Caching strategies in FastAPI

Introduction

Caching helps your FastAPI app respond faster by saving data it already got. This means less waiting for users and less work for your server.

When your API returns data that doesn't change often, like a list of countries.

When you want to reduce the load on your database by reusing recent query results.

When you want to speed up responses for popular requests that many users make.

When you want to temporarily store computed results to avoid repeating heavy calculations.

Syntax

FastAPI

from fastapi import FastAPI
from fastapi_cache import FastAPICache
from fastapi_cache.backends.inmemory import InMemoryBackend
from fastapi_cache.decorator import cache

app = FastAPI()

@app.on_event("startup")
async def startup():
    FastAPICache.init(InMemoryBackend())

@app.get("/items/{item_id}")
@cache(expire=60)
async def read_item(item_id: int):
    # simulate slow operation
    return {"item_id": item_id, "value": "some data"}

The @cache decorator tells FastAPI to save the response for a set time (in seconds).

You must initialize the cache backend (like in-memory or Redis) when the app starts.

Examples

This caches the function result for 2 minutes.

FastAPI

from fastapi_cache.decorator import cache

@cache(expire=120)
async def get_data():
    return {"data": "cached for 2 minutes"}

Setting expire=0 disables caching for this endpoint.

FastAPI

@cache(expire=0)
async def get_fresh_data():
    return {"data": "no caching"}

This example shows how to use Redis as a cache backend instead of in-memory.

FastAPI

import aioredis
from fastapi_cache.backends.redis import RedisBackend

@app.on_event("startup")
async def startup():
    redis = aioredis.from_url("redis://localhost")
    FastAPICache.init(RedisBackend(redis))

Sample Program

This FastAPI app has one endpoint that waits 2 seconds before returning data. But thanks to caching, if you call it again within 10 seconds, it returns instantly.

FastAPI

from fastapi import FastAPI
from fastapi_cache import FastAPICache
from fastapi_cache.backends.inmemory import InMemoryBackend
from fastapi_cache.decorator import cache
import asyncio

app = FastAPI()

@app.on_event("startup")
async def startup():
    FastAPICache.init(InMemoryBackend())

@app.get("/slow-data/{item_id}")
@cache(expire=10)
async def slow_data(item_id: int):
    await asyncio.sleep(2)  # simulate slow operation
    return {"item_id": item_id, "info": "This data is cached for 10 seconds"}

Important Notes

In-memory cache is simple but resets when the app restarts.

For production, use Redis or another persistent cache backend.

Set cache expiration wisely to balance freshness and speed.

Summary

Caching saves repeated work and speeds up your FastAPI app.

Use the @cache decorator with an expiration time to enable caching.

Choose the right cache backend for your needs, like in-memory for testing or Redis for production.

Practice

1. What is the main purpose of using caching in a FastAPI application?

easy

A. To increase the size of the application code

B. To remove all data from the server

C. To make the app slower for testing

D. To save repeated work and speed up response times

Solution

1. Step 1: Understand caching concept

   Caching stores results of expensive operations to reuse later.

2. Step 2: Identify caching benefit in FastAPI

   This reuse saves repeated work and speeds up response times.

3. Final Answer:

   To save repeated work and speed up response times -> Option D

4. Quick Check:

   Caching purpose = speed up responses [OK]

Hint: Caching means saving work to respond faster [OK]

Common Mistakes:

• Thinking caching increases code size
• Believing caching slows down the app
• Confusing caching with deleting data

2. Which of the following is the correct way to apply caching with expiration in FastAPI using the decorator?

easy

A. @cache(expire=60)

B. @cache_time(60)

C. @cache(expiration=60)

D. @cache(60_seconds)

Solution

1. Step 1: Recall FastAPI cache decorator syntax

   The correct decorator is @cache(expire=seconds) to set expiration time.

2. Step 2: Match options with correct syntax

   Only @cache(expire=60) matches the correct pattern.

3. Final Answer:

   @cache(expire=60) -> Option A

4. Quick Check:

   Decorator with expire=60 is correct [OK]

Hint: Use @cache with expire=seconds for expiration [OK]

Common Mistakes:

• Using wrong decorator names like @cache_time
• Using incorrect parameter names like expiration
• Passing expiration time without parameter name

3. Given this FastAPI code snippet, what will be the output on the second call to /data within 10 seconds?

from fastapi import FastAPI
from fastapi_cache.decorator import cache

app = FastAPI()

@cache(expire=10)
async def get_data():
    print('Fetching data')
    return {'value': 42}

@app.get('/data')
async def data():
    return await get_data()

medium

A. {'value': 42} and prints 'Fetching data' once only

B. {'value': 42} and prints 'Fetching data' every call

C. Error because cache decorator is missing setup

D. Empty response because cache expired immediately

Solution

1. Step 1: Check for cache initialization

   The code uses @cache but lacks FastAPICache.init with a backend on startup.

2. Step 2: Analyze execution

   Without init, FastAPICache.get raises AttributeError on first call, before executing get_data or printing.

3. Final Answer:

   Error because cache decorator is missing setup -> Option C

4. Quick Check:

   Missing FastAPICache.init causes runtime error [OK]

Hint: Cache decorator requires FastAPICache.init on startup [OK]

Common Mistakes:

• Assuming caching works without FastAPICache.init, print once only
• Thinking no caching, print every call
• Believing cache expires immediately

4. Identify the error in this FastAPI caching setup:

from fastapi import FastAPI
from fastapi_cache import FastAPICache
from fastapi_cache.backends.inmemory import InMemoryBackend

app = FastAPI()

@app.on_event('startup')
async def startup():
    FastAPICache.init(InMemoryBackend())

@cache(expire=30)
async def get_info():
    return {'info': 'cached data'}

medium

A. InMemoryBackend requires a Redis URL parameter

B. Cache decorator is used without importing it

C. Missing await keyword when calling FastAPICache.init

D. Startup event should be named 'start' instead of 'startup'

Solution

1. Step 1: Check imports for cache decorator

   The code uses @cache but does not import it from fastapi_cache.decorator.

2. Step 2: Verify other parts for correctness

   FastAPICache.init is correctly called; InMemoryBackend needs no parameters; event name 'startup' is correct.

3. Final Answer:

   Cache decorator is used without importing it -> Option B

4. Quick Check:

   Missing import of cache decorator causes error [OK]

Hint: Always import @cache decorator before using it [OK]

Common Mistakes:

• Forgetting to import cache decorator
• Passing Redis URL to InMemoryBackend
• Renaming startup event incorrectly

5. You want to cache user profile data in FastAPI using Redis backend with a 5-minute expiration. Which setup correctly initializes caching and applies it to the get_user_profile function?

from fastapi import FastAPI
from fastapi_cache import FastAPICache
from fastapi_cache.backends.redis import RedisBackend
from fastapi_cache.decorator import cache
import aioredis

app = FastAPI()

@app.on_event('startup')
async def startup():
    redis = aioredis.from_url('redis://localhost')
    FastAPICache.init(RedisBackend(redis), prefix='fastapi-cache')

@cache(expire=300)
async def get_user_profile(user_id: int):
    # Simulate fetching user profile
    return {'user_id': user_id, 'name': 'Alice'}

hard

A. Correct setup: Redis backend initialized with aioredis, cache decorator with expire=300

B. Incorrect: RedisBackend needs a string URL, not aioredis instance

C. Incorrect: Cache decorator expire should be in milliseconds, not seconds

D. Incorrect: FastAPICache.init must be called inside the cached function

Solution

1. Step 1: Verify Redis backend initialization

   Using aioredis.from_url and passing RedisBackend(redis) is correct for Redis caching.

2. Step 2: Check cache decorator usage

   @cache(expire=300) sets 5 minutes expiration correctly in seconds.

3. Final Answer:

   Correct setup: Redis backend initialized with aioredis, cache decorator with expire=300 -> Option A

4. Quick Check:

   Redis backend + expire=300 seconds = correct caching [OK]

Hint: Use aioredis instance with RedisBackend and expire in seconds [OK]

Common Mistakes:

• Passing Redis URL string directly instead of aioredis instance
• Using expire in milliseconds instead of seconds
• Calling FastAPICache.init inside cached function