operation big- efficiency copy (nget item ( set item ( delete item ( contains (ino( iteration (ntable big- efficiency of python dictionary operations is summarized in table one important side note on dictionary performance is that the efficiencies we provide in the table are for average performance in some rare cases the containsget itemand set item operations can degenerate into (nperformance but we will get into that in later when we talk about the different ways that dictionary could be implemented for our last performance experiment we will compare the performance of the contains operation between lists and dictionaries in the process we will confirm that the contains operator for lists is (nand the contains operator for dictionaries is ( the experiment we will use to compare the two is simple we'll make list with range of numbers in it then we will pick numbers at random and check to see if the numbers are in the list if our performance tables are correct the bigger the list the longer it should take to determine if any one number is contained in the list we will repeat the same experiment for dictionary that contains numbers as the keys in this experiment we should see that determining whether or not number is in the dictionary is not only much fasterbut the time it takes to check should remain constant even as the dictionary grows larger the code below implements this comparison notice that we are performing exactly the same operationnumber in container the difference is that on line is listand on line is dictionary import timeit import random for in range( , , ) timeit timer("random randrange(%din "% "from __main__ import random, " list(range( )lst_time timeit(number= { :none for in range( )d_time timeit(number= print("% ,% ,% (ilst_timed_time)figure summarizes the results you can see that the dictionary is consistently faster for the smallest list size of elements dictionary is times faster than list for the largest list size of elements the dictionary is times fasteryou can also see that the time it takes for the contains operator on the list grows linearly with the size of the list this verifies the assertion that the contains operator on list is (nit can also be seen that the performance of python data structures