What data can be validated using Pydantic?

Pydantic allows validation of the following data types:

• Standard Python types: int, float, str, bool, list, dict, tuple, set, bytes, bytearray.
• Nested Pydantic models: Enables creating complex structures.
• Enumerations (Enums): Restricts possible values to a predefined set.
• Dates and times: datetime, date, time, timedelta.
• UUIDs: For globally unique identifiers.
• URL: With format validation.
• IPv4/IPv6 addresses: With format validation.
• Email addresses: With basic format validation.
• Types from the typing module: Optional, Union, Literal, Final, Annotated, and others.
• Custom types: By defining validators.

Validation example:

from pydantic import BaseModel, Field, EmailStr
from typing import List, Optional
from datetime import date

class User(BaseModel):
    user_id: int = Field(gt=0) // Integer greater than 0
    username: str = Field(min_length=3) // String with minimum 3 characters
    email: EmailStr // Valid email string
    is_active: bool = True // Boolean (default True)
    registration_date: date // Date
    tags: Optional[List[str]] = None // Optional list of strings

class Product(BaseModel):
    product_id: int
    name: str
    price: float = Field(ge=0) // Number with decimal, greater than or equal to 0