computational complexity on it the computer did nothing but sort those file names alphabetically for around when this was discoveredthe programmer rewrote the sorting code to be more efficient and reduced the sorting time to around that' big differenceit also illustrates just how important this idea of computational complexity is if we take another look at our pylist append method we might be able to make it more efficient if we didn' have to access each element of the first list when concatenating the two lists the use of the operator is what causes python to access each element of that first list when is used new list is created with space for one more element then all the elements from the old list must be copied to the new list and the new element is added at the end of this list using the append method on lists changes the code to use mutator method to alter the list by adding just one more element it turns out that adding one more element to an already existing list is very efficient in python in factappending an item to list is ( operation as we'll see later in this this means to append items to list we have gone from ( to (nlater in this we'll learn just how python can insure that we get ( complexity for the append operation the blue line in fig shows how the pylist append method works when the operator is replaced by calling the list append method instead at , elements fig the complexity of appending to pylist this copy belongs to 'acha