Better Django management commands with django-click and django-typer

Streamline Django management commands using django-click and django-typer for cleaner syntax, built-in argument parsing, and richer output via type annotations and customizable CLI styling.

Using the Python Match Statement

Beyond htmx: building modern Django apps with Alpine AJAX

Faster Python: Concurrency in async/await and threading

If you have been coding with Python for a while, especially if you have been using frameworks and libraries such as Fast API and discord.py, then you have probably been using async/await or asyncio.

How Local Variables Work in Python Bytecode

To better understand the internals of an interpreter, this article shows you how local variables get stored and how stacks and frames work.

Data Validation Libraries for Polars (2025 Edition)

Object Detection and Visual Grounding with Qwen 2.5

Automatic Dead‑Link Detection

django-linkcheck is a Django app that automates dead link detection in URLFields and HTML content, schedules checks, and provides an admin interface.

Optimizing Django Docker Builds with Astral’s `uv`

Astral’s uv dramatically accelerates and secures Django Docker builds by leveraging multi-stage images, cache mounts, and strict lockfile verification for deterministic dependency management.

Pointblank: Data Validation for DataFrames and DBs

Writing Portable DataFrame Code for Lazy Execution

Learn one simple concept, and you can rid your code of row-ordering assumptions - it will then work seamlessly across eager and lazy DataFrames

Content Moderation via Zero Shot Learning with Qwen 2.5

Docker: disable “What’s next” adverts

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Writing your own CUPS printer driver in 100 lines of Python (2018)

Pyrefly vs. ty: Comparing Python’s Two New Rust-Based Type Checkers

GitHub Actions: avoid double runs from on: [push, pull_request]

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Dataclass For Django Custom Command Arguments

Leveraging dataclasses for Django custom command arguments centralizes default settings and URL query construction, streamlining code and reducing potential mismatches.

Python⇒Speed: Loading Pydantic models from JSON without running out of memory

How to separate test data from code: testing with CSV in pytest

Want to test a function with dozens of variants? I'll show you how to organize test cases in a CSV file and connect them to pytest using the pytest-csv-params plugin.

Why, in 2025, do we still need a 3rd party app to write a REST API with Django?