Unique Collections and Fast Membership Checks¶
Sets help you think about uniqueness instead of order or labels¶
Lists focus on sequence. Dictionaries focus on lookup by key. Sets solve a different problem: you care most about whether a value is present and whether duplicates should collapse into one unique collection.
Core Explanation¶
Sets are useful for:
removing duplicates
testing whether a value exists
comparing overlapping groups
Continuity from dictionaries
Dictionaries answer “what value belongs to this key?” Sets answer “is this value present, and which values are unique or shared?”
customers = {"C001", "C002", "C002", "C003"}
print(customers)
print("C001" in customers)Worked Example: remove duplicates and test membership¶
The code above shows the two main beginner uses of sets at once: duplicate values collapse automatically, and membership checks read clearly with in.
Exercises¶
Create a set of product categories.
Remove duplicates from a small list by converting it to a set.
Explain why sets are good for membership checks.
Give one example where uniqueness matters more than order.
Hint
If you only care whether a value appears and you do not want duplicates, a set is usually a strong fit.
Quick Summary
sets store unique values
sets support efficient membership testing
sets are useful for overlap and uniqueness problems
sets are best when order is not the main concern
Practice Lab¶
Expected output
{101, 102, 103, 104}Expected output
True
2Set Methods¶
Use these short examples to practice one set method at a time.
add()¶
Use add() to place one new value into a set.
update()¶
Use update() to merge several new values into the set.
discard()¶
Use discard() to remove a value without raising an error if it is missing.
remove()¶
Use remove() when the value must exist and you want to delete it.
union()¶
Use union() to combine values from two sets.
intersection()¶
Use intersection() to keep only shared values.
Guided Practice¶
What makes a set different from a list?¶
Why is `len(regions)` equal to 2 in the example?¶
Key Takeaway¶
Sets are the natural choice when uniqueness and membership matter more than position or labels. They make deduplication and overlap checks simple to express.
Deeper Python Set Patterns¶
Adapted for this course from the Python Tutorial data structures chapter.
This section extends the core set idea into patterns you will use often in real Python code:
creating sets from repeated values
set algebra operations such as union and intersection
membership tests
set comprehensions
How to read this section
Focus on the question each pattern answers: remove duplicates, combine groups, find overlap, or build a filtered unique collection.
# Set creation and basic operations
basket = {'apple', 'orange', 'apple', 'pear', 'orange', 'banana'}
print('Unique basket items:', basket)
print('orange in basket?', 'orange' in basket)
a = set('abracadabra')
b = set('alacazam')
print('a:', a)
print('b:', b)
print('Difference (a - b):', a - b)
print('Union (a | b):', a | b)
print('Intersection (a & b):', a & b)
print('Symmetric difference (a ^ b):', a ^ b)
# Set comprehension
comp = {x for x in 'abracadabra' if x not in 'abc'}
print('Comprehension result:', comp)