Python Weekly - Python Weekly - Issue 664

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Welcome to issue 664 of Python Weekly. Let's get straight to the links this week.
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Articles, Tutorials and Talks

Python's Preprocessor
Every now and then you hear outrageous claims such as “Python has no preprocessor”. This is simply not true. In fact, Python has the best preprocessor of all languages - it quite literally allows us to do whatever we want, and a lot more. It’s just a little tricky to (ab)use.

Try LangChain with Python and Upstash Vector 
The video covers setting up a Lang chain for custom data sets using a variety of tools like Python, Jupyter, and OpenAI, demonstrating API creation, embedding models, and vector database integration. It also discusses implementing rate limiting in a FastAPI application and setting up agents for querying and handling data.

How to build a query language in Python
The article discusses the complexities and challenges of building a custom query language, highlighting key considerations such as syntax design, parsing, and execution. It provides insights and practical tips for developers looking to create or improve their own query languages.

Rye and uv: August is Harvest Season for Python Packaging
The post discusses the evolution of Python packaging tools, highlighting the recent advancements in uv and its potential to become the dominant tool in the space. 

Coding a Multimodal (Vision) Language Model from scratch in PyTorch with full explanation 
The video explains how to code a visual language model from scratch using PyTorch, covering topics such as vision transformers, contrastive learning, and language models. It provides a detailed walkthrough of implementing various components, including the vision encoder, language model, and how to combine image and text embeddings, with explanations of key concepts like attention mechanisms and normalization.

Gemma for Streaming ML with Dataflow
The article demonstrates how to integrate Google's Gemma 2 language model into a Dataflow pipeline for real-time sentiment analysis and response generation in customer support chats. It provides a practical example of using Gemma to process streaming data, including code snippets for creating prompts, running inference, and handling model outputs within a scalable data processing framework.

Saving Scrapy Crawl Stats to PostgreSQL with a Custom Extension and SQLAlchemy
The post explains how to extend Scrapy to save crawl statistics directly into a PostgreSQL database, detailing the implementation process and configuration needed. It provides a guide for integrating Scrapy with PostgreSQL to enhance data management and analysis.


Interesting Projects, Tools and Libraries

RAG_Techniques
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems.

LabelU
Data annotation toolbox supports image, audio and video data.

awaitless 
Making asyncio less painful in ipython.

NomadNet
Off-grid, resilient mesh communication with strong encryption, forward secrecy and extreme privacy.

Qik
Qik is a command runner that understands the import graph, allowing you to cache commands and only run the things that matter. Can dramatically speed up CI/dev in large monorepos.

Pare
Pare is the easiest way to deploy Python Lambdas alongside your primary web application.

llmio
A Lightweight Library for LLM I/O.


Upcoming Events and Webinars

BayPIGgies Meetup August 2024
There will be following talks
  • Zero Code Change GPU-Accelerated Data Science in Python
  • Scalene to keep your code fast enough

Virtual: Python New Zealand Meetup August 2024
There will be following talks
  • The mechanics of matplotlib and how one could embed charts into various outputs
  • ReportLab PDF Toolkit

Virtual: PyLadies Amsterdam Meetup August 2024
There will be a workshop, Build a Data Science Portfolio that Gets You Noticed.

PyData Amsterdam Meetup August 2024
There will be following talks
  • Payments Data Science at Uber
  • Exploring ESG performance in job ads through AI and Data Science
  • Polar Expedition: Speed and Developer Experience Insights of transitioning ML pipelines to Polars

PyData Zurich Meetup August 2024
There will be following talks
  • Streamlining Python Development: A Practical Approach to CI/CD with GitHub Actions
  • Fast and user-friendly GLMs with glum 3

PyData Calgary Meetup August 2024
There will be a talk, AI Beyond the hype: Applying Large Language Models and Agentic AI to simplify knowledge curation and retrieval.
 
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