How to generate code with prompts using Copilot [2 of 6]

Microsoft Developer
9 Mar 202304:35

TLDRThe video tutorial demonstrates how to use GitHub Copilot for generating code based on prompts within a Python API project. The presenter ensures GitHub Codespaces is active and guides viewers on integrating JavaScript into an HTML form for interactive functionality. Copilot assists by suggesting code snippets, which the user accepts and refines as needed. The presenter emphasizes that while Copilot's suggestions are helpful, they may require minor adjustments to fit the specific requirements of the project. The video showcases the efficiency of using prompts in VS Code to accelerate the coding process, even for those with limited JavaScript experience.

Takeaways

  • 💻 Use GitHub Codespaces to work on a Python API project.
  • 🔍 Ensure that Codespaces is enabled and running for your account.
  • 📝 Start with a template and modify it according to your needs.
  • 🌐 Include HTML and JavaScript for interactive web elements.
  • 🔑 Understand the API endpoint you are working with (e.g., /generate).
  • ✅ Use comments in your code to guide the AI in generating code snippets.
  • 🔑 Accept suggestions by hitting 'tab' to integrate them into your code.
  • 🔄 Copilot may not generate perfect code, but it can get you most of the way there.
  • 🛠️ Make necessary adjustments to the generated code to fit your application's needs.
  • 📈 Copilot can significantly speed up the coding process.
  • 📚 Even with limited JavaScript knowledge, you can effectively use Copilot to generate code.

Q & A

  • What is the main topic of the transcript?

    -The main topic of the transcript is about generating code with prompts using GitHub Copilot, specifically within a Python API context.

  • What is the first thing the speaker suggests to check before starting to work with code?

    -The first thing the speaker suggests checking is that GitHub Codespaces is enabled and running for your account.

  • What does the speaker plan to do with the HTML in the project?

    -The speaker plans to make interactive changes to the HTML by adding JavaScript to create a form that accepts user input and sends it as a synchronous request to a generate API endpoint.

  • How does the speaker use GitHub Copilot to generate code?

    -The speaker uses GitHub Copilot by typing a comment in the code that describes what they want to achieve, and then Copilot generates code based on that prompt.

  • What does the speaker do after Copilot generates the code?

    -The speaker hits the 'tab' key to accept the generated code and continues to receive suggestions from Copilot, making necessary adjustments as needed.

  • Why does the speaker mention that they are not a full-time JavaScript developer?

    -The speaker mentions this to highlight that even with limited JavaScript knowledge, they are able to generate most of the needed code with the help of GitHub Copilot.

  • What does the speaker identify as a necessary change in the generated code?

    -The speaker identifies that instead of using the raw input, they need to use 'length' and 'length input' for the application to work correctly.

  • How does the speaker describe the efficiency of using GitHub Copilot for code generation?

    -The speaker describes the efficiency of using GitHub Copilot as a way to get almost all of the way to the final code, which allows them to work much faster.

  • What is the role of the 'generate' API endpoint in the context of the speaker's project?

    -The 'generate' API endpoint is used as the destination for the form data to be sent as a synchronous request in the speaker's project.

  • How does the speaker interact with the generated code?

    -The speaker interacts with the generated code by accepting it with the 'tab' key, making small adjustments, and continuing to receive suggestions from Copilot.

  • What is the significance of using comments as prompts in VS Code with GitHub Copilot?

    -Using comments as prompts in VS Code with GitHub Copilot allows the AI to understand the context and generate code snippets that are more relevant to the developer's needs.

  • What does the speaker imply about the accuracy of the code generated by GitHub Copilot?

    -The speaker implies that while the code generated by GitHub Copilot might not be 100% accurate, it is usually close enough that making small changes can lead to a complete solution.

Outlines

00:00

💻 Setting Up GitHub Code Spaces for Python API Development

The speaker begins by introducing a GitHub code spaces template for a Python API project. They emphasize the importance of ensuring that code spaces are enabled and operational for the user's account. The speaker then demonstrates how to utilize the code spaces environment by navigating to the static folder and focusing on the index.html file. They express their intention to enhance the project with interactive elements, specifically by modifying the HTML to include a form that will make a synchronous request to a generate API endpoint. The speaker also discusses the use of JavaScript to achieve this interactivity, despite not being a full-time JavaScript developer.

Mindmap

Keywords

💡GitHub Codespaces

GitHub Codespaces is a cloud-based development environment provided by GitHub that allows developers to write, build, and test code directly from their browser. In the video, it is used as the platform where the Python API is being developed, highlighting its role in facilitating the coding process.

💡Python API

A Python API, or Application Programming Interface, is a set of rules and protocols that allows software applications to communicate and interact with each other. In the context of the video, the Python API is the main project being worked on, and it is used to demonstrate how to generate code with prompts.

💡HTML

HTML, or Hypertext Markup Language, is the standard markup language used to create web pages. The video mentions HTML in the context of a simple web page that is part of the Python API project, where the presenter wants to add interactivity using JavaScript.

💡JavaScript

JavaScript is a high-level, interpreted scripting language that is commonly used to create interactive elements on web pages. In the video, the presenter discusses adding JavaScript to the HTML to create an interactive form that communicates with the Python API.

💡Copilot

Copilot is a term used in the video to refer to an AI-powered code generation tool that assists developers by providing code suggestions based on prompts or comments in the code. It is central to the video's theme of generating code efficiently.

💡Prompt-based generation

Prompt-based generation is a method of using AI tools like Copilot, where the developer provides a prompt or comment in the code that the AI uses to generate relevant code snippets. This technique is demonstrated in the video as a way to speed up the coding process.

💡API endpoint

An API endpoint is a specific location in an API that can be called upon to perform an action or retrieve data. In the video, the presenter refers to the 'slash generate' as the API endpoint for the Python API, which is the target for the JavaScript form submission.

💡Synchronous request

A synchronous request is a type of communication between a client and a server where the client waits for a response before continuing to execute further instructions. The video script mentions a synchronous request being used to communicate with the API endpoint.

💡Code generation

Code generation is the process of automatically creating source code in a programming language. In the video, the presenter uses code generation to quickly produce code snippets that would otherwise take more time to write manually.

💡Stringify

In programming, 'stringify' refers to the process of converting data into a string format. In the context of the video, the presenter corrects the code generated by Copilot by changing the raw input to a 'length' property, indicating the need for data to be in a specific format for the API to work correctly.

💡VS Code

VS Code, or Visual Studio Code, is a popular source code editor developed by Microsoft that includes support for debugging, Git control, syntax highlighting, intelligent code completion, and code refactoring. It is mentioned in the video as the environment where the presenter is using Copilot to generate code.

Highlights

Using GitHub code spaces for Python API development

Ensuring code spaces is enabled and running for the account

Demonstrating prompt-based code generation

Incorporating HTML into a Python HTTP API

Navigating to the 'static' directory and working with 'index.html'

Collapsing sections for better visibility

Adding an interactive form using JavaScript

Using HTML comments to guide Copilot suggestions

Generating a form that makes a synchronous request to an API endpoint

Accepting Copilot's generated code with a tab

Continuing to receive suggestions after accepting the generated code

Need to close the HTML tag after accepting suggestions

Technical details may require manual adjustments to the generated code

Example of changing 'stringify' line to use 'length' instead of raw input

Copilot making real-time suggestions as the user types

Efficiency of using a comment as a prompt in VS Code

Generated code might not be 100% correct but is a solid starting point

Making small changes to the generated code to fit specific needs

Accelerating development process with Copilot's assistance

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