Consider the following Python code: 
F1 & F2 share the same list
The question involves understanding closures in Python and how they maintain their own environments.
Let's analyze the provided Python code step-by-step:
outer() is defined, which initializes an empty list x.outer(), there's an inner function inner(val) that appends val to x and returns x.outer() returns the inner function.The code execution proceeds as follows:
F1 = outer() creates a new list x for F1 and assigns the inner function to F1.F2 = outer() creates another new list x for F2, independent of F1's list.print(F1(10)): Calls F1's function, which adds 10 to x. The list becomes [10].print(F1(20)): Calls F1 again, adding 20 to x. The list becomes [10, 20].print(F2(30)): Calls F2, which is independent, adding 30 to its list. The list for F2 becomes [30].print(F2(40)): Calls F2 again, adding 40. The list for F2 becomes [30, 40].Now, let's match this with the given options:
print(F1(20)), which indeed outputs [10, 20].F2(40), having no connection to the F1 list.F1 and F2 have separate lists.Based on the above reasoning, the correct answer is:
Output of line Q is [10, 20]
The maximum value of \(x\) such that the edge between the nodes B and C is included in every minimum spanning tree of the given graph is __________ (answer in integer).
The value printed by the given C program is __________ (Answer in integer).
Consider the following \(B^+\) tree with 5 nodes, in which a node can store at most 3 key values. The value 23 is now inserted in the \(B^+\) tree. Which of the following options(s) is/are CORRECT?

Given the Python code: 
