The O(...) refers to Big-O notation, which is a simple way of describing how many operations an algorithm takes to do something. This is known as time complexity.
In Big-O notation, the cost of an algorithm is represented by its most costly operation at large numbers. If an algorithm took
n3 + n2 + n steps, it would be represented O(n3). An algorithm that counted each item in a list would operate in O(n) time, called linear time.
For a list of the names and classic examples on Wikipedia: Orders of common functions
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- A beginner's guide to Big O notation
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