Deploying Python Web Applications with Docker

The post is a hands-on guide explaining why the author migrated his Python web applications to Docker containers, highlighting Docker’s consistent isolation and practical benefits for deployment compared to traditional setups like system Python and virtual environments. It walks through what to include in the container (base image, Python, virtual environment, and WSGI server such as gun...

https://chriswarrick.com/blog/2026/02/06/deploying-python-web-applications-with-docker/

Better Python tests with inline-snapshot

Learn how Pydantic uses inline-snapshot and dirty-equals for better testing.

https://pydantic.dev/articles/inline-snapshot

Webmentions with batteries included

A zero-cost library to integrate Webmentions in your website.

https://blog.fabiomanganiello.com/article/webmentions-with-batteries-included

The "LLM-as-Analyst" Trap: A Technical Deep-Dive into Agentic Data Systems

Why the simplest agentic pattern is the most dangerous for factual data operations.

https://appliedingenuity.substack.com/p/the-llm-as-analyst-trap-a-technical

Zoocache

Semantic dependency based cache with high performance and concurrency in mind.

https://github.com/albertobadia/zoocache

microgpt.py

Train and inference GPT in 243 lines of pure, dependency-free Python.

https://gist.github.com/karpathy/8627fe009c40f57531cb18360106ce95

Arbalister

Dataframe viewer for Jupyter over Arrow.

https://github.com/QuantStack/Arbalister

airs-bench

An AI Research Science benchmark for quantifying the end-to-end AI research abilities of LLM agents.

https://github.com/facebookresearch/airs-bench

Python 3.12 vs 3.13 vs 3.14: What Changed and Which Should You Use

Compare Python 3.12, 3.13, and 3.14 side by side. See what changed across free-threading, JIT, t-strings, performance, and library support plus which version you should actually use in 2026.

https://releaserun.com/python-3-12-vs-3-13-vs-3-14-comparison/

Stop Building Ugly APIs: Use the Fluent Interface Pattern

The video walks through refactoring a small Python animation API from a clunky configuration style into a fluent interface that reads like a story using method chaining and domain specific methods. It also explains what the fluent interface pattern is, how it differs from the builder pattern, where it already appears in Python, and when it is appropriate or inappropriate to use.

https://www.youtube.com/watch?v=f1Nb_JV_s8Y

memory_graph

Teaching tool and debugging aid in context of references, mutable data types, and shallow and deep copy.

https://github.com/bterwijn/memory_graph

Making Pyrefly Diagnostics 18x Faster

Learn about the recent performance improvements made to Pyrefly's language server capabilities.

https://pyrefly.org/blog/2026/02/06/performance-improvements/

Rewriting pycparser with the help of an LLM

Eli describes how he used an LLM coding agent (Codex) to help rewrite the popular Python C parser pycparser, replacing its old PLY based parser with a hand-written recursive descent parser that passes the full test suite and is easier to maintain. He found the experience efficient and insightful, noting the agent did most of the heavy work in far less time than doing it manually while hi...

https://eli.thegreenplace.net/2026/rewriting-pycparser-with-the-help-of-an-llm/

Calling Lean Functions As Python Functions

Philip Zucker introduces leancall, a Python library designed to bridge the gap between Lean 4 and Python by allowing Lean functions to be called as native Python functions. He demonstrates its utility through practical examples like balancing a Cartpole in a reinforcement learning environment and building a ray tracer, highlighting Lean's performance benefits while leveraging Python's va...

https://www.philipzucker.com/leancall/

review-prompts

AI-assisted code review prompts for Linux kernel and systemd development. Works with Claude Code and other AI tools.

https://github.com/masoncl/review-prompts

InstaCloud

Cloud Storage using Instagram.

https://github.com/depreciating/InstaCloud/

Speeding up NumPy with parallelism

Parallelism can speed up your NumPy code… and can still benefit from other optimizations.

https://pythonspeed.com/articles/numpy-parallelism/

Auto-Claude

Autonomous multi-agent coding framework that plans, builds, and validates software for you.

https://github.com/AndyMik90/Auto-Claude