Custom middleware creation in FastAPI - Performance & Optimization

Performance: Custom middleware creation

MEDIUM IMPACT

This affects the request-response cycle speed and server throughput by adding processing steps before and after handling requests.

Adding custom logic to process requests and responses

FastAPI

from fastapi import FastAPI
from starlette.middleware.base import BaseHTTPMiddleware
import asyncio

app = FastAPI()

class EfficientMiddleware(BaseHTTPMiddleware):
    async def dispatch(self, request, call_next):
        # Non-blocking async processing
        await asyncio.sleep(0.1)  # does not block event loop
        response = await call_next(request)
        return response

app.add_middleware(EfficientMiddleware)

Uses async sleep to avoid blocking event loop, allowing other requests to be processed concurrently.

📈 Performance GainNon-blocking delay improves throughput and reduces request latency under load.

Adding custom logic to process requests and responses

FastAPI

from fastapi import FastAPI
from starlette.middleware.base import BaseHTTPMiddleware

app = FastAPI()

class SlowMiddleware(BaseHTTPMiddleware):
    async def dispatch(self, request, call_next):
        # Heavy synchronous processing
        import time
        time.sleep(0.1)  # blocks event loop
        response = await call_next(request)
        return response

app.add_middleware(SlowMiddleware)

Blocking the event loop with synchronous sleep delays all requests, reducing throughput and increasing latency.

📉 Performance CostBlocks event loop for 100ms per request, increasing response time and reducing concurrency.

Performance Comparison

Pattern	DOM Operations	Reflows	Paint Cost	Verdict
Blocking synchronous middleware	N/A	N/A	N/A	[X] Bad
Async non-blocking middleware	N/A	N/A	N/A	[OK] Good
CPU-heavy synchronous middleware	N/A	N/A	N/A	[X] Bad
CPU work offloaded to thread pool	N/A	N/A	N/A	[OK] Good

Rendering Pipeline

Middleware runs during the server's request-response cycle before and after the main handler. It adds processing steps that can delay response generation.

→Request Handling

→Response Generation

⚠️ BottleneckSynchronous or CPU-heavy middleware blocks the event loop, delaying all requests.

Optimization Tips

1Avoid synchronous blocking code in middleware to keep the event loop free.

2Use async/await and non-blocking operations inside middleware.

3Offload CPU-intensive tasks to threads or background workers.

Performance Quiz - 3 Questions

What is the main performance risk of using synchronous blocking code in FastAPI middleware?

A It blocks the event loop, increasing request latency and reducing throughput.

B It increases the size of the response payload.

C It causes layout shifts in the browser.

D It improves CPU utilization.

DevTools: Performance

How to check: Record a server request in DevTools Performance panel, look for long tasks blocking the main thread or event loop.

What to look for: Long blocking tasks or delays before response indicate middleware blocking; short async tasks indicate good performance.

Practice

1. What is the main purpose of creating custom middleware in FastAPI?

easy

A. To handle user authentication only

B. To define database models

C. To create HTML templates

D. To run code before and after each request is processed

Solution

1. Step 1: Understand middleware role

   Middleware runs code around request processing, before and after the main handler.

2. Step 2: Identify correct purpose

   Custom middleware is not for database or templates but for request/response handling.

3. Final Answer:

   To run code before and after each request is processed -> Option D

4. Quick Check:

   Middleware = pre/post request code [OK]

Hint: Middleware wraps requests to add extra processing [OK]

Common Mistakes:

• Confusing middleware with database or template code
• Thinking middleware only handles authentication
• Believing middleware runs only after requests

2. Which method must be overridden when creating a custom middleware class in FastAPI?

easy

A. dispatch

B. execute

C. process

D. handle_request

Solution

1. Step 1: Recall FastAPI middleware structure

   Custom middleware classes override the dispatch method to handle requests.

2. Step 2: Match method names

   Only dispatch is the correct method name; others are invalid in FastAPI middleware.

3. Final Answer:

   dispatch -> Option A

4. Quick Check:

   dispatch method overrides middleware behavior [OK]

Hint: dispatch handles request and response in middleware [OK]

Common Mistakes:

• Using incorrect method names like handle_request
• Confusing middleware methods with route handlers
• Forgetting to override dispatch method

3. Given this middleware code snippet, what will be printed when a request is processed?

class LogMiddleware:
    async def dispatch(self, request, call_next):
        print('Before request')
        response = await call_next(request)
        print('After request')
        return response

medium

A. Only Before request printed

B. Before request printed, then After request printed after response

C. Only After request printed

D. No output printed

Solution

1. Step 1: Analyze dispatch method flow

   Print 'Before request' runs before calling next handler, 'After request' runs after awaiting response.

2. Step 2: Understand async call_next behavior

   call_next processes the request and returns response; code after await runs after response is ready.

3. Final Answer:

   Before request printed, then After request printed after response -> Option B

4. Quick Check:

   Print before and after call_next = B [OK]

Hint: Code before await runs first, after await runs last [OK]

Common Mistakes:

• Thinking 'After request' prints before response
• Ignoring async await order
• Assuming only one print runs

4. Identify the error in this custom middleware code:

class MyMiddleware:
    async def dispatch(self, request):
        response = await call_next(request)
        return response

medium

A. Response must be created manually, not awaited

B. dispatch method should not be async

C. Missing call_next parameter in dispatch method

D. Middleware class must inherit from BaseHTTPMiddleware

Solution

1. Step 1: Check dispatch method signature

   dispatch must accept both request and call_next parameters to call next handler.

2. Step 2: Identify missing parameter

   Code lacks call_next parameter, causing runtime error when calling call_next(request).

3. Final Answer:

   Missing call_next parameter in dispatch method -> Option C

4. Quick Check:

   dispatch(request, call_next) required [OK]

Hint: dispatch needs call_next argument to forward requests [OK]

Common Mistakes:

• Omitting call_next parameter
• Making dispatch synchronous
• Not inheriting middleware base class (optional but recommended)

5. You want to create a middleware that adds a custom header 'X-Process-Time' showing how long the request took. Which code snippet correctly implements this?

hard

A. class TimerMiddleware:
async def dispatch(self, request, call_next):
start = time.time()
response = await call_next(request)
process_time = time.time() - start
response.headers['X-Process-Time'] = str(process_time)
return response

B. class TimerMiddleware:
async def dispatch(self, request):
start = time.time()
response = await call_next(request)
response.headers['X-Process-Time'] = str(time.time() - start)
return response

C. class TimerMiddleware:
def dispatch(self, request, call_next):
start = time.time()
response = call_next(request)
response.headers['X-Process-Time'] = str(time.time() - start)
return response

D. class TimerMiddleware:
async def dispatch(self, request, call_next):
response = await call_next(request)
response.headers['X-Process-Time'] = time.time()
return response

Solution

1. Step 1: Check dispatch method signature and async usage

   dispatch must be async and accept request and call_next parameters.

2. Step 2: Verify timing and header addition

   Start time before await call_next, calculate duration after, add header as string.

3. Step 3: Identify correct code snippet

   class TimerMiddleware: async def dispatch(self, request, call_next): start = time.time() response = await call_next(request) process_time = time.time() - start response.headers['X-Process-Time'] = str(process_time) return response correctly implements timing, async, and header addition.

4. Final Answer:

   The code snippet that correctly adds X-Process-Time header -> Option A

5. Quick Check:

   Async dispatch with timing and header = A [OK]

Hint: Measure time before and after await call_next, add header [OK]

Common Mistakes:

• Missing call_next parameter
• Not awaiting call_next
• Adding header before timing calculation
• Using synchronous dispatch method