GitHub Copilot in 7 Minutes 👨‍💻🤖🚀

GitHub Copilot is revolutionizing code writing by offering an AI-powered autocomplete feature that enhances developer productivity and efficiency. The tool suggests code based on context and libraries in use, potentially introducing developers to new functions and libraries. With machine learning capabilities, GitHub Copilot improves over time, predicting code needs more accurately. It can also generate code from comments, making it invaluable for new project joins or understanding others' code. Users can toggle through suggestions and use shortcuts for additional code suggestions. GitHub Copilot Labs offers experimental features like code explanation, language translation, and debugging assistance, all aimed at improving code quality and project collaboration. Despite occasional errors, the tool has a high user satisfaction rate, with a 9 out of 10 rating from the presenter. It's recommended for a trial to assess its benefits in coding.

Takeaways

• 🚀 GitHub Copilot enhances coding efficiency by providing autocomplete suggestions based on code context and libraries.
• 📚 The tool can help developers discover new functions and libraries they were previously unaware of.
• 🔍 As a machine learning model, GitHub Copilot improves its predictions the more it's used, tailoring to the user's coding style.
• ✍️ The feature to generate code from comments is particularly useful for new developers or when understanding others' code.
• 🔄 Users can toggle through suggestions using the option key and brackets, allowing for quick refinement of the generated code.
• 🛠️ GitHub Copilot Labs offers experimental features like code translation, additional templates, and debugging assistance.
• 🌐 The language translation feature is beneficial for multi-language projects or when converting code from one language to another.
• 📝 Brushes in GitHub Copilot Labs provide code templates and snippets for readability, type annotations, and debugging.
• 🧹 The clean brush simplifies code by removing unused variables and functions, enhancing code clarity.
• 📋 The list steps brush aids in creating step-by-step instructions for complex tasks, especially in multi-developer projects.
• 💡 Custom brush allows for creating custom commands to manipulate code according to specific needs without leaving the editor.
• 🌟 The speaker rates GitHub Copilot 9 out of 10, noting its increasing utility over time and the room for improvement in error reduction.

Q & A

What is the primary function of GitHub Copilot?

GitHub Copilot is an AI-powered coding assistant that automatically generates suggestions for code lines as you type, based on the context of your code and the libraries you are using.

How does GitHub Copilot enhance developer productivity?

GitHub Copilot enhances developer productivity by providing autocomplete suggestions, reducing the amount of typing, discovering new functions and libraries, and improving code prediction through machine learning capabilities.

What is the benefit of using comments with GitHub Copilot?

Using comments with GitHub Copilot allows the tool to generate code based on the described intentions within the comments, which is particularly useful for new developers on a project or when understanding someone else's code.

How can GitHub Copilot help with code optimization and refactoring?

GitHub Copilot can generate additional suggestions for code using the control enter keyboard shortcut, which can help improve code quality, optimize performance, and make the code more efficient.

How can users toggle through suggestions provided by GitHub Copilot?

Users can toggle through suggestions by holding the option key and using the closing brackets on each side to go back and forth through the suggestions.

What is GitHub Copilot Labs and what does it offer?

GitHub Copilot Labs is an initiative by GitHub that offers experimental features for developers to try before public release. It includes features like code explanation, language translation, code templates, and debugging assistance.

How does the 'Explained' feature in GitHub Copilot Labs help with code collaboration?

The 'Explained' feature allows developers to highlight a piece of code and provide an explanation of its functionality, which aids in collaboration by making the code more understandable to others.

What is the purpose of the 'Brushes' feature in GitHub Copilot Labs?

The 'Brushes' feature offers additional code templates and snippets for specific use cases, such as making code more readable, adding type annotations, fixing bugs, and generating documentation, enhancing code quality and maintainability.

How can developers provide feedback on the experimental features of GitHub Copilot?

Developers can provide feedback on experimental features by participating in GitHub Copilot Labs, which helps in shaping the future updates and improvements of GitHub Copilot.

What is the rating the speaker gives to GitHub Copilot and why?

The speaker rates GitHub Copilot 9 out of 10. The reason for not giving a perfect score is that it occasionally produces errors, but the speaker has noticed improvements over time with increased usage.

How can new users try out GitHub Copilot?

New users can try out GitHub Copilot through a two-month free trial to see if it can assist them in their coding tasks.

What does the speaker suggest for those who find the video informative?

The speaker suggests that those who find the video informative should like, comment, and subscribe to the channel, and also consider checking out related videos.

Outlines

00:00

🚀 Introduction to GitHub Copilot

GitHub Copilot is a revolutionary tool that enhances code writing efficiency by generating suggestions based on the code context and libraries used. It not only saves time by reducing manual typing but also introduces developers to new functions and libraries. With machine learning capabilities, Copilot improves over time in predicting the needed code. It can also generate code from comments, facilitating understanding and collaboration. Users can navigate through suggestions using keyboard shortcuts and can toggle the tool on or off through the command palette or VS Code toolbar. GitHub Copilot Labs offers experimental features like code explanation, translation, and additional code templates to further assist in writing better and more efficient code.

05:01

🛠️ Advanced Features of GitHub Copilot

GitHub Copilot offers advanced features such as toggling through suggestions, generating additional code suggestions with a keyboard shortcut, and a suite of brushes in GitHub Copilot Labs for various coding tasks. These brushes include 'explain' for code clarification, 'translate' for language conversion, 'brushes' for code templates and snippets, and 'fix a bug' for identifying and suggesting fixes for errors. Other brushes like 'clean', 'list steps', 'make robust', 'chunk code', and 'document code' are designed to improve code readability, provide instructions, ensure robustness, manage code chunks, and generate documentation. The 'custom brush' allows for tailored commands based on highlighted code. The speaker rates GitHub Copilot highly, at 9 out of 10, noting its increasing utility over time and recommending the two-month free trial for others to experience its benefits.

Keywords

💡GitHub Copilot

GitHub Copilot is an AI-powered code generation tool developed by GitHub. It assists developers by providing code suggestions as they type, making the coding process faster and more efficient. In the video, it is described as a tool that enhances productivity by predicting the code a developer needs and generating it for them, based on the context and libraries in use.

💡Autocomplete Feature

The autocomplete feature in GitHub Copilot suggests code as a developer types, reducing the amount of manual typing required. It is a powerful tool that not only saves time but also introduces developers to new functions and libraries they may not have known about. The video emphasizes how this feature becomes more accurate with increased usage due to machine learning capabilities.

💡Code Generation

GitHub Copilot's ability to generate code based on comments is a significant feature. Developers can write comments describing what they want to achieve, and the tool will generate the corresponding code. This is particularly useful for new developers on a project or when understanding someone else's code, as it aids in making code more understandable and accessible.

💡Machine Learning

Machine learning is a type of artificial intelligence that allows systems to learn and improve from experience without being explicitly programmed. In the context of GitHub Copilot, machine learning is used to improve the accuracy of code suggestions over time, making the tool better at predicting what code a developer needs as it learns from the developer's coding patterns.

💡Code Suggestions

GitHub Copilot provides code suggestions that developers can choose from as they write code. These suggestions are context-aware, based on the current code and the libraries being used. The video script mentions that if a developer does not like the suggestions, they can toggle through the options to find the one that best fits their needs.

💡GitHub Copilot Labs

GitHub Copilot Labs is an initiative by GitHub that allows developers to try out experimental features of GitHub Copilot before they are released to the public. It is designed to help developers write better code faster and more efficiently. The video discusses how participating in Labs can provide valuable feedback on these features.

💡Code Optimization

The ability to generate additional suggestions for optimizing or refactoring code is a powerful feature of GitHub Copilot. When a developer uses the control-enter keyboard shortcut, GitHub Copilot opens a window of suggestions that can help improve code quality, optimize performance, and make the code more efficient.

💡Code Templates and Snippets

GitHub Copilot Labs provides additional code templates and snippets for specific use cases, which can save developers time and effort. These templates and snippets are pre-written code structures that can be used to quickly generate common patterns or functionalities in a program.

💡Type Annotations

Type annotations are a feature in programming languages that allow for the explicit declaration of the data types of variables. In the context of the video, the 'add types' brush in GitHub Copilot Labs is mentioned as a way to add these annotations to a JavaScript file, which can be particularly useful for large projects to ensure code consistency and understandability.

💡Debugging

Debugging is the process of finding and resolving bugs or errors in a computer program. The 'fix a bug' brush in GitHub Copilot Labs uses machine learning to analyze code and suggest possible fixes for errors, automating part of the debugging process and saving developers time.

💡Documentation

Documentation in programming refers to the written explanations of what the code does, how it does it, and why certain design decisions were made. The 'document code' brush in GitHub Copilot Labs generates comments and documentation for code, making it easier for other developers to understand and maintain the project.

💡Custom Brush

The custom brush in GitHub Copilot Labs allows developers to highlight code and create custom commands for specific actions they want to perform with a piece of code. This feature provides a high degree of flexibility and customization, enabling developers to tailor the tool to their specific needs and workflows.

Highlights

GitHub Copilot automates code generation based on context and libraries used, enhancing developer productivity and efficiency.

The more you use GitHub Copilot, the better it becomes at predicting the code you need through machine learning capabilities.

GitHub Copilot can generate code from comments, aiding in understanding and maintaining codebases.

Writing clear comments is crucial for GitHub Copilot to generate accurate code based on your intentions.

Developers can toggle through suggestions using the option key and brackets to find the most suitable code.

The control enter keyboard shortcut opens a window of suggestions to optimize or refactor code.

GitHub Copilot can be toggled on or off from the command palette or the VS Code toolbar.

GitHub Copilot Labs offers experimental features for developers to try before public release.

The explained feature in Labs provides explanations for code snippets, aiding in collaboration and understanding.

Language translation feature allows code conversion between different programming languages.

Brushes in Labs offer code templates and snippets for specific use cases, like readability and type annotations.

The fix a bug brush uses machine learning to identify and suggest fixes for code errors.

The debug brush adds debugging code to help identify and resolve issues in complex projects.

The clean brush removes unused variables and functions for a more streamlined and readable codebase.

The list steps brush creates step-by-step instructions for specific tasks, aiding multi-developer projects.

The make robust brush adds error handling to ensure code runs smoothly and doesn't crash.

The chunk code brush helps split code into smaller chunks for easier management and reduced likelihood of errors.

The document code brush generates comments and documentation to maintain well-documented code.

The custom brush allows for highlighting code and issuing custom commands for specific tasks.

GitHub Copilot has a two-month free trial, encouraging developers to test its utility in their coding workflow.

The reviewer has been using GitHub Copilot for a few months and rates it 9 out of 10, noting its increasing usefulness over time.