Awesome Python Weekly

Popular News and Articles

• 
  Why Polars uses less memory than Pandas

  pythonspeed.com
• 
  How to improve Python packaging, or why fourteen tools are at least twelve too many

  chriswarrick.com
• 
  Researchers from Meta AI released ‘balance,’ a Python Package for Balancing Biased Data Samples

  www.marktechpost.com
• 
  

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• 
  Python's Assignment Operator: Write Robust Assignments – Real Python

  realpython.com
• 
  An open source Python project CI pipeline

  brntn.me
• 
  Supply Chain Attack Using Identical PyPI Packages, “colorslib”, “httpslib”, and “libhttps” | FortiGuard Labs

  www.fortinet.com
• 
  Python Folium: Create Web Maps From Your Data – Real Python

  realpython.com
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• 
  Why I Like Nox

  hynek.me
• 
  How Nvidia’s CUDA Monopoly In Machine Learning Is Breaking - OpenAI Triton And PyTorch 2.0

  www.semianalysis.com
• 
  Creating Virtual Environments - Python

  dev.to

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Trending packages and projects

• ManimML

  » Machine Learning    » neural-network

  ManimML is a project focused on providing animations and visualizations of common machine learning concepts with the Manim Community Library.

  
• GLM-130B

  GLM-130B: An Open Bilingual Pre-Trained Model

  
• public-apis

  » Resources    » open-source

  A collaborative list of public APIs for developers

  
• octosuite

  » Framework    » Frameworks

  Advanced Github OSINT Framework

  
• fastdup

  » Deep Learning    » Machine Learning

  FastDup is a tool for gaining insights from a large image collection. It can find anomalies, duplicate and near duplicate images, clusters of similaritity, learn the normal behavior and temporal interactions between images. It can be used for smart subsampling of a higher quality dataset, outlier removal, novelty detection of new information to be sent for tagging. FastDup scales to millions of images running on CPU only.