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Source channel @githubtrending · Post #14807 · Jun 8
#other#agents#agi#ai#anthropic#artifacts#awesome#awesome_list#bots#chatbot#chatgpt#claude#exploit#gemini#google#gpt#hack#jailbreak#openai#prompts#spam AI tools like autonomous software engineers can help developers by completing tasks independently or working alongside them. This can increase productivity by automating repetitive tasks, allowing developers to focus on more complex and creative work. AI also helps reduce errors and improves code quality, making the development process faster and more efficient. Overall, using AI in software development can lead to better outcomes and more innovative solutions. https://github.com/friuns2/BlackFriday-GPTs-Prompts
Search: #sequential
@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.
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@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.