product_catalog.py

from product_data import products
# TODO: Step 1 - Print out the products to see the data that you are working with.



# TODO: Step 2 - Create a list called customer_preferences and store the user preference in this list.


response = ""
while response != "N":
    print("Input a preference:")
    preference = input()
    # Add the customer preference to the list

    response = input("Do you want to add another preference? (Y/N): ").upper()
  

# TODO: Step 3 - Convert customer_preferences list to set to eliminate duplicates.



# TODO: Step 4 - Convert the product tags to sets in order to allow for faster comparisons.
converted_products = []




# TODO: Step 5 - Write a function to calculate the number of matching tags
def count_matches(product_tags, customer_tags):
    '''
    Args:
        product_tags (set): A set of tags associated with a product.
        customer_tags (set): A set of tags associated with the customer.
    Returns:
        int: The number of matching tags between the product and customer.
    '''
    pass




# TODO: Step 6 - Write a function that loops over all products and returns a sorted list of matches
def recommend_products(products, customer_tags):
    '''
    Args:
        products (list): A list of product dictionaries.
        customer_tags (set): A set of tags associated with the customer.
    Returns:
        list: A list of products containing product names and their match counts.
    '''
    pass



# TODO: Step 7 - Call your function and print the results




# DESIGN MEMO (write below in a comment):
# 1. What core operations did you use (e.g., intersections, loops)? Why?
# 2. How might this code change if you had 1000+ products?