List and set validation in FastAPI

Introduction

We use list and set validation to make sure the data we get is the right kind and shape. This helps keep our app safe and working well.

When you expect a user to send multiple items like tags or IDs.

When you want to make sure a list has unique items using a set.

When you want to check that each item in a list or set follows certain rules.

When you want to automatically convert input data into Python lists or sets.

When you want to reject bad data early before processing it.

Syntax

FastAPI

from pydantic import BaseModel
from typing import List, Set

class MyModel(BaseModel):
    names: List[str]  # List of strings
    unique_ids: Set[int]  # Set of unique integers

Use List when order matters and duplicates are allowed.

Use Set when you want only unique items and order does not matter.

Examples

This model accepts a list of strings called tags. Duplicates are allowed.

FastAPI

from pydantic import BaseModel
from typing import List

class ModelWithList(BaseModel):
    tags: List[str]

This model accepts a set of integers. Duplicates will be removed automatically.

FastAPI

from pydantic import BaseModel
from typing import Set

class ModelWithSet(BaseModel):
    unique_numbers: Set[int]

This model allows the list to be empty by default.

FastAPI

from pydantic import BaseModel
from typing import List

class EmptyListModel(BaseModel):
    items: List[str] = []

This model accepts a set of unique integers.

FastAPI

from pydantic import BaseModel
from typing import Set

class SingleItemSetModel(BaseModel):
    ids: Set[int]

Sample Program

This FastAPI app defines a POST endpoint that accepts a JSON body with a list of names and a set of unique IDs. The set automatically removes duplicates. The test client sends data with duplicates to show how validation works.

FastAPI

from fastapi import FastAPI
from pydantic import BaseModel
from typing import List, Set
from fastapi.testclient import TestClient

app = FastAPI()

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

@app.post('/items/')
async def create_item(item: ItemModel):
    return {
        'names_received': item.names,
        'unique_ids_received': sorted(item.unique_ids)
    }

client = TestClient(app)

# Test data with duplicates in list and set
response = client.post('/items/', json={
    'names': ['apple', 'banana', 'apple'],
    'unique_ids': [1, 2, 2, 3]
})
print('Status code:', response.status_code)
print('Response JSON:', response.json())

Important Notes

List validation keeps the order and allows duplicates.

Set validation removes duplicates automatically but does not keep order.

Validation happens automatically when FastAPI receives data matching the model.

Use sorted() if you want to display set items in order.

Summary

Use List for ordered collections that can have duplicates.

Use Set for collections that must have unique items.

FastAPI with Pydantic validates and converts input data automatically.

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