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nodejs-best-practices

Node.js development principles and decision-making. Framework selection, async patterns, security, and architecture. Teaches thinking, not copying.

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Node.js Best Practices

Principles and decision-making for Node.js development in 2025. Learn to THINK, not memorize code patterns.


⚠️ How to Use This Skill

This skill teaches decision-making principles, not fixed code to copy.

  • ASK user for preferences when unclear
  • Choose framework/pattern based on CONTEXT
  • Don't default to same solution every time

1. Framework Selection (2025)

Decision Tree

What are you building?
│
├── Edge/Serverless (Cloudflare, Vercel)
│   └── Hono (zero-dependency, ultra-fast cold starts)
│
├── High Performance API
│   └── Fastify (2-3x faster than Express)
│
├── Enterprise/Team familiarity
│   └── NestJS (structured, DI, decorators)
│
├── Legacy/Stable/Maximum ecosystem
│   └── Express (mature, most middleware)
│
└── Full-stack with frontend
    └── Next.js API Routes or tRPC

Comparison Principles

FactorHonoFastifyExpress
Best forEdge, serverlessPerformanceLegacy, learning
Cold startFastestFastModerate
EcosystemGrowingGoodLargest
TypeScriptNativeExcellentGood
Learning curveLowMediumLow

Selection Questions to Ask:

  1. What's the deployment target?
  2. Is cold start time critical?
  3. Does team have existing experience?
  4. Is there legacy code to maintain?

2. Runtime Considerations (2025)

Native TypeScript

Node.js 22+: --experimental-strip-types
├── Run .ts files directly
├── No build step needed for simple projects
└── Consider for: scripts, simple APIs

Module System Decision

ESM (import/export)
├── Modern standard
├── Better tree-shaking
├── Async module loading
└── Use for: new projects

CommonJS (require)
├── Legacy compatibility
├── More npm packages support
└── Use for: existing codebases, some edge cases

Runtime Selection

RuntimeBest For
Node.jsGeneral purpose, largest ecosystem
BunPerformance, built-in bundler
DenoSecurity-first, built-in TypeScript

3. Architecture Principles

Layered Structure Concept

Request Flow:
│
├── Controller/Route Layer
│   ├── Handles HTTP specifics
│   ├── Input validation at boundary
│   └── Calls service layer
│
├── Service Layer
│   ├── Business logic
│   ├── Framework-agnostic
│   └── Calls repository layer
│
└── Repository Layer
    ├── Data access only
    ├── Database queries
    └── ORM interactions

Why This Matters:

  • Testability: Mock layers independently
  • Flexibility: Swap database without touching business logic
  • Clarity: Each layer has single responsibility

When to Simplify:

  • Small scripts → Single file OK
  • Prototypes → Less structure acceptable
  • Always ask: "Will this grow?"

4. Error Handling Principles

Centralized Error Handling

Pattern:
├── Create custom error classes
├── Throw from any layer
├── Catch at top level (middleware)
└── Format consistent response

Error Response Philosophy

Client gets:
├── Appropriate HTTP status
├── Error code for programmatic handling
├── User-friendly message
└── NO internal details (security!)

Logs get:
├── Full stack trace
├── Request context
├── User ID (if applicable)
└── Timestamp

Status Code Selection

SituationStatusWhen
Bad input400Client sent invalid data
No auth401Missing or invalid credentials
No permission403Valid auth, but not allowed
Not found404Resource doesn't exist
Conflict409Duplicate or state conflict
Validation422Schema valid but business rules fail
Server error500Our fault, log everything

5. Async Patterns Principles

When to Use Each

PatternUse When
async/awaitSequential async operations
Promise.allParallel independent operations
Promise.allSettledParallel where some can fail
Promise.raceTimeout or first response wins

Event Loop Awareness

I/O-bound (async helps):
├── Database queries
├── HTTP requests
├── File system
└── Network operations

CPU-bound (async doesn't help):
├── Crypto operations
├── Image processing
├── Complex calculations
└── → Use worker threads or offload

Avoiding Event Loop Blocking

  • Never use sync methods in production (fs.readFileSync, etc.)
  • Offload CPU-intensive work
  • Use streaming for large data

6. Validation Principles

Validate at Boundaries

Where to validate:
├── API entry point (request body/params)
├── Before database operations
├── External data (API responses, file uploads)
└── Environment variables (startup)

Validation Library Selection

LibraryBest For
ZodTypeScript first, inference
ValibotSmaller bundle (tree-shakeable)
ArkTypePerformance critical
YupExist