Why rate limiting protects services in Rest API - See It in Action

Why Rate Limiting Protects Services

📖 Scenario: You are building a simple web service that allows users to request data. To keep the service reliable and fair for everyone, you need to limit how many requests each user can make in a short time.

🎯 Goal: Build a basic rate limiting mechanism that counts user requests and blocks users who exceed the allowed number of requests.

📋 What You'll Learn

Create a dictionary to track user request counts

Set a maximum request limit per user

Implement logic to check and update request counts

Display a message when a user is blocked due to too many requests

💡 Why This Matters

🌍 Real World

Rate limiting helps keep websites and APIs running smoothly by preventing overload from too many requests.

💼 Career

Understanding rate limiting is important for backend developers and system administrators to protect services from abuse and ensure fair usage.

1

Create a dictionary to track user requests

Create a dictionary called user_requests with these exact entries: 'alice': 0, 'bob': 0, 'carol': 0 to track how many requests each user has made.

Rest API

# Create the user_requests dictionary to track requests
# Your code here

Need a hint?

Use curly braces to create a dictionary with keys 'alice', 'bob', and 'carol' all set to 0.

2

Set the maximum request limit

Create a variable called max_requests and set it to 3 to limit how many requests each user can make.

Rest API

user_requests = {'alice': 0, 'bob': 0, 'carol': 0}
# Set the maximum allowed requests per user
# Your code here

Need a hint?

Just create a variable named max_requests and assign it the number 3.

3

Implement request checking and updating

Write a function called handle_request that takes a user parameter. Inside the function, check if user_requests[user] is less than max_requests. If yes, increase user_requests[user] by 1 and return "Request allowed". Otherwise, return "Too many requests".

Rest API

user_requests = {'alice': 0, 'bob': 0, 'carol': 0}
max_requests = 3
# Define the handle_request function below
# Your code here

Need a hint?

Use an if-else statement to check the user's request count and update it accordingly.

4

Test and display the rate limiting result

Call handle_request three times for user 'alice' and print the result each time. Then call it a fourth time for 'alice' and print the result to show the blocking message.

Rest API

user_requests = {'alice': 0, 'bob': 0, 'carol': 0}
max_requests = 3

def handle_request(user):
    if user_requests[user] < max_requests:
        user_requests[user] += 1
        return "Request allowed"
    else:
        return "Too many requests"

# Call handle_request for 'alice' 4 times and print each result
# Your code here

Need a hint?

Use four print statements calling handle_request('alice') to see the allowed and blocked messages.