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- Python Weekly (Issue 691 March 20 2025)
Python Weekly (Issue 691 March 20 2025)
Rahul Chaudhary
March 20, 2025
Welcome to issue 691 of Python Weekly. Let's get straight to the links this week.
Articles, Tutorials and Talks
This episode of Talking Postgres features Dawn Wages, chair of the Python Software Foundation, discussing why Python and Django developers favor PostgreSQL. They explore her "Just Use Postgres" philosophy, the Djangonaut Space mentoring program, and Python's strengths.
Astral is developing a new Python type checker, aiming to be significantly faster than mypy. The author explores building and running it, finding it promisingly fast but still a work in progress with some type checking discrepancies.
Marimo reinvents Python notebooks as reusable Python programs by storing them as plaintext .py files, improving version control, reusability, and testability compared to traditional JSON-based .ipynb notebooks. This new format allows notebooks to be imported, executed as scripts, and integrated with standard Python tools, while still maintaining interactivity.
This video tutorial demonstrates how to use the Flet framework in Python to build cross-platform mobile and desktop apps, even without prior front-end development experience. It walks through creating a simple quiz application, explaining how to structure the UI with Flet controls and handle user interactions.
This video provides a step-by-step guide to creating optimized and efficient Docker images for Python applications, covering topics like choosing the right base image, cleaning up dependencies, using multi-stage builds, and enhancing security. It also highlights the frustrations of working with Docker and potential pitfalls to avoid.
This post advocates for testing Django admin changelist views, which are often overlooked despite being prone to errors due to Django's "magic-string"-heavy admin DSL. The author provides a parametric test using pytest to ensure that every admin view can render its empty state, catching potential issues early.
This tutorial guides viewers through creating a Python program that simulates the March Madness tournament, using team seeds to generate realistic probabilities and predict potential upsets. The program utilizes Python's dataclasses and the random module to build a tournament function that determines the champion.
This blog post introduces egglog, a new library that combines equality saturation and datalog, offering advantages over traditional e-graph libraries like egg. It highlights egglog's cleaner syntax, efficient execution through database techniques, and improved performance in areas like multi-pattern matching and incremental e-matching.
Cocoa, coffee, and other commodities have gotten expensive -- but by how much? In this video, we explore the World Bank's "pink sheet" that tracks commodity prices, and then plot these changes using Seaborn.
Use python’s shelve as a quick and easy, persistent key-value store for LLM workflows.
The Hugging Face post discusses a signature detection model built using the YOLOv8 object detection framework. The model accurately detects signatures in various documents, demonstrating its effectiveness in document verification, fraud detection, and automation processes.
Books
This handbook guides Python developers through the ecosystem of tools that enhance productivity, covering areas like packaging, linting, formatting, and dependency management. It's structured to provide tutorials, how-to guides, explanations, and references to help make sense of the complex world of Python development.
Interesting Projects, Tools, and Libraries
A collaborative note taking, wiki and documentation platform that scales. Built with Django and React. Opensource alternative to Notion or Outline.
A Conversational Speech Generation Model.
RA.Aid (pronounced "raid") helps you develop software autonomously. It is a standalone coding agent built on LangGraph's agent-based task execution framework. The tool provides an intelligent assistant that can help with research, planning, and implementation of multi-step development tasks.
Fully local web research and report writing assistant.
Basic Memory is a knowledge management system that allows you to build a persistent semantic graph from conversations with AI assistants. All knowledge is stored in standard Markdown files on your computer, giving you full control and ownership of your data.
An open agentic framework that uses computers like a human.
Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation.
Lightweight Pandas monkey-patch that adds async support to map, apply, applymap, aggregate, and transform, enabling seamless handling of async functions with controlled max_parallel execution.
Pythonx runs a Python interpreter in the same OS process as your Elixir application, allowing you to evaluate Python code and conveniently convert between Python and Elixir data structures.
A 1.3B generalist diffusion model for Novel View Synthesis (NVS), generating 3D consistent novel views of a scene, given any number of input views and target cameras.
Pruna is a model optimization framework built for developers, enabling you to deliver faster, more efficient models with minimal overhead.
A simple tool that let's you explore different possible paths that an LLM might sample.
New Releases
Upcoming Events and Webinars
There will be following talks
Purr-mission Granted: Machine Vision in the Real World
Data Science Without Data: Building Models When Real Data is Scarce
There will be following talks
Building RAG Systems for Enterprises
Unlocking Efficiency: AI-Driven Email Classification for Salesforce Customer Support
There will be following talks
Navigating the Intersection of MLOps and GenAI: A Comparative Exploration
Building LEGO Castles Instead of Sandcastles: A Tale of Modularity in Data & ML Systems
There will be following talks
How to Hack an Agent – or Not
AI & Data Strategy after NVIDIA GTC 2025
There will be following talks
Machine learning based video processing
How LLMs Can Transform the Landscape of Web Scraping?
There will be a talk, From Batch to Brilliant: Cheap Real-Time Spark Streaming Made Simple.
There will be a talk, A Beginner’s Guide to Building LLM Apps with Python.
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