Python list to set time complexity

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This page documents the time-complexity (aka «Big O» or «Big Oh») of various operations in current CPython. Other Python implementations (or older or still-under development versions of CPython) may have slightly different performance characteristics. However, it is generally safe to assume that they are not slower by more than a factor of O(log n).

Generally, ‘n’ is the number of elements currently in the container. ‘k’ is either the value of a parameter or the number of elements in the parameter.

list

The Average Case assumes parameters generated uniformly at random.

Internally, a list is represented as an array; the largest costs come from growing beyond the current allocation size (because everything must move), or from inserting or deleting somewhere near the beginning (because everything after that must move). If you need to add/remove at both ends, consider using a collections.deque instead.

collections.deque

A deque (double-ended queue) is represented internally as a doubly linked list. (Well, a list of arrays rather than objects, for greater efficiency.) Both ends are accessible, but even looking at the middle is slow, and adding to or removing from the middle is slower still.

See dict — the implementation is intentionally very similar.

• As seen in the source code the complexities for set difference s-t or s.difference(t) (set_difference()) and in-place set difference s.difference_update(t) (set_difference_update_internal()) are different! The first one is O(len(s)) (for every element in s add it to the new set, if not in t). The second one is O(len(t)) (for every element in t remove it from s). So care must be taken as to which is preferred, depending on which one is the longest set and whether a new set is needed.
• To perform set operations like s-t, both s and t need to be sets. However you can do the method equivalents even if t is any iterable, for example s.difference(l), where l is a list.

dict

The Average Case times listed for dict objects assume that the hash function for the objects is sufficiently robust to make collisions uncommon. The Average Case assumes the keys used in parameters are selected uniformly at random from the set of all keys.

Note that there is a fast-path for dicts that (in practice) only deal with str keys; this doesn’t affect the algorithmic complexity, but it can significantly affect the constant factors: how quickly a typical program finishes.

Notes

[1] = These operations rely on the «Amortized» part of «Amortized Worst Case». Individual actions may take surprisingly long, depending on the history of the container. [2] = Popping the intermediate element at index k from a list of size n shifts all elements after k by one slot to the left using memmove. n — k elements have to be moved, so the operation is O(n — k). The best case is popping the second to last element, which necessitates one move, the worst case is popping the first element, which involves n — 1 moves. The average case for an average value of k is popping the element the middle of the list, which takes O(n/2) = O(n) operations. [3] = For these operations, the worst case n is the maximum size the container ever achieved, rather than just the current size. For example, if N objects are added to a dictionary, then N-1 are deleted, the dictionary will still be sized for N objects (at least) until another insertion is made.

TimeComplexity (last edited 2023-01-19 22:35:03 by AndrewBadr )

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Convert List to Set Python

Data structures are the foundations of any programming language. Depending on the circumstance, data can be more effectively accessible by using data structures. Lists and sets are used in Python to store multiple elements in a single variable.

In this article, we will go over methods to convert lists to set in Python .

Introduction

• Data structure offers a method for effectively managing , organizing , and storing data.
• Data structures make it simple to navigate the data elements. Data structures offer productivity, reuse, and abstraction.
• We can think of lists as a box containing a finite number of elements. Similarly, a set can be considered a box where no duplicate elements are allowed.
• In the example below, we can see a list ([10, 50, 10, 70, 10, 50, 20, 70]) getting converted into a list, which comprises only the unique elements of the list.
• A list allows any number of variables in it, but a set doesn’t allow duplicates.
• A compelling use case of sets is when we are given a list and have to return only the unique elements .
• A list looks something like this:

• The most striking difference between a list and a set is list is represented by [] , whereas a set is represented by <> .
• Hence, this article will unravel the methods of converting lists into sets .

Method 1: Using the set() function to convert the list to a set in Python

• The set() function will help us to convert a list to a set.
• The order of the set would be different, as a set displays the items in random order. Syntax:

As you can see, the set only contains unique elements from the list.

Note: A list can contain any data type; it can be a list of strings, integers, floats, etc.

Method 2: Using for-loop to convert list to set in Python

• In this technique, we access each list element using Python’s for-loop method before adding it to a set using the add() function. Syntax:

The set automatically handles the repeated values .

Method 4: Using Set comprehension to convert a list to set

• Set Comprehension is a method in Python from which we can generate sets in a single line.
• In Python, comprehensions are used to create new sequences from existing ones. You can read more about comprehension here
• Programmers use set comprehension when creating an extra/dummy set in their code.
• In set comprehension, we use an in-place for loop to convert a list into a set.

Time Complexity to convert list to set

• The general time complexity to convert a list into a set is O(N) , where N N N represents the number of elements in the list. A question might arise as to how we know if the available time complexity is O(N) . We’ll figure it out!
• The time complexity in a set to add/delete elements is O(1) . Assuming the number of elements in our list to be N N N , we’d have to traverse every element in the list.
• Hence, the time complexity will be calculated as follows:

Similar Topics

Conclusion

In this article, we have covered the following:

• Utility of lists and sets , how they are used, and their purpose.
• Difference between sets and lists, along with comprehensive examples.
• Methods to convert list to set .
• Time Complexity of different methods and a thorough explanation regarding the time complexity.

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How to convert list to set Python (4 Easy Ways)

In this article, we will solve a problem statement of how to convert List to Set Python. We will be discussing the steps and python methods required to solve this problem and also the time complexity of the methods used to convert list to set in python.

Understanding the Problem Statement

Before jumping directly into the python program let’s know about the background of the problem statement, python list, and python set.

What is List in Python? The list is one of the 4 built-in data types in Python used to store data that is mutable, can be ordered, and can be duplicated within the list. The list is created by placing all the elements within the square brackets and separated by commas.

Example : list1 = [1,2,3,'john',7.5,3]

What is Set in Python? Like list, Set is also one of the 4 built-in data types in Python used to store data but cannot have duplicate elements and cannot be modified. The Set is created by placing all the elements within the curly brackets separated by commas.

Since now we know that set contains only distinct elements, hence when we create a set from a list we will get all distinct elements of a list in the set.

Difference between List and Set in Python

The list allows duplicate elements

The list is an ordered sequence

The elements in the list are present in square brackets [ ].

Using the list we can implement ArrayList, LinkedList, Vector, Stack

How to Convert list to set Python

1. Using set() method
2. Using For loop and set.add() method
3. Using set comprehension
4. Using dict.fromkey() method

All the above ways are discussed below in detail.

Method 1- Using set()

The best way to convert list to set in Python is by using the set() function. The set() method is used to convert an iterable element such as a list, dictionary, or tuple into the set.

Python Code:

# sample_list is defined list sample_list = [1,2,3,'seeker',3,7.5] # set() to convert list to set sample_set = set(sample_list) print(sample_set) #printing set

Method 2- For Loop and set add() method

In this method, we use for loop to access each element of a list and add that element in a set by using add() function.

Python Code

# sample_list is defined list sample_list = [1,2,3,'seeker',3,7.5] # set() to convert list to set sample_set = set() # defining set #using for loop for i in sample_list: #adding i to b sample_set.add(i) print(sample_set)

Method 3- Using Set Comprehension

In this method, we will be using set comprehension. You can know about set comprehension from here.

Python Code

# a is defined list a = [1,2,3,'seeker',3,7.5] t = # set comprehension print(t)

Method 4- Using dict.fromkey()

In this method, we will be using the dictionary fromkeys() method. To know about dict.fromkey() method you can visit here.
The only disadvantage of this method is we don’t get set in an orderly manner.

Python Code

# a is defined list a = [1,2,3,'seeker',3,7.5] # Using dict.fromkeys() method x = list(dict.fromkeys(a)) converted_set = set(x) print(converted_set)

Time Complexity to convert list to set in Python?

The time complexity to convert list to set is Big O(N), where N is the number of elements present in the list, i.e it is linear to the elements present in the list. This is because the complexity of set operations to add/delete an element is O(1). Hence while converting a list of N elements into a set, we require such N operations, which will have the complexity of N * O(1) i.e O(N * 1) = O(N).

Above, we have discussed 4 methods that can help you to convert list to set in python. But which method is best from above with respect to time so that you can practice using that method in upcoming projects or problems.

From the above table, we can see that using the set() function method takes less time compared to other methods.

Conclusion

Hence we can convert list to set Python by using set() method, for loop, and set comprehension. The Time complexity for converting the list to set is O(N). We can also conclude the best way to convert list to set is by using the set() method.

I am Passionate Computer Engineer. Writing articles about programming problems and concepts allows me to follow my passion for programming and helping others.

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