Field types and constraints in FastAPI - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ component_behavior

intermediate

What is the output of this FastAPI endpoint with constrained fields?

Consider this FastAPI model and endpoint. What will be the response when sending {"age": 25, "name": "Anna"}?

FastAPI

from fastapi import FastAPI
from pydantic import BaseModel, Field

app = FastAPI()

class User(BaseModel):
    name: str = Field(min_length=3, max_length=10)
    age: int = Field(gt=18, lt=30)

@app.post("/user")
async def create_user(user: User):
    return {"message": f"User {user.name} aged {user.age} created"}

A 422 Unprocessable Entity error due to name length

B 422 Unprocessable Entity error due to age constraint

C {"message": "User Anna aged 25 created"}

D 500 Internal Server Error

💡 Hint

Check the constraints on name and age fields carefully.

The name "Anna" has length 4, which is between 3 and 10. The age 25 is greater than 18 and less than 30. So the input passes validation and the endpoint returns the success message.

📝 Syntax

intermediate

Which option correctly defines a constrained string field in FastAPI?

You want a string field 'title' that must be at least 5 characters and at most 20 characters. Which code snippet is correct?

A title: str = Field(size=(5,20))

B title: str = Field(length=(5,20))

C title: str = Field(min=5, max=20)

D title: str = Field(min_length=5, max_length=20)

💡 Hint

Look for the correct parameter names for string length constraints in Pydantic Field.

The correct parameters for string length constraints are min_length and max_length. Other options use invalid parameter names.

🔧 Debug

advanced

Why does this FastAPI model raise a validation error for input {"score": 101}?

Given this model, why does sending {"score": 101} cause a validation error?

FastAPI

from pydantic import BaseModel, Field

class Result(BaseModel):
    score: int = Field(ge=0, le=100)

A Because score must be a string, not an int

B Because 101 is greater than the maximum allowed value 100

C Because Field does not support ge and le parameters

D Because 101 is less than the minimum allowed value 0

💡 Hint

Check the meaning of ge and le parameters in Field.

The parameters ge=0 and le=100 mean the value must be between 0 and 100 inclusive. 101 is outside this range, so validation fails.

❓ state_output

advanced

What is the value of 'user' after parsing this input with the model?

Given this model and input, what will be the value of the 'user' variable?

FastAPI

from pydantic import BaseModel, Field

class User(BaseModel):
    username: str = Field(min_length=3, max_length=8)
    active: bool = Field(default=True)

input_data = {"username": "bob"}
user = User(**input_data)

A User(username='bob', active=True)

B User(username='bob', active=False)

C ValidationError due to missing 'active' field

D User(username='bob') without 'active' attribute

💡 Hint

Check the default value of the 'active' field.

The 'active' field has a default value of True, so if not provided, it will be set to True automatically.

🧠 Conceptual

expert

Which statement about FastAPI field constraints is TRUE?

Select the correct statement about using Field constraints in FastAPI models.

A Field constraints like min_length and gt are enforced at runtime during request validation.

B Field constraints only affect the OpenAPI schema but do not validate input data.

C Field constraints can only be applied to string fields, not numbers.

D Field constraints automatically convert invalid input to the nearest valid value.

💡 Hint

Think about when and how Pydantic validates data in FastAPI.

Field constraints are enforced by Pydantic during runtime validation of incoming data, rejecting invalid inputs with errors.