IPython - 8.30.0

Интерактивная оболочка для языка программирования Python. Скачать можно по ссылке: https://pypi.python.org/pypi/IPython

htmy: Async, Pure-Python Server-Side Rendering Engine

pex: Generate Python EXecutable Files, Lock Files and Venvs

Python Dependency Management Is a Dumpster Fire

Managing dependencies in Python can be a bit of a challenge. This deep dive article shows you all the problems and how the problems are mitigated if not solved.

Django Performance and Optimization

“This document provides an overview of techniques and tools that can help get your Django code running more efficiently - faster, and using fewer system resources.”

Django: fix a view using a debugger with breakpoint()

aiohttp - 3.11.8

http клиент/сервер для asyncio. Скачать можно по ссылке: https://pypi.python.org/pypi/aiohttp

selenium - 4.27.1

Модуль для автоматизации тестирования web-приложений. Скачать можно по ссылке: https://pypi.python.org/pypi/selenium/

virtualenv - 20.28.0

Инструмент создания виртуального рабочего окружения. Скачать можно по ссылке: https://pypi.python.org/pypi/virtualenv

selenium - 4.27.0

Модуль для автоматизации тестирования web-приложений. Скачать можно по ссылке: https://pypi.python.org/pypi/selenium/

Talk Python to Me: #486: CSnakes: Embed Python code in .NET

Audio

pretix/pretix

Ticket shop application for conferences, festivals, concerts, tech events, shows, exhibitions, workshops, barcamps, etc.

Is async django ready for prime time?

Django's async capabilities have significantly improved, making it a viable option for production use, especially in AI applications where I/O-bound tasks are prevalent.

Django Channels 4.2.0

FireDucks : Pandas but 100x faster

Security means securing people where they are

Huey Background Worker - Building SaaS #207

Diagram-as-Code: Creating Dynamic and Interactive Documentation for Visual Content

Django: find ghost tables without associated models

NumPy Practical Examples: Useful Techniques

In this tutorial, you'll learn how to use NumPy by exploring several interesting examples. You'll read data from a file into an array and analyze structured arrays to perform a reconciliation. You'll also learn how to quickly chart an analysis and turn a custom function into a vectorized function.