PythonHub

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/

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/

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

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

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/

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

Arbalister Dataframe viewer for Jupyter over Arrow. https://github.com/QuantStack/Arbalister

microgpt.py Train and inference GPT in 243 lines of pure, dependency-free Python. https://gist.github.com/karpathy/8627fe009c40f57531cb18360106ce95

Zoocache Semantic dependency based cache with high performance and concurrency in mind. https://github.com/albertobadia/zoocache

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

Webmentions with batteries included A zero-cost library to integrate Webmentions in your website. https://blog.fabiomanganiello.com/article/webmentions-with-batteries-included

VOOG – Moog-style polyphonic synthesizer in Python with tkinter GUI https://github.com/gpasquero/voog

Better Python tests with inline-snapshot Learn how Pydantic uses inline-snapshot and dirty-equals for better testing. https://pydantic.dev/articles/inline-snapshot

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/

Python as you've never seen it before https://www.reddit.com/r/Python/comments/1qxohhp/python_as_youve_never_seen_it_before/

Monty: A minimal, secure Python interpreter written in Rust for use by AI https://github.com/pydantic/monty

Skills in OpenAI API https://developers.openai.com/cookbook/examples/skills_in_api

disler / claude-code-hooks-mastery Master Claude Code Hooks https://github.com/disler/claude-code-hooks-mastery

Django: profile memory usage with Memray The article shows how to profile Python-based Django apps using Memray to find memory leaks and inefficient allocations by capturing allocation snapshots and comparing them over time. It walks through setup, running profiles locally, analyzing results, and using traces to make targeted improvements that reduce memory usage and improve performance. https://adamj.eu/tech/2026/01/29/django-profile-memray/

10 Python Features You’re Not Using (But Really Should) The video highlights lesser-known but powerful Python features that can significantly improve code readability, safety, and performance. Through practical before-and-after examples, it shows experienced Python developers how small language features can meaningfully level up real-world code. https://www.youtube.com/watch?v=cXl-AUXHHZY