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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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@githubtrending · Post #15171 · 09/27/2025, 11:30 AM

#ruby#backup#network#nms#rancid Oxidized is a free tool that automatically backs up network device configurations from over 130 device types, replacing older tools like RANCID. It runs efficiently by adjusting how many tasks it uses based on your setup and offers a web API to manage backups and see changes. It can track who made changes using syslog and integrates with Git to show detailed version history. You can install it on many systems, configure it easily with YAML files, and use various sources and outputs for flexibility. This helps you keep your network device settings safe, organized, and easy to review or restore when needed. https://github.com/ytti/oxidized