6. Lighthouse

Level 3 · Update the stock sheet

From Debra Marshall, Warehouse Manager

“Quick stock update: 20 Brass Floor Lamps just arrived, we sold 5 Oak Side Tables this morning, and we've started carrying a Stoneware Mug Set, 48 in stock.”

Your goal

Update stock so Brass Floor Lamp goes up by 20, Oak Side Table goes down by 5, and a new key 'Stoneware Mug Set' holds 48. Set result to the updated dictionary (all four products).

  • Store a dict in result

Your code

Python

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    ResultPress Run to see yours

    Mote checks your result

    Press Run. Each row that matches the goal becomes a firefly in your lantern.

    The lesson

    Looking things up by name

    A list finds items by position. A dictionary (dict) finds them by a key that you choose. It’s written with curly braces and key: value pairs:

    stock = {
    "Oak Side Table": 14,
    "Brass Floor Lamp": 0,
    "Linen Throw Pillow": 37,
}

stock["Oak Side Table"]     # 14

    Think of it as a two-column lookup table. Keys are unique: one product, one stock count. Keys are usually strings or numbers; values can be anything, including lists or other dictionaries.

    Changing and adding

    Assigning to a key updates it if it exists and adds it if it doesn’t:

    stock["Brass Floor Lamp"] = 20      # update
stock["Oak Side Table"] -= 5        # change relative to the current value
stock["Stoneware Mug Set"] = 48     # new key

    del stock["Linen Throw Pillow"] removes a key, and "Oak Side Table" in stock checks whether a key exists (True or False).

    Missing keys

    Reading a key that doesn’t exist raises a KeyError:

    stock["Walnut Bookshelf"]       # KeyError: 'Walnut Bookshelf'

    When a key might be missing, use .get, which returns a default instead of failing:

    stock.get("Walnut Bookshelf", 0)   # 0
stock.get("Oak Side Table", 0)     # 9 after the sale

    .get is the safe way to read data you didn’t create yourself, such as an API response or a row from a file where some fields may be absent.

    Looping over a dictionary

    .items() gives you each key and value together, which is the loop you’ll write most:

    for product, count in stock.items():
    if count == 0:
        print(f"{product} is out of stock")

    .keys() and .values() give just one side, so sum(stock.values()) is the total number of units on hand.

    Order and equality

    Since Python 3.7, dictionaries remember the order you inserted keys, which makes printed output predictable. Two dictionaries are equal when they hold the same keys with the same values, regardless of order, so {"a": 1, "b": 2} == {"b": 2, "a": 1} is True.

    Why analysts care

    Dictionaries show up everywhere: a row of data, a JSON record from a web API, a mapping from codes to labels ({"WEB": "web", "APP": "app"}), a set of parameters for a function. pandas uses them too, for example to rename columns or to map values in a column.

    Common mistakes

    • Using square brackets to read a key that may not exist. Use .get with a default.
    • Typos in keys. "Oak side table" is a different key from "Oak Side Table", so assigning to it quietly creates a fourth product.
    • Expecting result = stock to make a copy. Both names point at the same dictionary, so a later change to stock also shows up in result. Use stock.copy() when you need a separate one.