/api-design-principles

name: api-design-principles
description: "Use when designing a new REST or GraphQL API, reviewing an API spec before implementation, setting team API standards, or migrating REST to GraphQL. Covers resources, HTTP semantics, pagination, error handling, and pitfalls."
domain: engineering

API Design Principles

Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers and stand the test of time.

When to Use This Skill

• Designing new REST or GraphQL APIs
• Refactoring existing APIs for better usability
• Establishing API design standards for your team
• Reviewing API specifications before implementation
• Migrating between API paradigms (REST to GraphQL, etc.)
• Creating developer-friendly API documentation
• Optimizing APIs for specific use cases (mobile, third-party integrations)

Core Concepts

1. RESTful Design Principles

**Resource-Oriented Architecture**

• Resources are nouns (users, orders, products), not verbs
• Use HTTP methods for actions (GET, POST, PUT, PATCH, DELETE)
• URLs represent resource hierarchies
• Consistent naming conventions

**HTTP Methods Semantics:**

• `GET`: Retrieve resources (idempotent, safe)
• `POST`: Create new resources
• `PUT`: Replace entire resource (idempotent)
• `PATCH`: Partial resource updates
• `DELETE`: Remove resources (idempotent)

2. GraphQL Design Principles

**Schema-First Development**

• Types define your domain model
• Queries for reading data
• Mutations for modifying data
• Subscriptions for real-time updates

**Query Structure:**

• Clients request exactly what they need
• Single endpoint, multiple operations
• Strongly typed schema
• Introspection built-in

3. API Versioning Strategies

**URL Versioning:**

/api/v1/users
/api/v2/users

**Header Versioning:**

Accept: application/vnd.api+json; version=1

**Query Parameter Versioning:**

/api/users?version=1

REST API Design Patterns

Pattern 1: Resource Collection Design

# Good: Resource-oriented endpoints
GET    /api/users              # List users (with pagination)
POST   /api/users              # Create user
GET    /api/users/{id}         # Get specific user
PUT    /api/users/{id}         # Replace user
PATCH  /api/users/{id}         # Update user fields
DELETE /api/users/{id}         # Delete user

# Nested resources
GET    /api/users/{id}/orders  # Get user's orders
POST   /api/users/{id}/orders  # Create order for user

# Bad: Action-oriented endpoints (avoid)
POST   /api/createUser
POST   /api/getUserById
POST   /api/deleteUser

Pattern 2: Pagination and Filtering

from typing import List, Optional
from pydantic import BaseModel, Field

class PaginationParams(BaseModel):
    page: int = Field(1, ge=1, description="Page number")
    page_size: int = Field(20, ge=1, le=100, description="Items per page")

class FilterParams(BaseModel):
    status: Optional[str] = None
    created_after: Optional[str] = None
    search: Optional[str] = None

class PaginatedResponse(BaseModel):
    items: List[dict]
    total: int
    page: int
    page_size: int
    pages: int

    @property
    def has_next(self) -> bool:
        return self.page < self.pages

    @property
    def has_prev(self) -> bool:
        return self.page > 1

# FastAPI endpoint example
from fastapi import FastAPI, Query, Depends

app = FastAPI()

@app.get("/api/users", response_model=PaginatedResponse)
async def list_users(
    page: int = Query(1, ge=1),
    page_size: int = Query(20, ge=1, le=100),
    status: Optional[str] = Query(None),
    search: Optional[str] = Query(None)
):
    # Apply filters
    query = build_query(status=status, search=search)

    # Count total
    total = await count_users(query)

    # Fetch page
    offset = (page - 1) * page_size
    users = await fetch_users(query, limit=page_size, offset=offset)

    return PaginatedResponse(
        items=users,
        total=total,
        page=page,
        page_size=page_size,
        pages=(total + page_size - 1) // page_size
    )

Pattern 3: Error Handling and Status Codes

from fastapi import HTTPException, status
from pydantic import BaseModel

class ErrorResponse(BaseModel):
    error: str
    message: str
    details: Optional[dict] = None
    timestamp: str
    path: str

class ValidationErrorDetail(BaseModel):
    field: str
    message: str
    value: Any

# Consistent error responses
STATUS_CODES = {
    "success": 200,
    "created": 201,
    "no_content": 204,
    "bad_request": 400,
    "unauthorized": 401,
    "forbidden": 403,
    "not_found": 404,
    "conflict": 409,
    "unprocessable": 422,
    "internal_error": 500
}

def raise_not_found(resource: str, id: str):
    raise HTTPException(
        status_code=status.HTTP_404_NOT_FOUND,
        detail={
            "error": "NotFound",
            "message": f"{resource} not found",
            "details": {"id": id}
        }
    )

def raise_validation_error(errors: List[ValidationErrorDetail]):
    raise HTTPException(
        status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
        detail={
            "error": "ValidationError",
            "message": "Request validation failed",
            "details": {"errors": [e.dict() for e in errors]}
        }
    )

# Example usage
@app.get("/api/users/{user_id}")
async def get_user(user_id: str):
    user = await fetch_user(user_id)
    if not user:
        raise_not_found("User", user_id)
    return user

Pattern 4: HATEOAS (Hypermedia as the Engine of Application State)

class UserResponse(BaseModel):
    id: str
    name: str
    email: str
    _links: dict

    @classmethod
    def from_user(cls, user: User, base_url: str):
        return cls(
            id=user.id,
            name=user.name,
            email=user.email,
            _links={
                "self": {"href": f"{base_url}/api/users/{user.id}"},
                "orders": {"hre