2nd/10_Wiki/Topics/AI_and_ML/Schema.md

---
id: wiki-2026-0508-schema
title: Schema
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: [Data Schema, Schema Definition]
duplicate_of: none
source_trust_level: A
confidence_score: 0.9
verification_status: applied
tags: [schema, validation, zod, json-schema, database]
raw_sources: []
last_reinforced: 2026-05-10
github_commit: pending
tech_stack:
  language: TypeScript
  framework: Zod 4
---

# Schema

## 매 한 줄
> **"매 schema 는 data 의 contract — 매 runtime + compile-time 양쪽에서 enforce"**. 매 origin 은 1970s relational DB DDL; 매 modern state 는 Zod 4 (TS-first, runtime + types), JSON Schema 2020-12, Schema.org (web), Avro/Protobuf (wire), Postgres 17 declarative migration.

## 매 핵심

### 매 schema layer (매 stack 별)
- **DB schema**: DDL (Postgres `CREATE TABLE`), constraints, indexes.
- **Wire schema**: Protobuf, Avro, JSON Schema — 매 inter-service contract.
- **App-runtime schema**: Zod, Pydantic, Valibot — 매 API boundary 의 validation.
- **Web schema**: Schema.org JSON-LD — 매 SEO + semantic web.
- **AI schema**: 매 LLM structured output (OpenAI structured outputs, Anthropic tool use schema).

### 매 Zod 4 의 modern 위치 (2026)
- 매 single source of truth → infer TS type + runtime validate + JSON Schema 변환.
- v4 (2026) 의 major: pure-ESM, smaller bundle, sync error throw, `.brand()` first-class.

### 매 응용
1. API request/response validation (Hono, tRPC, Next.js Route Handler).
2. Form validation (React Hook Form + Zod resolver).
3. LLM structured output (Anthropic tool schema, function calling).
4. Config validation (env vars at boot).

## 💻 패턴

### 매 Zod 4 schema → TS type infer
```ts
import { z } from "zod";

export const UserSchema = z.object({
  id: z.string().uuid(),
  email: z.string().email(),
  age: z.number().int().min(0).max(150),
  role: z.enum(["admin", "user", "guest"]),
  createdAt: z.date(),
});

export type User = z.infer<typeof UserSchema>;
// → { id: string; email: string; age: number; role: "admin"|"user"|"guest"; createdAt: Date }

const parsed = UserSchema.parse(rawJson);  // 매 throw on invalid
const safe = UserSchema.safeParse(rawJson); // 매 { success, data | error }
```

### 매 Zod → JSON Schema (LLM structured output)
```ts
import { z } from "zod";
import { zodToJsonSchema } from "zod-to-json-schema";

const ExtractedInvoice = z.object({
  vendor: z.string(),
  total: z.number(),
  lineItems: z.array(z.object({
    desc: z.string(),
    qty: z.number().int(),
    unitPrice: z.number(),
  })),
});

const jsonSchema = zodToJsonSchema(ExtractedInvoice);
// 매 Anthropic tool input_schema 에 그대로 사용
```

### 매 Anthropic tool use (Claude Opus 4.7 structured output)
```python
import anthropic
client = anthropic.Anthropic()

resp = client.messages.create(
    model="claude-opus-4-7",
    max_tokens=2048,
    tools=[{
        "name": "extract_invoice",
        "description": "Extract structured invoice data",
        "input_schema": {
            "type": "object",
            "properties": {
                "vendor": {"type": "string"},
                "total": {"type": "number"},
                "line_items": {
                    "type": "array",
                    "items": {
                        "type": "object",
                        "properties": {
                            "desc": {"type": "string"},
                            "qty": {"type": "integer"},
                            "unit_price": {"type": "number"},
                        },
                        "required": ["desc", "qty", "unit_price"],
                    },
                },
            },
            "required": ["vendor", "total", "line_items"],
        },
    }],
    tool_choice={"type": "tool", "name": "extract_invoice"},
    messages=[{"role": "user", "content": invoice_text}],
)
# resp.content[0].input → 매 schema-validated dict
```

### 매 Postgres 17 declarative schema (with constraints)
```sql
CREATE TABLE users (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  email TEXT NOT NULL UNIQUE CHECK (email ~ '^[^@]+@[^@]+$'),
  age INT NOT NULL CHECK (age >= 0 AND age <= 150),
  role TEXT NOT NULL CHECK (role IN ('admin','user','guest')),
  created_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);

CREATE INDEX idx_users_email_lower ON users (LOWER(email));
CREATE INDEX idx_users_role_created ON users (role, created_at DESC);
```

### 매 Schema.org JSON-LD (SEO, 매 Article)
```html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Modern Schema Validation in 2026",
  "author": {"@type": "Person", "name": "Jane Doe"},
  "datePublished": "2026-05-10",
  "image": "https://example.com/cover.jpg"
}
</script>
```

### 매 Pydantic v2 (Python, 매 FastAPI 와 함께)
```python
from pydantic import BaseModel, EmailStr, Field
from typing import Literal

class User(BaseModel):
    id: str
    email: EmailStr
    age: int = Field(ge=0, le=150)
    role: Literal["admin", "user", "guest"]

# FastAPI route — 매 자동 OpenAPI + validation
@app.post("/users")
def create_user(user: User) -> User:
    return user
```

### 매 schema migration (Drizzle, TS 2026)
```ts
// schema.ts — 매 source of truth
import { pgTable, uuid, text, integer, timestamp } from "drizzle-orm/pg-core";

export const users = pgTable("users", {
  id: uuid("id").primaryKey().defaultRandom(),
  email: text("email").notNull().unique(),
  age: integer("age").notNull(),
  role: text("role", { enum: ["admin","user","guest"] }).notNull(),
  createdAt: timestamp("created_at").notNull().defaultNow(),
});

// $ drizzle-kit generate  → 매 SQL migration auto
// $ drizzle-kit migrate
```

## 매 결정 기준
| 상황 | Approach |
|---|---|
| 매 TS API boundary | Zod 4 |
| 매 Python API | Pydantic v2 |
| 매 cross-language wire | Protobuf / Avro |
| 매 LLM structured output | JSON Schema (via Zod/Pydantic) |
| 매 SEO web page | Schema.org JSON-LD |
| 매 RDB | Postgres DDL + Drizzle/Prisma migration |

**기본값**: TS 면 Zod 4 (single source → type + runtime + JSON Schema).

## 🔗 Graph
- 부모: [[TypeScript 타입 시스템 (TypeScript Type System)|Type System]] · [[Validation]]
- 변형: [[Zod]] · [[JSON Schema]] · [[Protobuf]]
- 응용: [[API Design]]
- Adjacent: [[OpenAPI]]

## 🤖 LLM 활용
**언제**: 매 LLM structured output 강제 (tool use input_schema). 매 unstructured text → typed object extraction.
**언제 X**: 매 schema 자체의 design — 매 domain modeling 은 human 의 일.

## ❌ 안티패턴
- **`z.any()` everywhere**: 매 schema 의 의미 X.
- **Schema drift**: API schema 와 DB schema 가 따로 → 매 single source 필요.
- **Over-validation in hot path**: 매 매 request 마다 deep validate → 매 boundary 만 validate.
- **Stringly-typed enums**: 매 `z.string()` for role → 매 `z.enum()` 으로 narrow.

## 🧪 검증 / 중복
- Verified (Zod docs v4, JSON Schema 2020-12 spec, Schema.org, Postgres 17 docs).
- 신뢰도 A.

## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — Zod 4 + Pydantic v2 + LLM tool schema + Drizzle |