Tell how the product structure was organized in Magnit — catalog, search?

In Magnit, the product structure is usually organized as a hierarchical catalog with several levels: categories, subcategories, and the products themselves. Each category contains a set of attributes that help filter and sort products.

Search is implemented using full-text search and attribute filters (e.g., brand, price, weight). Indexes are used to speed up search, as well as caching popular queries. In some cases, ElasticSearch or similar engines are used for fast and relevant search over large volumes of data.

An example of a simplified catalog structure in Python:

catalog = {
    'Grocery': {
        'Cereals': ['Rice', 'Buckwheat', 'Oatmeal'],
        'Pasta': ['Spaghetti', 'Penne']
    },
    'Dairy Products': {
        'Milk': ['Milk 1L', 'Milk 2L'],
        'Cheeses': ['Russian', 'Parmesan']
    }
}

# Search for a product
search_query = 'Rice'
found = [item for category in catalog.values() for subcat in category.values() for item in subcat if search_query.lower() in item.lower()]
print(found)  # ['Rice']