As a beginner software developer, you may find the process of writing long and monotonous code both boring and time-consuming. You might wonder if there are any AI tools available that can alleviate these coding challenges and make your work easier. Well, the answer is yes, and that’s where GitHub Copilot comes into the picture. GitHub Copilot is an AI-powered tool specifically designed to solve your coding problems.

In this article, we will explore the remarkable capabilities of GitHub Copilot and how it can enhance your coding experience. Say goodbye to lengthy code writing and embrace the power of AI assistance with GitHub Copilot.

What is GitHub Copilot?

Before we start, you should know that GitHub Copilot is powered by OpenAI’s Codex, a Machine Learning model trained on a vast amount of publicly available code.

GitHub Copilot is like having an AI partner to help you write code. It provides helpful suggestions that help developers to code faster, improve the quality of code and learn new skills while they are writing code, similar to how autocomplete in VS Code works.

With GitHub Copilot, you can get suggestions in two ways.

1. You can start typing the code you need, and it will suggest how to complete it.
2. You can write a comment in plain English to describe what you want the code to do, and it will generate code based on your description.

In both cases, GitHub Copilot acts as a smart assistant, giving you ideas and saving you time by providing code suggestions while you’re programming.

Stay with us until the end of this article to gather all the relevant information about GitHub Copilot. By the time you finish reading, you’ll have a comprehensive understanding of this AI-powered pair programmer.

How does it work?

As discussed, GitHub is powered by Codex so it works by using the Codex model, which is a large language model trained on billions of lines of code from public GitHub repositories. 

Codex can analyze the context of the code that the user is writing and generates suggestions for code completion, function definition, or algorithm implementation. It can also use natural language comments or prompts to understand the user’s intention and generate relevant code. 

However, you might be curious about the inner workings of GitHub Copilot and how it provides code suggestions. To gain a better understanding, let’s explore the following diagram that illustrates its functioning.

GitHub Copilot is an extension for Visual Studio Code that assists developers in writing code by providing intelligent suggestions. To begin using Copilot, the user installs the extension and logs in with their GitHub account. Once set up, they can start writing code in their preferred programming language and framework within Visual Studio Code.

As the user writes code, the Copilot extension sends relevant information about the editor’s context, such as the file name, programming language, and code snippets, to the GitHub Copilot Service.

Using this information, the Service leverages the power of machine learning to generate suggestions for code completion, function definitions, or even complete algorithm implementations. It takes into account the patterns and structures found in the public code to provide intelligent recommendations.

What sets GitHub Copilot apart is its ability to also analyze the user’s private code to further enhance the suggestions and tailor them to the user’s specific coding style and requirements. This way, Copilot can provide more personalized and relevant recommendations.

The Service then sends these suggestions back to the Copilot extension, which displays them to the user directly in the code editor. The suggestions can appear as inline comments or pop-ups, making it easy for the user to see and consider them while writing code.

The user has full control over the suggestions and can choose to accept, reject, or modify them as they see fit. Additionally, Copilot allows the user to cycle through alternative suggestions if they want to explore different options. Furthermore, the user can even write natural language comments or prompts in their code to guide Copilot and receive more contextually relevant suggestions.

Deploying GitHub Copilot in your favorite IDE

In order to begin utilizing the capabilities, you need to set up a free trial or subscription for your personal GitHub account. This step is essential to gain access to the full range of features and benefits offered by GitHub Copilot for individuals.

STEP 1: Login into your GitHub account and go to settings.

STEP 2: Now, under the section “Code, planning and automation“, click on “GitHub Copilot“.

STEP 3: After that, click on “Enable GitHub Copilot“. Select your preferences, then click “Save and get started“.

STEP 4: Now, Select the plan: Monthly Plan or Yearly Plan. Enter the payment details and then click “Save“.

STEP 5: Now, enter the credentials and then click “Continue“.

After you end up doing the settings, you will get all the instructions in your email on how to start using GitHub Copilot.

What if you want to install the GitHub Copilot extension for VS Code?

To install the GitHub Copilot extension for Visual Studio Code, follow the below steps:

STEP 1: Go to VS Code marketplace and then go to the Github Copilot extension page and click “Install”.

STEP 2: A prompt box will appear. Click on “Open Visual Studio Code“.

STEP 3: Now, in the “Extension: GitHub Copilot“, click Install.

STEP 4: In your browser, GitHub will request the necessary permissions for GitHub Copilot. Click on “Authorize Visual Studio Code” to approve. After that click Open.

Congratulations! Your GitHub Copilot settings are all set up and ready to go. Now, utilizing this powerful tool is as simple as typing whatever code you need. Let me demonstrate with an example.

What if you want to use GitHub Copilot for different IDEs?

The most important thing before using GitHub Copilot is that you need to have an active GitHub Copilot subscription.

Now, the second most important and obvious thing is that if you want to use GitHub Copilot for IDE such as JetBrains, you must have a compatible JetBrains IDE installed before using it. Here is the list which you can consider to check which IDE is compatible with GitHub Copilot:

1. IntelliJ IDEA (Ultimate, Community, Educational)
2. Android Studio
3. AppCode
4. CLion
5. Code With Me Guest
6. DataGrip
7. DataSpell
8. GoLand
9. JetBrains Client
10. MPS
11. PhpStorm
12. PyCharm (Professional, Community, Educational)
13. Rider
14. RubyMine
15. WebStorm

How you can use GitHub Copilot for PyCharm?

PyCharm is the best IDE for Python. and Python is the most popular language. So let’s learn how to utilize GitHub Copilot within PyCharm, it is crucial to ensure that PyCharm is correctly installed on your device. You can easily find PyCharm on JetBrains’ official website.

If you do not have PyCharm installed, you can download it by clicking on the following link: Download PyCharm

Once you have PyCharm installed, you can proceed to install GitHub Copilot by following the steps outlined below:

STEP 1: Open PyCharm and press CTRL+ALT+S to open the settings. In the left panel, under the Editor, click on Plugins.

STEP 2: Go to Marketplace and search “GitHub Copilot“. Click Install.

STEP 3: When the installation is completed, you need to restart the PyCharm.

STEP 4: After restarting, go to Tools, select “GitHub Copilot” and enter your credentials to log in to GitHub.

STEP 5: A “Sign in to GitHub” dialog box will appear. This dialog box will contain the GitHub website and a device code. Click on “Copy and Open“.

STEP 6: Now, a device activates window will open in your browser. Paste the device code and click “Continue“.

STEP 7: Click “Authorize GitHub Copilot Plugin” to approve the GitHub Copilot permissions.

STEP 8: You will get a confirmation from your JetBrains IDE. Click OK.

Now, you are all set to use GitHub Copilot with PyCharm. Utilize this tool and enhance your coding experience. Enjoy the benefits it brings to your development process!

How to use GitHub Copilot to generate a code for you?

Take a look at the image below. In this example, I’ve posed a question: “Can you write a set of unit test functions for the given code?” It’s so simple. All you have to do is type what you require, and GitHub Copilot will generate the corresponding code for you, simplifying your coding process.

GitHub Copilot Pricing

At the time of writing this article. GitHub Copilot is available in two plans:

1. Copilot for Individuals: $10 USD/month or $100 USD/year per seat.
2. Copilot for Business: $19 ISD per user per month.

To use it, you have the option to start with a 30-day free trial, which allows you to experience its capabilities without an upfront payment. Once the trial period ends, you can choose a plan that aligns with your budget and requirements. This flexibility enables you to explore its benefits and make an informed decision about the pricing plan that suits you best.

Click the link to start your free trial – GitHub Copilot: Your AI Pair Programmer

Benefits of using GitHub Copilot

Here we have some of the benefits of using GitHub Copilot:

1. Saves time and effort: Code generation reduces the need to write repetitive or boilerplate code, allowing you to focus on solving more significant problems. It automates the creation of commonly used code patterns, freeing you from manual coding tasks.
2. Increases confidence in unfamiliar areas: When working in a new language or framework, or when learning to code, code generation can be a valuable tool. It provides assistance and generates code snippets that help you navigate and understand unfamiliar territory, boosting your confidence as you explore new coding environments.
3. Enhances code quality and readability: Code generation tools often incorporate best practices and common coding patterns. By suggesting and generating optimized code, they help improve the quality and readability of your codebase. This can lead to cleaner, more maintainable code and facilitate collaboration with other developers.
4. Encourages exploration and innovation: Code generation offers multiple alternatives and suggestions for coding tasks. This enables you to explore new ideas and experiment with different approaches. It opens doors to discovering innovative problem-solving methods and allows you to expand your coding skills and knowledge.

Challenges of working with GitHub Copilot and how to overcome them?

The introduction of GitHub Copilot has generated excitement among developers due to its potential to save time and effort. However, like any new technology, it also brings some challenges that need to be addressed.

Here, we will explore the potential challenges it may present:

Challenge 1: Generating Correct Code

One challenge is the possibility of generating incorrect or low-quality code. While it provides helpful suggestions, it’s important to carefully review and test the code it generates. Sometimes, the code may contain syntax errors, logical mistakes, security vulnerabilities, or performance issues. These issues can impact the overall functionality and reliability of your application. Therefore, it is important to exercise caution and validate the generated code to ensure it meets your project’s requirements and quality standards.

Challenge 2: Compatibility with libraries or frameworks

Providing code suggestions can generate code that might be outdated, deprecated, or incompatible with the specific libraries or frameworks you are working with. For example, it may suggest code that relies on older versions of libraries or frameworks that are no longer supported or maintained. (Until the next update)

Additionally, there could be breaking changes or compatibility issues between the suggested code and your current development environment.

Therefore, it’s important to carefully assess the compatibility of the generated code with your project’s dependencies and make any necessary adjustments or updates to ensure seamless integration.

Challenge 3: Copyright Considerations

Generated code can intrude upon copyright or license agreements. The AI model behind Copilot is trained on publicly available code from GitHub repositories, which means it may generate code that is identical or similar to existing code without providing appropriate attribution or license information. This can lead to legal and ethical concerns for developers who use or distribute the generated code.

It’s important to be mindful of copyright restrictions, respect the intellectual property rights of others, and ensure that any code generated by Copilot is used in compliance with relevant licenses and permissions. Proper attribution and understanding of the licensing terms are essential to navigate these copyright considerations responsibly.

Challenge 4: Handling Complex Algorithms

GitHub Copilot might struggle when dealing with complex logic, algorithms, or design patterns as it is still under development. Generating code for such scenarios often requires a deeper understanding of the problem domain and user requirements, as well as a broader context of the codebase.

For example, if you are working on a project that requires a complex algorithm, you may need to provide Copilot with more information about the problem domain and user requirements. You may also need to provide some examples of code that you would like Copilot to generate. This will help Copilot to better understand the task at hand and generate more accurate code.

Challenge 5: Maintaining Developer Flow and Creativity

It can sometimes disrupt the flow and creativity of developers who rely too heavily on its suggestions. While it provides helpful code suggestions, there is a risk that developers may become overly dependent on them, neglecting their ideas and skills. This overreliance on Copilot can hinder the development of their coding abilities and knowledge.

Additionally, Copilot may not always provide useful or relevant suggestions for every task or scenario. This can lead to frustration or disappointment when developers expect it to offer assistance but find the suggestions lacking or unsuitable.

Challenge 6: Limited language, IDEs, or Technology support

This may have limited support for certain programming languages, IDEs, or technologies. For instance, it might not work as effectively with less popular or less structured languages like R or Perl. Similarly, it may not be compatible with specific IDEs that are not supported by the Copilot extension, such as Eclipse or Sublime Text. (Until the next update)

Furthermore, Copilot may encounter difficulties when dealing with more specialized or domain-specific technologies, such as blockchain or quantum computing. Its capabilities might be better suited for widely-used languages and mainstream technologies.

When working with less supported languages, IDEs, or specialized technologies, developers may experience limitations or find that Copilot’s suggestions are less accurate or relevant.

Conclusion

GitHub Copilot is a powerful tool that can help developers write better code faster and easier. It is an AI-powered code completion system that learns from billions of lines of code and suggests relevant snippets as you type. In this guide, we have covered the basics of GitHub Copilot, how to install and use it, its benefits and limitations, and some challenges which you can face while working with it. We hope that this guide has given you a clear overview and how it can enhance your coding experience. Whether you are a beginner or an expert, It can help you save time, avoid errors, and discover new possibilities in your projects.