We’ve already seen a bunch of data types that have been built into Pyret, such as String, Number, Table, and Boolean. We’ve even used our own custom data types, like TimeData and Posn! By creating custom data types, we can describe a piece of data with many components.
Today, we’ll do another design problem that draws on datatypes, tables, and lists.
Beep and Boop have enjoyed their time on Earth so much that they have decided to stick around for a little while longer – congrats on being good hosts! Realizing that the holiday season is arriving soon, Beep and Boop have decided to do their holiday shopping here on Earth, because who doesn’t love receiving exotic, intergalactic gifts?
They head to their favorite online site, https://sunshineshops.beep, which provides its catalogue as an unsophisticated spreadsheet. Beep and Boop start placing orders, but the site produces strange totals and takes a long time to place orders. They use their alien charms to get permission for a closer look at the data organization being used under the hood.
The first thing they notice is that the catalogue spreadsheet gets loaded into a table, but the dimensions are stored as strings rather than in a format that makes it easy to determine item shapes and volumes for shipping purposes. They set out to fix this problem.
Import the catalog google sheet into your program as a table by copying the following lines of code into the Pyret definitions window:
include shared-gdrive("cs111-2018.arr", "1XxbD-eg5BAYuufv6mLmEllyg28IR7HeX")
include gdrive-sheets
import lists as L
import math as M
ssid = "1pNe1SQXe1IGOgI3XyAU4ugk9Ko5T3gzebJZZK-LZ7MM"
data-sheet = load-spreadsheet(ssid)
item-table =
load-table: item-id, item-description, price, weight, dimensions
source: data-sheet.sheet-by-name("Sheet1", true)
end
Create a dimension datatype, and transform the dimensions column of the loaded catalogue table into a dimension value (use transform-column).
NOTE: the original dimensions column is a string formatted as: "w x d x h" (but without the spaces around x)
You’ll want to use the function string-to-number to convert the original dimensions from strings to numbers. Since someone might try to convert a string with characters other than digits, string-to-number returns a special type (called an Option) that signals whether the conversion worked. Here’s how to use string-to-number to extract the number for a string of only digits (note the .value on the end):
>>> string-to-number("42").value
42
Next, Beep and Boop get a peek at how SunshineShops is storing its orders. There is one table created per day with the items that people ordered (orders are bundled together and shipped each evening, so one shipment goes to each person per table). Here is an example:
| name | description | price | count | weight | dimensions |
|---|---|---|---|---|---|
| Anne | Cork Board | 8.29 | 1 | 1.2 | 17x0.8x23 |
| John | Fuzzy Socks | 2.50 | 5 | 0.1 | 9x7x0.5 |
| Ken | Fedora | 16.99 | 2 | 0.1 | 9x9x4 |
| Anne | Printer | 129.99 | 1 | 9.5 | 15.4x11.8x5.7 |
| Anne | Fuzzy Socks | 2.50 | 3 | 0.1 | 9x7x0.5 |
| Ken | Printer | 129.99 | 1 | 9.5 | 15.4x11.8x5.7 |
| John | Lamp | 79.99 | 1 | 2.57 | 10.5x7x20.5 |
| Ken | Fuzzy Socks | 2.50 | 1 | 0.1 | 9x7x0.5 |
| Anne | Gift Card | 40.00 | 1 | 0 | 0 |
| Ken | Gift Card | 20.00 | 2 | 0 | 0 |
Gift cards don’t appear in the catalogue because they are electronic, but people can still include them in their orders.
Beep and Boop, being smart alien scientists (who just found out that they won the science fair, btw!!), are quite unsettled by this method of tracking orders. They know that SunshineShops needs to be able to perform several tasks with their data:
Look at the two tables (catalogue and orders), and keep these tasks in mind as you work on the following problems:
Discuss with your partner the strengths and weaknesses of the current data organization. Write down your main concerns as a collection of brief bullet points.
Spend 5-10 minutes coming up with an alternative proposal for the datatypes, tables, and lists that you might use. Indicate the types of all of your columns, components, and list contents. How does your proposal address each of your concerns from the previous question?
Now, take a look at two of our concrete proposals, listed in this document. Which do you prefer and why?
To get more practice working with datatypes, we will now work with the second of our proposals.
Define the datatypes for each of Order, UserOrder, and ItemData as described in that proposal.
How specifically does this collection of datatypes address the issues that we identified with the original SunshineShops design?
Recreate the information in the above example orders table with your new datatypes (name it orders).
NOTE: you should use all three of the datatypes you defined, in addition to the dimension datatype.
Write a function any-oversized that takes a List<Order> and returns a Boolean indicating whether any single item in the order has a total linear dimension (length + width + height) of more than 40 inches (the same units as the original table).
Write a function more-socks that takes a List<Order> and returns a List<Order> that has the items from the original orders, except each item matching the description “Fuzzy Socks” has its count increased by 1.
Write a function order-cost that takes a List<UserOrder> and a customer name and returns the total price of the items in that person’s orders. Gift-cards cost their amount plus a 50 cent processing fee. Physical items cost the price associated with the item (ignore tax, shipping costs, etc). Assume that the customer is in the list.
Get a copy of the dictionary practice handout from your lab TAs. In lecture on Monday we saw that Pyret doesn’t do substitution; rather, it maintains a dictionary that maps names in your program to values. When Pyret is doing a computation and comes across a name, it looks it up in the dictionary.
This handout has you work through some questions on dictionaries, including extending their use to recursive functions and tables. Our goal with this exercise is to assess your intuitions about dictionaries so we can plan course material going forward.