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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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@JianjiaoPD · Post #10145 · 01/01/2026, 03:33 PM

✈️VvEnc | 拖个文件夹进去就批量转 MP4,还能保留原目录结构 🏷 检索标签:#BatchVideoEncoder#VvEnc#视频转码#FFmpeg#视频#MP4 ⭐️ 详情介绍:真正在剪辑前后折磨人的不是转一条视频,而是“十几二十条一起转还得盯着别翻车”,这个基于 PyQt5 + FFmpeg 的批量编码工具就专门治这种活——文件/文件夹直接拖放进来排队跑,多格式输入统一输出 MP4,还会把原来的目录结构给你原样保留,你不用再手动建文件夹对齐素材;队列状态、单文件进度和整体进度都能看到,失败/挂起这种也能在任务里管理 注意:它本质还是 FFmpeg 前端,编码质量和体积最终看你选的参数,想“又小又清晰”就别偷懒,先用一小批样本试跑一轮更稳 📖Github · 🪟Releases下载 😌频道 |🙂群聊 |😋中文包 |☺️搜索