Claude Code - Introduction

Overview

Estimated time: 30–40 minutes

Claude Code is Anthropic's AI assistant specialized for programming tasks. With superior code analysis capabilities and large context windows, it excels at understanding complex codebases, detailed refactoring, and comprehensive documentation generation.

Learning Objectives

• Access and configure Claude for coding tasks
• Master effective prompting patterns for code analysis
• Use Claude's large context window for codebase understanding
• Apply Claude for refactoring, documentation, and code review

Prerequisites

• AI Agents - Introduction
• Understanding of software development concepts
• Access to Claude (web interface or API)

What is Claude Code?

Claude is Anthropic's AI assistant with exceptional code analysis capabilities. Unlike completion-focused tools, Claude excels at understanding, explaining, and improving existing code.

Access Methods

Web Interface (claude.ai)

1. Visit claude.ai
2. Sign up with email or Google account
3. Choose plan:
   - Free: Limited messages per day
   - Pro: $20/month, 5x more usage
   - Team: $25/user/month, collaboration features

4. Upload files or paste code directly
5. Start conversations about your code

API Integration

# Install Claude API client
pip install anthropic

# Basic setup
export ANTHROPIC_API_KEY="your-api-key-here"

# Example usage
curl https://api.anthropic.com/v1/messages \
  -H "Content-Type: application/json" \
  -H "X-API-Key: $ANTHROPIC_API_KEY" \
  -d '{
    "model": "claude-3-sonnet-20240229",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Analyze this code..."}]
  }'

VS Code Extensions

Popular Claude Extensions:
1. "Claude Dev" - Direct integration
2. "Anthropic Claude" - API wrapper
3. "AI Code Assistant" - Multi-provider including Claude

Setup:
1. Install extension
2. Add API key in settings
3. Use Command Palette: "Claude: ..."

Core Use Cases

Code Analysis & Understanding

# Upload this complex function to Claude
def process_payment_batch(transactions, config):
    """Process a batch of payment transactions with various validations."""
    results = {'success': [], 'failed': [], 'retries': []}
    
    for tx in transactions:
        try:
            # Validate transaction format
            if not validate_transaction_format(tx):
                results['failed'].append({
                    'tx_id': tx.get('id'),
                    'error': 'Invalid format',
                    'retry': False
                })
                continue
                
            # Check account balance
            if not check_sufficient_balance(tx['from_account'], tx['amount']):
                if tx.get('retry_count', 0) < config['max_retries']:
                    results['retries'].append(tx)
                else:
                    results['failed'].append({
                        'tx_id': tx['id'],
                        'error': 'Insufficient balance',
                        'retry': False
                    })
                continue
                
            # Process the transaction
            result = execute_payment(tx)
            if result['status'] == 'success':
                results['success'].append(result)
            else:
                handle_payment_failure(tx, result, results)
                
        except Exception as e:
            log_payment_error(tx, e)
            results['failed'].append({
                'tx_id': tx.get('id'),
                'error': str(e),
                'retry': should_retry_on_error(e)
            })
    
    return results

Claude's Analysis Response:

Code Refactoring

Prompt: "Refactor this code to be more maintainable, add proper error handling, and follow Python best practices. Also suggest a class-based approach."

Claude Response:
1. Identifies code smells (long function, mixed responsibilities)
2. Suggests separation of concerns
3. Proposes class-based design
4. Adds type hints and proper documentation
5. Implements better error handling patterns
6. Suggests unit testing approach

Documentation Generation

// Give Claude this undocumented API
class UserService {
    constructor(database, cache, logger) {
        this.db = database;
        this.cache = cache;
        this.logger = logger;
    }
    
    async getUser(id, includeDeleted = false) {
        const cacheKey = `user:${id}:${includeDeleted}`;
        let user = await this.cache.get(cacheKey);
        
        if (!user) {
            const query = includeDeleted ? 
                'SELECT * FROM users WHERE id = ?' :
                'SELECT * FROM users WHERE id = ? AND deleted_at IS NULL';
            user = await this.db.query(query, [id]);
            await this.cache.set(cacheKey, user, 300);
        }
        
        return user;
    }
}

Claude generates comprehensive documentation:

/**
 * UserService handles user data operations with caching and logging support.
 * 
 * @class UserService
 * @description Provides methods for user retrieval with built-in caching layer
 * and soft delete support. Implements database abstraction with query optimization.
 */
class UserService {
    /**
     * Creates a new UserService instance.
     * 
     * @param {Database} database - Database connection instance
     * @param {Cache} cache - Cache provider (Redis, Memcached, etc.)  
     * @param {Logger} logger - Logging service for audit and debugging
     */
    constructor(database, cache, logger) {
        this.db = database;
        this.cache = cache;
        this.logger = logger;
    }
    
    /**
     * Retrieves a user by ID with optional soft-delete inclusion.
     * 
     * @async
     * @param {number|string} id - User ID to retrieve
     * @param {boolean} [includeDeleted=false] - Whether to include soft-deleted users
     * @returns {Promise} User object or null if not found
     * @throws {DatabaseError} When database query fails
     * @throws {CacheError} When cache operations fail
     * 
     * @example
     * // Get active user
     * const user = await userService.getUser(123);
     * 
     * @example  
     * // Get user including deleted
     * const deletedUser = await userService.getUser(123, true);
     */
    async getUser(id, includeDeleted = false) {
        // Implementation...
    }
}

Advanced Prompting Patterns

Code Review Pattern

Prompt Template:
"Please review this code as a senior developer would. Focus on:
1. Security vulnerabilities
2. Performance issues  
3. Maintainability concerns
4. Best practice violations
5. Potential bugs or edge cases

[Paste code here]

For each issue found, provide:
- Severity level (Critical/High/Medium/Low)
- Explanation of the problem
- Specific fix recommendation
- Code example of the fix"

Architecture Analysis Pattern

Prompt Template:
"Analyze this codebase architecture. I'm uploading multiple files that represent [describe system]. Please:

1. Identify the overall architecture pattern
2. Map out the data flow
3. Highlight coupling issues
4. Suggest improvements for scalability
5. Identify missing patterns or components

Files: [upload multiple files]

Focus on enterprise-level concerns and provide a technical report suitable for architecture review."

Legacy Code Modernization

Prompt Template:
"This is legacy code written in [year/version]. Please modernize it to current best practices:

1. Update to modern language features
2. Improve error handling
3. Add proper typing/interfaces
4. Implement current design patterns
5. Suggest testing strategy
6. Identify breaking changes and migration path

Original code:
[paste legacy code]

Provide both the modernized version and a detailed migration guide."

Working with Large Codebases

File Upload Strategy

Best Practices:
1. Start with main entry points (main.py, index.js, app.js)
2. Include configuration files (package.json, requirements.txt)
3. Add key modules in logical order
4. Include tests for context
5. Provide README or documentation

Example Upload Order:
1. README.md + package.json (context)
2. src/app.js (entry point)
3. src/routes/ (API structure)
4. src/models/ (data layer)
5. src/utils/ (helper functions)
6. tests/ (test examples)

Context Management

For projects > 200K tokens:
1. Break into logical chunks
2. Start with high-level analysis
3. Deep-dive into specific modules
4. Maintain conversation history
5. Summarize findings between sessions

Example conversation flow:
Session 1: "Overall architecture analysis"
Session 2: "Deep dive into authentication module"  
Session 3: "Database layer optimization"
Session 4: "API security review"

Integration Workflows

Code Review Workflow

# 1. Export Git diff for review
git diff main..feature-branch > changes.patch

# 2. Upload to Claude with prompt:
# "Review this Git patch for a [feature description]. 
#  Focus on potential issues and improvement suggestions."

# 3. Create GitHub comment with Claude's feedback
# 4. Address issues and re-submit for final review

Documentation Workflow

# 1. Extract code structure
find src -name "*.js" -exec head -20 {} \; > code-structure.txt

# 2. Ask Claude to generate:
# - API documentation
# - README updates  
# - Code comments
# - Architecture diagrams (in text/mermaid)

# 3. Integrate generated docs into project

Refactoring Workflow

Large Refactoring Process:
1. Upload current code to Claude
2. Describe refactoring goals and constraints
3. Get high-level refactoring plan
4. Implement changes incrementally
5. Use Claude to review each step
6. Generate tests for refactored code
7. Create migration documentation

Best Practices

Effective Prompting

Quality Assurance

Privacy & Security

• Remove secrets: Never upload API keys or passwords
• Sanitize data: Remove production data from code samples
• Company policies: Check if your organization allows AI code analysis
• Retention policies: Understand how long Claude stores conversations

Limitations & Considerations

What Claude Excels At

• ✅ Code analysis and explanation
• ✅ Architecture review and recommendations
• ✅ Documentation generation
• ✅ Security vulnerability identification
• ✅ Refactoring suggestions

What Claude Struggles With

• ❌ Real-time code completion
• ❌ IDE integration (limited)
• ❌ Running/executing code
• ❌ Access to external resources
• ❌ Very cutting-edge frameworks (training cutoff)

Checks for Understanding

1. What is Claude's main advantage for code analysis?
2. How should you prepare code for upload to Claude?
3. What types of tasks is Claude best suited for?

Exercises

1. Upload a complex function to Claude and ask for a detailed analysis
2. Request Claude to generate comprehensive documentation for an undocumented module
3. Ask Claude to review your code for security vulnerabilities
4. Practice the architecture analysis pattern on a multi-file project