Retry and failure handling in Rest API - Mini Project: Build & Apply

Retry and Failure Handling in REST API Calls

📖 Scenario: You are building a small program that calls a REST API to get the current weather for a city. Sometimes the API might fail or be slow, so you want to try again a few times before giving up.

🎯 Goal: Build a program that tries to get data from a REST API with retry attempts and handles failure gracefully.

📋 What You'll Learn

Create a variable with the API URL

Create a variable for maximum retry attempts

Write a loop to retry the API call up to the maximum attempts

Print the API response if successful or an error message if all attempts fail

💡 Why This Matters

🌍 Real World

Retrying API calls is common when working with web services that might be slow or temporarily unavailable.

💼 Career

Many software jobs require handling network errors and making programs more reliable by retrying failed requests.

1

Set up the API URL

Create a variable called api_url and set it to the string "https://api.example.com/weather?city=London".

Rest API

# Create the API URL variable
# Your code here

Hint

Use a string variable to store the full API URL.

2

Set the maximum retry attempts

Create a variable called max_retries and set it to the integer 3.

Rest API

api_url = "https://api.example.com/weather?city=London"
# Create the max_retries variable
# Your code here

Hint

Use an integer variable to store how many times to retry.

3

Write the retry loop with failure handling

Write a for loop using attempt in range(max_retries). Inside the loop, use a try block to call requests.get(api_url) and store the result in response. If response.status_code is 200, break the loop. If an exception occurs, catch it with except Exception as e and continue to the next attempt.

Rest API

api_url = "https://api.example.com/weather?city=London"
max_retries = 3

# Write a retry loop to call the API
# Your code here

Hint

Use a for loop with try-except inside to retry the API call.

4

Print the result or failure message

Add response = None right after the max_retries line (before the loop). After the loop, use an if statement to check if response is not None and response.status_code == 200. If yes, print response.text. Otherwise, print "Failed to get data after 3 attempts.".

Rest API

import requests

api_url = "https://api.example.com/weather?city=London"
max_retries = 3

# Add response = None here, then print the API response text if successful, else print failure message after the loop
for attempt in range(max_retries):
    try:
        response = requests.get(api_url)
        if response.status_code == 200:
            break
    except Exception as e:
        continue

# Your code here

Hint

Initialize response = None before the loop. Check both that response is not None and status code is 200 before printing the text.

Practice

1.

What is the main purpose of retry and failure handling in REST API calls?

easy

A. To speed up the API response time

B. To ignore errors and continue without notification

C. To automatically try the request again if it fails

D. To permanently stop the app on first failure

Solution

1. Step 1: Understand retry purpose

   Retry means trying the same request again if it fails, to handle temporary issues.

2. Step 2: Compare options

   Only To automatically try the request again if it fails describes retry correctly. Others describe wrong or harmful behaviors.

3. Final Answer:

   To automatically try the request again if it fails -> Option C

4. Quick Check:

   Retry = try again [OK]

Hint: Retry means trying again after failure [OK]

Common Mistakes:

• Thinking retry speeds up response
• Ignoring errors without handling
• Stopping app immediately on failure

2.

Which of the following is the correct way to set a maximum retry count in a REST API client configuration?

retry_config = {
    'max_retries': ?
}

easy

A. 'max_retry': 5

B. 'max_retries': 5

C. 'maxRetries': 5

D. 'max-retries': 5

Solution

1. Step 1: Identify correct key name

   The standard key for retry count is 'max_retries' with underscore.

2. Step 2: Check option values

   'max_retries': 5 uses correct key and value format. Others use wrong keys or casing.

3. Final Answer:

   'max_retries': 5 -> Option B

4. Quick Check:

   Correct key is max_retries [OK]

Hint: Use underscores for config keys like max_retries [OK]

Common Mistakes:

• Using camelCase instead of snake_case
• Misspelling the key as max_retry
• Using hyphens in keys

3.

Consider this Python code snippet for retrying a REST API call:

import time

def call_api():
    for attempt in range(3):
        response = make_request()
        if response.status_code == 200:
            return 'Success'
        time.sleep(1)
    return 'Failed'

What will be the output if all three requests fail with status code 500?

medium

A. "Success"

B. An exception is raised

C. The function runs forever

D. "Failed"

Solution

1. Step 1: Analyze retry loop behavior

   The loop tries 3 times. If status_code is 200, returns 'Success'. Otherwise, waits 1 second and retries.

2. Step 2: Check failure case

   All attempts return 500, so loop finishes without returning 'Success'. Then returns 'Failed'.

3. Final Answer:

   "Failed" -> Option D

4. Quick Check:

   All fail -> return 'Failed' [OK]

Hint: If no success in retries, function returns failure [OK]

Common Mistakes:

• Assuming success on failure status
• Expecting infinite loop
• Thinking exception is raised automatically

4.

Find the error in this retry logic snippet:

def fetch_data():
    retries = 3
    while retries > 0:
        response = api_call()
        if response.status_code == 200:
            return response.data
        retries -= 1
    return None
    retries -= 1

medium

A. The last line decreases retries after return, unreachable code

B. Missing sleep between retries

C. No check for network exceptions

D. Should use for loop instead of while

Solution

1. Step 1: Review code flow

   The last line retries -= 1 is after return None, so it never runs.

2. Step 2: Identify unreachable code problem

   Code after return is unreachable and unnecessary, indicating a logic error.

3. Final Answer:

   The last line decreases retries after return, unreachable code -> Option A

4. Quick Check:

   Code after return is unreachable [OK]

Hint: Code after return is never executed [OK]

Common Mistakes:

• Ignoring unreachable code warnings
• Forgetting to add wait between retries
• Not handling exceptions

5.

You want to implement retry logic that tries up to 4 times with increasing wait times: 1s, 2s, 4s, then stops. Which code snippet correctly implements this?

Option A:
for i in range(3):
    response = call_api()
    if response.ok:
        break
    time.sleep(2 ** i)

Option B:
for i in range(1, 5):
    response = call_api()
    if response.ok:
        break
    time.sleep(i)

Option C:
for i in range(4):
    response = call_api()
    if response.ok:
        break
    time.sleep(i)

Option D:
for i in range(4):
    response = call_api()
    if response.ok:
        break
    time.sleep(2 * i)

hard

A. Option A

B. Option B

C. Option C

D. Option D

Solution

1. Step 1: Understand wait time pattern

   Wait times should double each retry: 1s, 2s, 4s, then stop after 4 tries.

2. Step 2: Check the options' sleep times

   The code with time.sleep(2 ** i) and range(3) gives waits of 1s (i=0), 2s (i=1), 4s (i=2). This matches exponential backoff for up to 4 tries (3 retries after initial call).

3. Step 3: Compare distractors

   The range(1,5) with time.sleep(i) uses linear 1,2,3,4s. range(4) with time.sleep(i) uses 0,1,2,3s. time.sleep(2 * i) uses 0,2,4,6s. None match doubling from 1s.

4. Final Answer:

   Option A -> Option A

5. Quick Check:

   Exponential backoff uses 2 ** i [OK]

Hint: Use 2 ** i for doubling wait times [OK]

Common Mistakes:

• Starting wait time at 0 seconds
• Using linear instead of exponential waits
• Not stopping after max retries