BaseModel

Learn to define models with pydantic.BaseModel.

BaseModel

pydantic.BaseModel is the base class for data models. You derive a class, give types to fields; Pydantic validates the data and converts it automatically.

from pydantic import BaseModel

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

u = User(name="Ayşe", age=30)
print(u.name, u.age)  # Ayşe 30

Wrong types raise a Pydantic error. You can also build a model from a dict; a missing field still raises an error.

Fields and types

Each field is defined with a type: str, int, float, bool, list and so on. Pydantic tries to convert data to this type; if it cannot, it raises.

class User(BaseModel):
    name: str
    age: int
    active: bool

u = User(name="Ayşe", age="30", active=True)
print(u.age)  # 30 (converted to int)

This is useful when the data source is untrusted; for example, strings from a form are turned into integers automatically.

Exercise Create a User model

Start with from pydantic import BaseModel. Define class User(BaseModel): with fields name: str and age: int. Create an instance with u = User(name="Ayşe", age=30). Print the values with print(u.name, u.age).

Show example solution

from pydantic import BaseModel

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

u = User(name="Ayşe", age=30)
print(u.name, u.age)

Test yourself

What happens if you omit a field in a model derived from BaseModel?
- The field becomes None
- An error is raised
- The field becomes an empty string
- A warning is issued but it continues
Show answer

An error is raised — A missing required field raises a Pydantic error.

Complete the BaseModel derivation

from pydantic import BaseModel

class User(____):
    name: str
    age: int

Show answer

from pydantic import BaseModel

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

Match the BaseModel concepts

BaseModel

Is the base class
name: str

Is a field definition
User(name=, age=)

Creates an instance
u.name

Is the field value

Next lesson: Field

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