Agent skill
backend-patterns
Patrons d'architecture backend, conception d'API, optimisation de bases de données et bonnes pratiques côté serveur pour Node.js, Express et les routes API Next.js.
Install this agent skill to your Project
npx add-skill https://github.com/Dedalus-ERP-PAS/hexagone-foundation-skills/tree/main/skills/backend-patterns
Metadata
Additional technical details for this skill
- author
- Foundation Skills
SKILL.md
Backend Development Patterns
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
API Design Patterns
RESTful API Structure
// ✅ Resource-based URLs
GET /api/markets # List resources
GET /api/markets/:id # Get single resource
POST /api/markets # Create resource
PUT /api/markets/:id # Replace resource
PATCH /api/markets/:id # Update resource
DELETE /api/markets/:id # Delete resource
// ✅ Query parameters for filtering, sorting, pagination
GET /api/markets?status=active&sort=volume&limit=20&offset=0
Repository Pattern
// Abstract data access logic
interface MarketRepository {
findAll(filters?: MarketFilters): Promise<Market[]>
findById(id: string): Promise<Market | null>
create(data: CreateMarketDto): Promise<Market>
update(id: string, data: UpdateMarketDto): Promise<Market>
delete(id: string): Promise<void>
}
class SupabaseMarketRepository implements MarketRepository {
async findAll(filters?: MarketFilters): Promise<Market[]> {
let query = supabase.from('markets').select('*')
if (filters?.status) {
query = query.eq('status', filters.status)
}
if (filters?.limit) {
query = query.limit(filters.limit)
}
const { data, error } = await query
if (error) throw new Error(error.message)
return data
}
// Other methods...
}
Service Layer Pattern
// Business logic separated from data access
class MarketService {
constructor(private marketRepo: MarketRepository) {}
async searchMarkets(query: string, limit: number = 10): Promise<Market[]> {
// Business logic
const embedding = await generateEmbedding(query)
const results = await this.vectorSearch(embedding, limit)
// Fetch full data
const markets = await this.marketRepo.findByIds(results.map(r => r.id))
// Sort by similarity
return markets.sort((a, b) => {
const scoreA = results.find(r => r.id === a.id)?.score || 0
const scoreB = results.find(r => r.id === b.id)?.score || 0
return scoreA - scoreB
})
}
private async vectorSearch(embedding: number[], limit: number) {
// Vector search implementation
}
}
Middleware Pattern
// Request/response processing pipeline
export function withAuth(handler: NextApiHandler): NextApiHandler {
return async (req, res) => {
const token = req.headers.authorization?.replace('Bearer ', '')
if (!token) {
return res.status(401).json({ error: 'Unauthorized' })
}
try {
const user = await verifyToken(token)
req.user = user
return handler(req, res)
} catch (error) {
return res.status(401).json({ error: 'Invalid token' })
}
}
}
// Usage
export default withAuth(async (req, res) => {
// Handler has access to req.user
})
Database Patterns
Query Optimization
// ✅ GOOD: Select only needed columns
const { data } = await supabase
.from('markets')
.select('id, name, status, volume')
.eq('status', 'active')
.order('volume', { ascending: false })
.limit(10)
// ❌ BAD: Select everything
const { data } = await supabase
.from('markets')
.select('*')
N+1 Query Prevention
// ❌ BAD: N+1 query problem
const markets = await getMarkets()
for (const market of markets) {
market.creator = await getUser(market.creator_id) // N queries
}
// ✅ GOOD: Batch fetch
const markets = await getMarkets()
const creatorIds = markets.map(m => m.creator_id)
const creators = await getUsers(creatorIds) // 1 query
const creatorMap = new Map(creators.map(c => [c.id, c]))
markets.forEach(market => {
market.creator = creatorMap.get(market.creator_id)
})
Transaction Pattern
async function createMarketWithPosition(
marketData: CreateMarketDto,
positionData: CreatePositionDto
) {
// Use Supabase transaction
const { data, error } = await supabase.rpc('create_market_with_position', {
market_data: marketData,
position_data: positionData
})
if (error) throw new Error('Transaction failed')
return data
}
// SQL function in Supabase
CREATE OR REPLACE FUNCTION create_market_with_position(
market_data jsonb,
position_data jsonb
)
RETURNS jsonb
LANGUAGE plpgsql
AS $$
BEGIN
-- Start transaction automatically
INSERT INTO markets VALUES (market_data);
INSERT INTO positions VALUES (position_data);
RETURN jsonb_build_object('success', true);
EXCEPTION
WHEN OTHERS THEN
-- Rollback happens automatically
RETURN jsonb_build_object('success', false, 'error', SQLERRM);
END;
$$;
Caching Strategies
Redis Caching Layer
class CachedMarketRepository implements MarketRepository {
constructor(
private baseRepo: MarketRepository,
private redis: RedisClient
) {}
async findById(id: string): Promise<Market | null> {
// Check cache first
const cached = await this.redis.get(`market:${id}`)
if (cached) {
return JSON.parse(cached)
}
// Cache miss - fetch from database
const market = await this.baseRepo.findById(id)
if (market) {
// Cache for 5 minutes
await this.redis.setex(`market:${id}`, 300, JSON.stringify(market))
}
return market
}
async invalidateCache(id: string): Promise<void> {
await this.redis.del(`market:${id}`)
}
}
Cache-Aside Pattern
async function getMarketWithCache(id: string): Promise<Market> {
const cacheKey = `market:${id}`
// Try cache
const cached = await redis.get(cacheKey)
if (cached) return JSON.parse(cached)
// Cache miss - fetch from DB
const market = await db.markets.findUnique({ where: { id } })
if (!market) throw new Error('Market not found')
// Update cache
await redis.setex(cacheKey, 300, JSON.stringify(market))
return market
}
Error Handling Patterns
Centralized Error Handler
class ApiError extends Error {
constructor(
public statusCode: number,
public message: string,
public isOperational = true
) {
super(message)
Object.setPrototypeOf(this, ApiError.prototype)
}
}
export function errorHandler(error: unknown, req: Request): Response {
if (error instanceof ApiError) {
return NextResponse.json({
success: false,
error: error.message
}, { status: error.statusCode })
}
if (error instanceof z.ZodError) {
return NextResponse.json({
success: false,
error: 'Validation failed',
details: error.errors
}, { status: 400 })
}
// Log unexpected errors
console.error('Unexpected error:', error)
return NextResponse.json({
success: false,
error: 'Internal server error'
}, { status: 500 })
}
// Usage
export async function GET(request: Request) {
try {
const data = await fetchData()
return NextResponse.json({ success: true, data })
} catch (error) {
return errorHandler(error, request)
}
}
Retry with Exponential Backoff
async function fetchWithRetry<T>(
fn: () => Promise<T>,
maxRetries = 3
): Promise<T> {
let lastError: Error
for (let i = 0; i < maxRetries; i++) {
try {
return await fn()
} catch (error) {
lastError = error as Error
if (i < maxRetries - 1) {
// Exponential backoff: 1s, 2s, 4s
const delay = Math.pow(2, i) * 1000
await new Promise(resolve => setTimeout(resolve, delay))
}
}
}
throw lastError!
}
// Usage
const data = await fetchWithRetry(() => fetchFromAPI())
Authentication & Authorization
JWT Token Validation
import jwt from 'jsonwebtoken'
interface JWTPayload {
userId: string
email: string
role: 'admin' | 'user'
}
export function verifyToken(token: string): JWTPayload {
try {
const payload = jwt.verify(token, process.env.JWT_SECRET!) as JWTPayload
return payload
} catch (error) {
throw new ApiError(401, 'Invalid token')
}
}
export async function requireAuth(request: Request) {
const token = request.headers.get('authorization')?.replace('Bearer ', '')
if (!token) {
throw new ApiError(401, 'Missing authorization token')
}
return verifyToken(token)
}
// Usage in API route
export async function GET(request: Request) {
const user = await requireAuth(request)
const data = await getDataForUser(user.userId)
return NextResponse.json({ success: true, data })
}
Role-Based Access Control
type Permission = 'read' | 'write' | 'delete' | 'admin'
interface User {
id: string
role: 'admin' | 'moderator' | 'user'
}
const rolePermissions: Record<User['role'], Permission[]> = {
admin: ['read', 'write', 'delete', 'admin'],
moderator: ['read', 'write', 'delete'],
user: ['read', 'write']
}
export function hasPermission(user: User, permission: Permission): boolean {
return rolePermissions[user.role].includes(permission)
}
export function requirePermission(permission: Permission) {
return async (request: Request) => {
const user = await requireAuth(request)
if (!hasPermission(user, permission)) {
throw new ApiError(403, 'Insufficient permissions')
}
return user
}
}
// Usage
export const DELETE = requirePermission('delete')(async (request: Request) => {
// Handler with permission check
})
Rate Limiting
Simple In-Memory Rate Limiter
class RateLimiter {
private requests = new Map<string, number[]>()
async checkLimit(
identifier: string,
maxRequests: number,
windowMs: number
): Promise<boolean> {
const now = Date.now()
const requests = this.requests.get(identifier) || []
// Remove old requests outside window
const recentRequests = requests.filter(time => now - time < windowMs)
if (recentRequests.length >= maxRequests) {
return false // Rate limit exceeded
}
// Add current request
recentRequests.push(now)
this.requests.set(identifier, recentRequests)
return true
}
}
const limiter = new RateLimiter()
export async function GET(request: Request) {
const ip = request.headers.get('x-forwarded-for') || 'unknown'
const allowed = await limiter.checkLimit(ip, 100, 60000) // 100 req/min
if (!allowed) {
return NextResponse.json({
error: 'Rate limit exceeded'
}, { status: 429 })
}
// Continue with request
}
Background Jobs & Queues
Simple Queue Pattern
class JobQueue<T> {
private queue: T[] = []
private processing = false
async add(job: T): Promise<void> {
this.queue.push(job)
if (!this.processing) {
this.process()
}
}
private async process(): Promise<void> {
this.processing = true
while (this.queue.length > 0) {
const job = this.queue.shift()!
try {
await this.execute(job)
} catch (error) {
console.error('Job failed:', error)
}
}
this.processing = false
}
private async execute(job: T): Promise<void> {
// Job execution logic
}
}
// Usage for indexing markets
interface IndexJob {
marketId: string
}
const indexQueue = new JobQueue<IndexJob>()
export async function POST(request: Request) {
const { marketId } = await request.json()
// Add to queue instead of blocking
await indexQueue.add({ marketId })
return NextResponse.json({ success: true, message: 'Job queued' })
}
Logging & Monitoring
Structured Logging
interface LogContext {
userId?: string
requestId?: string
method?: string
path?: string
[key: string]: unknown
}
class Logger {
log(level: 'info' | 'warn' | 'error', message: string, context?: LogContext) {
const entry = {
timestamp: new Date().toISOString(),
level,
message,
...context
}
console.log(JSON.stringify(entry))
}
info(message: string, context?: LogContext) {
this.log('info', message, context)
}
warn(message: string, context?: LogContext) {
this.log('warn', message, context)
}
error(message: string, error: Error, context?: LogContext) {
this.log('error', message, {
...context,
error: error.message,
stack: error.stack
})
}
}
const logger = new Logger()
// Usage
export async function GET(request: Request) {
const requestId = crypto.randomUUID()
logger.info('Fetching markets', {
requestId,
method: 'GET',
path: '/api/markets'
})
try {
const markets = await fetchMarkets()
return NextResponse.json({ success: true, data: markets })
} catch (error) {
logger.error('Failed to fetch markets', error as Error, { requestId })
return NextResponse.json({ error: 'Internal error' }, { status: 500 })
}
}
Best Practices
- Use patterns appropriate to your scale: Start simple, add complexity only when needed
- Separate concerns: Keep business logic, data access, and API layers separate
- Handle errors consistently: Use centralized error handling
- Cache strategically: Cache frequently accessed, slowly changing data
- Log structured data: Use structured logging for better observability
- Secure by default: Always validate input, authenticate requests, and authorize actions
- Optimize queries: Avoid N+1 queries, select only needed columns
- Use transactions: For operations that must succeed or fail together
- Rate limit: Protect your APIs from abuse
- Monitor and measure: Track performance and errors
Remember: Backend patterns enable scalable, maintainable server-side applications. Choose patterns that fit your complexity level.
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
ubiquitous-language
Extrait un glossaire de langage ubiquitaire style DDD de la conversation en cours, signale les ambiguïtés et propose des termes canoniques. Sauvegarde dans UBIQUITOUS_LANGUAGE.md. À utiliser quand l'utilisateur veut définir des termes métier, construire un glossaire, durcir la terminologie, créer un langage ubiquitaire ou mentionne « domain model », « DDD », « glossaire » ou « langage ubiquitaire ».
hexagone-web-feature-extractor
Explore any Hexagone Web space via Playwright headless browser, capture screenshots, and produce a PO-oriented Markdown document.
gitlab-issue
Crée, récupère, met à jour et gère les issues GitLab avec collecte complète du contexte. À utiliser quand l'utilisateur veut créer une nouvelle issue, voir les détails d'une issue, mettre à jour des issues existantes, lister les issues du projet ou gérer les workflows d'issues dans GitLab.
tdd
Développement piloté par les tests avec boucle red-green-refactor. À utiliser quand l'utilisateur veut construire des fonctionnalités ou corriger des bugs en TDD, mentionne « red-green-refactor », veut des tests d'intégration ou demande du développement test-first.
testing-patterns
Patrons et stratégies de test complets pour les projets JavaScript/TypeScript. Couvre les tests unitaires, d'intégration et E2E, les stratégies de mocking, l'organisation des tests et les anti-patrons courants. À utiliser quand l'utilisateur veut écrire des tests, améliorer la couverture de tests, établir une stratégie de test ou corriger des tests instables.
uniface-procscript
Navigue et interroge la documentation de référence officielle Uniface 9.7 ProcScript (594 entrées couvrant les instructions, fonctions, triggers, types de données, directives préprocesseur et fonctions struct). À utiliser quand l'utilisateur pose des questions sur la syntaxe ProcScript, les triggers Uniface, les opérations base de données, la gestion des listes, la manipulation d'entités, les fonctions de chaînes, la gestion d'erreurs ou tout sujet de programmation Uniface 9.7.
Didn't find tool you were looking for?