Bulk operations in FastAPI - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ component_behavior

intermediate

Bulk Create Endpoint Behavior

Consider a FastAPI endpoint designed to create multiple user records at once using a list of user data. What will be the response if one of the user entries in the list is missing a required field?

FastAPI

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class User(BaseModel):
    id: int
    name: str

@app.post('/users/bulk')
async def create_users(users: list[User]):
    return {'created': len(users)}

A The endpoint creates all users except the one missing the field and returns the count of created users.

B The endpoint returns a 422 Unprocessable Entity error and no users are created.

C The endpoint ignores validation and creates all users, filling missing fields with null.

D The endpoint returns a 500 Internal Server Error due to missing data.

💡 Hint

Think about how Pydantic validates input data before the endpoint logic runs.

FastAPI uses Pydantic to validate input data. If any item in the list is missing a required field, validation fails and FastAPI returns a 422 error before entering the endpoint function.

📝 Syntax

intermediate

Correct Bulk Update Syntax

Which of the following FastAPI endpoint definitions correctly accepts a list of items for bulk update using Pydantic models?

FastAPI

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    id: int
    value: str

A

@app.put('/items/bulk')
async def update_items(items: list[Item]):
    return {'updated': len(items)}

B

@app.put('/items/bulk')
async def update_items(items: Item):
    return {'updated': 1}

C

@app.put('/items/bulk')
async def update_items(items: dict[int, Item]):
    return {'updated': len(items)}

D

@app.put('/items/bulk')
async def update_items(items: Item[]):
    return {'updated': len(items)}

💡 Hint

Remember how Python type hints express lists and arrays.

In Python, a list of Pydantic models is typed as list[Model]. Option A uses this correct syntax. Option A expects a single item, C uses a dict which is not expected, and D uses invalid syntax.

❓ state_output

advanced

Bulk Delete Endpoint Output

Given a FastAPI endpoint that deletes multiple records by their IDs, what will be the output if some IDs do not exist in the database?

FastAPI

from fastapi import FastAPI

app = FastAPI()

fake_db = {1: 'a', 2: 'b', 3: 'c'}

@app.delete('/items/bulk')
async def delete_items(ids: list[int]):
    deleted = 0
    for id_ in ids:
        if id_ in fake_db:
            del fake_db[id_]
            deleted += 1
    return {'deleted': deleted, 'requested': len(ids)}

A {'deleted': number_of_existing_ids, 'requested': total_ids_passed}

B {'deleted': total_ids_passed, 'requested': total_ids_passed}

C Raises a KeyError when a non-existing ID is deleted.

D {'deleted': 0, 'requested': total_ids_passed}

💡 Hint

Look at how the code checks if an ID exists before deleting.

The code only deletes IDs found in the fake_db and counts them. It returns how many were deleted and how many were requested. It does not raise errors for missing IDs.

🔧 Debug

advanced

Debugging Bulk Insert with Async DB

Why does this FastAPI bulk insert endpoint fail to insert all items into the database?

FastAPI

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Record(BaseModel):
    id: int
    data: str

fake_db = {}

@app.post('/records/bulk')
async def bulk_insert(records: list[Record]):
    for record in records:
        fake_db[record.id] = record.data
    return {'inserted': len(records)}

A The endpoint fails because the fake_db dictionary is not thread-safe for async operations.

B The endpoint fails because the records parameter should be a dict, not a list.

C The endpoint fails because the loop should use await when inserting each record.

D The endpoint works correctly; no failure occurs.

💡 Hint

Consider that fake_db is a simple dictionary and the code is synchronous inside the async function.

The code runs synchronously inside the async function and updates a simple dictionary. No async database calls are made, so no concurrency issues arise. The endpoint works as expected.

🧠 Conceptual

expert

Best Practice for Bulk Operations in FastAPI

Which approach is best to handle large bulk operations in FastAPI to avoid blocking the server and ensure responsiveness?

A Process all items synchronously in the request handler, returning only after completion.

B Split the bulk list into single-item requests and process them one by one synchronously.

C Use background tasks or external workers to process bulk operations asynchronously after responding.

D Reject bulk requests and force clients to send single-item requests.

💡 Hint

Think about server load and user experience when processing large data.

Handling large bulk operations synchronously can block the server and degrade performance. Using background tasks or external workers allows the server to respond quickly and process data asynchronously, improving responsiveness and scalability.