Python's experimental JIT to be removed

Custom Voices With Qwen3-TTS

With my kids I’m currently building a little dungeron crawler and we’re trying to learn a bit about game development along the way. However given that we live in the modern times of increasing capabilities we wanted to get a narrator and voice over. But we also wanted it to not sound like everyone’s standard AI voices so I looked into what options there are on the table.

pip - 26.3

Утилита для управления модулями в Python. Скачать можно по ссылке: https://pypi.python.org/pypi/pip/

Talk Python to Me: #567: Personal AI Agents for Pythonistas

Audio

terrahour: World Clock With a Day/Night Map for the Terminal

amqp - 5.4.2

AMQP-клиент. Скачать можно по ссылке: https://pypi.python.org/pypi/amqp/

PyPy: The Shift of Theseus — Toy Bit Provenance Abstract Domain

HoloViz Lumen 1.4.0

HoloViz Lumen - агент обращения к данным на естественном языке

Введение в чтение barcode

Twisted - 26.10.0

Фреймворк для написания асинхронных приложений. Скачать можно по ссылке: https://pypi.python.org/pypi/twisted/

pyflakes - 4.1.0

Статический анализатор Python-кода. Скачать можно по ссылке: https://pypi.python.org/pypi/pyflakes/

flake8 - 7.5.0

Модуль проверки форматирования кода. Скачать можно по ссылке: https://pypi.python.org/pypi/flake8/

pytest - 9.2.0

Простой мощный инструмент тестирования в Python. Скачать можно по ссылке: https://pypi.python.org/pypi/pytest/

Text-to-Diagram for AI Systems: Designing a DSL an LLM Gets Right

Python Plotting With Matplotlib (Guide)

This article is a beginner-to-intermediate-level walkthrough on Python and matplotlib that mixes theory with example.

hindsight - Agent Memory That Learns

Is Python the favorite language of LLMs?

redis-search-django: Full-Text Search with RediSearch

Why Parquet Dominates Modern Data Engineering

How Parquet’s columnar layout, encodings, zstd compression, and row group statistics make it smaller and faster to read than CSV, measured on NYC taxi trips data with Polars, DuckDB, and PyArrow.

Bayesian Optimization for Efficient Hyperparameter Search

Instead of testing every hyperparameter combination, Bayesian optimization uses results from earlier trials to decide what to try next. This hands-on tutorial builds it step by step with scikit-learn’s GaussianProcessRegressor and a custom Expected Improvement function, plotting the model’s predictions and uncertainty along with each point the search picks.