Why caching reduces server load in Rest API - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to return cached data if available.

Rest API

if cache.get('data') is not [1]:
    return cache.get('data')

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

AFalse

BNone

CTrue

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using True or False instead of None to check cache presence.

We check if the cached data is not None to use it and avoid extra server processing.

2fill in blank

medium

Complete the code to store response in cache after fetching.

Rest API

response = fetch_data()
cache.[1]('data', response)

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

Aset

Bdelete

Cget

Dupdate

Attempts:

3 left

💡 Hint

Common Mistakes

Using get instead of set to store data.

We use set to save the response in cache for future requests.

3fill in blank

hard

Fix the error in the code to check cache before fetching data.

Rest API

if cache.[1]('data'):
    return cache.get('data')
else:
    data = fetch_data()
    cache.set('data', data)
    return data

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

Aget

Bcontains

Cexists

Dhas_key

Attempts:

3 left

💡 Hint

Common Mistakes

Using non-existent methods like has_key or contains.

Use get to check if 'data' exists in cache; it returns None if not found.

4fill in blank

hard

Fill both blanks to create a cache dictionary comprehension filtering keys.

Rest API

filtered_cache = {k: v for k, v in cache.items() if k [1] 'user' and v [2] None}

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

Astartswith

Bendswith

Cis not

Dis

Attempts:

3 left

💡 Hint

Common Mistakes

Using endswith instead of startswith.

Using 'is' instead of 'is not' for None check.

We filter keys starting with 'user' and values that are not None.

5fill in blank

hard

Fill all three blanks to create a cache update with conditional filtering.

Rest API

cache_update = [1]: [2] for [3], val in new_data.items() if val > 0

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

Akey

Bval

Ck

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing variable names or using undefined names.

We create a dictionary with keys k and values val from new_data filtering positive values.

Practice

1. Why does caching reduce the load on a server when handling REST API requests?

easy

A. Because it forces the server to recalculate data every time

B. Because it increases the number of requests the server must process

C. Because it deletes data from the server to free up space

D. Because it stores copies of responses to serve repeated requests faster

Solution

1. Step 1: Understand caching purpose

   Caching saves copies of data or responses so the server doesn't have to create them again for repeated requests.

2. Step 2: Effect on server load

   By serving stored copies, the server avoids extra processing, reducing its workload.

3. Final Answer:

   Because it stores copies of responses to serve repeated requests faster -> Option D

4. Quick Check:

   Caching reduces server work = D [OK]

Hint: Caching saves repeated work by storing data copies [OK]

Common Mistakes:

• Thinking caching increases server calculations
• Confusing caching with deleting data
• Believing caching forces recalculation every time

2. Which HTTP header is commonly used to control caching behavior in REST APIs?

easy

A. Cache-Control

B. Authorization

C. Content-Type

D. User-Agent

Solution

1. Step 1: Identify caching headers

   The HTTP header that controls caching rules is named Cache-Control.

2. Step 2: Verify other headers

   Authorization is for security, Content-Type defines data format, and User-Agent identifies the client.

3. Final Answer:

   Cache-Control -> Option A

4. Quick Check:

   Cache header = Cache-Control [OK]

Hint: Cache-Control header manages caching rules [OK]

Common Mistakes:

• Choosing Authorization for caching
• Confusing Content-Type with caching control
• Selecting User-Agent instead of cache header

3. Consider this REST API server with caching enabled. What will be the output of the following sequence?

1. Client requests resource A (not cached)
2. Server processes and caches response for A
3. Client requests resource A again
4. Server returns cached response

What happens at step 4?

medium

A. Server returns the cached response instantly without processing

B. Server processes resource A again and returns new response

C. Server returns an error because cache is empty

D. Server delays response to check for updates

Solution

1. Step 1: Understand caching steps

   At first request, server processes and caches the response. On the second request, the cached response is available.

2. Step 2: Behavior at repeated request

   Server returns the cached response immediately without reprocessing, speeding up response time.

3. Final Answer:

   Server returns the cached response instantly without processing -> Option A

4. Quick Check:

   Cached response served = A [OK]

Hint: Cached data skips processing on repeat requests [OK]

Common Mistakes:

• Thinking server recalculates every time
• Assuming cache is empty on second request
• Believing server delays to check updates

4. A developer added caching to their REST API but notices stale data is served too long. What is the likely cause?

medium

A. Cache is disabled in the server

B. Server is not processing requests

C. Cache expiration time is set too high

D. Client is not sending requests

Solution

1. Step 1: Identify stale data cause

   If cached data stays too long, it means the cache expiration or max-age is set too high, so data is not refreshed often.

2. Step 2: Check other options

   Cache disabled means no caching, so no stale data. Server not processing or client not sending requests would cause no responses, not stale data.

3. Final Answer:

   Cache expiration time is set too high -> Option C

4. Quick Check:

   Long cache time = stale data = B [OK]

Hint: Long cache expiration causes stale data [OK]

Common Mistakes:

• Assuming cache is off when stale data appears
• Blaming server or client inactivity
• Ignoring cache expiration settings

5. You want to reduce server load by caching REST API responses but also ensure data freshness. Which strategy best balances these needs?

hard

A. Cache responses indefinitely without validation

B. Set a short cache expiration and use conditional requests with ETag headers

C. Disable caching completely to always get fresh data

D. Only cache error responses to reduce load

Solution

1. Step 1: Understand caching and freshness tradeoff

   Short cache expiration limits stale data time. Conditional requests with ETag let server confirm if data changed before sending full response.

2. Step 2: Evaluate other options

   Disabling caching increases load. Indefinite caching causes stale data. Caching only errors doesn't reduce load effectively.

3. Final Answer:

   Set a short cache expiration and use conditional requests with ETag headers -> Option B

4. Quick Check:

   Short cache + ETag = freshness + load reduction = C [OK]

Hint: Use short cache and ETag for freshness and efficiency [OK]

Common Mistakes:

• Disabling caching to fix freshness
• Caching forever without validation
• Caching only error responses