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- Python Weekly (Issue 737 March 19 2026)
Python Weekly (Issue 737 March 19 2026)
Rahul Chaudhary
March 19, 2026
In partnership with
Welcome to issue 737 of Python Weekly. Let's get straight to the links this week.
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Articles, Tutorials and Talks
The pyca/cryptography team is moving away from OpenSSL 3 due to performance issues, complexity, and lack of memory safety progress, instead adopting alternatives like AWS-LC and BoringSSL. They are also oxidizing the codebase by integrating Rust for safer, faster cryptography (e.g., X.509 parsing) and preparing for future needs like post-quantum crypto.
The post explores a redesign of Python’s async runtime, arguing that the current async/await and event-loop model adds unnecessary complexity, and proposing a simpler runtime where concurrency is handled automatically without explicit async syntax.
The author experiments with a new runtime approach that can run async workloads 2–3.5× faster than traditional asyncio, suggesting Python’s concurrency model could be simpler and more performant if redesigned from the ground up.
Ken Jin reports that the Python 3.15 alpha JIT has surpassed its early performance targets, achieving an 11-12% speedup on macOS AArch64 and 5-6% on x86_64 Linux. The post outlines a roadmap toward a 10% faster JIT by Python 3.16, with a focus on implementing free-threading support and reducing the project's bus factor across its optimizer and code generator.
When you write typed Python, you expect your type checker to follow the rules of the language. But how closely do today's type checkers actually follow the Python typing specification? In this post, we look at what typing spec conformance means, how different type checkers compare, and what the conformance numbers don't tell you.
Django allows empty strings ('') even on non-nullable string fields, so you must explicitly enforce non-empty values using validation or database constraints rather than relying on null=False. The post argues for treating empty strings as invalid at the model or DB level (e.g., validators or CHECK constraints) to ensure true “required” semantics for string fields.
This Django package leverages the PostgreSQL Anonymizer extension to allow developers to define data masking and security labels directly within their models. By handling anonymization at the database level, it ensures the application only accesses masked data, preventing sensitive information leaks during LLM integration or data sharing.
By replacing primitives with immutable Value Objects, you can centralize validation and eliminate domain ambiguity for types like prices and percentages. This pattern ensures that invalid states are impossible to represent, creating a self-documenting and more reliable codebase without the overhead of heavy frameworks.
In this video, we'll take a look at Agents in Pydantic AI, and will create a simple Agent that can be run synchronously and asynchronously. We'll explore how to inspect agent outputs, and how to amend outputs using instructions that are passed to the LLM.
Dropbox used DSPy to turn prompt engineering for our relevance judge into a measurable, automated optimization loop, improving task performance, cost, and how reliably it works in production.
Interesting Projects, Tools, and Libraries
Open-source framework for building your org's internal coding agent.
Fully autonomous & self-evolving research from idea to paper. Chat an Idea. Get a Paper.
A lightweight, self-hosted terminal that gives AI agents and automation tools a dedicated environment to run commands, manage files, and execute code — all through a simple API.
Agent harness built with LangChain and LangGraph. Equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - well-equipped to handle complex agentic tasks.
Agentic IM Chatbot infrastructure that integrates lots of IM platforms, LLMs, plugins and AI feature, and can be your openclaw alternative.
The Agentive Operating System for Physical Space.
A 3D visualization library for Python. pip install, write a few lines, and you have a GPU-accelerated interactive 3D viewer.
A TUI command launcher built on top of just. Define recipes once, run them anywhere.
Speaker identification powered by pyannote and resemblyzer.
High-Performance, Zero-Copy Graph Engine for Massive Datasets on Consumer Hardware.
In-process virtual filesystem with hard quota for Python.
Open-source Terraform Enterprise replacement.
FastAPI-compatible Python framework. Zig HTTP core. 7x faster.
A type-safe, Pydantic-centric asynchronous ORM with a high-performance Rust core designed for clarity, speed, and reliability.
Upcoming Events and Webinars
There will be a talk, Building Beautiful Command Line Apps.
There will be following talks
Making a Match: How Open Source Maintainers and Contributors Can Find Each Other Better.
To Vibe or Not To Vibe: Lessons from Vibe-Coding Small, Imperfect AI Projects
There will be a talk, From ER Nurse to AI Engineer: Building Real Healthcare AI Systems with RAG & Agents.
There will be a talk, ValVet: An evaluation framework for large language models.
There will be following talks
AI bias – gender gap
Beyond Vibe Coding: Building an Agentic "Product Brain" for Engineering Teams
There will be following talks
GoFish: Make Expressive Data Visualizations with Ease
SPARQL-TOOL: Allow your Agent to query knowledge graphs
There will be following talks
Can AI agents help solve Europe’s Largest Cold Case?
From Keywords to Concepts: A Late Interaction Approach to Semantic Product Search on IKEA.com
There will be following talks
Garbage Semantics In, Garbage AI Out
Mapping the PyData Community
There will be a talk, An Unexpected Journey: Life Lessons from Conquering Tesla Solar with Python.
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