Efficient List Containment Check in Python: Short 'Contains' Function?

  1. Introduction
  2. The 'Contains' Function
  3. Why is this Function Efficient?
  4. Conclusion


When working with lists in Python, it's common to need to check if a certain element is present in the list. This can be done using the 'in' keyword, but for large lists or frequent checks, a more efficient solution may be desired. In this article, we'll explore a short 'contains' function that can perform list containment checks efficiently.

The 'Contains' Function

Here's the code for the 'contains' function:

def contains(element, lst):
    for item in lst:
        if item == element:
            return True
    return False

This function takes in an element and a list, and checks if the element is present in the list. It does this by iterating over each item in the list, and checking if it's equal to the element we're looking for. If a match is found, the function immediately returns True. If no match is found after iterating over the entire list, the function returns False.

Why is this Function Efficient?

This function is efficient because it doesn't need to create any additional data structures or perform any complex operations. It simply iterates over each item in the list, and checks if it's equal to the element we're looking for. This operation has a time complexity of O(n), where n is the length of the list. For small lists, this operation is fast enough to be performed frequently without any noticeable performance impact. For larger lists, this function may still be faster than using the 'in' keyword, especially if the list is sorted.


If you need to perform frequent list containment checks in Python, the short 'contains' function we've explored in this article can be a fast and efficient solution. By iterating over each item in the list and checking for a match, this function can quickly determine if an element is present in a list of any size. Just remember that for very large lists, other data structures or algorithms may be necessary for optimal performance.

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