Panduan Lengkap Menggunakan Pydantic: Data Validation Made Easy

Pydantic adalah library Python yang powerful untuk data validation dan settings management menggunakan Python type hints. Library ini sangat populer di ekosistem Python modern, terutama digunakan oleh FastAPI, dan menjadi standar de-facto untuk validasi data.

Dalam tutorial ini, kita akan mempelajari Pydantic dari dasar hingga advanced usage dengan contoh praktis.

Mengapa Pydantic?

Keunggulan Pydantic:

Instalasi

Install Pydantic v2 (Latest)

# Install Pydantic v2
pip install pydantic

Install dengan email validation
pip install "pydantic[email]"

Install dengan dotenv support
pip install "pydantic-settings"

Verifikasi Instalasi

import pydantic
print(f"Pydantic version: {pydantic.version}")

Should print 2.x.x

Basic Usage: Model Pertama Anda

1. Simple Model

from pydantic import BaseModel

class User(BaseModel):
    id: int
    name: str
    email: str
    age: int

Create instance
user = User(id=1, name="Ruby", email="ruby@rubythalib.ai", age=25)

print(user)
Output: id=1 name='Ruby' email='ruby@rubythalib.ai' age=25

print(user.modeldump())

Output: {'id': 1, 'name': 'Ruby', 'email': 'ruby@rubythalib.ai', 'age': 25}

from pydantic import BaseModel

class Product(BaseModel):
    id: int
    name: str
    price: float
    instock: bool

String akan di-convert ke int dan float
product = Product(
    id="123",           # String -> int
    name="Laptop",
    price="15000000",   # String -> float
    instock="yes"      # String -> bool

)

print(product.id, type(product.id))
Output: 123 

print(product.price, type(product.price))
Output: 15000000.0 

print(product.instock, type(product.instock))

Output: True 

from pydantic import BaseModel, ValidationError

class User(BaseModel):
    id: int
    name: str
    age: int

try:
    user = User(id="notanumber", name="Ruby", age=25)

except ValidationError as e:
    print(e)
    # Akan print error detail tentang invalid id

1 validation error for User
id
  Input should be a valid integer, unable to parse string as an integer [type=intparsing, inputvalue='notanumber', inputtype=str]

Field Types dan Constraints

1. Optional Fields

from typing import Optional
from pydantic import BaseModel

class User(BaseModel):
    id: int
    name: str
    email: Optional[str] = None  # Optional dengan default None
    phone: str | None = None     # Python 3.10+ syntax

user1 = User(id=1, name="Ruby")
print(user1.email)  # None

user2 = User(id=2, name="Ahmad", email="ahmad@example.com")
print(user2.email)  # ahmad@example.com

2. Default Values

from pydantic import BaseModel

class Product(BaseModel):
    id: int
    name: str
    price: float = 0.0
    category: str = "General"
    instock: bool = True


product = Product(id=1, name="Notebook")
print(product.modeldump())
{'id': 1, 'name': 'Notebook', 'price': 0.0, 'category': 'General', 'instock': True}

from pydantic import BaseModel, Field

class User(BaseModel):