List and set validation in FastAPI - Mini Project: Build & Apply

List and Set Validation with FastAPI

📖 Scenario: You are building a simple FastAPI app that accepts user input for favorite fruits. You want to make sure the input is a list of fruits and also check if the fruits are unique using a set.

🎯 Goal: Create a FastAPI endpoint that accepts a list of fruits, validates it, and converts it to a set to ensure uniqueness.

📋 What You'll Learn

Create a list variable called fruits with exact values: ['apple', 'banana', 'apple', 'orange']

Create a variable called unique_fruits that converts fruits to a set

Create a FastAPI app instance called app

Create a POST endpoint /fruits that accepts a list of strings called fruits in the request body

💡 Why This Matters

🌍 Real World

Validating lists and sets is common when handling user input in web apps, such as filtering unique items or preferences.

💼 Career

Backend developers often use FastAPI to build APIs that validate and process list data efficiently.

1

Create the initial list of fruits

Create a list variable called fruits with these exact values: ['apple', 'banana', 'apple', 'orange']

FastAPI

# Create the list of fruits
# Your code here

Hint

Use square brackets to create a list and include the fruits exactly as shown.

2

Convert the list to a set for uniqueness

Create a variable called unique_fruits that converts the list fruits to a set using set(fruits)

FastAPI

fruits = ['apple', 'banana', 'apple', 'orange']
# Convert fruits list to a set called unique_fruits
# Your code here

Hint

Use the set() function to remove duplicates from the list.

3

Create a FastAPI app instance

Import FastAPI from fastapi and create an app instance called app using app = FastAPI()

FastAPI

fruits = ['apple', 'banana', 'apple', 'orange']
unique_fruits = set(fruits)
# Import FastAPI and create app instance
# Your code here

Hint

Use from fastapi import FastAPI and then create app = FastAPI().

4

Create a POST endpoint to accept a list of fruits

Create a POST endpoint /fruits using @app.post('/fruits') that accepts a parameter fruits of type list[str] in the request body and returns the set of unique fruits using set(fruits)

FastAPI

from fastapi import FastAPI

fruits = ['apple', 'banana', 'apple', 'orange']
unique_fruits = set(fruits)

app = FastAPI()

# Create POST endpoint /fruits that accepts list[str] fruits and returns set of unique fruits
# Your code here

Hint

Use @app.post('/fruits') decorator and define an async function with parameter fruits: List[str]. Return the unique fruits as a list inside a dictionary.

Practice

1. In FastAPI, when should you use List instead of Set for request data validation?

easy

A. When you want to store only unique items without order

B. When you want to automatically remove duplicates

C. When you want to validate a single item only

D. When the order of items matters and duplicates are allowed

Solution

1. Step 1: Understand List characteristics

   A List keeps the order of items and allows duplicates.

2. Step 2: Compare with Set characteristics

   A Set removes duplicates and does not guarantee order.

3. Final Answer:

   When the order of items matters and duplicates are allowed -> Option D

4. Quick Check:

   List = ordered with duplicates [OK]

Hint: Use List for ordered duplicates, Set for unique unordered [OK]

Common Mistakes:

• Confusing Set with List and expecting order
• Using Set when duplicates are needed
• Thinking List removes duplicates automatically

2. Which of the following is the correct way to declare a FastAPI endpoint expecting a set of integers in the request body?

easy

A. def endpoint(items: List[int]):

B. def endpoint(items: Set[int]):

C. def endpoint(items: dict[int]):

D. def endpoint(items: tuple[int]):

Solution

1. Step 1: Identify the correct type for unique collection

   Set[int] is used to declare a set of integers with unique values.

2. Step 2: Verify other options

   List[int] allows duplicates, dict[int] is invalid syntax, tuple[int] is fixed-length and ordered.

3. Final Answer:

   def endpoint(items: Set[int]): -> Option B

4. Quick Check:

   Set[int] = unique integer collection [OK]

Hint: Use Set[int] for unique integer collections in FastAPI [OK]

Common Mistakes:

• Using dict[int] which is invalid syntax
• Using tuple[int] which expects fixed length
• Confusing List with Set for uniqueness

3. Given this FastAPI endpoint code snippet, what will be the output if the input JSON is {"items": [1, 2, 2, 3]}?

from fastapi import FastAPI
from pydantic import BaseModel
from typing import Set

app = FastAPI()

class Data(BaseModel):
    items: Set[int]

@app.post("/unique")
def unique_items(data: Data):
    return {"unique_items": list(data.items)}

medium

A. {"unique_items": [1, 2, 3]}

B. {"unique_items": [1, 2, 2, 3]}

C. ValidationError due to duplicate items

D. {"unique_items": []}

Solution

1. Step 1: Understand Set validation in Pydantic

   Pydantic converts the input list to a set, removing duplicates automatically.

2. Step 2: Analyze the input and output

   Input has duplicates [1, 2, 2, 3], output converts to unique set [1, 2, 3].

3. Final Answer:

   {"unique_items": [1, 2, 3]} -> Option A

4. Quick Check:

   Set removes duplicates automatically [OK]

Hint: Set input removes duplicates, output shows unique items [OK]

Common Mistakes:

• Expecting ValidationError on duplicates
• Assuming output keeps duplicates
• Confusing List and Set behavior

4. Identify the error in this FastAPI model using List and Set:

from pydantic import BaseModel
from typing import List, Set

class Model(BaseModel):
    names: List[str]
    unique_ids: List[int]

    def __init__(self, **data):
        super().__init__(**data)
        self.unique_ids = set(self.unique_ids)

medium

A. No error, code works fine

B. Using List instead of Set for unique_ids is correct

C. Assigning a set to a List field breaks Pydantic validation

D. Missing type annotation for unique_ids

Solution

1. Step 1: Check field type and assignment

   unique_ids is declared as List[int] but assigned a set in __init__, causing type mismatch.

2. Step 2: Understand Pydantic validation rules

   Pydantic expects unique_ids to be a list; assigning a set breaks validation and type consistency.

3. Final Answer:

   Assigning a set to a List field breaks Pydantic validation -> Option C

4. Quick Check:

   Field type must match assigned value [OK]

Hint: Match field type with assigned value to avoid validation errors [OK]

Common Mistakes:

• Assigning set to List field without changing type
• Ignoring Pydantic's type enforcement
• Assuming __init__ can override field types safely

5. You want to create a FastAPI endpoint that accepts a list of tags but ensures no empty or duplicate tags. Which is the best way to validate this using Pydantic?

hard

A. Use tags: Set[str] and add a validator to reject empty strings

B. Use tags: List[str] and manually check duplicates and empties in the endpoint

C. Use tags: List[str] with a validator that converts to set and removes empties

D. Use tags: Set[str] without any validator

Solution

1. Step 1: Ensure uniqueness with Set

   Using Set[str] automatically removes duplicates.

2. Step 2: Add validator to reject empty strings

   Since Set only ensures uniqueness, a validator is needed to reject empty tags.

3. Final Answer:

   Use tags: Set[str] and add a validator to reject empty strings -> Option A

4. Quick Check:

   Set + validator = unique + no empty tags [OK]

Hint: Use Set for uniqueness and validator for empties [OK]

Common Mistakes:

• Using List without uniqueness enforcement
• Not validating empty strings in Set
• Relying on manual checks in endpoint instead of validators