Example data in schema in FastAPI - Mini Project: Build & Apply

Example Data in Schema with FastAPI

📖 Scenario: You are building a simple API to share information about books. You want to make sure that when someone looks at the API documentation, they see example data for each book. This helps users understand what kind of information they can send or receive.

🎯 Goal: Create a FastAPI app with a Book schema that includes example data. This example data will show up in the API docs automatically.

📋 What You'll Learn

Create a Pydantic model called Book with fields title (string), author (string), and year (integer).

Add example data to the Book schema using Config.schema_extra.

Create a FastAPI app instance called app.

Add a POST endpoint /books/ that accepts a Book object.

💡 Why This Matters

🌍 Real World

APIs often show example data in their documentation to help developers understand how to use them. This project shows how to add that example data in FastAPI.

💼 Career

Knowing how to define schemas with example data is important for backend developers building APIs that are easy to use and well documented.

1

Create the Book schema

Create a Pydantic model called Book with these exact fields: title as a string, author as a string, and year as an integer.

FastAPI

# Your code here to create the Book model
from pydantic import BaseModel

Hint

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

2

Add example data to the Book schema

Inside the Book model, add a nested Config class with a schema_extra dictionary. Add an example key with this exact data: {"title": "The Great Gatsby", "author": "F. Scott Fitzgerald", "year": 1925}.

FastAPI

from pydantic import BaseModel

class Book(BaseModel):
    title: str
    author: str
    year: int

    # Add Config class with example data here

Hint

Define a nested Config class inside Book and add schema_extra with the example dictionary.

3

Create the FastAPI app instance

Import FastAPI and create an app instance called app.

FastAPI

from pydantic import BaseModel
from fastapi import FastAPI

class Book(BaseModel):
    title: str
    author: str
    year: int

    class Config:
        schema_extra = {
            "example": {
                "title": "The Great Gatsby",
                "author": "F. Scott Fitzgerald",
                "year": 1925
            }
        }

# Create FastAPI app instance here

Hint

Import FastAPI and create app = FastAPI().

4

Add POST endpoint to accept Book data

Add a POST endpoint at /books/ using @app.post("/books/"). The function should be called create_book and accept a parameter book of type Book. Return the book object.

FastAPI

from pydantic import BaseModel
from fastapi import FastAPI

class Book(BaseModel):
    title: str
    author: str
    year: int

    class Config:
        schema_extra = {
            "example": {
                "title": "The Great Gatsby",
                "author": "F. Scott Fitzgerald",
                "year": 1925
            }
        }

app = FastAPI()

# Add POST endpoint here

Hint

Use @app.post("/books/") decorator and define an async function create_book that takes book: Book and returns it.

Practice

1. What is the main purpose of adding example data in a FastAPI schema field?

easy

A. To automatically generate database tables

B. To validate the data type of the field at runtime

C. To encrypt the field data before sending

D. To show sample values for API fields to help users understand expected data

Solution

1. Step 1: Understand the role of example data in FastAPI

   Example data is used to provide sample values in API documentation, helping users know what to send or expect.

2. Step 2: Differentiate example data from validation or encryption

   Example data does not validate or encrypt; it only shows sample values in docs.

3. Final Answer:

   To show sample values for API fields to help users understand expected data -> Option D

4. Quick Check:

   Example data = sample values [OK]

Hint: Example data shows sample values in docs, not validation [OK]

Common Mistakes:

• Confusing example with validation
• Thinking example encrypts data
• Assuming example creates database schema

2. Which of the following is the correct way to add example data to a Pydantic model field in FastAPI?

easy

A. name: str = Field(example="John Doe")

B. name: str = Field(default="John Doe")

C. name: str = Field(description="John Doe")

D. name: str = Field(required=True)

Solution

1. Step 1: Recall the Field syntax for example data

   FastAPI uses Field(..., example=...) to add example data to schema fields.

2. Step 2: Identify the correct option

   name: str = Field(example="John Doe") uses Field(example="John Doe"), which is the correct syntax for example data.

3. Final Answer:

   name: str = Field(example="John Doe") -> Option A

4. Quick Check:

   Field(example=...) = correct syntax [OK]

Hint: Use Field(example=...) to add example data [OK]

Common Mistakes:

• Using default instead of example
• Confusing description with example
• Omitting Field() entirely

3. Given this Pydantic model in FastAPI:

from pydantic import BaseModel, Field

class User(BaseModel):
    username: str = Field(..., example="alice123")
    age: int = Field(..., example=30)

What example data will appear in the OpenAPI docs for the age field?

medium

A. "30"

B. 30

C. None

D. 0

Solution

1. Step 1: Check the example value assigned to the age field

   The age field has example=30, which is an integer value 30.

2. Step 2: Understand how example data is shown in docs

   FastAPI shows the example exactly as given, so the example for age will be 30 (integer).

3. Final Answer:

   30 -> Option B

4. Quick Check:

   Example for age = 30 [OK]

Hint: Example shows exact value given in Field(example=...) [OK]

Common Mistakes:

• Thinking example converts int to string
• Assuming example is None if not set
• Confusing example with default value

4. Identify the error in this FastAPI Pydantic model using example data:

from pydantic import BaseModel, Field

class Item(BaseModel):
    name: str = Field(example=123)
    price: float = Field(..., example="9.99")

medium

A. Example for name should be a string, not an integer

B. Missing default value for name field

C. Example for price should be a float, not a string

D. Field(...) is missing for name field

Solution

1. Step 1: Check example data types against field types

   The name field is str but example=123 (int) is allowed but not ideal; price is float but example="9.99" is a string, which is incorrect.

2. Step 2: Identify the type mismatch causing error

   Example for price should be a float (9.99), not a string "9.99"; this can cause schema confusion.

3. Final Answer:

   Example for price should be a float, not a string -> Option C

4. Quick Check:

   Example type must match field type [OK]

Hint: Match example type to field type exactly [OK]

Common Mistakes:

• Using string example for numeric fields
• Ignoring type mismatch warnings
• Omitting Field(...) for required fields

5. You want to create a FastAPI schema for a product with a nested model and provide example data for both levels. Which is the correct way to add example data for nested fields?

hard

A. Use example in Field() for each nested field separately

B. Add example data only to the top-level model, nested fields inherit automatically

C. Use example only in the nested model class, not in the parent

D. Example data cannot be added to nested models in FastAPI

Solution

1. Step 1: Understand example data usage in nested models

   Each field in nested models needs its own example data using Field(example=...) to show correct samples in docs.

2. Step 2: Confirm nested fields do not inherit example data

   Example data is not inherited; you must specify it explicitly for each nested field.

3. Final Answer:

   Use example in Field() for each nested field separately -> Option A

4. Quick Check:

   Example data must be set per field [OK]

Hint: Add example=... to every nested field explicitly [OK]

Common Mistakes:

• Assuming nested fields inherit example data
• Skipping example in nested models
• Thinking example data is only for top-level fields