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Source channel @githubtrending · Post #15482 · Feb 10

#python#ai#claude#gemini#llama#llm#openai You can access powerful AI language models for free or with trial credits through multiple legitimate platforms. Services like OpenRouter, Google AI Studio, Groq, and Mistral offer free tiers with varying request limits, while others like Fireworks, Baseten, and Inference.net provide trial credits ranging from $1 to $30. These platforms support diverse models including Llama, Gemma, Qwen, and DeepSeek, enabling you to build and test AI applications without upfront costs. The benefit is clear: you can prototype, develop, and deploy AI-powered features while managing your budget effectively, with options to scale up as your needs grow. https://github.com/cheahjs/free-llm-api-resources

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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.