How to Use GitHub Copilot to Become a Happier and More Productive Developer

As developers, we‘re always on the lookout for tools and techniques to streamline our workflow, write better code faster, and ultimately derive more satisfaction from our work. Enter GitHub Copilot – an AI-powered code completion and generation tool that integrates directly into your IDE. By leveraging the power of OpenAI‘s Codex language model trained on billions of lines of public code, Copilot offers intelligent code suggestions, accelerates the development process, and has the potential to significantly boost developer productivity and happiness.

In this in-depth guide, we‘ll walk through how to set up and make the most of GitHub Copilot. We‘ll explore its various features and use cases, provide concrete examples, and address potential limitations. By the end, you‘ll have a solid understanding of how Copilot can revolutionize your development workflow and why it‘s worth embracing this groundbreaking tool.

Setting Up GitHub Copilot

Before diving into usage, let‘s quickly cover installation and setup:

1. Sign up for Copilot on the official site. It offers a free trial, after which paid plans start at $10/month or $100/year.

2. Install the Copilot extension for your preferred IDE. It currently supports VS Code, Visual Studio, Neovim, and JetBrains IDEs. For this guide, we‘ll use the VS Code extension.

3. Launch VS Code and you should see a Copilot icon in the status bar. Click it and follow the prompts to authenticate with your GitHub account.

And that‘s it! Copilot is now activated and ready to offer code suggestions as you type. By default, it will display recommendations in-line as "ghost text". Pressing Tab will accept the suggestion.

Rapid Code Generation with Copilot

One of Copilot‘s standout features is its ability to generate entire blocks or even functions of code based on a natural language comment or a few starting lines. This can dramatically speed up the process of stubbing out new features and save you from having to remember every language-specific syntax and convention.

For example, let‘s say we want to write a Python function to calculate the nth Fibonacci number. We can simply start typing a comment specifying what we want:

# Function to calculate the nth Fibonacci number
def fib(n):

Copilot will automatically suggest an implementation:

def fib(n):
    if n <= 0:
        return 0
    elif n == 1:
        return 1
    else:
        return fib(n-1) + fib(n-2)

This recursively calculates the Fibonacci number, handling base cases for n <= 0 and n == 1. We can accept it as is, or modify it further, such as adding memoization to optimize for larger values of n. The key is that Copilot gives us a solid starting point and spares us from having to write out the full function from scratch.

Instant Code Explanations with Copilot

Ever come across a dense block of code and struggled to decipher what it does? Copilot offers a nifty "Explain" feature that provides a plain English description of selected code. This is immensely helpful for quickly getting up to speed on unfamiliar codebases or making sense of complex algorithms.

For instance, consider this concise JavaScript function:

const isDivisible = (num, divisor) => !(num % divisor);

To trigger an explanation, we can simply select the code and click on the Copilot "Explain" option that appears:

Copilot then displays a comment breakdown:

// This is an arrow function named isDivisible that takes two parameters: num and divisor.
// The function body consists of a single expression that checks if num is divisible by divisor.
// It does this by using the modulo operator (%) to get the remainder of the division of num by divisor.
// The ! (logical NOT) operator is then used to negate the result.
// So if num is divisible by divisor (i.e., remainder is 0), !0 evaluates to true.
// Otherwise, !(non-zero remainder) evaluates to false.
// Therefore, the function returns true if num is divisible by divisor, false otherwise.
const isDivisible = (num, divisor) => !(num % divisor);

This instant explanation capability can be a huge time-saver and aid in comprehension, especially when diving into a new codebase or reviewing pull requests.

Streamlined Debugging with Copilot

Debugging consumes a significant portion of developers‘ time and mental energy. Copilot endeavors to streamline the process by offering intelligent debugging assistance.

Let‘s say we have a JavaScript function that‘s supposed to calculate the area of a rectangle, but it‘s currently throwing an error:

function calculateArea(width, height) {
  const area = width * height;
  return "The area is: " + area + " square units";
}

console.log(calculateArea(10, "20"));

When we run this, we get the error: "TypeError: Area width must be a number". We can paste this error message into a comment and prompt Copilot for help:

// TypeError: Area width must be a number
function calculateArea(width, height) {
  const area = width * height;
  return "The area is: " + area + " square units";
}

console.log(calculateArea(10, "20"));

Copilot detects the issue and suggests a fix:

// TypeError: Area width must be a number
function calculateArea(width, height) {
  if (typeof width !== "number" || typeof height !== "number") {
    throw new Error("Area dimensions must be numbers");
  }
  const area = width * height;
  return "The area is: " + area + " square units";
}

console.log(calculateArea(10, 20));

It identified that the error was caused by passing a string "20" instead of a number 20 for the height parameter. To prevent this, it added a type check at the beginning of the function, throwing an explicit error if either width or height is not a number. It also corrected the function invocation to pass 20 as a number.

Having Copilot pinpoint bugs and propose solutions can greatly reduce debugging time and frustration.

Effortless Code Refactoring with Copilot

Refactoring code to be more efficient, readable, or adhere to best practices is an important but often tedious task. Copilot can assist by suggesting optimized versions of our code.

Consider this Python function to calculate the sum of a list of numbers:

def sum_list(numbers):
    total = 0
    for num in numbers:
        total += num
    return total

We can prompt Copilot to refactor this using a built-in function:

# Refactor to use a built-in function
def sum_list(numbers):
    total = 0
    for num in numbers:
        total += num
    return total

Copilot suggests:

def sum_list(numbers):
    return sum(numbers)

It recognized that we can achieve the same functionality more concisely using Python‘s built-in sum() function. This is a trivial example, but Copilot‘s refactoring capabilities extend to more complex scenarios like converting loops to list comprehensions, replacing iterative code with recursive functions, and more.

Automated Unit Test Generation with Copilot

Writing unit tests is crucial for ensuring code quality and catching bugs early, but it can be a time-consuming process, especially for large codebases. Copilot offers a feature to automatically generate unit tests based on your code.

Let‘s revisit our Fibonacci function from earlier:

def fib(n):
    if n <= 0:
        return 0
    elif n == 1:
        return 1
    else:
        return fib(n-1) + fib(n-2)

We can prompt Copilot to create unit tests for this function:

# Generate unit tests for the fib function

Copilot responds with:

def test_fib():
    assert fib(0) == 0
    assert fib(1) == 1
    assert fib(2) == 1
    assert fib(3) == 2
    assert fib(4) == 3
    assert fib(5) == 5
    assert fib(10) == 55

It generated a test function that checks the correctness of fib() for various input values, comparing the expected output with the actual returned value. This covers the base cases of n <= 0 and n == 1, as well as several other cases to verify the Fibonacci sequence is correctly calculated.

Having Copilot write these initial test cases saves us time and ensures we don‘t forget to test important scenarios. We can then expand upon these tests as needed.

Enhanced Code Reviews with Copilot for Pull Requests

GitHub is currently previewing a new feature called Copilot for Pull Requests, which aims to streamline the code review process. Some key capabilities include:

• Automatically filling in PR templates with a summary of code changes
• Suggesting additional tests to write based on the changed code
• Offering in-line code suggestions as you type comments on a PR
• Identifying potential bugs or improvements in the PR code

While not yet generally available, this upcoming feature has the potential to greatly enhance the efficiency and quality of code reviews.

Experimental Voice-Driven Development with Copilot Voice

For those keen on trying cutting-edge features, GitHub is also previewing Copilot Voice (formerly called "Hey, GitHub!"). This allows you to use natural language voice commands to:

• Trigger Copilot code suggestions
• Navigate through files and folders
• Execute IDE commands
• Get voice summaries of code

While still experimental, voice-driven development opens up exciting possibilities for more intuitive and accessible coding workflows.

Limitations and Downsides of Copilot

For all its impressive capabilities, it‘s important to remember that Copilot is a machine learning model, not a human developer. Some key limitations to be aware of:

1. Copilot can generate incorrect or suboptimal code, especially for complex or niche domains. Always review and test Copilot‘s suggestions before accepting them.

2. Copilot is not a substitute for understanding the fundamentals of programming and problem-solving. Over-reliance on Copilot without grasping underlying concepts can hinder growth as a developer.

3. There are ongoing discussions around the legal and ethical implications of AI code generation tools like Copilot, particularly around licensing, attribution, and potential biases in the training data.

As with any tool, Copilot is most effective when used judiciously and in combination with human expertise and judgment.

Conclusion

GitHub Copilot is a game-changing tool that has the potential to significantly boost developer productivity and job satisfaction. By providing intelligent code suggestions, explanations, debugging assistance, refactoring tips, and automated tests, Copilot streamlines many of the most time-consuming and mentally taxing aspects of development work.

While not a silver bullet, when used thoughtfully Copilot can dramatically speed up the coding process, improve code quality, and free up developers‘ cognitive load to focus on higher-level problem solving. Its upcoming integration with pull requests and experimental voice interface hint at even more exciting workflow enhancements on the horizon.

If you haven‘t already given Copilot a try, we highly recommend taking advantage of the free trial and experiencing firsthand how it can revolutionize your development workflow. Happy coding!