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Source channel @githubtrending · Post #15123 · Sep 6

#rust#artificial_intelligence#big_data#data_engineering#distributed_computing#machine_learning#multimodal#python#rust Daft is a powerful, easy-to-use data engine that lets you process large-scale data using Python or SQL with high speed and efficiency. It supports complex data types like images and tensors, works well interactively for quick data exploration, and can scale to huge cloud clusters using Ray. Daft integrates smoothly with cloud storage and data catalogs, making it ideal for data engineering, analytics, and machine learning workflows. By using Daft, you can handle big, multimodal datasets faster and more flexibly, improving your ability to analyze and prepare data for AI models without complex setup or slowdowns. https://github.com/Eventual-Inc/Daft

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djangoproject

@djangoproject · Post #551 · 01/23/2018, 04:28 PM

http://lxml.de/ #lxml is the most feature-rich and easy-to-use library for processing #XML and #HTML in the Python language. The lxml XML toolkit is a Pythonic binding for the #C libraries #libxml2 and #libxslt. It is unique in that it combines the speed and XML feature completeness of these libraries with the simplicity of a native Python #API, mostly compatible but superior to the well-known ElementTree API. The latest release works with all #CPython versions from 2.6 to 3.6. See the introduction for more information about background and goals of the lxml project. Some common questions are answered in the FAQ.