---
title: Python Sets - Python Cheatsheet
description: Python comes equipped with several built-in data types to help us organize our data. These structures include lists, dictionaries, tuples and sets.
---

<base-title :title="frontmatter.title" :description="frontmatter.description">
Python Sets
</base-title>

Python comes equipped with several built-in data types to help us organize our data. These structures include lists, dictionaries, tuples and **sets**.

<base-disclaimer>
  <base-disclaimer-title>
    From the Python 3 <a target="_blank" href="https://docs.python.org/3/tutorial/datastructures.html#sets">documentation</a>
  </base-disclaimer-title>
  <base-disclaimer-content>
    A set is an unordered collection with no duplicate elements. Basic uses include membership testing and eliminating duplicate entries.
  </base-disclaimer-content>
</base-disclaimer>

Read <router-link to="/blog/python-sets-what-why-how">Python Sets: What, Why and How</router-link> for a more in-deep reference.

## Initializing a set

There are two ways to create sets: using curly braces `{}` and the built-in function `set()`

<base-warning>
  <base-warning-title>
    Empty Sets
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  <base-warning-content>
    When creating set, be sure to not use empty curly braces <code>{}</code> or you will get an empty dictionary instead.
  </base-warning-content>
</base-warning>

```python
>>> s = {1, 2, 3}
>>> s = set([1, 2, 3])

>>> s = {}  # this will create a dictionary instead of a set
>>> type(s)
# <class 'dict'>
```

## Unordered collections of unique elements

A set automatically removes all the duplicate values.

```python
>>> s = {1, 2, 3, 2, 3, 4}
>>> s
# {1, 2, 3, 4}
```

And as an unordered data type, they can't be indexed.

```python
>>> s = {1, 2, 3}
>>> s[0]
# Traceback (most recent call last):
#   File "<stdin>", line 1, in <module>
# TypeError: 'set' object does not support indexing
```

## set add and update

Using the `add()` method we can add a single element to the set.

```python
>>> s = {1, 2, 3}
>>> s.add(4)
>>> s
# {1, 2, 3, 4}
```

And with `update()`, multiple ones:

```python
>>> s = {1, 2, 3}
>>> s.update([2, 3, 4, 5, 6])
>>> s
# {1, 2, 3, 4, 5, 6}
```

## set remove and discard

Both methods will remove an element from the set, but `remove()` will raise a `key error` if the value doesn't exist.

```python
>>> s = {1, 2, 3}
>>> s.remove(3)
>>> s
# {1, 2}

>>> s.remove(3)
# Traceback (most recent call last):
#   File "<stdin>", line 1, in <module>
# KeyError: 3
```

`discard()` won't raise any errors.

```python
>>> s = {1, 2, 3}
>>> s.discard(3)
>>> s
# {1, 2}
>>> s.discard(3)
```

## set union

`union()` or `|` will create a new set with all the elements from the sets provided.

```python
>>> s1 = {1, 2, 3}
>>> s2 = {3, 4, 5}
>>> s1.union(s2)  # or 's1 | s2'
# {1, 2, 3, 4, 5}
```

## set intersection

`intersection()` or `&` will return a set with only the elements that are common to all of them.

```python
>>> s1 = {1, 2, 3}
>>> s2 = {2, 3, 4}
>>> s3 = {3, 4, 5}
>>> s1.intersection(s2, s3)  # or 's1 & s2 & s3'
# {3}
```

## set difference

`difference()` or `-` will return only the elements that are unique to the first set (invoked set).

```python
>>> s1 = {1, 2, 3}
>>> s2 = {2, 3, 4}

>>> s1.difference(s2)  # or 's1 - s2'
# {1}

>>> s2.difference(s1) # or 's2 - s1'
# {4}
```

## set symmetric_difference

`symmetric_difference()` or `^` will return all the elements that are not common between them.

```python
>>> s1 = {1, 2, 3}
>>> s2 = {2, 3, 4}
>>> s1.symmetric_difference(s2)  # or 's1 ^ s2'
# {1, 4}
```