Pydantic model definition in FastAPI - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a Pydantic model in FastAPI?

A Pydantic model is a Python class used to define data shapes and validate data automatically. It helps FastAPI check and convert incoming data to the right types.

beginner

How do you define a simple Pydantic model with a name (string) and age (integer)?

You create a class that inherits from BaseModel and add attributes with types, like this:<br><pre>from pydantic import BaseModel

class Person(BaseModel):
    name: str
    age: int</pre>

beginner

What happens if data sent to a Pydantic model does not match the expected type?

Pydantic raises a validation error. FastAPI will return a clear error message to the user explaining what is wrong with the data.

intermediate

Can Pydantic models have default values? How?

Yes. You assign a default value to the attribute in the class. For example:<br><pre>class Person(BaseModel):
    name: str
    age: int = 30  # default age</pre>

beginner

Why use Pydantic models in FastAPI instead of plain Python dictionaries?

Pydantic models automatically check data types, convert data, and provide clear error messages. This makes your API safer and easier to maintain.

Which base class do you inherit from to create a Pydantic model?

A BaseModel

B ModelBase

C DataModel

D PydanticBase

Pydantic models always inherit from BaseModel to get validation and parsing features.

What type of error does Pydantic raise if data is invalid?

A ValueError

B TypeError

C ValidationError

D SyntaxError

Pydantic raises ValidationError when data does not match the model's expected types.

How do you specify a default value for a field in a Pydantic model?

A Assign it directly in the class attribute

B Use a decorator

C Set it in the constructor

D Use a separate config file

Default values are set by assigning them directly to the class attribute.

Which of these is a valid Pydantic model field declaration?

A age = int: 25

B age: int = 25

C int age = 25

D age: 'int' = '25'

The correct syntax is 'field_name: type = default_value'.

What benefit does Pydantic provide in FastAPI?

A Automatic HTML rendering

B Faster database queries

C Improved CSS styling

D Automatic data validation and conversion

Pydantic helps FastAPI by validating and converting data automatically.

Explain how to create a Pydantic model for a user with email (string) and is_active (boolean) fields.

Think about class syntax and type annotations.

Describe what happens when FastAPI receives data that does not match a Pydantic model's expected types.

Focus on validation and error handling.