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Source channel @githubtrending · Post #14842 · Jun 19

#typescript Cloudflare AI offers tools and packages to help you build and run AI applications easily on Cloudflare’s global network, using their Workers AI and AI Gateway services. You can develop, test, and deploy AI-powered apps with low latency and high performance, thanks to Cloudflare’s edge computing and GPU infrastructure. The platform supports popular AI models and integrates with other Cloudflare services like vector databases and data lakes, reducing complexity and cost. It also ensures privacy by not training models on your data. This setup helps you quickly create scalable, efficient AI apps that deliver great user experiences and comply with data rules. https://github.com/cloudflare/ai

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djangoproject

@djangoproject · Post #98 · 07/11/2016, 12:22 PM

https://docs.python.org/3/library/asyncio.html #asyncio #Asynchronous programming is more complex than classical “#sequential” programming: see the Develop with asyncio page which lists common traps and explains how to avoid them. Enable the debug mode during development to detect common issues.

djangoproject

@djangoproject · Post #153 · 09/03/2016, 08:20 PM

http://wla.berkeley.edu/~cs61a/fa11/lectures/streams.html In this chapter, we continue our discussion of real-world applications by developing new tools to process #sequential#data. In Chapter 2, we introduced a sequence interface, implemented in Python by built-in data types such as #tuple and #list. #Sequences supported two operations: querying their length and accessing an element by index. In Chapter 3, we developed a user-defined implementations of the sequence interface, the Rlist class for representing recursive lists. These sequence types proved effective for representing and accessing a wide variety of sequential #datasets.