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Human-curated Python news, projects, articles & tools.

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This Design Pattern Replaces an Entire Class Hierarchy

This video compares three ways to model type-based variation in Python: subclasses, storing a type value such as an enum, and representing each variation as an object. Using a subscription system, it introduces the Type Object pattern and explains when each approach is the better fit.

https://www.youtube.com/watch?v=IdwdqdywNOM
Put the Arithmetic in the Tool: an MCP Server for an AWS Waste Scanner

The article shows how to add an MCP server to a Python-based AWS cost scanner so AI agents can query computed totals, breakdowns, filters, and cleanup plans without doing arithmetic themselves. It also covers JSON-RPC over stdio, read-only tool design, end-to-end testing, rounding consistency, and integration with Claude Code.

https://dev.to/aws-builders/put-the-arithmetic-in-the-tool-an-mcp-server-for-an-aws-waste-scanner-3n79
Share how you use Django with Django Probe

The post introduces Django Probe, a tool that scans Django projects and anonymously aggregates how framework APIs and patterns are actually used. The goal is to give Django maintainers better data for decisions around deprecations, new features, documentation, and community priorities.

https://www.better-simple.com/django/2026/09/17/share-how-you-use-django-with-django-probe/
TATS

TATS is an open-source Python tool for analyzing OAuth 2.0, OpenID Connect, and Microsoft Entra ID tokens, helping security researchers trace authentication flows, identify risky permissions, and visualize token lifecycles.

https://github.com/IceMoonHSV/TATS
Speeding Up a Python Service with CinderX: JIT and Static Typing

Timofei Ivankov explores how CinderX’s JIT compiler and Static Python can accelerate real-world Python services, comparing their internals and performance with CPython 3.14’s experimental JIT. Benchmarks show that combining Static Python with JIT compilation increased a CPU-bound endpoint’s throughput from 140 to 250 requests per second, while NumPy-heavy workloads saw no benefit and gar...

https://dev.to/deadlovelll/speeding-up-a-python-service-with-cinderx-jit-and-static-typing-53bh