Comparing Time of List To Set Conversion

Below are some of the comparisons for the time complexity of the list to set conversion in Python:

Using set() Constructor

In this example, the script measures the time taken to convert a small list (`small_list`) and a large list (`large_list`) to sets using the `set()` constructor. The execution time is calculated using the `time` module, showcasing the efficiency of the set conversion process for both small and large datasets.

Python3

import time
 
# For Small List
small_list = [1, 2, 3, 4, 5]
 
start = time.time()
small_set = set(small_list)
end = time.time()
 
print("The time to convert small list to set : ", round(end - start, 5))
print("The small set is : ", small_set)
 
# For Large List
 
large_list = list(range(1, 1000001))
start = time.time()
large_set = set(large_list)
end = time.time()
print("The time to convert large list to set : ", round(end - start, 5))

Output

The time to convert small list to set :  0.0
The small set is :  {1, 2, 3, 4, 5}
The time to convert large list to set :  0.0527

Using set() with unpacking

In this example, the script measures the time taken to convert a small list (`small_list`) and a large list (`large_list`) to sets using the `set()` constructor with the unpacking syntax (`*`). However, the usage of `*` in `set(*[small_list])` and `set(*[large_list])` is unnecessary and equivalent to `set(small_list)` and `set(large_list)`. The execution time is calculated using the `time` module, demonstrating the efficiency of the set conversion process for both small and large datasets.

Python3

import time
 
# For Small List
small_list = [1, 2, 3, 4, 5]
 
start = time.time()
small_set = set(*[small_list])
end = time.time()
 
print("The time to convert small list to set : ",round(end - start,5))
print("The set is : ",small_set)
 
# For Large List
 
large_list = list(range(1, 1000001))
start = time.time()
large_set = set(*[large_list])
end = time.time()
print("The time to convert large list to set : ",round(end - start,5))

Output

The time to convert small list to set :  0.0
The set is :  {1, 2, 3, 4, 5}
The time to convert large list to set :  0.05134

Using update method

In this example, the script measures the time taken to convert a small list (`small_list`) and a large list (`large_list`) to sets using the `update()` method of the `set` data structure. The `update` method efficiently incorporates the elements from the lists into the sets, and the execution time is calculated using the `time` module. The resulting sets, `small_set` and `large_set`, contain unique elements from the corresponding lists.

Python3

import time
 
# For Small List
small_list = [1, 2, 3, 4, 5]
 
small_set = set()
 
start = time.time()
small_set.update(small_list)
end = time.time()
 
print("The time to convert small list to set : ", round(end - start,5))
print("The set is : ", small_set)
 
# For Large List
 
large_list = list(range(1, 1000001))
large_set = set()
 
start = time.time()
large_set.update(large_list)
end = time.time()
 
print("The time to convert large list to set : ", round(end - start, 5))

Output

The time to convert small list to set :  0.0
The set is :  {1, 2, 3, 4, 5}
The time to convert large list to set :  0.05066

Using Loops and add() method of set

In this example, the script measures the time taken to convert a small list (`small_list`) and a large list (`large_list`) to sets using a `for` loop and the `add` method of the `set` data structure. The `add` method efficiently incorporates the elements from the lists into the sets, and the execution time is calculated using the `time` module. The resulting sets, `small_set` and `large_set`, contain unique elements from the corresponding lists. This approach offers explicit control over the set creation process, particularly useful for scenarios where customization is needed during the conversion.

Python3

import time
 
# For Small List
small_list = [1, 2, 3, 4, 5]
 
small_set = set()
 
start = time.time()
for element in small_list:
    small_set.add(element)
end = time.time()
 
print("The time to convert small list to set : ", round(end - start, 5))
print("The set is : ", small_set)
 
# For Large List
 
large_list = list(range(1, 1000001))
large_set = set()
 
start = time.time()
for element in large_list:
    large_set.add(element)
end = time.time()
 
print("The time to convert large list to set : ", round(end - start, 5))

Output

The time to convert small list to set :  0.0
The set is :  {1, 2, 3, 4, 5}
The time to convert large list to set :  0.21737

Time Complexity of A List to Set Conversion in Python

The time complexity of converting a list to a set is predominantly determined by the underlying hash function used by the set data structure. The average-case time complexity is O(n), where n is the number of elements in the list. In this article, we will see compare different scenarios in which we will compare time complexities for different conversion from a list to a set in Python.

Tags:

#time complexity #Python #Python Programs #python

Conclusion

Comparing Time of List To Set Conversion

Using set() Constructor

Python3

Using set() with unpacking

Python3

Using update method

Python3

Using Loops and add() method of set

Python3

Time Complexity of A List to Set Conversion in Python

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