ISF DP Computer Science

ADT: Sets #

In this lab we are going to introduce Abstract Data Types (ADTs), and specifically Sets.

Syllabus Topics [HL] #

  • B4.1.5 Construct and apply sets as an ADT

Key Vocabulary #

WordDefinition
Abstract Data Type (ADT)A model that defines operations and behavior for a data structure, without defining how these operations are implemeneted.
SetStores unordered, mutable, and unique values.
MutableData that can be changed after its been initialized
CastingConvert a variable from one data type to another

[0] What is a Set? #

A Set is an abstract data type that stores multiple items. It is unordered, mutable, and unindexable.

📖 Set Methods

# add
myset = {'apples','bananas', 'grapes'}
myset.add('pears') 
# myset = {'apples','bananas', 'grapes', 'pears'}

# remove
myset = {'apples','bananas', 'grapes'}
myset.remove('grapes') 
# myset = {'apples','bananas'}

# check if in 
myset = {'apples','bananas', 'grapes'}
'apples' in myset  # return True
'lemons' in myset  # return False

# number of items in a set
myset = {'apples','bananas', 'grapes'}
len(myset)  #returns 3

# loop through a set
myset = {'apples','bananas', 'grapes'}
for fruit in myset:
  print(fruit)

# create an empty set
myset = set()

📖 Set Operations

# union
a = {1,2,3,4}
b = {3,4,5,6}
unioin_set = a | b
# union_set = {1,2,3,4,5,6}

# intersection
a = {1,2,3,4}
b = {3,4,5,6}
interesection_set = a & b
# intersection_set = {3, 4}

# difference
a = {1,2,3,4}
b = {3,4,5,6}
difference_set = a - b
# difference_set = {1,2}

# subset
a = {1,2}
b = {1,2,3,4}
print(a.issubset(b)) # True

print(b.issubset(a)) # False

# superset
print(b.issuperset(a)) # True
print(a.issuperset(b)) # False

# To cast a List to a Set
fruit = ['apples', 'organges', 'peaches', 'apples']
set(fruit)

💻 Practice using Set methods and operations with exercises HERE

[1] Set up #

💻 Go to your dpcs/unit00_strings folder.

cd ~/desktop/dpcs/unit00_strings/

💻 Clone your repo. This will copy it onto your computer. Be sure to replace yourgithubusername, to your actual username. e.g. https://github.com/isf-dp-cs/lab_sets_brittegenzlinger

git clone https://github.com/isf-dp-cs/lab_sets_yourgithubusername
💻 In the Terminal, type the following command to open the lab folder.
cd lab_sets_yourgithubusername

💻 Enter the Poetry Shell to start the lab. As a reminder, we will run this command at the start of each lab, but only when we are inside a lab folder.

poetry shell
👾 💬 Exiting the poetry shell

When you want to exit the shell, you can type exit or ^D

[2] Music Playlists #

Sets are particularly useful for determining what is similar and what is different in sets of data. In this lab you will compare and contrast 10 individuals’ favorite music.

💻 In set_music_examples follow along and complete each TODO item. They get more challenging as you work from top to bottom. It can help to write out a mini example on a whiteboard/notebook. ✅ Check your answers with a friend. When you’re confident, check with a teacher.

[3] Deliverables #

⚡✨ Once you complete the lab, be sure to complete these two steps:

📋 Update Syllabus Tracker: Go to your Syllabus Content Checklist in your Google Drive and update it accordingly.

💻 Push your work to Github

  • git status
  • git add -A
  • git status
  • git commit -m "describe your code here"
  • git push
  • git remote

[4] Solutions #