Concurrent task execution in FastAPI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the module needed for running tasks concurrently in FastAPI.

FastAPI

from fastapi import FastAPI
import [1]

app = FastAPI()

Drag options to blanks, or click blank then click option'

Ajson

Brequests

Ctime

Dasyncio

Attempts:

3 left

💡 Hint

Common Mistakes

Importing synchronous modules like requests instead of asyncio.

Forgetting to import any concurrency module.

The asyncio module is used in FastAPI to run tasks concurrently using async features.

2fill in blank

medium

Complete the code to define an async endpoint that runs two tasks concurrently using asyncio.

FastAPI

import asyncio
from fastapi import FastAPI

app = FastAPI()

async def task1():
    await asyncio.sleep(1)
    return "Task 1 done"

async def task2():
    await asyncio.sleep(1)
    return "Task 2 done"

@app.get("/run-tasks")
async def run_tasks():
    results = await asyncio.[1](task1(), task2())
    return {"results": results}

Drag options to blanks, or click blank then click option'

Await

Bgather

Crun

Dsleep

Attempts:

3 left

💡 Hint

Common Mistakes

Using asyncio.sleep which just pauses execution.

Using asyncio.wait which returns futures, not results directly.

asyncio.gather runs multiple async tasks concurrently and waits for all to finish.

3fill in blank

hard

Fix the error in the code to correctly run two async tasks concurrently and return their results.

FastAPI

import asyncio
from fastapi import FastAPI

app = FastAPI()

async def task1():
    await asyncio.sleep(1)
    return "Done 1"

async def task2():
    await asyncio.sleep(1)
    return "Done 2"

@app.get("/tasks")
async def tasks():
    results = await asyncio.[1](task1(), task2())
    return {"results": results}

Drag options to blanks, or click blank then click option'

Agather

Brun

Cwait

Dcreate_task

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting to put await before asyncio.gather.

Using asyncio.run inside an async function.

To get the results of concurrent tasks, you must await asyncio.gather. The code was missing await, so adding await asyncio.gather(...) fixes it.

4fill in blank

hard

Fill both blanks to create a background task in FastAPI that runs concurrently without blocking the response.

FastAPI

from fastapi import FastAPI, BackgroundTasks

app = FastAPI()

def write_log(message: str):
    with open("log.txt", "a") as f:
        f.write(message + "\n")

@app.post("/send-message")
async def send_message(message: str, background_tasks: [1]):
    background_tasks.[2](write_log, message)
    return {"message": "Message received"}

Drag options to blanks, or click blank then click option'

ABackgroundTasks

Bbackground_tasks

Cadd_task

Drun_task

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong parameter type like background_tasks lowercase.

Calling a non-existent method like run_task.

The parameter must be typed as BackgroundTasks. To add a background task, use background_tasks.add_task().

5fill in blank

hard

Fill all three blanks to create a FastAPI endpoint that runs multiple async tasks concurrently and returns their results as a dictionary.

FastAPI

import asyncio
from fastapi import FastAPI

app = FastAPI()

async def fetch_data1():
    await asyncio.sleep(1)
    return "Data 1"

async def fetch_data2():
    await asyncio.sleep(1)
    return "Data 2"

@app.get("/fetch-all")
async def fetch_all():
    results = await asyncio.[1](fetch_data1(), fetch_data2())
    return {"first": results[[2]], "second": results[[3]]}

Drag options to blanks, or click blank then click option'

Agather

B0

C1

Dwait

Attempts:

3 left

💡 Hint

Common Mistakes

Using asyncio.wait which returns futures, not results directly.

Mixing up the indexes for results.

asyncio.gather runs tasks concurrently and returns results in order. Index 0 is the first task's result, index 1 is the second.

Practice

1. What is the main benefit of using asyncio.create_task() in FastAPI?

easy

A. It stops all tasks from running until manually restarted.

B. It makes the code run slower by adding delays.

C. It converts synchronous code into synchronous code.

D. It allows running multiple tasks at the same time without waiting for each to finish.

Solution

1. Step 1: Understand asyncio.create_task() purpose

   This function schedules a coroutine to run concurrently as a separate task without blocking the main program.

2. Step 2: Identify the benefit in FastAPI context

   Using it lets FastAPI handle multiple operations at once, improving responsiveness and efficiency.

3. Final Answer:

   It allows running multiple tasks at the same time without waiting for each to finish. -> Option D

4. Quick Check:

   Concurrent task execution = run tasks simultaneously [OK]

Hint: Remember: create_task starts tasks without waiting [OK]

Common Mistakes:

• Thinking create_task slows code down
• Confusing async with sync code
• Believing tasks stop until restarted

2. Which of the following is the correct way to run two async functions concurrently and wait for both to finish in FastAPI?

easy

A. func1(); func2()

B. await asyncio.create_task(func1()); await asyncio.create_task(func2())

C. await asyncio.gather(func1(), func2())

D. asyncio.run(func1(), func2())

Solution

1. Step 1: Understand how to run and wait for multiple async tasks

   asyncio.gather() runs multiple coroutines concurrently and waits for all to complete.

2. Step 2: Check each option's correctness

   await asyncio.gather(func1(), func2()) correctly uses await asyncio.gather(func1(), func2()). await asyncio.create_task(func1()); await asyncio.create_task(func2()) starts tasks but awaits them separately, not concurrently. func1(); func2() runs functions synchronously. asyncio.run(func1(), func2()) is invalid syntax.

3. Final Answer:

   await asyncio.gather(func1(), func2()) -> Option C

4. Quick Check:

   Use gather to run and wait multiple tasks [OK]

Hint: Use gather to wait all tasks together [OK]

Common Mistakes:

• Awaiting tasks separately losing concurrency
• Calling async functions without await
• Using asyncio.run inside async code

3. Given this FastAPI async endpoint code, what will be the output?

import asyncio
from fastapi import FastAPI
app = FastAPI()

async def task1():
    await asyncio.sleep(1)
    return "Task 1 done"

async def task2():
    await asyncio.sleep(2)
    return "Task 2 done"

@app.get("/run")
async def run_tasks():
    results = await asyncio.gather(task1(), task2())
    return {"results": results}

medium

A. {"results": ["Task 1 done", "Task 2 done"]}

B. {"results": ["Task 2 done", "Task 1 done"]}

C. {"results": ["Task 1 done"]}

D. TimeoutError

Solution

1. Step 1: Analyze the async tasks and their sleep durations

   task1 sleeps 1 second, task2 sleeps 2 seconds. Both run concurrently with gather.

2. Step 2: Understand gather result order

   asyncio.gather returns results in the order of the input tasks, regardless of completion time.

3. Final Answer:

   {"results": ["Task 1 done", "Task 2 done"]} -> Option A

4. Quick Check:

   Gather preserves input order in results [OK]

Hint: Gather returns results in input order, not finish order [OK]

Common Mistakes:

• Assuming results order matches finish order
• Expecting partial results if one task is slower
• Confusing gather with wait

4. What is wrong with this FastAPI code snippet for running tasks concurrently?

import asyncio
from fastapi import FastAPI
app = FastAPI()

async def task():
    await asyncio.sleep(1)
    return "Done"

@app.get("/test")
async def test():
    task1 = asyncio.create_task(task())
    task2 = asyncio.create_task(task())
    return {"result": task1.result() + task2.result()}

medium

A. Calling task1.result() before task completion causes an error.

B. Using create_task is not allowed in FastAPI endpoints.

C. The tasks should not be async functions.

D. The endpoint should not be async.

Solution

1. Step 1: Identify how task results are accessed

   Calling task1.result() immediately after creating the task tries to get the result before the task finishes, causing an error.

2. Step 2: Understand correct way to wait for task completion

   You must await the task or use await asyncio.gather(task1, task2) before accessing results.

3. Final Answer:

   Calling task1.result() before task completion causes an error. -> Option A

4. Quick Check:

   Access task result only after await [OK]

Hint: Always await tasks before accessing results [OK]

Common Mistakes:

• Accessing .result() too early
• Thinking create_task is forbidden
• Making endpoint synchronous

5. You want to run three independent async tasks in a FastAPI endpoint and return their results as soon as all finish. Which approach correctly handles errors in any task without stopping others and returns all results or error messages?

hard

A. Use asyncio.create_task() for each task but do not await them before returning.

B. Use asyncio.gather(task1(), task2(), task3(), return_exceptions=True) and process results for exceptions.

C. Use await task1(); await task2(); await task3() sequentially and catch exceptions globally.

D. Run tasks synchronously in a loop and catch exceptions inside each.

Solution

1. Step 1: Understand error handling in concurrent tasks

   Using asyncio.gather() with return_exceptions=True lets all tasks run concurrently and collects exceptions as results without stopping others.

2. Step 2: Compare options for correct concurrency and error handling

   Use asyncio.gather(task1(), task2(), task3(), return_exceptions=True) and process results for exceptions. correctly runs all tasks concurrently and handles errors individually. Use await task1(); await task2(); await task3() sequentially and catch exceptions globally. runs tasks sequentially, losing concurrency. Use asyncio.create_task() for each task but do not await them before returning. does not await tasks, so results are unavailable. Run tasks synchronously in a loop and catch exceptions inside each. runs synchronously, blocking concurrency.

3. Final Answer:

   Use asyncio.gather(task1(), task2(), task3(), return_exceptions=True) and process results for exceptions. -> Option B

4. Quick Check:

   Gather with return_exceptions handles errors concurrently [OK]

Hint: Use gather with return_exceptions=True for safe concurrency [OK]

Common Mistakes:

• Awaiting tasks sequentially losing concurrency
• Not awaiting tasks before returning
• Ignoring exceptions stopping all tasks