Django: Introducing django-watchfiles, for more efficient runserver autoreloading

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Playwright & pytest techniques that bring me joy

A collection of real-world techniques for Playwright and pytest. As a project grows to do more with HTMX and Alpine in the markup, there’s less unit and integration test coverage and a greater need for end to end tests.

Playwright vs Pydoll

A deep-dive look at these two popular packages, comparing Pydoll's claims around speed and ergonomics vs Playright.

Adopting LLMs in a startup

Wise words and practical lessons from gradually increasing usage of LLM tools into production.

Basics of Equality Saturation

Equality saturation — это техника для построения оптимизирующих компиляторов с использованием e-графов. Создаем оптимизатор для подмножества линейной алгебры с помощью egglog. Начнём с оптимизации простых арифметических выражений с целыми числами. 

Rye Tables vs Python/Pandas: A Different Way to Wrangle Data

Python 3.14 Preview: REPL Autocompletion and Highlighting

Benchmarking MicroPython

This post compares the performance of running Python on several microcontroller boards.

Production-Grade Python Logging Made Easier With Loguru

While Python’s standard logging module is powerful, navigating its system of handlers, formatters, and filters can often feel like more work than it should be. This article describes how to achieve the same (and better) results with a fraction of the complexity using Loguru.

Feature Flags in Depth

Feature flags are a way to enable or disable blocks of code without needing to re-deploy your software. This post shows you several different approaches to feature flags.

What Does -> Mean in Python Function Definitions?

Wondering what the arrow notation means in Python? Discover how -> is used in type hints, functions, and more with simple explanations and examples.

Comparison of New Python Type Checkers: Ty, Pyrefly, and Zuban

How to Drop Null Values in pandas

Learn how to use .dropna() to drop null values from pandas DataFrames so you can clean missing data and keep your Python analysis accurate.

Scaling asyncio on Free-Threaded Python

A recap on the work done in Python 3.14 to enable asyncio to scale on the free-threaded build of CPython.

Python⇒Speed: Testing the compiler optimizations your code relies on

Python 3.14: 3 Smaller Features

With a jam packed 3.14 release around the corner, it’s also important to look at the smaller features coming to Python

Python Memory Tricks: Optimize Your Code for Efficiency in 2025

Learn 8 tricks to reduce memory use in Python programs. Fix memory leaks, pick better data structures, and work with large amounts of data more easily. Use tools like generators and slots with simple code examples. These tips help make your programs faster and stop MemoryErrors.

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Python: capture stdout and stderr in unittest

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Sharing a mutable reference between Rust and Python