# Python Set – A Complete Guide to Get Started Quickly

In this class, you’ll discover what a Python Set is, what can you do with it and how to use it in programs. Moreover, you’ll essentially learn how to create a Set, add/remove elements in it and all other operations that you can execute using Sets in Python.

## Python Set – Introduction

A set is a term which originates from Mathematics. It is a collection type which can store elements of different data types but doesn’t index them in a particular order.

A Python Set has the following properties.

• The elements don’t have a specific order, hence, shall exist in a random style.
• Each item is unique in a Set and therefore, can’t have duplicates.
• The elements are immutable and hence, can’t accept changes once added.
• A set is itself mutable and allows addition or deletion of items.

With Sets, we can execute several mathematical operations such as Union, Intersection, Symmetric Difference, and Complement.

Python Set – A Complete Guide to Get Started

### How to instantiate a Set in Python?

You can invoke any of the following two methods to create a Python Set.

1. If you have a fixed set of elements, then group them using a comma as the separator and enclose the group inside curly braces.
2. Another way is to call the built-in “set()” method which can also be used to add elements at run-time.

Also, remember, the elements can be of any types such as an integer, a float, a tuple, or strings, etc. The only exception with a Set is that it can’t store a mutable item such as a list, a set or a dictionary.

# create a set of numbers
py_set_num = {3, 7, 11, 15}
print(py_set_num)

# create a set of mixed data types
py_set_mix = {11, 1.1, "11", (1, 2)}
print(py_set_mix)

Executing the above code will return the following output.

# output
{3, 11, 7, 15}
{(1, 2), 1.1, 11, '11'}

Follow one more examples of Python Set to gain more clarity.

# set can't store duplicate elements
py_set_num = {3, 7, 11, 15, 3, 7}
# it'll automatically filter the duplicates
print(py_set_num)

# create a set using the set() method
# creating set with a fixed set of elements
py_set_mix = set([11, 1.1, "11", (1, 2)])
print(py_set_mix)

# creating set with dynamic elements
py_list = [11, 1.1, "11", (1, 2)]
py_list.append(12)
print(py_list)
py_set_mix = set(py_list)
print(py_set_mix)

Check out the result of above code after execution.

# output
{11, 3, 15, 7}
{(1, 2), 1.1, 11, '11'}
[11, 1.1, '11', (1, 2), 12]
{(1, 2), 1.1, 11, '11', 12}

Let’s now do one more test with sets. We’ll no try to create an empty Python Set.

# Let's try to create an empty Python set
py_set_num = {}
print("The value of py_set_num:", py_set_num)
print("The type of py_set_num:", type(py_set_num))

py_set_num = set()
print("The value of py_set_num:", py_set_num)
print("The type of py_set_num:", type(py_set_num))

Here is the explanation of the above code.

The first statement would result in the creation of a dictionary object instead of creating a set. You can’t just use curly braces and expect a “Set” in return.

While in the next non-print statement, we used the set() function but didn’t pass any argument to it. It will eventually return us an empty Set object.

Please refer the below output of the last example.

# output
The value of py_set_num: {}
The type of py_set_num: <class 'dict'>
The value of py_set_num: set()
The type of py_set_num: <class 'set'>

### How to modify a Set in Python?

Python Set is a mutable object. However, it doesn’t use any indexing, and hence it doesn’t have any order.

It also means that you can’t change its elements by accessing through an index or via slicing.

However, there are Set methods like the add() which adds a single element and the update() which can add more than one item.

The update() method can even accept tuples, lists, strings or other sets as an argument. However, the duplicate elements will automatically get excluded.

# Let's try to change a Python set
py_set_num = {77, 88}

try:
print(py_set_num[0])
except Exception as ex:
print("Error in py_set_num[0]:", ex)

print("The value of py_set_num:", py_set_num)

# Let's add an element to the set
print("The value of py_set_num:", py_set_num)

# Let's add multiple elements to the set
py_set_num.update([44, 55, 66])
print("The value of py_set_num:", py_set_num)

# Let's add a list and a set as elements
py_set_num.update([4.4, 5.5, 6.6], {2.2, 4.4, 6.6})
print("The value of py_set_num:", py_set_num)

In the above example, the first line is demonstrating that a set doesn’t allow indexing. We’ve kept that code inside the try-except block so that we can catch the error, print it, and continue with rest of the execution.

In the next section of the example, you can see the Set’s add() and update() methods in action.

Now, check out the output of the above Python Set example.

# output
Error in py_set_num[0]: 'set' object does not support indexing
The value of py_set_num: {88, 77}
The value of py_set_num: {88, 99, 77}
The value of py_set_num: {66, 99, 44, 77, 55, 88}
The value of py_set_num: {66, 99, 4.4, 5.5, 6.6, 2.2, 44, 77, 55, 88}

### How to delete single or multiple elements from a set in Python?

You can use the following Set methods to delete elements from it.

2. Remove() method

There is a small difference in the way these two methods operate. The discard() method doesn’t throw any error if the target item is not the part of the set.

On the contrary, the remove() method will throw the “KeyError” error in such a case.

Follow the below example to get more clarity.

# Let's try to use a Python set
py_set_num = {22, 33, 55, 77, 99}

# discard an element from the set

# remove an element from the set
py_set_num.remove(77)
print("py_set_num.remove(77):", py_set_num)

# discard an element not present in the set

# remove an element not present in the set
try:
py_set_num.remove(44)
except Exception as ex:
print("py_set_num.remove(44) => KeyError:", ex)

It’ll generate the following result.

# output
py_set_num.remove(77): {33, 22, 55}
py_set_num.remove(44) => KeyError: 44

Apart from the methods, you’ve so far seen, there is a pop() method to remove an element.

Also, since the Set doesn’t use indexing, so you can’t be sure which of the item would get popped. It’ll randomly pick one element and remove it.

There is also a clear() method which can flush everything from a Set object.

# Let's use the following Python set
py_set_num = {22, 33, 55, 77, 99}
print("py_set_num:", py_set_num)

# pop an element from the set
py_set_num.pop()
print("py_set_num.pop():", py_set_num)

# pop one more element from the set
py_set_num.pop()
print("py_set_num.pop():", py_set_num)

# clear all elements from the set
py_set_num.clear()
print("py_set_num.clear():", py_set_num)

Thie example will produce the following result.

# output
py_set_num: {33, 99, 77, 22, 55}
py_set_num.pop(): {99, 77, 22, 55}
py_set_num.pop(): {77, 22, 55}
py_set_num.clear(): set()

## Python Set – Native Operations

Like in mathematics, the set supports operations like union, intersection, difference, and complement so does it in Python.

There are methods as well as operators available to perform the set operations.

For the illustration purpose, we will use the following two sets in the next examples.

# We'll use the setA and setB for our illustration
setA = {'a', 'e', 'i', 'o', 'u', 'g', 'h'}
setB = {'a', 'e', 'z', 'b', 't', 'o', 'u'}

### Union operation

Union of setA and setB is a new set combining all the elements from both the Sets.

Python Set – Union

The “|” operator is the one to perform the union operation on the sets.

# We'll use the setA and setB for our illustration
setA = {'a', 'e', 'i', 'o', 'u', 'g', 'h'}
setB = {'a', 'e', 'z', 'b', 't', 'o', 'u'}

print("Initial setA:", setA, "size:", len(setA))
print("Initial setB:", setB, "size:", len(setB))

print("(setA | setB):", setA | setB, "size:", len(setA | setB))

We’ve used the Len() method to calculate the length of the set. The output of this examples is as follows.

# output
Initial setA: {'u', 'i', 'g', 'o', 'e', 'h', 'a'} size: 7
Initial setB: {'u', 'z', 'b', 'o', 'e', 'a', 't'} size: 7
(setA | setB): {'h', 'u', 'z', 'b', 't', 'g', 'o', 'e', 'i', 'a'} size: 10

You can also accomplish the similar results using the union() method.

# Python set example using the union() method
setA = {'a', 'e', 'i', 'o', 'u', 'g', 'h'}
setB = {'a', 'e', 'z', 'b', 't', 'o', 'u'}

print("setA.union(setB):", setA.union(setB), "size:", len(setA.union(setB)))
print("setB.union(setA):", setB.union(setA), "size:", len(setB.union(setA)))

You can apply the union() method on any of the set (i.e., set A or B); the output will remain the same.

# output
setA.union(setB): {'a', 'o', 'e', 'b', 'u', 't', 'i', 'g', 'z', 'h'} size: 10
setB.union(setA): {'a', 'o', 'e', 'b', 'u', 't', 'i', 'g', 'z', 'h'} size: 10

### Intersection operation

The intersection of setA and setB will produce a set comprising common elements in both the Sets.

Python Set – Intersection

You can use Python’s “&” operator to perform this operation.

# Python intersection example using the & operator
setA = {'a', 'e', 'i', 'o', 'u', 'g', 'h'}
setB = {'a', 'e', 'z', 'b', 't', 'o', 'u'}

print("Initial setA:", setA, "size:", len(setA))
print("Initial setB:", setB, "size:", len(setB))

print("(setA & setB):", setA & setB, "size:", len(setA & setB))

This example will produce the following result.

# output
Initial setA: {'e', 'o', 'h', 'a', 'g', 'u', 'i'} size: 7
Initial setB: {'b', 'e', 't', 'o', 'z', 'a', 'u'} size: 7
(setA & setB): {'o', 'a', 'u', 'e'} size: 4

Alternatively, you can call the intersection() method perform this operation.

# Python set example using the intersection() method
setA = {'a', 'e', 'i', 'o', 'u', 'g', 'h'}
setB = {'a', 'e', 'z', 'b', 't', 'o', 'u'}

intersectAB = setA.intersection(setB)
print("setA.intersection(setB):", intersectAB, "size:", len(intersectAB))
intersectBA = setB.intersection(setA)
print("setB.intersection(setA):", intersectBA, "size:", len(intersectBA))

This example will produce the following result.

# output
setA.intersection(setB): {'a', 'u', 'e', 'o'} size: 4
setB.intersection(setA): {'a', 'u', 'e', 'o'} size: 4

### Difference Operation on the Set

When you perform the difference operation on two Sets, i.e., <setA – setB>,  the resultant will be a set of elements that exist in the left but not in the right object.

Python Set – Difference

Likewise, the operation <setB – setA> will return those elements of setB which don’t exist in the setA.

You can use the minus (-) operator to carry out this operation.

# Python set's difference operation
setA = {'a', 'e', 'i', 'o', 'u', 'g', 'h'}
setB = {'a', 'e', 'z', 'b', 't', 'o', 'u'}

diffAB = setA - setB
print("diffAB:", diffAB, "size:", len(diffAB))
diffBA = setB - setA
print("diffBA:", diffBA, "size:", len(diffBA))

There are three unique elements in both of our input sets which don’t exist in another. Check the output below.

# output
diffAB: {'i', 'g', 'h'} size: 3
diffBA: {'z', 'b', 't'} size: 3

The next example will demonstrate the same set operation using the difference() method.

# Python set's difference operation using the difference() method
setA = {'a', 'e', 'i', 'o', 'u', 'g', 'h'}
setB = {'a', 'e', 'z', 'b', 't', 'o', 'u'}

diffAB = setA.difference(setB)
print("diffAB:", diffAB, "size:", len(diffAB))
diffBA = setB.difference(setA)
print("diffBA:", diffBA, "size:", len(diffBA))

The execution of the above example would produce the below output.

# output
diffAB: {'i', 'g', 'h'} size: 3
diffBA: {'b', 't', 'z'} size: 3

### Symmetric Difference operation on the Set

The symmetric difference of two sets will generate a set of elements which exist in <setA> and <setB> but not in both.

Python Set – Symmetric Difference

You can execute this operation with the help of caret operator (^) in Python.

# Python set example using the caret ^ operator
setA = {'a', 'e', 'i', 'o', 'u', 'g', 'h'}
setB = {'a', 'e', 'z', 'b', 't', 'o', 'u'}

symdiffAB = setA^setB
print("symdiffAB:", symdiffAB, "size:", len(symdiffAB))
symdiffBA = setB^setA
print("symdiffBA:", symdiffBA, "size:", len(symdiffBA))

The output is as follows.

symdiffAB: {'z', 't', 'h', 'g', 'b', 'i'} size: 6
symdiffBA: {'z', 'h', 'g', 't', 'b', 'i'} size: 6

You can also get the operation done with the method symmetric_difference().

# Python set example using the symmetric_difference() method
setA = {'a', 'e', 'i', 'o', 'u', 'g', 'h'}
setB = {'a', 'e', 'z', 'b', 't', 'o', 'u'}

symdiffAB = setA.symmetric_difference(setB)
print("symdiffAB:", symdiffAB, "size:", len(symdiffAB))
symdiffBA = setB.symmetric_difference(setA)
print("symdiffBA:", symdiffBA, "size:", len(symdiffBA))

The result is as follows.

# result
symdiffAB: {'z', 'h', 'i', 'g', 't', 'b'} size: 6
symdiffBA: {'z', 'i', 'g', 'b', 't', 'h'} size: 6

## Miscellaneous Set Operations

### How to access data elements in a Set?

It’s not possible to access an element directly in a set. But you can fetch all of them together. You need a loop to retrieve a list of particular items over the Set.

# Python set example to access elements from a set
basket = set(["apple", "mango", "banana", "grapes", "orange"])

print(fruit)

After executing the above code, you’ll see the following output.

# output
apple
banana
mango
orange
grapes

### How to perform membership test in a Set?

You can surely check if a set contains a particular element or not. You can make use of the “in” keyword for this purpose.

# Python set example to test elements in a set
basket = set(["apple", "mango", "banana", "grapes", "orange"])

# confirm if 'apple' is in the basket

# confirm if 'grapes' is in the basket

After executing the above code, you’ll see the following output.

# output
Is 'apple' in the basket? True
Is 'watermelon' in the basket? False

## Frozen Sets in Python

It is a unique type of set which is immutable and doesn’t allow changing its elements after assignment.

It supports all methods and operators applicable to a set but those that don’t alter its content.

As you now know that the sets are mutable and thus become unhashable. So, we can’t use them as keys for a Python dictionary. On the contrary, the Frozen Set is by default hashable and can work as keys to a dictionary.

You can create a Frozen set with the help of the following function.

frozenset()

Also, the following Python methods can work with the Frozen set.

copy()
difference()
intersection()
isdisjoint()
issubset()
issuperset()
symmetric_difference()
union()

The methods which perform add or remove operations aren’t applicable for Frozen sets as they are immutable.

The below sample exhibits the differences between a standard vs. the frozen set.

# Python Sample - Standard vs. Frozen Set

# A standard set
std_set = set(["apple", "mango","orange"])

# Adding an element to normal set is fine

print("Standard Set:", std_set)

# A frozen set
frozen_set = frozenset(["apple", "mango","orange"])

print("Frozen Set:", frozen_set)

# Below code will raise an error as we are modifying a frozen set
try:
except Exception as ex:
print("Error:", ex)

## Quick wrap up – Python Set

In this tutorial, we covered “Python Set” which is one of the core data structures available. Hence, it is utmost necessary that you are aware of how the sets work in Python.

Now, if you’ve learned something from this class, then care to share it with your colleagues. Also, connect to our social media (Facebook/Twitter) accounts to receive timely updates.

Best,

TechBeamers