Sets in Python

A set is a collection that holds only unique items, with no duplicates and no fixed order. You write it with curly braces:

numbers = {1, 2, 3, 3, 2, 1}
print(numbers)        # {1, 2, 3} — duplicates removed automatically

That automatic de-duplication is the headline feature. Sets are also fast at checking "is this item present?". Let's explore.

Creating sets

Use curly braces with comma-separated items, or the set() function. There's one catch: an empty {} makes a dictionary, not a set — so use set() for an empty one:

fruits = {"apple", "banana", "cherry"}

empty_set = set()        # correct way to make an empty set
not_a_set = {}           # this is an empty DICTIONARY!

# Turn a list into a set (great for removing duplicates)
nums = [1, 2, 2, 3, 3, 3]
unique = set(nums)
print(unique)            # {1, 2, 3}

Adding and removing

colours = {"red", "green"}

colours.add("blue")          # add one item
print(colours)               # {'red', 'green', 'blue'}

colours.discard("green")     # remove if present (no error if missing)
colours.remove("red")        # remove, but errors if missing

print(colours)               # {'blue'}

Use .discard() when you're not sure the item exists — unlike .remove(), it won't crash on a missing item.

Sets have no order or index

Because sets are unordered, you cannot access items by position. my_set[0] raises an error. You can only check membership or loop over them:

fruits = {"apple", "banana", "cherry"}

# Membership check — this is very fast
print("apple" in fruits)     # True
print("mango" in fruits)     # False

# Looping works, but order is not guaranteed
for fruit in fruits:
    print(fruit)

Set operations: the real superpower

Sets shine when comparing groups. Python supports the same operations you learned in maths:

maths = {"Asha", "Ravi", "Meena"}
science = {"Ravi", "Meena", "Kiran"}

# Union: everyone in either class
print(maths | science)       # {'Asha', 'Ravi', 'Meena', 'Kiran'}

# Intersection: students in BOTH classes
print(maths & science)       # {'Ravi', 'Meena'}

# Difference: in maths but NOT in science
print(maths - science)       # {'Asha'}

# Symmetric difference: in one class but not both
print(maths ^ science)       # {'Asha', 'Kiran'}

These read almost like English and replace what would otherwise be messy loops.

A practical example

# Find common interests between two people

asha_likes = {"coding", "music", "cricket", "reading"}
ravi_likes = {"cricket", "movies", "coding", "gaming"}

# What do they have in common?
common = asha_likes & ravi_likes
print(f"Shared interests: {common}")
# Shared interests: {'coding', 'cricket'}

# What's unique to Asha?
only_asha = asha_likes - ravi_likes
print(f"Only Asha likes: {only_asha}")

Common mistakes

• Using {} for an empty set: {} creates an empty dictionary. Use set() instead.
• Expecting order: Sets don't keep insertion order. Don't rely on items printing in any particular sequence; if order matters, use a list.
• Indexing a set: my_set[0] raises a TypeError. Sets have no positions.
• .remove() on a missing item: It raises a KeyError. Use .discard() if the item may not be there.
• Putting unhashable items in a set: A set can't contain lists or other sets (they're mutable). It can hold numbers, strings, and tuples.

FAQ

When should I use a set instead of a list? Use a set when you need unique items, fast membership tests, or set maths (union/intersection). Use a list when order matters or duplicates are allowed.

How do I remove duplicates from a list but keep order? Convert to a set and back loses order. To keep order, use list(dict.fromkeys(my_list)), which preserves first-seen order while dropping duplicates.

Is there an immutable set? Yes — frozenset() creates a set that can't be changed, useful as a dictionary key or set member.

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Sets round out Python's core collections alongside Lists in Python and Dictionaries in Python. Browse everything on the Python learning hub.

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