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

Microsoft Developer
9 Mar 202304:35

TLDRThe video script demonstrates how to use GitHub Codespaces for Python API development and leverages the AI-powered code generation tool, Copilot, for prompt-based code generation. The presenter ensures Codespaces is active and then focuses on integrating interactive JavaScript into an HTML project. They show how to use a comment as a prompt in Visual Studio Code to generate a form that submits data to an API endpoint. While the generated code is mostly correct, the presenter makes a necessary adjustment to use 'length' instead of raw input for the application to function properly. The demonstration highlights the efficiency of using Copilot for generating code, even for developers who are not specialists in JavaScript.

Takeaways

  • 🖥️ Ensure GitHub Codespaces is enabled and running for your account to use Copilot effectively.
  • 🔍 Use prompt-based code generation in Python HTTP API by providing context to Copilot through comments.
  • 📝 Accept Copilot's suggestions by hitting the 'tab' key to integrate them into your code.
  • 🔗 Understand that Copilot can generate code snippets for both HTML and JavaScript within a project.
  • ✅ Test the generated code by accepting it and making minor adjustments as needed.
  • 🛠️ Recognize that while Copilot can provide a solid foundation, manual adjustments might be necessary for technical accuracy.
  • 📈 Use Copilot to speed up the development process by generating most of the needed code.
  • 🔄 Accept the generated HTML form and JavaScript code snippets by hitting 'tab' and 'return'.
  • 📱 Interactive elements like buttons and forms can be created with JavaScript, as demonstrated in the script.
  • 🔑 For API endpoints, provide the endpoint path in the comment to guide Copilot's suggestions.
  • 🧩 Copilot's suggestions can be a starting point, but developers should verify and refine the code for their specific needs.

Q & A

  • What is the main topic of the transcript?

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

  • Why is it important to ensure that GitHub Codespaces is working?

    -It is important to ensure that GitHub Codespaces is working because it is the environment where the user is working and it needs to be enabled and running for the account to function properly.

  • What is the purpose of using a comment as a prompt in VS Code?

    -Using a comment as a prompt in VS Code allows GitHub Copilot to understand the context and generate code snippets that are relevant to the comment, making the coding process more efficient.

  • How does the user plan to make the HTML interactive?

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

  • What does the user do after pasting the HTML comment?

    -After pasting the HTML comment, the user hits return to generate suggestions from Copilot, then accepts the suggestions by hitting tab and return, which places the cursor at the end for further input.

  • What does the user mean when they say 'Copilot understands what I want'?

    -The user means that by providing context through comments, Copilot can generate code that aligns with the user's intentions and the specific requirements of the project.

  • Why does the user accept the generated output?

    -The user accepts the generated output because it closely matches what they need, although it may not be 100% correct, it provides a solid foundation that requires only minor adjustments.

  • What is the user's role in the process of code generation with Copilot?

    -The user's role is to provide context through comments, accept or reject the suggestions made by Copilot, and make any necessary adjustments to the generated code to fit the project's requirements.

  • What is the user's background in JavaScript development?

    -The user is not a full-time JavaScript developer but has some knowledge of JavaScript, which allows them to understand and make small changes to the generated code.

  • How does the user know what changes to make to the generated code?

    -The user knows what changes to make based on their understanding of the project requirements and their knowledge of JavaScript, such as knowing that 'length' was needed instead of 'input' in one part of the code.

  • What is the benefit of using GitHub Copilot for code generation?

    -The benefit of using GitHub Copilot for code generation is that it speeds up the development process by providing suggestions that are close to what the user needs, allowing the user to focus on refining and finalizing the code.

Outlines

00:00

💻 Setting Up GitHub Code Spaces for Python API Development

The speaker introduces a GitHub code spaces template for a Python API project. They emphasize the importance of ensuring code spaces is active and enabled for the user's account. The focus then shifts to demonstrating how to generate code interactively using an HTML comment as a prompt in Visual Studio Code. The speaker navigates through the project files, highlighting a simple HTML structure and expressing the intention to make it interactive. They proceed to paste an HTML comment to guide the AI copilot in generating JavaScript code for an interactive form that will send a synchronous request to the 'generate' API endpoint. The speaker accepts the AI's suggestions step by step, making minor adjustments to fit their needs, and acknowledges that while the generated code is not perfect, it significantly speeds up the development process.

Mindmap

Keywords

💡GitHub Code Spaces

GitHub Code Spaces 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 primary workspace for creating a Python API. It is essential as it provides the environment where the coding and the use of Copilot take place.

💡Python API

A Python API (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 presenter is using a Python API to create a service that can be accessed over the internet. The API is the central focus of the coding demonstration.

💡Copilot

Copilot is an AI-powered code generation tool developed by GitHub and OpenAI that assists developers by providing code suggestions and autocompletion as they write code. In the video, Copilot is used to generate code snippets based on prompts, which significantly speeds up the development process.

💡HTML

HTML, or HyperText Markup Language, is the standard markup language used to create web pages. In the video, the presenter mentions a small portion of HTML code within the Python API project, indicating that the API also involves some front-end web development.

💡JavaScript

JavaScript is a high-level, interpreted scripting language that is commonly used to create interactive elements on web pages. The video discusses adding JavaScript to enhance the interactivity of the HTML page associated with the Python API, showing how to use it for form handling and making synchronous requests.

💡API Endpoint

An API endpoint refers to a specific location in a network where an API can be accessed. In the video, the presenter refers to 'slash generate' as the API endpoint for the application, which is the URL that the front-end JavaScript code will use to send requests to the back-end Python API.

💡Interactive Form

An interactive form is a user interface element that allows users to input data, which can then be processed by a program. In the context of the video, the presenter wants to replace static buttons with an interactive form that can accept user input and submit it to the API endpoint.

💡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 making a synchronous request to the generate API endpoint, which means the JavaScript code will wait for a response from the server before proceeding.

💡Code Generation

Code generation is the process of automatically producing code from a set of specifications or prompts. The video demonstrates code generation using Copilot, where the tool suggests code based on the context provided by the developer, such as a comment in the code.

💡Code Completion

Code completion is a feature that automatically completes code entries for developers, saving time and reducing errors. Copilot offers this feature, as shown in the video, by providing suggestions as the developer types, which the developer can accept to complete the code.

💡Contextual Understanding

Contextual understanding in the realm of AI tools like Copilot refers to the ability of the tool to comprehend the context in which it is generating code. In the video, the presenter provides context to Copilot by explaining what the code is intended to do, enabling Copilot to make more accurate suggestions.

Highlights

Using GitHub code spaces for Python API development

Ensuring code spaces is enabled and running for your account

Demonstration of prompt-based generation of code

Incorporating a little bit of HTML into a Python HTTP API

Collapsing code sections for better visibility

Working with an index.html file

Adding JavaScript to a project for interactivity

Using an HTML comment as a prompt for Copilot

Generating an interactive form with JavaScript

Creating a synchronous request to an API endpoint

Contextualizing the API endpoint for Copilot understanding

Accepting generated code suggestions with the Tab key

Continuing to receive suggestions after accepting code

Closing HTML tags with Copilot's assistance

Addressing technical details manually when needed

Making small changes to generator code for customization

Understanding the necessity of 'length' in input data

Using comments as prompts to generate code in VS Code

Efficiency gains from using Copilot for code generation