google-deepmind / gemma

Gemma open-weight LLM library, from Google DeepMind

https://github.com/google-deepmind/gemma

What's new in pip 26.1

pip 26.1 adds support for dependency cooldowns, experimental support for reading/installing from standard lockfiles (pylock.toml), fixes several long-standing limitations of the 2020 resolver, and drops support for Python 3.9.

https://ichard26.github.io/blog/2026/04/whats-new-in-pip-26.1/

ml-intern

An open-source ML engineer that reads papers, trains models, and ships ML models.

https://github.com/huggingface/ml-intern

honker

SQLite extension + bindings for Postgres NOTIFY/LISTEN semantics with durable queues, streams, pub/sub, and scheduler

https://github.com/russellromney/honker

Easily Stream LLM Responses with Django-Bolt and PydanticAI

A guide showing how easy it is to start using django-bolt and PydanticAI agents together.

https://www.caktusgroup.com/blog/2026/04/27/django-bolt-easy-pydanticai-streaming/

Choosing a Python Logging Library in 2026

Compare Pythons standard logging module structlog and Loguru with real benchmarks OpenTelemetry integration paths and frameworkspecific guidance for Django FastAPI and Flask.

https://www.dash0.com/guides/python-logging-libraries

Databases Were Not Designed For This

The post defines defensive databases as systems designed to protect data from buggy, noisy, or autonomous applications through safeguards such as idempotency, auditability, soft deletes, controlled writes, and strict permissions. As AI agents and distributed services generate more unpredictable traffic, data stores must actively preserve integrity rather than assuming every client behave...

https://arpitbhayani.me/blogs/defensive-databases