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feat: 更新术语译法 提示词工程 -> 提示工程
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README.md

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5. [第五章 理解 Python 代码(下)](https://github.com/cssmagic/Learn-AI-Assisted-Python-Programming/issues/11)
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* (本章正文略)
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* [本章小结](https://github.com/cssmagic/Learn-AI-Assisted-Python-Programming/issues/18)
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6. [第六章 程序测试与提示词工程](https://github.com/cssmagic/Learn-AI-Assisted-Python-Programming/issues/12)
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6. [第六章 程序测试与提示工程](https://github.com/cssmagic/Learn-AI-Assisted-Python-Programming/issues/12)
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* (本章正文略)
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* [本章小结](https://github.com/cssmagic/Learn-AI-Assisted-Python-Programming/issues/19)
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7. [第七章 分解问题](https://github.com/cssmagic/Learn-AI-Assisted-Python-Programming/issues/13)
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* 编写提示词,精确引导 Copilot
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* 阅读 Python 代码并理解其功能
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* 测试你的程序,确保它们按照你的意图运作
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* 利用提示词工程或人工微调来修复代码
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* 利用提示工程或人工微调来修复代码
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* 创造性地运用 Python 来优化工作流程
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_Learn AI-Assisted Python Programming: With GitHub Copilot and ChatGPT_ is a hands-on beginner’s guide that is written by two esteemed computer science university professors. It teaches you everything you need to start programming Python in an AI-first world. You’ll hit the ground running, writing prompts that tell your AI-assistant exactly what you want your programs to do. Along the way, you’ll pick up the essentials of Python programming and practice the higher-level thinking you’ll need to create working apps for data analysis, automating tedious tasks, and even video games.

content/chapter-1/106.md

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不,并非如此。虽然一些程序员所依赖的技能(例如,编写正确的语法)的重要性将会减少,但其他技能仍然非常关键。例如,你不能简单地把一个庞大的任务扔给 Copilot,比如说,
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"Make a video game. Oh, and make it fun." Copilot will fail. Instead, we need to break down such a large problem into smaller tasks that Copilot can help us with. And how do we break a problem down like that? Not easily, it turns out. This is a key skill that humans need to hone in their conversations with tools like Copilot, and a skill that we will teach throughout the book.
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“创建一个视频游戏,并确保它富有乐趣。” Copilot 将难以胜任。相反,我们需要将这一庞大的任务分解成 Copilot 能帮忙的小任务。那么,我们怎样才能做到这一点呢?事实证明,这并非易事。这是人们在与 Copilot 这类工具交流时必须培养的关键技能,也是本书将要教授的技能。
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Other skills, believe it or not, may take on even more importance with Copilot than without. Testing code has always been a critical task in writing code that works. We know a lot about testing code written by humans, because we know where to look for typical problems. We know that humans often make programming errors at the boundaries of values. For example, if we wrote a program to multiply two numbers, it’s likely that we’d get it right with most values but maybe not for when one value is 0. What about code written by AI, where twenty lines of flawless code could hide one line so absurd that we likely wouldn't expect it there? We don’t have experience with that. We need to test even more carefully than before.
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信不信由你,有些技能在使用 Copilot 的时候可能比不用时更为重要。测试代码始终是编写可靠代码的关键任务。我们对于测试人类编写的代码有很多了解,因为我们知道应该在哪里寻找常见的问题。我们知道,人们在处理值的边界条件时经常会出错。例如,如果我们编写一个程序来乘两个数,大部分时候我们可能会做得很好,但对于其中一个值是 0 的情况可能就不行。那么,对于 AI 编写的代码,如果在二十行完美的代码中隐藏着一行我们完全不会预料到的荒唐代码呢?我们对此尚无经验。因此,我们需要比之前更加细致地进行测试。
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Finally, some required skills are entirely new. The main one here is called _prompt engineering_, which involves how to tell Copilot what to do. When we're asking Copilot to write some code, we're using a _prompt_ to make the request. It's true that we can use English to write that prompt and ask for what we want, but that alone isn't enough. We need to be very precise if we want Copilot to have any chance of doing the right thing. And even when we are precise, Copilot may still do the wrong thing. In that case, we need to first identify that Copilot has indeed made a mistake, and then tweak our description to hopefully nudge it in the right direction. In our experience, seemingly minor changes to the prompt can have outsized effects on what Copilot produces.
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最后,一些必须掌握的技能是全新的。其中最关键的一项称为 “提示词工程”,这涉及到如何准确告诉 Copilot 需要它做什么。当我们向 Copilot 请求编写代码时,我们通过一个 “提示词” 来提出这一请求。虽然我们可以用英语来编写这个提示词并表达我们的需求,但仅仅这样做是不足够的。如果我们希望 Copilot 有可能正确执行任务,我们就需要极为精确。即使我们已经足够精确,Copilot 还是可能会犯错。在这种情况下,我们首先需要确认 Copilot 确实出现了错误,然后调整我们的描述,希望能将其引导至正确的方向。根据我们的经验,即使是看似微不足道的提示词变动,也可能对 Copilot 生成的结果产生极大的影响。
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最后,一些必须掌握的技能是全新的。其中最关键的一项称为 “提示工程”,这涉及到如何准确告诉 Copilot 需要它做什么。当我们向 Copilot 请求编写代码时,我们通过一个 “提示词” 来提出这一请求。虽然我们可以用英语来编写这个提示词并表达我们的需求,但仅仅这样做是不足够的。如果我们希望 Copilot 有可能正确执行任务,我们就需要极为精确。即使我们已经足够精确,Copilot 还是可能会犯错。在这种情况下,我们首先需要确认 Copilot 确实出现了错误,然后调整我们的描述,希望能将其引导至正确的方向。根据我们的经验,即使是看似微不足道的提示词变动,也可能对 Copilot 生成的结果产生极大的影响。
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In this book, we will teach you all of these skills.
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content/chapter-1/108.md

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* Copilot 是一款 AI 助手,这是一个能够帮助你完成工作的人工智能代理。
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* Copilot 重新定义了人与计算机的交互方式及程序编写方法。
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* Copilot 转变了我们技能提升的焦点(减少对语法的关注,增加对提示词工程和测试的重视)。
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* Copilot 转变了我们技能提升的焦点(减少对语法的关注,增加对提示工程和测试的重视)。
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* Copilot 具有非确定性特点;它有时能生成正确的代码,有时却不能。我们需要时刻保持警惕。
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* 关于代码的版权、教育与职业培训以及 Copilot 结果中的偏见问题仍需要解决。代码版权、教育与职业培训问题,以及 Copilot 结果的偏见等问题,仍需寻找解决方案。

content/chapter-3/307.md

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title: "[译] [307] 本章小结"
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## Summary
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## 本章小结
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* 叶子函数不会调用其他任何函数来完成其任务。
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* 测试函数是否正确的一个方法是,用不同类型的输入去调用它。
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* 每个 Python 的值都有类型,比如数字、文本(字符串)、真/假值(布尔)、或值的集合(列表或字典)。
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* 提示词工程指的是调整我们对 Copilot 的提示词,以影响我们获得的代码。
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* 提示工程指的是调整我们对 Copilot 的提示词,以影响我们获得的代码。
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* 我们需要确保我们的代码使用的任何模块(例如 string)都被导入。

content/chapter-6/600.md

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title: "[译] [600] 第六章 程序测试与提示词工程"
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title: "[译] [600] 第六章 程序测试与提示工程"
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# 6 Testing and Prompt Engineering
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# 第六章 程序测试与提示词工程
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# 第六章 程序测试与提示工程
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### This chapter covers
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### 本章内容概要

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