PYTHON 3: Iterators and Iterator Decorators via Generators**if an argument is iterable, it means that you can call only iter on it, and then call next on the value iter returns (for loops do this automatically). There is no guarantee you can call len on the iterable or index/slice it. You may not copy all the values of an iterable into a list (or any other data structure). You may create local data structures storing as many values as the arguments or the result that the function returns, but not all the values in the iterable. prints combus; if the iterable produces < n values, it terminates immediately, on the first call to next. A. The drop_last generator takes one iterable and one int as a parameter (call it n): it produces every value from the iterable except for the last n values (without being able to count how many values the iterableproduces) Hint: I used an explicit call to iter and a while loop and a comprehension that creates a list that stores at most n values (so that data structure is allowed here). For examplefor i in drop_last ('combustible', 5): print (i, end-i')B. The yield_and_skip generator takes one iterable and one function (which takes one argument and returns an int) as parameters: it produces a value from the iterable but then it then skips the number of values specified when the function argument is called on the just-produced value. Hint:I used an explicit call to iter and a while and for loop. For example1) Write generators below that satisfy the following specifications. You may not import any of the generators in itertools or any other modules to write your generators. You may use any of the standard functions like zip and enumerate. for i in yield_and_skip('abbaxcabbcaccabb', lambda x : ['a':1,'b':2,'c',3] .get(x, o)): print(i, end=' ')