Graceful degradation in Rest API - Mini Project: Build & Apply

Graceful Degradation in REST API

📖 Scenario: You are building a simple REST API for a weather service. Sometimes, the detailed weather data might not be available due to external service issues. You want your API to still respond with basic information instead of failing completely.

🎯 Goal: Create a REST API endpoint that tries to return detailed weather data. If detailed data is unavailable, it should gracefully degrade and return basic weather data instead.

📋 What You'll Learn

Create a dictionary called weather_data with keys 'temperature', 'humidity', and 'detailed_forecast' with exact values.

Create a boolean variable called is_detailed_available to simulate availability of detailed data.

Write a function called get_weather() that returns detailed data if available, otherwise returns basic data.

Print the result of calling get_weather().

💡 Why This Matters

🌍 Real World

APIs often depend on external services that may fail or be slow. Graceful degradation helps keep the API responsive by providing simpler data when full data is unavailable.

💼 Career

Understanding graceful degradation is important for backend developers and API designers to build reliable and user-friendly services.

1

DATA SETUP: Create the weather data dictionary

Create a dictionary called weather_data with these exact entries: 'temperature': 22, 'humidity': 60, and 'detailed_forecast': 'Sunny with light clouds'.

Rest API

# Your code here

Hint

Use curly braces to create a dictionary and separate keys and values with colons.

2

CONFIGURATION: Add a flag for detailed data availability

Create a boolean variable called is_detailed_available and set it to False to simulate that detailed data is not available.

Rest API

weather_data = {
    'temperature': 22,
    'humidity': 60,
    'detailed_forecast': 'Sunny with light clouds'
}
# Your code here

Hint

Use False to indicate the detailed data is not available.

3

CORE LOGIC: Write the function to return weather data with graceful degradation

Write a function called get_weather() that returns a dictionary with 'temperature' and 'humidity' always. If is_detailed_available is True, include 'detailed_forecast' from weather_data in the returned dictionary. Otherwise, return only the basic data.

Rest API

weather_data = {
    'temperature': 22,
    'humidity': 60,
    'detailed_forecast': 'Sunny with light clouds'
}
is_detailed_available = False

# Your code here

Hint

Use an if statement inside the function to check is_detailed_available and add the detailed forecast if true.

4

OUTPUT: Print the weather data returned by the function

Write a print statement to display the result of calling get_weather().

Rest API

weather_data = {
    'temperature': 22,
    'humidity': 60,
    'detailed_forecast': 'Sunny with light clouds'
}
is_detailed_available = False

def get_weather():
    basic_data = {
        'temperature': weather_data['temperature'],
        'humidity': weather_data['humidity']
    }
    if is_detailed_available:
        basic_data['detailed_forecast'] = weather_data['detailed_forecast']
    return basic_data

# Your code here

Hint

Call get_weather() inside print() to show the output.

Practice

1. What is the main goal of graceful degradation in REST APIs?

easy

A. To keep the API working even if some parts fail

B. To stop the API immediately when an error occurs

C. To ignore all errors and continue without response

D. To make the API faster by skipping error checks

Solution

1. Step 1: Understand graceful degradation purpose

   Graceful degradation means the system still works even if some parts fail.

2. Step 2: Compare options with this meaning

   Only To keep the API working even if some parts fail matches this idea by keeping the API working despite failures.

3. Final Answer:

   To keep the API working even if some parts fail -> Option A

4. Quick Check:

   Graceful degradation = keep working despite failure [OK]

Hint: Graceful degradation means continue working despite errors [OK]

Common Mistakes:

• Thinking it stops the API on error
• Assuming errors are ignored without response
• Confusing with performance optimization

2. Which of the following is the correct way to handle errors for graceful degradation in a REST API response (in pseudocode)?

easy

A. ignore errors and return nothing

B. return data; if error then stop

C. try { return data } catch { return fallbackData }

D. throw error without handling

Solution

1. Step 1: Identify error handling syntax

   Graceful degradation uses try-catch to handle errors and provide fallback data.

2. Step 2: Match options to this pattern

   try { return data } catch { return fallbackData } shows try-catch with fallback, others either stop or ignore errors.

3. Final Answer:

   try { return data } catch { return fallbackData } -> Option C

4. Quick Check:

   Use try-catch with fallback for graceful degradation [OK]

Hint: Use try-catch to return fallback on error [OK]

Common Mistakes:

• Not catching errors properly
• Stopping API on first error
• Ignoring fallback responses

3. Consider this pseudocode for a REST API endpoint:

function getUserData() {
  try {
    return fetchUserFromDB();
  } catch (error) {
    return { name: "Guest", id: 0 };
  }
}

What will getUserData() return if the database fetch fails?

medium

A. An error message

B. Nothing, the function crashes

C. Null

D. A default user object with name 'Guest' and id 0

Solution

1. Step 1: Analyze try block behavior

   If fetchUserFromDB() works, it returns user data.

2. Step 2: Analyze catch block fallback

   If an error occurs, catch returns default user object with name 'Guest' and id 0.

3. Final Answer:

   A default user object with name 'Guest' and id 0 -> Option D

4. Quick Check:

   Error fallback returns default user object [OK]

Hint: Catch returns default object on failure [OK]

Common Mistakes:

• Assuming function crashes on error
• Expecting null instead of fallback object
• Thinking error message is returned

4. This REST API code snippet is meant to provide graceful degradation but has a bug:

function getData() {
  try {
    return fetchData();
  } catch (error) {
    fallbackData;
  }
}

What is the problem?

medium

A. The try block is missing

B. The fallback data is not returned in the catch block

C. The function does not catch errors

D. The function returns twice

Solution

1. Step 1: Check catch block code

   The catch block has fallbackData; but does not return it.

2. Step 2: Understand function return behavior

   Without return, the function returns undefined on error, breaking graceful degradation.

3. Final Answer:

   The fallback data is not returned in the catch block -> Option B

4. Quick Check:

   Catch must return fallback data for graceful degradation [OK]

Hint: Always return fallback data inside catch block [OK]

Common Mistakes:

• Forgetting to return fallback data
• Misplacing try-catch blocks
• Assuming catch auto-returns value

5. You have a REST API that fetches user profile and user posts separately. To apply graceful degradation, which approach is best?

hard

A. If fetching posts fails, return profile with empty posts list

B. If fetching posts fails, return error and no profile

C. Stop API if either profile or posts fail

D. Ignore profile and only return posts

Solution

1. Step 1: Understand graceful degradation in multi-part fetch

   It means returning partial data if one part fails, not stopping all.

2. Step 2: Evaluate options for partial fallback

   If fetching posts fails, return profile with empty posts list returns profile and empty posts if posts fail, matching graceful degradation.

3. Final Answer:

   If fetching posts fails, return profile with empty posts list -> Option A

4. Quick Check:

   Partial data returned on failure = graceful degradation [OK]

Hint: Return partial data with fallback for failed parts [OK]

Common Mistakes:

• Stopping API on any failure
• Returning no data if one part fails
• Ignoring fallback for partial data