pydantic — Easy Playground

Data validation using Python type annotations; settings management

Getting started with pydanticRun locally

Install

pip install pydantic

Python CodeRun locally

# Install: pip install pydantic
from pydantic import BaseModel, field_validator

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

    @field_validator("age")
    @classmethod
    def validate_age(cls, v):
        if v < 0 or v > 150:
            raise ValueError("Invalid age")
        return v

user = User(name="Alice", age=30, email="alice@example.com")
print(user.model_dump())

# Install: pip install pydantic
from pydantic import BaseModel, field_validator

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

    @field_validator("age")
    @classmethod
    def validate_age(cls, v):
        if v < 0 or v > 150:
            raise ValueError("Invalid age")
        return v

user = User(name="Alice", age=30, email="alice@example.com")
print(user.model_dump())

Expected Output

# Expected output shown below
# (Run locally with: pydantic)

pydantic is a third-party package. Data validation using Python type annotations; settings management. Install with: pip install pydantic

Challenge

Try modifying the code above to explore different behaviors. Can you extend the example to handle a new use case?

View all Easy examples for pydantic