GitHub Copilot: A Getting Started Guide to GitHub Copilot

Note: I’ve decided to start writing up the multitude of AI tools/tooling and this is the first of many posts on this topic. This post is effectively a baseline of what one should be familiar with to get rolling with Github Copilot. As I add posts, I’ll add them at the bottom of this post to reference the different tools, as well as back reference them to this post, etc, so that they’re all easily findable. With that, let’s roll…

Intro

GitHub Copilot is thoroughly changing how developers write code, serving as a kind of industry standard – almost – for AI-powered code completion and generation. As someone who’s been in software development for over two decades, I’ve seen many tools come and go, but the modern variant of Copilot represents a fundamental shift in how we approach coding – it’s not just a tool, it’s a new paradigm for human-AI collaboration in software development.

In this comprehensive guide, I’ll walk you through everything you need to know to get started with GitHub Copilot, from basic setup to advanced features that will transform your development workflow.

What is GitHub Copilot?

GitHub Copilot is an AI-powered code completion tool that acts as your virtual pair programmer. It’s built on OpenAI’s Codex model and trained on billions of lines of public code, making it incredibly adept at understanding context, suggesting completions, and even generating entire functions based on your comments and existing code.

Key Capabilities

  • Real-time code suggestions as you type
  • Comment-to-code generation from natural language descriptions
  • Multi-language support across 50+ programming languages
  • Context-aware completions that understand your project structure
  • IDE integration with VS Code, Visual Studio, Neovim, and JetBrains IDEs

Getting Started: Setup and Installation

Prerequisites

Installation Steps

1. Subscribe to GitHub Copilot

2. Install the Extension

  • VS Code: Search for “GitHub Copilot” in the Extensions marketplace
  • Visual Studio: Install from Visual Studio Marketplace
  • JetBrains IDEs: Install from JetBrains Marketplace
  • Neovim: Use copilot.vim or copilot.lua

3. Authenticate

  • Sign in to your GitHub account when prompted
  • Authorize the extension to access your account
  • Verify your Copilot subscription is active
Screenshot of Visual Studio Code showing the welcome interface, including options for opening chat features, managing code completions, and accessing recent projects.

Core Features and How to Use Them

1. Inline Suggestions

Copilot provides real-time code suggestions as you type. These appear as gray text that you can accept by pressing Tab or Enter.

# Type this comment and Copilot will suggest the function
def calculate_compound_interest(principal, rate, time, compounds_per_year):
    # Copilot will suggest the complete implementation

2. Comment-to-Code Generation

One of Copilot’s most powerful features is generating code from natural language comments.

// Create a function that validates email addresses using regex
// Copilot will generate the complete function with proper validation

3. Function Completion

Start typing a function and let Copilot complete it based on context:

def process_user_data(user_input):
    # Start typing and Copilot will suggest the next lines
    if not user_input:
        return None
    
    # Continue with the implementation

4. Test Generation

Copilot can generate test cases for your functions:

def add_numbers(a, b):
    return a + b

# Type "test" or "def test_" and Copilot will suggest test functions

Advanced Features and Techniques

1. Multi-line Completions

Press Tab to accept suggestions line by line, or use Alt + ] to accept multiple lines at once.

2. Alternative Suggestions

When Copilot suggests code, press Alt + [ or Alt + ] to cycle through alternative suggestions.

3. Inline Chat (Copilot Chat)

The newer Copilot Chat feature allows you to have conversations about your code:

  • Press Ctrl + I (or Cmd + I on Mac) to open inline chat
  • Ask questions about your code
  • Request refactoring suggestions
  • Get explanations of complex code sections

4. Custom Prompts

Learn to write effective prompts for better code generation:

Good prompts:

# Create a REST API endpoint that accepts POST requests with JSON data,
# validates the input, and returns a success response with status code 201

Less effective prompts:

# Make an API endpoint

Best Practices for Effective Copilot Usage

1. Write Clear Comments

The quality of Copilot’s suggestions directly correlates with the clarity of your comments and context.

# Good: Clear, specific description
def parse_csv_file(file_path, delimiter=',', skip_header=True):
    """
    Parse a CSV file and return a list of dictionaries.
    
    Args:
        file_path (str): Path to the CSV file
        delimiter (str): Character used to separate fields
        skip_header (bool): Whether to skip the first row as header
    
    Returns:
        list: List of dictionaries where keys are column names
    """

2. Provide Context

Help Copilot understand your project structure and coding style:

# This function follows the project's error handling pattern
# and uses the standard logging configuration
def process_payment(payment_data):

3. Review Generated Code

Always review and test code generated by Copilot:

  • Check for security vulnerabilities
  • Ensure it follows your project’s coding standards
  • Verify the logic matches your requirements
  • Run tests to confirm functionality

4. Iterative Refinement

Use Copilot as a starting point, then refine the code:

  • Accept the initial suggestion
  • Modify it to match your specific needs
  • Ask Copilot to improve specific aspects
  • Iterate until you have the desired result

Language-Specific Tips

Python

  • Copilot excels at Python due to its extensive training data
  • Great for data science, web development, and automation scripts
  • Excellent at generating docstrings and type hints

JavaScript/TypeScript

  • Strong support for modern ES6+ features
  • Good at React, Node.js, and frontend development patterns
  • Effective at generating test files and API clients

Java

  • Good support for Spring Boot and enterprise patterns
  • Effective at generating boilerplate code and tests
  • Strong understanding of Java conventions

Go

  • Growing support with good understanding of Go idioms
  • Effective at generating HTTP handlers and data structures
  • Good at following Go best practices

Troubleshooting Common Issues

1. Suggestions Not Appearing

  • Verify your Copilot subscription is active
  • Check that you’re signed into the correct GitHub account
  • Restart your IDE after authentication
  • Ensure the extension is properly installed and enabled

2. Poor Quality Suggestions

  • Improve your comments and context
  • Check that your file has the correct language extension
  • Provide more context about your project structure
  • Use more specific prompts

3. Performance Issues

  • Disable other AI coding extensions that might conflict
  • Check your internet connection (Copilot requires online access)
  • Restart your IDE if suggestions become slow
  • Update to the latest version of the extension

4. Security Concerns

  • Never paste sensitive data or credentials into Copilot
  • Review generated code for security vulnerabilities
  • Use Copilot in private repositories when possible
  • Be cautious with code that handles user input or authentication

Integration with Development Workflows

1. Pair Programming

Copilot can act as a third member of your pair programming session:

  • Generate alternative implementations for discussion
  • Create test cases to explore edge cases
  • Suggest refactoring opportunities
  • Help with debugging by generating test scenarios

2. Code Review

Use Copilot to enhance your code review process:

  • Generate additional test cases
  • Suggest alternative implementations
  • Identify potential improvements
  • Create documentation for complex functions

3. Learning and Exploration

Copilot is excellent for learning new technologies:

  • Generate examples of new language features
  • Create sample projects to explore frameworks
  • Build reference implementations
  • Practice with different coding patterns

Enterprise and Team Features

1. GitHub Copilot Business

  • Cost: $19/user/month
  • Features: Advanced security, compliance, and team management
  • Use Cases: Enterprise development teams, compliance requirements

2. GitHub Copilot Enterprise

  • Cost: Custom pricing
  • Features: Advanced security, custom models, dedicated support
  • Use Cases: Large enterprises, government, highly regulated industries

3. Team Management

  • Centralized billing and user management
  • Usage analytics and reporting
  • Security and compliance features
  • Integration with enterprise identity providers

Resources and Further Learning

Official Resources

Third-Party Tutorials and Guides

Advanced Techniques and Pro Tips

1. Custom Snippets and Templates

Create custom snippets that work well with Copilot:

// VS Code snippets.json
{
  "API Endpoint": {
    "prefix": "api-endpoint",
    "body": [
      "app.post('/${1:endpoint}', async (req, res) => {",
      "  try {",
      "    const { ${2:params} } = req.body;",
      "    ${3:// Copilot will suggest validation and processing logic}",
      "    res.status(201).json({ success: true, data: result });",
      "  } catch (error) {",
      "    res.status(500).json({ success: false, error: error.message });",
      "  }",
      "});"
    ]
  }
}

2. Context-Aware Prompts

Learn to write prompts that leverage your project’s context:

# This function should follow the same pattern as the other API functions
# in this file, using the shared error handling and response formatting
def get_user_profile(user_id):

3. Testing Strategies

Use Copilot to generate comprehensive test suites:

# Generate tests that cover edge cases, error conditions, and normal operation
# Use the same testing patterns as the existing test files in this project
def test_user_authentication():

4. Documentation Generation

Let Copilot help with documentation:

# Generate comprehensive docstring following Google style
# Include examples, parameter descriptions, and return value details
def process_payment(payment_data, user_id, options=None):

Security and Privacy Considerations

1. Data Privacy

  • Copilot processes your code to provide suggestions
  • Avoid pasting sensitive information, credentials, or proprietary code
  • Use private repositories when working with confidential code
  • Review GitHub’s privacy policy and data handling practices

2. Code Security

  • Generated code may contain security vulnerabilities
  • Always review and test generated code
  • Use security scanning tools to identify potential issues
  • Follow security best practices for your specific domain

3. Compliance Requirements

  • Consider compliance requirements for your industry
  • Evaluate whether Copilot meets your security standards
    • Will the data going out and back be ok with the org?
    • Do additional SLAs or other requirements need put in place?
  • Consult with your security team before adoption
    • That in and out, being it is a service, could pose a significant number of risks for any org.
  • Document usage policies and guidelines

Performance Optimization

1. IDE Configuration

Optimize your IDE for better Copilot performance:

// VS Code settings.json
{
  "github.copilot.enable": {
    "*": true,
    "plaintext": false,
    "markdown": false,
    "scminput": false
  },
  "github.copilot.suggestions": {
    "enable": true,
    "showInlineSuggestions": true
  }
}

2. Network Optimization

  • Ensure stable internet connection
  • Use VPN if required by your organization
  • Consider enterprise deployment for better performance
  • Monitor network usage and optimize as needed

3. Resource Management

  • Disable other AI coding extensions
  • Monitor memory and CPU usage
  • Restart IDE periodically if performance degrades (?? I’ve seen this suggestion multiple places and it bothers me immensely)
  • Update extensions and IDE regularly

Conclusion

GitHub Copilot represents a fundamental shift in software development, moving us from manual coding to AI-assisted development. While it’s not a replacement for understanding programming fundamentals, it’s a powerful tool that can significantly enhance your productivity and code quality.

The key to success with Copilot is learning to work with it effectively writing clear prompts, providing good context, and always reviewing generated code. Start with the basics, practice regularly, and gradually incorporate more advanced features into your workflow.

As we move forward in this AI-augmented development era, developers who can effectively collaborate with AI tools like Copilot will have a significant advantage. The future of programming isn’t about replacing developers – albeit a whole lot of that might be happening right now – it’s more about augmenting their capabilities and enabling them to focus on higher-level problem solving and innovation.

Next Steps

  1. Set up your GitHub Copilot subscription and install the extension
  2. Practice with simple projects to get comfortable with the workflow
  3. Experiment with different prompting techniques to improve suggestion quality
  4. Integrate Copilot into your daily development routine
  5. Share your experiences and learn from the community

Remember, mastery of AI programming tools like GitHub Copilot is a journey, not a destination. Start today, practice consistently, and you’ll be amazed at how quickly it transforms your development experience.

Next up, more on getting started with the various tools and the baseline knowledge you should have around each.

Follow me on LinkedIn, Mastadon, or Blue Sky for more insights on AI programming and software development.

Published by Adron

See: http://compositecode.blog/about

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