Whether you're a seasoned coder, or just starting out, GitHub Copilot's new feature will have everyone in a buzz.
If you have access to GitHub Copilot, you can download an additional extension, GitHub Copilot Labs. This gives you access to some cool new features. One of these features explains the code you have in plain language. Let's show you how to do that.
Step 1. Install Copilot Labs
Make sure you have GitHub Copilot installed*. If you have access to Copilot, you'll also be able download and install GitHub Copilot Labs.
Step 2. Choose code to explain
Open your VS Code editor and open a file with code you want explained.
Also, make sure you have Copilot turned on. You can find the Copilot icon in the bottom tray on the left hand side. Click it, and sure you select "Enable".
I always click "Enable Globally" because then Copilot works for everything and not just the file I have open.
Step 3. GitHub Copilot Labs sidebar
The GitHub Copilot Labs sidebar has everything you need to explain and translate code. You'll find the toolbar on the left side of the screen. If you can't see it, click the ellipses and you'll find a list of any additional extensions you have installed.
The GitHub Copilot Labs icon will only appear if you have installed GitHub Copilot Labs. Click the icon and it will toggle open a new pane. If you still have your code highlighted, your screen should look something like:
Step 4. Highlight Code
Now that you have the Copilot Labs sidebar open, highlight the chunk of code you'd like to better understand.
Step 5. Explain Code
The GitHub Copilot Labs pane will show a section called "Explain". Under this section, your highlighted code will appear, along with a box saying "Explain code".
Here, you can choose how you want the code explained. You can choose:
- "Explain code": step by step what the code is checking for and what it is outputting.
- "Code does following": brief summary of what the code is does.
- "Code does following (English)": detailed explain (in plain English) of what the code does.
- "Show example code": provides an input example and shows how the code calls a function and works.
Select one, and click "Ask Copilot". Your result will be immediately displayed:
Since this is a learning tool, you might be shown a slightly different result each time you "Ask Copilot". Experiment with various languages and compare the different results. This is a great way to learn and understand your code better.
Step 6. Feedback
GitHub Copilot and GitHub Copilot Labs are very new features. They are both in technical preview stage. After your code has been explained you'll be able to provide feedback on how well Copilot did.
You can read more about how GitHub Copilot works and the training set that powers this technology by heading to the Copilot website, and clicking "Learn more" in the top right. Also check out our tutorial on how Copilot can translate code into other languages.
*GitHub Copilot is in technical preview, and thus not all users will be able to access this feature. If you'd like to sign up to the technical preview, please join the waitlist.
Top comments (5)
I'm a bit sceptical. Looking at the example, all this seems to do is explain the code to someone who doesn't understand the semantics of a language. But I don't see how this would be of any value to someone who knows what they're doing.
Are there other examples where this feature adds a bit more value than re-phrasing what the code already says?
Sometimes, the vars are named so poorly, it's a nightmare to understand things. Copilot comes handy in there. Also helps with third-party tech, like while working with Deepgram's APIs, etc.
GitHub Copilot is similar in functionality to Google's search suggestions, but for code. Google learns about you as a user and provides more relevant results based on your previous searches and your other online habits. Copilot works in a similar way, but instead of providing search results -- it provides code suggestions. Just like Google needing relevant search terms to provide useful results, we can safely assume GitHub's Copilot and it's future iterations will also require valuable starting data to provide useful recommendations.
In Copilots' technical preview, it was able to guess the content correctly in about 43% of the demonstrated cases. To use this tool effectively you have to deeply understand every line of code. Using it requires you to have been able to write whatever snippet was autocompleted yourself. Even if this percentage approaches 100%, the developer will still need to input the project requirements (aka code) in a schema that Copilot will be able to understand.
If you would like to learn a bit more about GitHub Copilot, I'd suggest checking out this article written by my colleague, Rafael: scalablepath.com/full-stack/ai-pai...
This is quite interesting. I think this is good for beginner to learn if they really don't understand the code. For seasoned programmer, I don't think it will be much help I guess.
"join the waitlist" leads to 404 error