How to Use GitHub Copilot: A Comprehensive Guide

An AI pair programmer called GitHub Copilot provides autocomplete-style suggestions as you type. You can ask GitHub Copilot for advice by either writing the code you wish to use or leaving a comment in natural language outlining your desired behavior for the code. GitHub Copilot examines the context of the file you are editing and any connected files, then provides recommendations directly from your text editor. OpenAI Codex, a brand-new AI system made by OpenAI, powers GitHub Copilot.

All languages used in publicly accessible repositories were used in GitHub Copilot's training. Depending on the quantity and variety of training data available for each language, the quality of the suggestions you get may vary by language. For instance, one of GitHub Copilot's top supported languages is JavaScript, which is widely used in public repositories. Less frequently used languages in public repositories might generate fewer or weaker suggestions.

On June 29, 2021, GitHub, aka Microsoft, released GitHub Copilot. OpenAI GPT-3, a languageprediction model created to produce text that resembles that of a human, powers the tool. The most sophisticated autoregressive model ever built by humans is GPT 3. The AI itself was trained using the GitHub code available to the public. There is a lot of money invested in this answer. Two billion dollars have been invested in this initiative by Microsoft and OpenAI, who worked on the development of Copilot. The result of that investment is what we see today.

What is GitHub Copilot?

GitHub Copilot makes use of Codex, an OpenAI-attributed generative pre-trained language model. This AI pair programmer will help you create code quickly and effectively. Your staff can use the time and effort they save to accomplish other tasks. Using context from comments and code, GitHub Copilot rapidly offers specific lines of code and entire functions. Additionally, natural language content and source code from various publicly accessible sources, such as GitHub's public repositories, were used to train the product.

It's important to note that while GitHub Copilot can only generate code based on context, it cannot write faultless code. Additionally, the suggested code is not tested, so do it yourself. However, it's a wonderful place to start if you want to simplify the process.

The ideal approach to view GitHub Copilot is as a code-writing apprentice. Will it always get it right? No. Will it save time and effort by providing a base for future growth? Yes.

How much does GitHub Copilot cost?

If you're considering utilizing GitHub Copilot, you probably want to know how much it will cost and whether it will fit your company's budget. The good thing is that you have a few pricing options

First, GitHub Copilot is available for free for 60 days. You can choose to continue using the product once your trial is up. If so, the cost is $100 annually or $10 per month for each user.

You may be able to use the product for free under certain circumstances. Verified students, professors, and those who look after some well-known open-source products can use GitHub CoPilot for free.

GitHub Copilot for businesses is anticipated to launch later this year but is not yet accessible. You may sign up for the waitlist if you want to be informed when it launches.

How do you use GitHub Copilot?

You know that GitHub Copilot writes code using artificial intelligence (AI). Let's explore this product's uses in more detail so that you can decide where and how to use it.

The software is offered as an add-on for the JetBrains suite's Visual Studio Code, Visual Studio, Neovim, and Integrated Development Environments. You must have — you guessed it — Visual Code Studio installed if you want to use GitHub Copilot in that program.

It is appropriate for programming and human languages because it was educated on natural language and open-source code. The GitHub Copilot extension transmits your code and comments to the Copilot service, which generates suggestions based on context. The product may additionally gather URL repositories or file locations to assess context. The context is then matched with your comments and code. OpenAI's Codex uses this to provide both single lines and entire functions.

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Tips & Tricks for GitHub Copilot

Do you intend to purchase GitHub Copilot? Using these pointers and techniques, you may get the most out of the product. Here are some of our top recommendations to get you going.

  • Be mindful of which language and framework you're using.
    Although the program provides recommendations for several languages and frameworks, it does have its preferences. Because it performs best for them, we advise using GitHub Copilot with JavaScript, TypeScript, Python, Ruby, Go, C#, and C++.
  • Remember, this product uses the context you provide.
    Keep in mind that GitHub Copilot makes suggestions using artificial intelligence. Therefore, the more context you provide, such ideas will be more accurate and useful. Use descriptive names for your function parameters, provide strong docstrings and comments, and break up your code into smaller, easier-to-read functions for the best results.
  • Test and vet your code.
    We cannot stress enough how important it is to always test your code. There is never a bad time to test your code, whether artificial intelligence is developing it or you are. If you do this, you'll be able to immediately spot any code that isn't working properly or doesn't make sense.


Copilot GitHub: Final thoughts

From my vantage point, it appears that developers will write less and less code over the next few years—possibly a decade. One of the numerous tools that have improved and will continue to improve our work is Copilot. Excessively Relying on such technologies could result in extra work or major issues. It is by no means a replacement for programmers.

However, when it comes down to it, computers are simply superior to people in writing boilerplate code, algorithms, and performing computations.

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