Async vs sync decision in FastAPI - Hands-On Comparison

Async vs Sync Decision in FastAPI

📖 Scenario: You are building a simple web API using FastAPI. You want to understand how to write endpoints that handle requests either synchronously or asynchronously. This helps your API respond efficiently depending on the task.

🎯 Goal: Create a FastAPI app with two endpoints: one synchronous and one asynchronous. Learn how to define each type and see how FastAPI handles them.

📋 What You'll Learn

Create a FastAPI app instance named app

Write a synchronous endpoint /sync that returns a greeting message

Write an asynchronous endpoint /async that returns a greeting message

Use async def for the async endpoint and def for the sync endpoint

💡 Why This Matters

🌍 Real World

Web APIs often need to handle tasks that can be done quickly or tasks that wait for other services. Knowing when to use async or sync helps make APIs faster and more efficient.

💼 Career

FastAPI is popular for building modern web APIs. Understanding async vs sync endpoints is important for backend developers to write scalable and responsive services.

1

Create FastAPI app instance

Import FastAPI from fastapi and create an app instance called app.

FastAPI

# Import FastAPI and create app instance
# Your code here

Hint

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

2

Add synchronous endpoint

Add a synchronous endpoint /sync using @app.get("/sync") and a function named sync_endpoint that returns the dictionary {"message": "Hello from sync"}.

FastAPI

from fastapi import FastAPI

app = FastAPI()

# Add synchronous endpoint /sync here
# Your code here

Hint

Use @app.get("/sync") decorator and define a normal def function.

3

Add asynchronous endpoint

Add an asynchronous endpoint /async using @app.get("/async") and a function named async_endpoint defined with async def that returns the dictionary {"message": "Hello from async"}.

FastAPI

from fastapi import FastAPI

app = FastAPI()

@app.get("/sync")
def sync_endpoint():
    return {"message": "Hello from sync"}

# Add asynchronous endpoint /async here
# Your code here

Hint

Use async def to define the async endpoint function.

4

Run FastAPI app with Uvicorn

Add the code block to run the FastAPI app with Uvicorn when the script is executed directly. Use if __name__ == "__main__" and call uvicorn.run(app, host="127.0.0.1", port=8000). Import uvicorn at the top.

FastAPI

from fastapi import FastAPI

app = FastAPI()

@app.get("/sync")
def sync_endpoint():
    return {"message": "Hello from sync"}

@app.get("/async")
async def async_endpoint():
    return {"message": "Hello from async"}

# Add code to run app with uvicorn here
# Your code here

Hint

Import uvicorn and use the if __name__ == "__main__" block to run the app.

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