Amazon CodeWhisperer Cheat Sheet

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Overview

Amazon CodeWhisperer is AWS's AI-powered code completion service that provides intelligent code suggestions in real-time. It analyzes your code and comments to generate contextually relevant recommendations, supporting multiple programming languages and integrating with popular IDEs.

⚠️ Note: CodeWhisperer has been rebranded as Amazon Q Developer. This cheatsheet covers the legacy CodeWhisperer interface and commands.

Installation & Setup

VS Code Extension

# Install AWS Toolkit extension (includes CodeWhisperer)
code --install-extension AmazonWebServices.aws-toolkit-vscode

# Or install standalone CodeWhisperer extension
code --install-extension AmazonWebServices.codewhisperer-for-command-line-companion

JetBrains IDEs

# Install AWS Toolkit plugin
# File > Settings > Plugins > Marketplace
# Search "AWS Toolkit" and install

Command Line Integration

# Install CodeWhisperer CLI
npm install -g @amzn/codewhisperer-cli

# Or using pip
pip install codewhisperer-cli

Authentication

AWS Builder ID (Free)

# Sign up for AWS Builder ID
# Free tier with usage limits
# No AWS account required

# Authentication in IDE:
# 1. Click "Start" in CodeWhisperer panel
# 2. Choose "Use for free with AWS Builder ID"
# 3. Complete browser authentication

AWS IAM Credentials

# Configure AWS credentials
aws configure
# Enter Access Key ID
# Enter Secret Access Key
# Enter Default region
# Enter Default output format

# Or use environment variables
export AWS_ACCESS_KEY_ID=your_access_key
export AWS_SECRET_ACCESS_KEY=your_secret_key
export AWS_DEFAULT_REGION=us-east-1

AWS SSO Integration

# Configure SSO profile
aws configure sso
# Enter SSO start URL
# Enter SSO region
# Complete browser authentication

# Use SSO profile
aws sso login --profile your-profile

Core Features

Code Completion

# Automatic suggestions while typing
# Press Tab to accept suggestion
# Press Esc to dismiss suggestion
# Use arrow keys to navigate multiple suggestions

# Trigger manual suggestions
# Ctrl+Space (VS Code)
# Alt+C (JetBrains)

Comment-to-Code Generation

# Type descriptive comment
# Function to calculate compound interest
def calculate_compound_interest(principal, rate, time, compound_frequency):
    # CodeWhisperer generates the implementation
    amount = principal * (1 + rate/compound_frequency) ** (compound_frequency * time)
    return amount - principal

Multi-line Code Generation

// Generate entire functions from comments
// Create Express.js REST API endpoint for user management
app.post('/api/users', async (req, res) => {
    try {
        const { name, email, password } = req.body;
        const hashedPassword = await bcrypt.hash(password, 10);
        const user = new User({ name, email, password: hashedPassword });
        await user.save();
        res.status(201).json({ message: 'User created successfully', userId: user._id });
    } catch (error) {
        res.status(400).json({ error: error.message });
    }
});

Language Support

Supported Languages

# Fully supported languages:
- Python
- Java
- JavaScript
- TypeScript
- C#
- Go
- Rust
- PHP
- Ruby
- Kotlin
- C++
- Shell scripting (Bash)
- SQL
- Scala
- R
- Swift

Framework Integration

# Popular frameworks supported:
- React/Next.js
- Angular
- Vue.js
- Spring Boot
- Django/Flask
- Express.js
- .NET Core
- Laravel
- Rails

IDE Integration

VS Code Commands

# Command Palette commands:
"AWS: CodeWhisperer - Start"
"AWS: CodeWhisperer - Pause"
"AWS: CodeWhisperer - Resume"
"AWS: CodeWhisperer - Show Security Scan"
"AWS: CodeWhisperer - Open Settings"

# Keyboard shortcuts:
Alt+C           # Trigger suggestion
Tab             # Accept suggestion
Esc             # Dismiss suggestion
Ctrl+Right      # Accept word

JetBrains Commands

# Tools menu:
Tools > AWS > CodeWhisperer > Start
Tools > AWS > CodeWhisperer > Pause
Tools > AWS > CodeWhisperer > Settings

# Context menu:
Right-click > AWS CodeWhisperer > Accept Suggestion
Right-click > AWS CodeWhisperer > Reject Suggestion

Configuration Settings

// VS Code settings.json
{
    "aws.codeWhisperer.shareCodeWhispererContentWithAWS": false,
    "aws.codeWhisperer.includeSuggestionsWithCodeReferences": true,
    "aws.codeWhisperer.automaticTrigger": true,
    "aws.codeWhisperer.maxSuggestions": 5
}

Security Scanning

Vulnerability Detection

# Automatic security scanning
# Detects common vulnerabilities:
# - SQL injection
# - Cross-site scripting (XSS)
# - Hardcoded credentials
# - Insecure cryptographic practices
# - Path traversal vulnerabilities

Manual Security Scan

# VS Code:
# 1. Open Command Palette (Ctrl+Shift+P)
# 2. Type "CodeWhisperer Security Scan"
# 3. Select files to scan
# 4. Review results in Problems panel

# JetBrains:
# 1. Tools > AWS > CodeWhisperer > Security Scan
# 2. Select scope (file/project)
# 3. Review results in inspection panel

Security Scan Results

# High severity issues:
# - Critical security vulnerabilities
# - Immediate attention required
# - Detailed remediation steps provided

# Medium/Low severity:
# - Potential security concerns
# - Best practice recommendations
# - Code quality improvements

Command Line Usage

CLI Installation

# Install via npm
npm install -g @amzn/codewhisperer-cli

# Install via pip
pip install codewhisperer-cli

# Verify installation
codewhisperer --version

CLI Authentication

# Authenticate with AWS Builder ID
codewhisperer auth login

# Use AWS credentials
codewhisperer auth login --profile your-aws-profile

# Check authentication status
codewhisperer auth status

Code Generation via CLI

# Generate code from prompt
codewhisperer generate --prompt "Python function to sort dictionary by values"

# Generate with context file
codewhisperer generate --prompt "Add error handling" --context main.py

# Interactive mode
codewhisperer interactive

Best Practices

Effective Prompting

# Good: Specific and descriptive comments
# Function to validate email format using regex and return boolean
def validate_email(email):
    # CodeWhisperer generates accurate implementation

# Bad: Vague comments
# Email function
def email_func():
    # Less accurate suggestions

Code Review

# Always review generated code:
# 1. Check for logical correctness
# 2. Verify security implications
# 3. Ensure code style consistency
# 4. Test functionality thoroughly
# 5. Validate error handling

Security Considerations

# Review security scan results regularly
# Don't ignore vulnerability warnings
# Validate all input parameters
# Use secure coding practices
# Keep dependencies updated

Usage Limits & Pricing

Free Tier (AWS Builder ID)

# Monthly limits:
# - Code suggestions: Unlimited
# - Security scans: 50 per month
# - Supported languages: All
# - IDE integrations: All

Professional Tier

# Features (when available):
# - Higher usage limits
# - Priority support
# - Advanced security features
# - Team management
# - Usage analytics

Troubleshooting

Common Issues

# CodeWhisperer not working:
# 1. Check internet connection
# 2. Verify authentication status
# 3. Restart IDE
# 4. Update AWS Toolkit extension

# No suggestions appearing:
# 1. Check if CodeWhisperer is enabled
# 2. Verify file type is supported
# 3. Check automatic trigger settings
# 4. Try manual trigger (Alt+C)

Performance Issues

# Slow suggestions:
# 1. Close unnecessary files
# 2. Reduce project size
# 3. Check network connectivity
# 4. Update to latest extension version

# High CPU usage:
# 1. Adjust suggestion frequency
# 2. Disable automatic triggers
# 3. Use manual triggers only
# 4. Configure suggestion limits

Debug Information

# VS Code debug info:
# 1. View > Output
# 2. Select "AWS Toolkit" from dropdown
# 3. Check for error messages

# JetBrains debug info:
# 1. Help > Show Log in Explorer
# 2. Look for AWS-related log files
# 3. Check for error patterns

Code Examples

Python Data Processing

# Function to process CSV file and calculate statistics
import pandas as pd
import numpy as np

def process_sales_data(file_path):
    df = pd.read_csv(file_path)

    # Calculate key metrics
    total_sales = df['amount'].sum()
    avg_sale = df['amount'].mean()
    top_products = df.groupby('product')['amount'].sum().sort_values(ascending=False).head(5)

    return {
        'total_sales': total_sales,
        'average_sale': avg_sale,
        'top_products': top_products.to_dict()
    }

JavaScript API Integration

// Function to fetch user data with error handling and retry logic
async function fetchUserData(userId, maxRetries = 3) {
    for (let attempt = 1; attempt <= maxRetries; attempt++) {
        try {
            const response = await fetch(`/api/users/${userId}`);

            if (!response.ok) {
                throw new Error(`HTTP error! status: ${response.status}`);
            }

            const userData = await response.json();
            return userData;

        } catch (error) {
            console.error(`Attempt ${attempt} failed:`, error.message);

            if (attempt === maxRetries) {
                throw new Error(`Failed to fetch user data after ${maxRetries} attempts`);
            }

            // Wait before retry
            await new Promise(resolve => setTimeout(resolve, 1000 * attempt));
        }
    }
}

Java Spring Boot Controller

// REST controller for product management with validation
@RestController
@RequestMapping("/api/products")
@Validated
public class ProductController {

    @Autowired
    private ProductService productService;

    @PostMapping
    public ResponseEntity<Product> createProduct(@Valid @RequestBody ProductDTO productDTO) {
        try {
            Product product = productService.createProduct(productDTO);
            return ResponseEntity.status(HttpStatus.CREATED).body(product);
        } catch (ValidationException e) {
            return ResponseEntity.badRequest().build();
        } catch (Exception e) {
            return ResponseEntity.status(HttpStatus.INTERNAL_SERVER_ERROR).build();
        }
    }
}

Migration to Amazon Q

Transition Guide

# CodeWhisperer is now Amazon Q Developer
# Migration steps:
# 1. Update to latest AWS Toolkit
# 2. Existing settings are preserved
# 3. Authentication remains the same
# 4. Enhanced features available in Amazon Q

New Features in Amazon Q

# Additional capabilities:
# - Chat interface for code questions
# - Application modernization
# - Code explanations
# - Unit test generation
# - Enhanced security scanning

Resources

Documentation

• CodeWhisperer User Guide
• AWS Toolkit for VS Code
• AWS Toolkit for JetBrains

Community

• AWS Developer Forums
• GitHub Issues
• Stack Overflow

Training

• AWS CodeWhisperer Workshop
• Getting Started Guide
• Best Practices Documentation