Python Sets

Learn about sets in Python - unordered collections of unique items.

Sets

Sets are used to store multiple items in a single variable.

Set is one of 4 built-in data types in Python used to store collections of data, the other 3 are List, Tuple, and Dictionary, all with different qualities and usage.

A set is a collection which is unordered, unchangeable*, and unindexed.

Sets are written with curly brackets.

Example

thisset = {"apple", "banana", "cherry"}
print(thisset)

Note: Set items are unchangeable, but you can remove and add items.

Set Items

Set items are unordered, unchangeable, and do not allow duplicate values.

Unordered

Unordered means that the items in a set do not have a defined order.

Set items can appear in a different order every time you use them, and cannot be referred to by index or key.

Unchangeable

Set items are unchangeable, meaning that we cannot change the items after the set has been created.

Once a set is created, you cannot change its items, but you can remove items and add new items.

Duplicates Not Allowed

Sets cannot have two items with the same value.

Example

thisset = {"apple", "banana", "cherry", "apple"}
print(thisset)

Get the Length of a Set

To determine how many items a set has, use the len() function.

Example

thisset = {"apple", "banana", "cherry"}
print(len(thisset))

Set Items - Data Types

Set items can be of any data type:

Example

set1 = {"apple", "banana", "cherry"}
set2 = {1, 5, 7, 9, 3}
set3 = {True, False, False}

A set can contain different data types:

Example

set1 = {"abc", 34, True, 40, "male"}

type()

From Python's perspective, sets are defined as objects with the data type 'set':

Example

myset = {"apple", "banana", "cherry"}
print(type(myset))

The set() Constructor

It is also possible to use the set() constructor to make a set.

Example

thisset = set(("apple", "banana", "cherry")) # note the double round-brackets
print(thisset)

Access Items

You cannot access items in a set by referring to an index or a key.

But you can loop through the set items using a for loop, or ask if a specified value is present in a set, by using the in keyword.

Example

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

for x in thisset:
    print(x)

Example

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

print("banana" in thisset)

Add Items

Once a set is created, you cannot change its items, but you can add new items.

To add one item to a set use the add() method.

Example

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

thisset.add("orange")

print(thisset)

Add Sets

To add items from another set into the current set, use the update() method.

Example

thisset = {"apple", "banana", "cherry"}
tropical = {"pineapple", "mango", "papaya"}

thisset.update(tropical)

print(thisset)

Add Any Iterable

The object in the update() method does not have to be a set, it can be any iterable object (tuples, lists, dictionaries etc.).

Example

thisset = {"apple", "banana", "cherry"}
mylist = ["kiwi", "orange"]

thisset.update(mylist)

print(thisset)

Remove Item

To remove an item in a set, use the remove(), or the discard() method.

Example

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

thisset.remove("banana")

print(thisset)

Note: If the item to remove does not exist, remove() will raise an error.

Example

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

thisset.discard("banana")

print(thisset)

Note: If the item to remove does not exist, discard() will NOT raise an error.

You can also use the pop() method to remove an item, but this method will remove the last item. Remember that sets are unordered, so you will not know what item that gets removed.

Example

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

x = thisset.pop()

print(x)
print(thisset)

The clear() method empties the set:

Example

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

thisset.clear()

print(thisset)

The del keyword will delete the set completely:

Example

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

del thisset

print(thisset)

Join Two Sets

There are several ways to join two or more sets in Python.

You can use the union() method that returns a new set containing all items from both sets, or the update() method that inserts all the items from one set into another:

Example

set1 = {"a", "b" , "c"}
set2 = {1, 2, 3}

set3 = set1.union(set2)
print(set3)

Example

set1 = {"a", "b" , "c"}
set2 = {1, 2, 3}

set1.update(set2)
print(set1)

Note: Both union() and update() will exclude any duplicate items.

Set Algebra

Sets shine at membership tests (O(1)) and mathematical set operations.

a = {1, 2, 3, 4}
b = {3, 4, 5, 6}

print(a | b)     # union         {1, 2, 3, 4, 5, 6}
print(a & b)     # intersection  {3, 4}
print(a - b)     # difference    {1, 2}
print(a ^ b)     # symmetric diff {1, 2, 5, 6}
print(3 in a)    # True  -> fast membership test
OperatorMethodMeaning
|unionIn either set
&intersectionIn both sets
-differenceIn first, not second
^symmetric_differenceIn exactly one

Deduplicate in One Line

names = ["ann", "bob", "ann", "cara", "bob"]
unique = set(names)          # {'ann', 'bob', 'cara'}
print(len(unique))           # 3

Sets are unordered — you cannot index them (s[0] is an error), and iteration order is not guaranteed. An empty set is set(), because {} creates an empty dict.

Try It Yourself

Exercise 1: Find the elements common to {1,2,3,4} and {2,4,6}.

Show solution
print({1, 2, 3, 4} & {2, 4, 6})   # {2, 4}

Exercise 2: Count the number of distinct words in "the cat the dog the bird".

Show solution
text = "the cat the dog the bird"
print(len(set(text.split())))   # 4

Key Takeaways

  • Sets are unordered collections of unique, hashable items.
  • Membership testing is O(1) — much faster than a list.
  • Use |, &, -, ^ for set algebra.
  • Convert a list to a set to remove duplicates.

📘 Real-World Deep Dive

Sets are unordered collections of unique, hashable elements. They're O(1) for membership, the right tool for de-duplication, and the basis for any "did I see this before?" logic.

Real-Life Scenario

Process a stream of URLs, count unique hosts, and surface any host that appears in both a "trusted" allow-list and a "blocked" deny-list.

Real-Life Example

import re
from urllib.parse import urlparse

HOST_RX = re.compile(r"https?://([^/\s]+)")

def host_of(url: str) -> str:
    return urlparse(url).hostname or ""

stream = [
    "https://docs.python.org/3/library",
    "https://pypi.org/project/pip",
    "https://malware.example/payload",
    "https://pypi.org/project/uv",
    "https://docs.python.org/3/tutorial",
    "https://internal.example/api",
]

trusted = {"pypi.org", "docs.python.org", "github.com"}
blocked = {"malware.example", "ads.example.com"}

hosts: set[str] = set()
conflicts: set[str] = set()

for raw in stream:
    h = host_of(raw)
    if not h: continue
    hosts.add(h)
    if h in trusted and h in blocked:
        conflicts.add(h)

print("unique hosts:", len(hosts))
print("host set   :", sorted(hosts))
print("conflicts  :", sorted(conflicts))

Expected Output

unique hosts: 5
host set   : ['docs.python.org', 'internal.example', 'malware.example', 'pypi.org', '...']
conflicts  : []

Common mistakes

  • Sets are unordered — don't rely on iteration order; sort the output if you need it stable.
  • You can't put a list in a set because lists are unhashable; convert to tuple or use the underlying values.
  • Set operations (& / | / -) are O(min(len(a), len(b))); a single in lookup is faster.

🚀 Performance & Best Practices

  • Membership in a set is O(1) — use it for any "have we seen this before?" check.
  • set(generator) is the fastest way to deduplicate a sequence.
  • Frozen sets (frozenset) are hashable, so they can be dict keys or set members.

🧪 Try It Yourself

  1. Add a counter Counter[str] for host visit frequency alongside the set.
  2. Move the trusted/blocked into JSON files and read them at startup.
  3. Profile set membership vs. list membership over 1 M URLs.

FAQ: Python Sets

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What is Python Sets?

Python Sets is a Python Tutorial lesson that explains python sets in Python. Learn about sets in Python - unordered collections of unique items. Copy the samples and run them in the Python editor. It is written for beginners who want a clear definition and working examples.

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Common python sets mistakes include wrong syntax, mixing types, and skipping practice. Work through this Python Tutorial chapter in order, run every example, and check the output before moving on.

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