In the previous blog, we got to know about Python’s other data structure “Tuples↖︎”. In this blog, we will discuss “Set”.

Let’s get started.

What is a Python Set?

Imagine we’re organizing a party. We make a guest list, but realize… we accidentally wrote some names twice!
This is where sets come in — they automatically remove duplicates and help keep things neat.

In Python, a set is just a bag of unique items. No duplicates, and the order doesn’t matter.

Properties of a Set in Python

1. Unordered

Sets do not maintain any specific order of elements.

s = {3, 1, 4, 2}
print(s)  # Output might be: {1, 2, 3, 4} or any order

2. No Duplicates Allowed

Sets automatically eliminate duplicate values.

s = {1, 2, 2, 3, 4, 4}
print(s)  # Output: {1, 2, 3, 4}

3. Mutable (Changeable)

We can add or remove elements from a set.

Hashable:
Has a fixed (unchanging) value (i.e., it's immutable).

unhashable:
Unhashable means an object that do not have hash value , mutable. Set is unhashable.

s = {1, 2}
s.add(3)      # Adds 3 to the set
s.remove(2)   # Removes 2 from the set
print(s)      # Output: {1, 3}

4. No Indexing or Slicing

Since sets are unordered, we can't access elements by index.

s = {1, 2, 3}
# s[0] → will raise TypeError

5. Supports Set Operations

We can do mathematical set operations like union, intersection so on.

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

print(a | b)  # Union: {1, 2, 3, 4, 5}
print(a & b)  # Intersection: {3}
print(a - b)  # Difference: {1, 2}

6. Dynamic Size

Sets can grow or shrink as elements are added or removed.

s = set()
s.add("apple")
s.add("banana")
s.remove("apple")

Python Built-in Functions:

Function	Description
`len()`	Get the length of the iterable.
`type()`	Get the type of object.
`str()`, `int()`, `float()`	Convert to string, integer, or float.
`list()`, `set()`, `tuple()`	Convert to list, set, tuple.
`range()`	Create a range of numbers.
`sum()`	Return the sum of iterable.
`max()`, `min()`	Return the largest/smallest item.
`sorted()`	Return a sorted list from an iterable.
`input()`	Read input from the user.
`abs()`	Return the absolute value.
`round()`	Round a number.
`enumerate()`	Return index-item pairs.
`zip()`	Combine two or more iterables.
`map()`	Apply a function to each item.
`filter()`	Filter items using a condition.
`all()`, `any()`	Return True if all/any are True.
`dir()`	List attributes/methods of the object.
`help()`	Show help for the object.

Let’s explore all the set methods in python:

https://www.w3schools.com/Python/python_ref_set.asp

Let’s explore properties of List, Tuple, Set in Python:

Property	List	Tuple	Set
Mutability	Mutable	Immutable	Mutable (elements must be immutable)
Indexing	Supports indexing	Supports indexing	No indexing
Duplicates	Allows duplicates	Allows duplicates	No duplicates
Order	Ordered (since Python 3.7)	Ordered	Ordered (since Python 3.7)*
Syntax	`[1, 2, 3]`	`(1, 2, 3)`	`{1, 2, 3}`

Here are some code snippets in Colab about Python List:

https://colab.research.google.com/drive/13hEY4OCPHisY57tt1RO07PHRdVheeAdK?usp=sharing

Conclusion on Python Sets:

Python sets are powerful, built-in data structures used to store unordered, mutable, and unique elements. They are ideal for operations involving membership testing, removing duplicates, and performing standard mathematical set operations such as union, intersection, and difference.

With a rich collection of built-in methods, sets make tasks like filtering, combining datasets, and comparing collections efficient and readable. Their performance and simplicity make them a valuable tool for any Python programmer.

Hope you enjoyed reading this blog and gained some useful insights from it!

Sets in Python – Built-in Duplicate Bouncer