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Book Overview & Buying
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Table Of Contents
Supercharged Coding with GenAI
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Writing code is rarely an isolated task. We will typically have to incorporate our Python snippets into a larger code base that includes project files, often structured under a /src folder, along with dependencies listed in a requirements.txt file and other non-project files, such as a Dockerfile that defines container specifications.
In this chapter, we will work with a code base that computes the Manhattan distance between two matrices represented as pandas DataFrames. With the help of ChatGPT, GitHub Copilot, and OpenAI API, we will explore how various GenAI tools can support us in efficiently understanding both non-project files and the main business logic. We will also examine how generating calls with sample parameters can improve our understanding of more complex code.
Here are the key topics covered in this chapter: