Python Weekly - Python Weekly - Issue 641

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Welcome to issue 641 of Python Weekly. Let's get straight to the links this week.
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Articles, Tutorials and Talks

Python Upgrade Playbook
In this post, we’ll cover how Lyft upgrades Python at scale — 1500+ repos spanning 150+ teams — and the latest iteration of the tools and strategy we’ve built to optimize both the overall time to upgrade and the work required from our engineers. We’ve successfully used (and evolved) this playbook over multiple upgrades, from Python 2 to Python 3.10.

Building an LLM fine-tuning Dataset 
The video shares insights on building a comprehensive dataset for AI model training using Reddit comments, highlighting challenges such as working with large datasets and filtering out low-quality comments. The creator discusses methods like loading, sorting, and filtering data to create training samples and models, emphasizing the abundance of comments available for analysis and the process of fine-tuning models for efficient training. Ultimately, they decide to use the llama 27b model and discuss plans for utilizing the 480 super GPU for faster fine-tuning and uploading datasets.

Better PC cooling with Python and Grafana
The article discusses improving PC cooling using Python and Grafana, focusing on finding the minimum and maximum fan speeds to optimize cooling performance by exploiting thermal mass and running fans at empirically derived speeds, resulting in enhanced cooling efficiency and reduced noise levels

Create a quiz app in 6 minutes with HTMX and Django
This guide shows you how to build a simple quiz application using Django and HTMX in 6 minutes. HTMX is great for creating dynamic web applications without writing JavaScript.

Multilingual Support In Django
The article delves into the complexities of implementing multilingual support in Django, exploring the challenges and processes involved in internationalization (i18n) and localization. It provides insights into how Django facilitates the translation of strings, the use of GNU gettext framework, and the overall framework for supporting multiple languages within Django projects.

Machine Learning in 2024 – Beginner's Course 
This machine learning course is created for beginners who are learning in 2024. The course begins with a Machine Learning Roadmap for 2024, emphasizing career paths and beginner-friendly theory. Then it the course moves on to hands-on practical applications and a comprehensive end-to-end project using Python.

Intro to DSPy: Goodbye Prompting, Hello Programming!
How the DSPy framework solves the fragility problem in LLM-based applications by replacing prompting with programming and compiling.

How fast can we process a CSV file
The article explores the speed of processing CSV files, highlighting the use of PyArrow to enhance CSV reading speed significantly. It compares different methods like pandas with C engine, pure Python looping, and pandas with PyArrow engine, showcasing the efficiency of PyArrow in processing CSV files faster and more effectively

Levels of Complexity: RAG Applications
This post is a comprehensive guide to understanding and implementing RAG applications across different levels of complexity. Whether you're a beginner eager to learn the basics or an experienced developer looking to deepen your expertise, you'll find valuable insights and practical knowledge to help you on your journey. Let's embark on this exciting exploration together and unlock the full potential of RAG applications.

Combining Rust and Python: The Best of Both Worlds? 
This video shows you how to seamlessly integrate Rust with Python using Pyo3. This library allows you to write Python modules with Rust. This means that we get the speed and safety of Rust along with Python's easy-to-use features!

Deploying Django Apps in Kubernetes
Learn you can optimize Django deployments seamlessly in a Kubernetes environment, whether you are a Django developer or a Kubernetes enthusiast.

Get started with conda environments
This post explains the benefits of virtual environments and how to use virtual environments in conda.

From Beeps to Toots: Reviving Pagers with Python and Mastodon
The article showcases a unique application of Python programming by connecting pagers with Mastodon, blending the reliability of pagers with modern social media interactions. It highlights the versatility of Python in bridging analog devices like pagers with digital platforms, demonstrating the enduring relevance of traditional communication methods in today's digital age.

Python environment management using JupyterLab Desktop CLI
The article discusses Python environment management using the JupyterLab Desktop CLI, which offers various commands and options to manage Python environments efficiently within the application. It covers setting up the JupyterLab Desktop CLI, creating new Python environments, and utilizing bundled environment installers or downloading packages from the registry to enhance the development process.

6 ways to improve the architecture of your Python project (using import-linter)
The article discusses six ways to enhance the architecture of Python projects, focusing on maintaining clear dependency relationships between packages and modules to avoid tangled inter-module dependencies. It addresses challenges like high architectural understanding costs for newcomers and reduced development efficiency due to difficulties in locating code within large projects.


Interesting Projects, Tools and Libraries

Hatchet
A Distributed, Fault-Tolerant Task Queue.

BlendSQL
Unified dialect for orchestrating SQLite logic and LLM reasoning.

django-admin-shellx
A Django Admin Web Shell using Xterm.js and Django Channels.

Bonito
A lightweight library for generating synthetic instruction tuning datasets for your data without GPT.

FastUI
Build better UIs faster.

Hancho
A simple pleasant build system in Python.

Cadwyn
Production-ready community-driven modern Stripe-like API versioning in FastAPI.

flect
A pure Python full-stack web apps framework inspired by Next.js.

pfl
Python framework for Private Federated Learning simulations.

EvalPlus
EvalPlus for rigourous evaluation of LLM-synthesized code.

polars_ds_extension
Polars extension for general data science use cases.


New Releases

Django security releases issued: 5.0.3, 4.2.11, and 3.2.25


Upcoming Events and Webinars

San Francisco Python Meetup March 2024
There will be following talks
  • Spreadsheet Does What?!?
  • Unstructured: an ETL for LLMs
  • Data Pipeline Scorecard
  • Helping Developers Help Themselves

Django London Meetup March 2024
There will be following talks
  • WASM-powered Django apps with PyScript
  • Navigating your job search in 2024

PuPPy Meetup March 2024
There will be following talks
  • Simulating the 3-Polarizer Experiment on a Quantum Computer
  • Why I love planning and you should too!
  • The Rising Sea

Virtual: PyMNtos Python Presentation Night #123
There will be following talks
  • Ideas for the Third Edition of "Introducing Python"
  • Multi-modal Image Search with CLIP

PyData NYC Meetup March 2024
There will be following talks
  • Building LLM Applications in Production
  • But, Did You Tune the Hyperparameters Enough?

PyData Johannesburg Meetup March 2024
There will be a talk, Demystifying Data Ingestion Challenges with Apache Nifi.

PyData Zurich Meetup March 2024
There will be a talk, The Versatility of Attention-Based Autoregressive Models.
 
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