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GitHub Copilot, GitHub’s AI pair programmer, has been making waves since its preview launch in 2021. Integrating with code editors like Visual Studio Code (VSCode), Copilot offers suggestions for entire lines, functions, and blocks of code as developers type, with with the aim of increasing their productivity.
But how exactly does Copilot work within VSCode, and what can developers expect from its code additions and other features? This article takes an in-depth look at the capabilities, installation process, integration, and usage of GitHub Copilot within VSCode, specifically to help you maximize what this AI coder has to offer.
See more: Alaya AI: Features, Price, Uses and More
How GitHub Copilot aims to incentivize developers
GitHub designed Copilot to be more than just an autocomplete tool. The underlying AI model is trained on billions of lines of public code to generate suggestions in your own coding style. Here are some of the notable features:
AI pair programmer
Copilot is like having an AI developer pair program with you. As you write code, it suggests continuations of what you type, allowing you to effectively collaborate on the code as you go.
Code Completions++
It goes beyond basic code completion, with whole and multi-line suggestions based on deep knowledge, helping you write code faster.
Chat support
You can ask Copilot clarifying questions or explanations via the chat view. It can explain how a proposed block of code works or provide guidance if you’re stuck.
Additional help
In addition to writing code, Copilot can help with tasks such as generating commit messages, finding alternative ways to accomplish something, and more.
Broad language support
Copilot offers suggestions for many popular programming languages, such as JavaScript, TypeScript, Python, Ruby, and more, based on what it learns from public code.
Install GitHub Copilot in VSCode
GitHub Copilot is built directly into Visual Studio Code, making the installation process quick and seamless:
Step 1: Access the Copilot extension
In VSCode Marketplace, search for ‘GitHub Copilot’ and click on the entry under GitHub. You can also click on this direct link to the extension.
Step 2: Install the extension
On the Copilot extension page, click the “Install” button. A pop-up will ask to open VSCode – click ‘Open Visual Studio Code’.
Step 3: Authorize the installation
On the Extensions tab on the left in VSCode, click “Install” under “GitHub Copilot” to continue. If you are not already signed into GitHub, you will now be asked to sign in with your GitHub account.
And that’s it! The GitHub Copilot extension is installed and ready to use within VSCode.
Also read: Free trial of GitHub Copilot
Integrate GitHub Copilot into your VSCode workflow
Now that Copilot is installed, let’s see how you can integrate it into your regular VSCode workflow and leverage its AI superpowers effectively:
1. Enable Copilot in VSCode settings
By default, Copilot starts suggesting completions as soon as it is installed. You can adjust its behavior via Settings:
- View > Command Palette > Preferences: Open Settings
- Under Extensions > Copilot, adjust settings such as Editor: Suggestion enabled
2. Pay attention to highlighting suggestion syntax
Copilot’s suggestions have special syntax highlighting to distinguish:
- Blue – Suggestions for a lot of confidence
- Gray – Suggestions for less trust
The color indicates how likely Copilot thinks a suggestion fits the context.
3. Accept suggestions with Tab or Click
To accept a suggestion, simply press Tab or click on it. Pay attention to blue versus gray highlighting to determine optimal suggestions.
4. Refine searches in the chat view
Open the command palette and select GitHub Copilot: Open Chat View to access the Sidebar Chat. Here you can chat with Copilot, ask questions or ask for clarification.
Start typing // to activate inline chat anywhere in a file as well.
5. Generate tests, solutions and alternatives via chat
In addition to answering questions in Chat, you can ask Copilot to generate tests for your code or suggest fixes for bugs. For example:
// Can you generate unit tests for this function
// Could you provide an alternate implementationThis gives you a convenient way to access Copilot’s capabilities outside of writing code.
Unleash the full potential of GitHub Copilot
Now that Copilot is installed and integrated into your workflow, let’s take a look at some power user tips and techniques you can use to really unleash its AI coding capabilities:
Fast co-pilot with clear comments
Copilot works best if you effectively “prime” it with comments about your intentions before writing code. This provides useful context for more precise suggestions.
Use pragmatic coding patterns
Follow the conventions of patterns like test-driven development to automatically see suggestions for tests, bugs, fixes, etc. from Copilot.
Chat regularly for explanations
Have an ongoing conversation with Copilot as you code, explain context, and ask for clarifications and alternatives. More chat => better preparation.
Reuse the suggestions as future templates
Copilot can suggest an entire function that you can reuse as a template in the future, and train it on your own code over time.
Lean on its strengths and weaknesses
Use Copilot for rote coding tasks, but trust your own judgment for architectural decisions and creative problem solving.
Embrace continuous learning
Treat unexpected or unhelpful suggestions as learning opportunities about Copilot’s training and limitations.
With the right integration and prompting techniques, GitHub Copilot can feel like an AI programmer is permanently linking the coding alongside you within VSCode. Over time, learning the public code and your own software development habits continues.
While there is still room for improvement, GitHub Copilot represents a real step forward toward AI that meaningfully enhances human creativity rather than replacing it. For developers who use it wisely, Copilot promises to elevate coding from a mundane task to an enjoyable act of creation and collaboration with artificial intelligence.
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