-Carlo simulations

Monte Carlo simulations (or methods) is the technique of applying randomness and the Law of large numbers to the solution of various scientific and engineering problems.

Django: serve apple-app-site-association and assetlinks.json

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Static Analysis vs. Taint Analysis: Which One Secures Your Python Code?

Django: serve a security.txt file

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The last mile of a long road: faster NumPy in the browser

A Pause for the Python JIT

Django: serve the change password well-known URL

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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.