Field validation rules in FastAPI - Mini Project: Build & Apply

Field validation rules

📖 Scenario: You are building a simple API to register users. You want to make sure the data sent by users follows certain rules to keep your app safe and clean.

🎯 Goal: Create a FastAPI app with a user registration endpoint that validates the user's name, age, and email using field validation rules.

📋 What You'll Learn

Create a Pydantic model called User with fields name, age, and email

Add validation rules: name must be a string with minimum length 3, age must be an integer between 18 and 100, email must be a valid email address

Create a POST endpoint /register that accepts a User object

Return the user data if validation passes

💡 Why This Matters

🌍 Real World

APIs often need to check that incoming data is correct and safe before using it. Field validation helps catch mistakes early and improves user experience.

💼 Career

Backend developers use FastAPI and Pydantic to build reliable APIs with automatic data validation, which is a key skill in web development jobs.

1

Create the User model with fields

Create a Pydantic model called User with fields name as str, age as int, and email as str.

FastAPI

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

# Create User model with name, age, email fields
# Your code here

Hint

Use class User(BaseModel): and define the fields with their types inside.

2

Add validation rules to User model fields

Add validation rules to the User model: name must have min_length=3, age must be between 18 and 100, and email must be a valid email using EmailStr from pydantic.

FastAPI

from fastapi import FastAPI
from pydantic import BaseModel, EmailStr, Field

app = FastAPI()

class User(BaseModel):
    # Add validation rules here
    name: str = Field(..., min_length=3)
    age: int = Field(..., ge=18, le=100)
    email: EmailStr

# Your code here

Hint

Use Field to add min_length for name and ge, le for age. Use EmailStr type for email.

3

Create the POST /register endpoint

Create a POST endpoint /register that accepts a User object as input parameter called user.

FastAPI

from fastapi import FastAPI
from pydantic import BaseModel, EmailStr, Field

app = FastAPI()

class User(BaseModel):
    name: str = Field(..., min_length=3)
    age: int = Field(..., ge=18, le=100)
    email: EmailStr

@app.post("/register")
async def register(user: User):
    # Your code here

Hint

Use @app.post("/register") decorator and define an async function register with parameter user: User. Return the user object.

4

Complete the FastAPI app with validation

Ensure the FastAPI app is complete with the User model and the /register endpoint that returns the validated user data.

FastAPI

from fastapi import FastAPI
from pydantic import BaseModel, EmailStr, Field

app = FastAPI()

class User(BaseModel):
    name: str = Field(..., min_length=3)
    age: int = Field(..., ge=18, le=100)
    email: EmailStr

@app.post("/register")
async def register(user: User):
    return user

# The app is complete

Hint

Check that the model and endpoint are defined and the endpoint returns the user data.

Practice

1. What is the purpose of using Field with parameters like min_length or ge in FastAPI models?

easy

A. To validate and restrict input data before processing

B. To format the output data after processing

C. To create database tables automatically

D. To handle HTTP request routing

Solution

1. Step 1: Understand Field usage in FastAPI

   Field is used to define extra validation rules on model fields.

2. Step 2: Recognize validation purpose

   Parameters like min_length or ge ensure input data meets conditions before API logic runs.

3. Final Answer:

   To validate and restrict input data before processing -> Option A

4. Quick Check:

   Field validation = Input data check [OK]

Hint: Field with min_length or ge always validates input data [OK]

Common Mistakes:

• Confusing validation with output formatting
• Thinking Field creates database tables
• Assuming Field controls routing

2. Which of the following is the correct way to enforce a string field to have at least 3 characters using FastAPI's Field?

easy

A. name: str = Field(length_min=3)

B. name: str = Field(min_length=3)

C. name: str = Field(min=3)

D. name: str = Field(minsize=3)

Solution

1. Step 1: Recall correct parameter name for minimum length

   FastAPI uses min_length to set minimum string length.

2. Step 2: Match option with correct syntax

   name: str = Field(min_length=3) uses min_length=3, which is correct syntax.

3. Final Answer:

   name: str = Field(min_length=3) -> Option B

4. Quick Check:

   min_length = min_length [OK]

Hint: Use min_length for strings, not min or length_min [OK]

Common Mistakes:

• Using incorrect parameter names like min or length_min
• Confusing min_length with min for numbers
• Misspelling parameter names

3. Given this FastAPI model snippet:

from pydantic import BaseModel, Field

class User(BaseModel):
    age: int = Field(ge=18, le=65)

user = User(age=70)

What will happen when creating user?

medium

A. An error is raised because age is greater than 65

B. User instance is created with age 70 without error

C. Age is automatically set to 65

D. Age is ignored and set to default 0

Solution

1. Step 1: Understand ge and le constraints

   ge=18 means age must be >=18, le=65 means age must be <=65.

2. Step 2: Check provided age value

   Age 70 is greater than 65, violating the le constraint.

3. Step 3: FastAPI/Pydantic behavior on violation

   It raises a validation error when constraints are not met.

4. Final Answer:

   An error is raised because age is greater than 65 -> Option A

5. Quick Check:

   ge/le constraints cause error if violated [OK]

Hint: ge and le set min/max values; violation raises error [OK]

Common Mistakes:

• Assuming values auto-correct to limits
• Thinking invalid values are ignored
• Confusing ge/le with min_length/max_length

4. Identify the error in this FastAPI model field validation:

from pydantic import BaseModel, Field

class Product(BaseModel):
    code: str = Field(regex="[A-Z]{3}[0-9]{4}")

product = Product(code="abC1234")

medium

A. The code field should be an integer, not string

B. Field does not support regex parameter

C. The regex pattern is case-sensitive and input does not match

D. Missing default value for code field

Solution

1. Step 1: Analyze regex pattern

   Pattern requires exactly 3 uppercase letters followed by 4 digits.

2. Step 2: Check input against pattern

   Input "abC1234" has lowercase letters and does not fully match pattern.

3. Step 3: Understand validation result

   Regex is case-sensitive by default, so input fails validation causing error.

4. Final Answer:

   The regex pattern is case-sensitive and input does not match -> Option C

5. Quick Check:

   Regex is case-sensitive unless flagged [OK]

Hint: Regex in Field is case-sensitive by default [OK]

Common Mistakes:

• Assuming regex ignores case without flags
• Thinking Field does not accept regex
• Confusing data types for fields

5. You want to create a FastAPI model for a username that must be 5 to 10 characters long, only letters and digits allowed, and must start with a letter. Which Field validation is correct?

hard

A. username: str = Field(min_length=5, max_length=10, regex='^[0-9][a-zA-Z0-9]*$')

B. username: str = Field(min_length=5, max_length=10, regex='^[a-zA-Z]{5,10}$')

C. username: str = Field(min_length=5, max_length=10, regex='^[a-zA-Z0-9]{5,10}$')

D. username: str = Field(min_length=5, max_length=10, regex='^[a-zA-Z][a-zA-Z0-9]*$')

Solution

1. Step 1: Check length constraints

   min_length=5 and max_length=10 ensure username length between 5 and 10.

2. Step 2: Analyze regex pattern

   Regex '^[a-zA-Z][a-zA-Z0-9]*$' means username starts with a letter, followed by letters or digits.

3. Step 3: Verify other options

   Options starting with a digit are incorrect. Options using regex '^[a-zA-Z0-9]{5,10}$' allow starting with digits. Options using '^[a-zA-Z]{5,10}$' exclude digits.

4. Final Answer:

   username: str = Field(min_length=5, max_length=10, regex='^[a-zA-Z][a-zA-Z0-9]*$') -> Option D

5. Quick Check:

   Start letter + length + allowed chars = username: str = Field(min_length=5, max_length=10, regex='^[a-zA-Z][a-zA-Z0-9]*$') [OK]

Hint: Start letter regex: ^[a-zA-Z], then allowed chars [OK]

Common Mistakes:

• Allowing username to start with digit
• Not enforcing length limits
• Using regex that excludes digits or letters incorrectly