Python Hub Weekly Digest for 2023-10-01
💖 Most Popular
EuroPython 2023 Videos
Here are all the videos for the conference, brought to you by the EuroPython 2023 Team and the EuroPython Society.
Why Are There So Many Python Dataframes?
This post explores the proliferation of Python dataframes, dissecting the reasons behind their prevalence in data science and analysis, shedding light on the various libraries and frameworks that contribute to their abundance.
HomeHarvest
Python package for real estate scraping, supporting Zillow, Realtor.com & Redfin.
How to add serverless functions to Django in 6 minutes (with HTMX and AWS Lambda)
This article discusses the integration of serverless functions with Django, highlighting how developers can leverage the benefits of serverless computing for specific tasks in a Django application. It explores the advantages of serverless architecture and provides practical insights for implementation.
📖 Articles
Shshsh is a bridge connects Python and shell
ludwig-ai / ludwig
Low-code framework for building custom LLMs, neural networks, and other AI models
Compiling ML models to C for fun
ML models can be compiled to graphs, which can be traversed to perform forward and backward passes. This approach can improve performance and make it easier to debug ML models.
Speeding up Floyd-Steinberg dithering: an optimization exercise
A worked out example: optimizing low-level code to get significant performance and memory improvements.
I made a transformer by hand (no training!)
Simulate the Monty Hall problem in Python
Use Python to solve this classic probability puzzle that has stumped mathematicians and Nobel Prize winners!
Building RAG-based LLM Applications for Production (Part 1)
In this guide, we will learn how to develop and productionize a retrieval augmented generation (RAG) based LLM application, with a focus on scale, evaluation and routing.
Python 3.12.0 release candidate 3 now available
neulab / prompt2model
prompt2model - Generate Deployable Models from Natural Language Instructions
19X faster response time
Lincoln Loop optimized a large publishing platform's database performance. Overall, the database performance increased 19 times.
facebookresearch / codellama
Inference code for CodeLlama models
Python Hub Weekly Digest for 2023-09-24
⚙️ Projects
PyLLMCore
A pythonic library providing light-weighted interface with LLMs
vpselector
Visual Pandas Selector: Visualize and interactively select time-series data.
QuasiQueue
QuasiQueue is a MultiProcessing library for Python that makes it super easy to have long running MultiProcess jobs. QuasiQueue handles process creation and cleanup, signal management, cross process communication, and all the other garbage that makes people hate dealing with multiprocessing.
Galactic
Galactic provides cleaning and curation tools for massive unstructured text datasets. It's designed to help you curate fine-tuning datasets, create document collections for retrieval-augmented generation (RAG), and even perform deduplication of web-scale datasets for LLM pre-training. This
Logparser
Logparser provides a machine learning toolkit and benchmarks for automated log parsing, which is a crucial step for structured log analytics
llm-guard
The Security Toolkit for LLM Interactions.
PYOBD
Open source obd2 car diagnostics program.
HTTP-Shell
MultiPlatform HTTP Reverse Shell.
Temporian
Temporian is a Python library for feature engineering and data augmentation of temporal data (e.g. time-series, transactions) in machine learning applications.
EvoDiff
Generation of protein sequences and evolutionary alignments via discrete diffusion models.
PyGraft
Configurable Generation of Schemas and Knowledge Graphs at Your Fingertips.
👾 Reddits
Why does Python Code Run Faster in a Function?
Project by Ruslan Keba. Since 2012. Powered by Python. Made in 🇺🇦Ukraine.