Why caching reduces server load in Rest API - See It in Action

Why caching reduces server load

📖 Scenario: You are building a simple REST API server that returns user profile data. To make the server faster and reduce the work it does, you want to use caching.

🎯 Goal: Build a simple REST API that caches user data to reduce server load by avoiding repeated data fetching.

📋 What You'll Learn

Create a dictionary called user_data with exact user profiles

Create a variable called cache to store cached results

Write a function called get_user_profile that checks cache before fetching from user_data

Print the profile data for user "alice" twice to show caching in action

💡 Why This Matters

🌍 Real World

Caching is used in real web servers to speed up responses and reduce the work the server must do for repeated requests.

💼 Career

Understanding caching helps backend developers optimize APIs and improve user experience by making apps faster and more efficient.

1

DATA SETUP: Create user data dictionary

Create a dictionary called user_data with these exact entries: 'alice': {'age': 30, 'city': 'New York'}, 'bob': {'age': 25, 'city': 'Los Angeles'}, and 'carol': {'age': 27, 'city': 'Chicago'}.

Rest API

# Create the user_data dictionary with exact entries
# Your code here

Need a hint?

Use curly braces to create a dictionary with keys 'alice', 'bob', and 'carol'. Each key maps to another dictionary with keys 'age' and 'city'.

2

CONFIGURATION: Create cache dictionary

Create an empty dictionary called cache to store cached user profiles.

Rest API

user_data = {
    'alice': {'age': 30, 'city': 'New York'},
    'bob': {'age': 25, 'city': 'Los Angeles'},
    'carol': {'age': 27, 'city': 'Chicago'}
}

# Create an empty cache dictionary
# Your code here

Need a hint?

Use empty curly braces to create an empty dictionary called cache.

3

CORE LOGIC: Write caching function

Write a function called get_user_profile that takes a parameter username. Inside the function, first check if username is in cache. If yes, return the cached data. Otherwise, get the data from user_data, store it in cache, then return it.

Rest API

user_data = {
    'alice': {'age': 30, 'city': 'New York'},
    'bob': {'age': 25, 'city': 'Los Angeles'},
    'carol': {'age': 27, 'city': 'Chicago'}
}

cache = {}

# Define get_user_profile function with caching logic
# Your code here

Need a hint?

Use if username in cache to check cache. Use user_data.get(username) to get data if not cached.

4

OUTPUT: Print cached results

Print the result of calling get_user_profile with 'alice' twice to show caching reduces repeated data fetching.

Rest API

user_data = {
    'alice': {'age': 30, 'city': 'New York'},
    'bob': {'age': 25, 'city': 'Los Angeles'},
    'carol': {'age': 27, 'city': 'Chicago'}
}

cache = {}

def get_user_profile(username):
    if username in cache:
        return cache[username]
    else:
        profile = user_data.get(username)
        cache[username] = profile
        return profile

# Print user profile for 'alice' twice
# Your code here

Need a hint?

Use print(get_user_profile('alice')) twice to show the cached data is returned both times.