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Set

A set is a popular data structure used for storing a list of elements that are unique. A set doesn't have any particular ordering so the order you input elements and fetch them could be different.

Basic Structuring

Sets can be implemented in different ways depending on what speed and capacity you need. The most popular implementation is creating a set with just a list. List's are not the fastest implementation of sets but it's the least amount of code involved.

Other popular set implementations are trees and hash maps. They both will have lightning add, has, and delete speeds but you will need to have the other data structures created to implement them.

Add

The most basic function for sets is add. It will take one parameter and all it will do is check if the element isn't already in the set, and if it's not then the function will add the element to the set. We normally dont return anything back this method.

Has

We need to check what is in our set and we use has to do that. It's just as simple as set and all we need to do is just return back if the element is in our data structure.

Delete

This is the inverse of the add function. We want to check if the set has a certain value and if it does we delete it. We want to return a boolean of if the element was deleted from the set.

Union

Sets are popular to do calculations based on what's inside them. Union is basically just combining two sets together and returning a brand new set.

For example if you have a set that has [1, 2] and a set that has [2, 3] a union of the two sets will return [1, 2, 3].

Getting a union is quite simple, all you need to do is clone the first set then call the add function on all the elements in the second set.

Intersection

While union will return all the data from two sets, intersection will just return the elements that overlap.

Simple just look through the data in the first set and check if the second set has the current element, if it does add it to a return set then return that set once all the elements in the first set has been looked at.

If you use a HashMap to implement this you can get it down to O(n) while a list will get you up to O(n^2)

Difference

Difference is what it sounds like, calling it on a function will return the difference between two sets.

It's very similar to intersection but instead of adding the element to a return set if both sets have the element. You add the element to the return set if set b doesn't have (or has) it.

You will get the same speed from the intersection function.

Subset

This function will return if all the elements in the current set are in a separate set. All you need to do is loop through all the elements in the current set and check if the target set has the current element.

Speed will be O(n).

Iterator

We want this set to be iterable. So if you are in a language that you can make a class iterable this would be pretty smart. Check the code to see a python implementation.

When to use Sets

Sets are very helpful in many ways. They are extremely helpful in machine learning and math based algorithms because of the union, intersection, difference, and subset functions. But they are also very helpful in your day to day application.

It's good to use sets whenever you want to store elements that are unique and the ordering doesn't matter. They will typically be faster then lists so using them instead of lists in the situation stated is normally more efficient.

Some of the implementations of set's I've used today are:

  • Storing member ids that I was to find in a database from all orders from a certain restaurant.
  • Storing ids that will never overlap and don't need to retain order.