Blockchain use cases beyond crypto - Mini Project: Build & Apply

Explore Blockchain Use Cases Beyond Crypto

📖 Scenario: You are working as a developer for a company that wants to explore how blockchain technology can be used beyond cryptocurrencies. Your task is to create a simple Python program that lists some real-world blockchain use cases and filters them based on a category.

🎯 Goal: Build a Python program that stores a dictionary of blockchain use cases with their categories, sets a category filter, selects use cases matching that category using dictionary comprehension, and prints the filtered results.

📋 What You'll Learn

Create a dictionary called use_cases with exact entries of blockchain use cases and their categories

Create a variable called filter_category with the exact string value to filter use cases

Use dictionary comprehension with use_cases.items() to create a filtered dictionary called filtered_use_cases containing only use cases matching filter_category

Print the filtered_use_cases dictionary

💡 Why This Matters

🌍 Real World

Blockchain technology is used in many fields beyond cryptocurrencies, such as securing digital identities, improving supply chains, and managing healthcare records. This project helps understand how to organize and filter such information programmatically.

💼 Career

Understanding how to handle and filter data related to blockchain use cases is useful for roles in blockchain development, data analysis, and technology consulting.

1

DATA SETUP: Create the blockchain use cases dictionary

Create a dictionary called use_cases with these exact entries: 'Supply Chain': 'Logistics', 'Digital Identity': 'Security', 'Healthcare Records': 'Health', 'Voting Systems': 'Governance', 'Real Estate': 'Property'

Blockchain / Solidity

# Create the use_cases dictionary with the given entries
# Your code here

Need a hint?

Use curly braces {} to create a dictionary with keys and values separated by colons.

2

CONFIGURATION: Set the category filter

Create a variable called filter_category and set it to the string 'Security'

Blockchain / Solidity

use_cases = {
    'Supply Chain': 'Logistics',
    'Digital Identity': 'Security',
    'Healthcare Records': 'Health',
    'Voting Systems': 'Governance',
    'Real Estate': 'Property'
}
# Set the filter_category variable to 'Security'
# Your code here

Need a hint?

Assign the string 'Security' to the variable filter_category.

3

CORE LOGIC: Filter use cases by category using dictionary comprehension

Use dictionary comprehension with use_cases.items() to create a new dictionary called filtered_use_cases that contains only the entries where the category equals filter_category

Blockchain / Solidity

use_cases = {
    'Supply Chain': 'Logistics',
    'Digital Identity': 'Security',
    'Healthcare Records': 'Health',
    'Voting Systems': 'Governance',
    'Real Estate': 'Property'
}
filter_category = 'Security'
# Create filtered_use_cases dictionary using dictionary comprehension
# Your code here

Need a hint?

Use {key: value for key, value in dictionary.items() if condition} to filter the dictionary.

4

OUTPUT: Print the filtered use cases

Write a print statement to display the filtered_use_cases dictionary

Blockchain / Solidity

use_cases = {
    'Supply Chain': 'Logistics',
    'Digital Identity': 'Security',
    'Healthcare Records': 'Health',
    'Voting Systems': 'Governance',
    'Real Estate': 'Property'
}
filter_category = 'Security'
filtered_use_cases = {use_case: category for use_case, category in use_cases.items() if category == filter_category}
# Print the filtered_use_cases dictionary
# Your code here

Need a hint?

Use print(filtered_use_cases) to show the filtered dictionary.