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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 #408 · 08/10/2017, 10:42 AM

https://docs.python.org/3/library/xmlrpc.html #XML-#RPC is a #Remote_Procedure_Call method that uses XML passed via #HTTP as a transport. With it, a #client can call methods with parameters on a remote server (the #server is named by a URI) and get back structured data. #xmlrpc is a package that collects server and client modules implementing XML-RPC. The modules are: xmlrpc.client xmlrpc.server