The len() function in Python has a very peculiar characteristic that one had often wondered about. It takes absolutely no time, and equal time, in calculating the lengths of iterable data structures(string, array, tuple, etc.), irrespective of the size or type of data. This obviously implies O(1) time complexity. But have you wondered How?
Python follows the idea that keeping the length as an attribute is cheap and easy to maintain. len() is actually a function that calls the method ‘__len__()’. This method is defined in the predefined classes of iterable data structures. This method actually acts as a counter, that is automatically incremented as the data is defined and stored. Thus when you call the len() function, you do not give the interpreter the command to find the length by traversing, but rather you ask the interpreter to print a value that is already stored. Hence, len() function in Python runs in O(1) complexity.
Thus it can also be defined as:
def length(ar): # calling the internally # defined __len__() method return ar.__len__() # Driver codea = [1, 2, 3, 4]print(length(a)) |
Output:
4
Note: This might seem very beneficial, but remember that it puts a remarkable burden on the interpreter during the data definition phase. This is one of the many reasons why Python is slower during competitive programming, especially with big inputs.
