Async vs sync decision in FastAPI - Practice Questions

Challenge - 5 Problems

❓ component_behavior

intermediate

What is the output when mixing async and sync endpoints in FastAPI?

Consider a FastAPI app with one async endpoint and one sync endpoint. What happens when both are called concurrently?

FastAPI

from fastapi import FastAPI
import time
import asyncio

app = FastAPI()

@app.get('/sync')
def sync_endpoint():
    time.sleep(1)
    return {'message': 'sync done'}

@app.get('/async')
async def async_endpoint():
    await asyncio.sleep(1)
    return {'message': 'async done'}

A Both endpoints block independently; sync blocks the server thread, async allows concurrency.

B Both endpoints run concurrently without blocking each other.

C Sync endpoint runs asynchronously, async endpoint runs synchronously.

D Both endpoints block the server and cause a deadlock.

💡 Hint

Think about how Python handles time.sleep vs asyncio.sleep in FastAPI.

The sync endpoint uses time.sleep, which blocks the server thread, preventing other requests from running concurrently on that thread. The async endpoint uses await asyncio.sleep, which allows the event loop to switch tasks and handle other requests concurrently.

📝 Syntax

intermediate

Which FastAPI endpoint definition is correct for async behavior?

Select the correct FastAPI endpoint definition that properly uses async syntax.

A @app.get('/data')\ndef get_data():\n return {'data': await some_async_call()}

B @app.get('/data')\ndef get_data():\n await some_async_call()\n return {'data': 'async'}

C @app.get('/data')\nasync def get_data():\n time.sleep(1)\n return {'data': 'async'}

D @app.get('/data')\nasync def get_data():\n return {'data': 'async'}

💡 Hint

Remember that 'await' can only be used inside async functions.

Option D correctly defines an async function without blocking calls. Option D uses 'await' inside a sync function, causing a syntax error. Option D uses blocking time.sleep inside async, which blocks the event loop. Option D uses 'await' outside async function, causing syntax error.

❓ state_output

advanced

What is the output of this FastAPI async endpoint with blocking code?

Analyze the output and behavior of this endpoint when called multiple times concurrently.

FastAPI

from fastapi import FastAPI
import time
import asyncio

app = FastAPI()

@app.get('/block')
async def block_endpoint():
    time.sleep(2)
    return {'status': 'done'}

A The endpoint raises a RuntimeWarning but returns immediately.

B Requests run concurrently without blocking despite time.sleep usage.

C Each request blocks the event loop for 2 seconds, causing all requests to be processed sequentially.

D The server crashes due to mixing sync blocking code in async function.

💡 Hint

Consider what happens when blocking code runs inside an async function.

Using time.sleep inside an async function blocks the entire event loop, so all requests wait for the blocking call to finish, resulting in sequential processing.

🔧 Debug

advanced

Why does this FastAPI async endpoint cause slow responses?

Identify the cause of slow responses in this async endpoint code.

FastAPI

from fastapi import FastAPI
import time
import asyncio

app = FastAPI()

@app.get('/slow')
async def slow_endpoint():
    for _ in range(3):
        time.sleep(1)
    return {'message': 'done'}

A The for loop is not awaited causing the function to run synchronously.

B Using time.sleep inside async blocks the event loop causing slow responses.

C Missing await before time.sleep causes the function to hang.

D The endpoint lacks async keyword causing slow execution.

💡 Hint

Check which calls block the event loop in async functions.

time.sleep is a blocking call and should not be used inside async functions. It pauses the event loop, causing slow responses.

🧠 Conceptual

expert

When should you choose sync over async endpoints in FastAPI?

Select the best scenario to use synchronous endpoints instead of asynchronous ones in FastAPI.

A When the endpoint performs CPU-bound tasks that do not benefit from async concurrency.

B When the endpoint makes many network calls that support async operations.

C When you want to maximize concurrency for I/O-bound tasks.

D When the endpoint uses async libraries exclusively.

💡 Hint

Think about the nature of the task: CPU-bound vs I/O-bound.

Async endpoints help with I/O-bound tasks by allowing concurrency. CPU-bound tasks block the event loop and do not benefit from async, so sync endpoints are better for CPU-heavy work.

Practice

1. In FastAPI, when should you choose an async function over a def synchronous function?

easy

A. When the task is CPU-heavy and requires intense calculations

B. When the task involves waiting for external resources like databases or APIs

C. When you want the function to run slower

D. When you want to block other tasks until this finishes

Solution

1. Step 1: Understand async purpose in FastAPI

   Async functions let your app wait for external tasks like database calls without stopping other work.

2. Step 2: Match task type to function type

   Waiting for external resources is I/O-bound, so async is best to avoid blocking.

3. Final Answer:

   When the task involves waiting for external resources like databases or APIs -> Option B

4. Quick Check:

   Async = I/O-bound tasks [OK]

Hint: Use async for waiting tasks, sync for CPU tasks [OK]

Common Mistakes:

• Choosing async for CPU-heavy tasks
• Thinking async makes code slower
• Using sync for I/O-bound tasks

2. Which of the following is the correct way to define an asynchronous route handler in FastAPI?

easy

A. async get_data def(): return {'msg': 'Hello'}

B. def async get_data(): return {'msg': 'Hello'}

C. def get_data() async: return {'msg': 'Hello'}

D. async def get_data(): return {'msg': 'Hello'}

Solution

1. Step 1: Recall Python async function syntax

   Async functions start with async def followed by the function name and parentheses.

2. Step 2: Check each option's syntax

   Only async def get_data(): return {'msg': 'Hello'} uses the correct async def syntax; others are invalid Python syntax.

3. Final Answer:

   async def get_data(): return {'msg': 'Hello'} -> Option D

4. Quick Check:

   Async function syntax = async def [OK]

Hint: Async functions start with 'async def' in Python [OK]

Common Mistakes:

• Placing async keyword after def
• Using 'def async' instead of 'async def'
• Incorrect order of keywords

3. Consider this FastAPI code snippet:

from fastapi import FastAPI
import time

app = FastAPI()

@app.get('/sync')
def sync_endpoint():
    time.sleep(2)
    return {'message': 'Done'}

@app.get('/async')
async def async_endpoint():
    await some_async_task()
    return {'message': 'Done'}

What is the main difference in behavior between /sync and /async endpoints?

medium

A. Both block other requests equally

B. /async blocks other requests; /sync allows concurrency

C. /sync blocks other requests during sleep; /async allows concurrent handling

D. Both allow full concurrency without blocking

Solution

1. Step 1: Understand sync endpoint behavior

   The sync_endpoint uses time.sleep(2), which blocks the thread and stops handling other requests during that time.

2. Step 2: Understand async endpoint behavior

   The async_endpoint uses await on an async task, allowing the server to handle other requests while waiting.

3. Final Answer:

   /sync blocks other requests during sleep; /async allows concurrent handling -> Option C

4. Quick Check:

   Sync blocks, async allows concurrency [OK]

Hint: Sync blocks during wait; async frees server to handle others [OK]

Common Mistakes:

• Assuming sync allows concurrency
• Thinking async blocks like sync
• Confusing await with blocking

4. You wrote this FastAPI route:

@app.get('/data')
async def get_data():
    result = time.sleep(1)
    return {'result': result}

What is the problem with this code?

medium

A. Using time.sleep inside async blocks the event loop, causing delays

B. Missing await keyword before time.sleep

C. Function should not be async if it returns a dictionary

D. No problem; code works fine

Solution

1. Step 1: Identify blocking call in async function

   time.sleep(1) is a blocking call that pauses the whole thread, including the async event loop.

2. Step 2: Understand async best practices

   In async functions, use non-blocking calls like await asyncio.sleep(1) to avoid blocking the event loop.

3. Final Answer:

   Using time.sleep inside async blocks the event loop, causing delays -> Option A

4. Quick Check:

   Blocking calls in async cause delays [OK]

Hint: Never use time.sleep in async; use await asyncio.sleep instead [OK]

Common Mistakes:

• Trying to await time.sleep
• Ignoring blocking effect of time.sleep
• Thinking async auto makes code non-blocking

5. You have a FastAPI app that fetches data from a slow external API and then processes it heavily with CPU calculations. How should you design your endpoint for best performance?

hard

A. Make the endpoint async to await the API call, then run CPU work in a separate thread or process

B. Make the endpoint fully async and run CPU work directly inside it

C. Make the endpoint synchronous and run both API call and CPU work sequentially

D. Use synchronous endpoint but call the API asynchronously

Solution

1. Step 1: Separate I/O-bound and CPU-bound tasks

   Fetching data from an external API is I/O-bound and benefits from async to avoid blocking.

2. Step 2: Handle CPU-heavy work properly

   CPU-heavy processing blocks the event loop if run directly in async code, so it should run in a separate thread or process.

3. Step 3: Combine async I/O with offloaded CPU work

   Use async endpoint to await API call, then offload CPU work to thread/process to keep responsiveness.

4. Final Answer:

   Make the endpoint async to await the API call, then run CPU work in a separate thread or process -> Option A

5. Quick Check:

   Async for I/O + thread/process for CPU [OK]

Hint: Async for waiting; thread/process for CPU work [OK]

Common Mistakes:

• Running CPU work directly in async code
• Making endpoint fully sync causing blocking
• Mixing async and sync calls incorrectly