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News & links about Python programming.
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Python Pro Hub – Python Error Fixes, Data Science & AI Tutorials

Fix Python errors fast. Tutorials covering data science, AI projects, Flask, Django, and automation for all skill levels.

https://pythonprohub.com/
How and why to run modified Python code using the ast module

Learn how to use Python's ast module to parse, transform, and execute code at runtime, using eval-type-backport as a real-world Python metaprogramming example.

https://pydantic.dev/articles/eval-type-backport
Jupyter Enterprise Gateway: From Notebook to Kubernetes Cluster Admin

Security researchers at elttam uncovered three critical vulnerabilities in Jupyter Enterprise Gateway that allow notebook users to escalate privileges and potentially take over an entire Kubernetes cluster. The post walks through the attack chain from a Jupyter notebook to cluster-wide compromise, highlighting the risks of running multi-tenant notebook infrastructure without strong isola...

https://www.elttam.com/blog/jupyter-enterprise-gateway
Nested Loops Aren’t the Problem. This Is.

This video explains why nested loops are often a design problem rather than an algorithmic necessity, typically resulting from poor data structures or misplaced responsibilities. Using a real-world refactoring example, it shows how restructuring code can reduce complexity and improve maintainability.

https://www.youtube.com/watch?v=095HrcWwHLI
The 2026 way of using importmaps in Django

The post explains a modern Django approach to JavaScript using import maps, native browser modules, and a shared import map rendered by Django templates. It argues that import maps can eliminate the need for bundlers in many applications while still supporting cache-busted static assets and reusable third-party app JavaScript.

https://406.ch/writing/the-2026-way-of-using-importmaps-in-django/#the-2026-way-of-using-importmaps-in-django
Testing in Python with pytest: from the basics to advanced techniques

This comprehensive guide covers pytest from basic testing concepts to advanced techniques such as fixtures, parametrization, mocking, and asynchronous testing. It provides practical patterns for building maintainable, scalable Python test suites and leveraging pytest effectively in production environments.

https://en.andros.dev/blog/b6bf68de/testing-in-python-with-pytest-from-the-basics-to-advanced-techniques/
GitHub Pages alternative with native Python

This article shows how to recreate core GitHub Pages functionality using only Python's standard library, including static file serving, automated deployments, and HTTPS support. By extending http.server in just a few dozen lines of code, it demonstrates how native Python tools can power a lightweight static website hosting platform.

https://blog.klemek.fr/articles/2026-06-14/