Five Best Ways to Convert Sets to List Python

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The set data type is PythonSets are a collection of unique, unchangeable objects. Sets can be used to efficiently remove duplicates and perform mathematical set operation. Sometimes you will need to convert sets into lists, for serialization or further processing.

In this post, we’ll clearly understand the differences between Python sets and Lists, approaches to convert set to listPython, the use cases in which this conversion is required, best practices surrounding these conversions and related concepts that new Python programmers need to understand.

Python Lists vs. Sets

First, let’s recap some key traits differentiating Python listsThere are two types of built-in types.

  • Lists are ordered and indexed, allowing duplicate items like [1, 1, 2, 3], while sets are unordered collections of distinct objects such as {3, 2, 1}.
  • Lists can contain arbitrary data types and objects. Sets only hold a single data type – for example, a set of integers or a set of strings.
  • Sets test membership more efficiently by using hashes in place of linear scans.

Lists, unlike sets, make it possible to retrieve elements by index or maintain insertion order. Sets, on the other hand, provide faster membership testing and duplicate removal capabilities.

Read in more detail: Python List vs. Sets

How to Convert Sets to Lists in Python?

Now let’s tackle techniques to convert set to list Python. Imagine we have an integer set:

numbers_set = {1, 5, 2, 4, 5}

Approach 1Python Set to List Using The List() function

We can directly use Python’s list() function to convert set to list python:


numbers_list = list(numbers_set)
print(numbers_list) # [1, 2, 4, 5]

Approach 2: By Iteration and Appending

Alternatively, we can iterate through our Python set and as we encounter each element we add that to our Python list, hence in the end we’ll have a list of all our elements that were earlier present in the set.


numbers_list = [] 
for num in numbers_set:
print(numbers_list) # [1, 2, 4, 5]

Approach 3: Using List Comprehensions

We can use list comprehension to create a new list from the elements in the set. This method is more concise and can be faster than manual iteration.


numbers_list = [num for num in numbers_set]
print(numbers_list) # [1,2,3,4]

Approach 4: Unpacking the Set inside parentheses

This method involves unpacking the set inside a list literal, which is created due to the presence of a single comma. This approach is faster but suffers from readability


numbers_list = [*numbers_set]
print(numbers_list) # [1,2,3,4]

Approach 5: Using the mapFunction

We can use the map() Function to convert set to List Python by passing the set as an argument to the map() function and returning a list of the elements.


numbers_list = list(map(lambda x: x, numbers_set))
Print(numbers_list) # [1,2,3,4]

Use Cases Driving Set-List Conversions

Some common scenarios where converting a Python set into a list becomes necessary:

  • Serializing the collection to JSON or CSV which requires value ordering
  • Passing the data into a function expecting iterable arguments
  • Sorting or manually manipulating list elements (sets are unordered)
  • Maintaining insertion sequence along with membership testing abilities

For these use cases, sets provide efficient building blocks leveraging their uniqueness and membership testing. Yet interoperability with other functions needs ordered listings occasionally.

Best Practices You can also find out more about the following: Smooth Conversions

Follow these best practices when convertThe following are some examples of how to useg back and forth between sets and Lists in Python to avoid surprises:

  • Be aware ordering and duplicates get lost when casting lists to sets
  • Watch out for mixing data types if converting heterogeneous lists
  • Use list()Or the list constructor instead less readable alternatives
  • Note that nesting objects and sets also require HashingAll fields

And there you have it – a quick primer on effectively converting Python sets into lists using intuitive built-in functions as per application requirements!

While on the topic of Python sets, let’s also briefly mention related concepts that are handy to know:

1. Set Unions

Set unions are used to create a new collection of elements that do not overlap from two sets.


set_a = {1, 2, 3}
set_b = {3, 4, 5}

set_c = set_a | set_b # Set union => {1, 2, 3, 4, 5}

2. Set Intersections

Set intersections returns common elements in two sets


set_a = {1, 2, 3}  
set_b = {2, 3, 4}

set_c = set_a & set_b # Set intersection => {2, 3}

3. Frozensets

Frozensets is an immutable version of Python’s standard sets. This means elements can’t be added or removed once initialized like sets.


my_frozen_set = frozenset([1, 'Hi', True])


To sum up, the set and list data types have key differences in Python – sets are unordered collections of distinct elements supporting efficient membership testing, while lists maintain ordering and allow duplicates. When converting a set into a list, the elements are serialized via JSON, sorted, and have a sequenced order. However, they lose their uniqueness.

Direct type conversion is one of the common Pythonic methods to convert a list from a set.()Call a method or list on the sets. Lists enable certain use cases such as serializing, passing data as function arguments and sorting/processing which require set order and duplication.

It’s best practice in Python to type cast cleanly via list()Be aware that ordering/duplication can change. Also, frozensets provides immutable versions of sets in Python.

Also Read:


  1. How can you convert a Python set into a list?

    In Python, you can convert a Set to a List by using the list()List constructor or method.

  2. What is the difference between Python’s list and set?

    Lists and sets can both contain duplicate elements, but lists will always maintain the order. Sets support hash-based membership testing.

  3. Why would you need a Python list to convert from a set?

    Some common reasons to convert a collection to a listing include the need to serialize information, pass data into a function expecting to receive a number, sort elements, manipulate values by index or work with duplicates.

  4. What happens to the duplicates when you convert a collection to a listing?

    As Python sets only contain unique items, any duplicates will be collapsed when converted to a list. The result will be one list with only one instance for each item from the set.

  5. How can sets be unique while allowing for different data types to be used?

    Set elements need to be hashable. Sets can contain both an int and string. However, sets are usually composed of values that are all the same basic, immutable datatype, like ints or strings.

  6. Does the order of elements persist when converting a collection into a list

    No, because sets are by definition unordered, converting them to a list will result in the elements being arranged in any order. They will not retain any explicit or insertion-ordering.

  7. What is a Python set and how does it differ from a frozenset?

    A frozenset is a hashable, immutable sequence of unique elements, just like a set. However, unlike sets, it cannot be altered after creation.

  8. When should you use sets or lists in Python

    Sets are useful for removing duplicates and performing mathematical set operations. Use lists when you want to have different data types, indexes and ordering within a single structure.

  9. What are the most common set operations in Python?

    Python supports set intersections, set unions, and symmetrical difference through operators such as |, &, – and ^ respectively.

  10. How can you tell if a certain item is in a list or a set?

    Use the The following are some examples of how to useOperator for readability but it scans the whole list linearly whereas sets use highly optimized looksups hash to check membership.

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