Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
History is littered with hundreds of conflicts over the future of a community, group, location or business that were "resolved" when one of the parties stepped ahead and destroyed what was there. With the original point of contention destroyed, the debates would fall to the wayside. Archive Team believes that by duplicated condemned data, the conversation and debate can continue, as well as the richness and insight gained by keeping the materials. Our projects have ranged in size from a single volunteer downloading the data to a small-but-critical site, to over 100 volunteers stepping forward to acquire terabytes of user-created data to save for future generations.
The main site for Archive Team is at archiveteam.org and contains up to the date information on various projects, manifestos, plans and walkthroughs.
This collection contains the output of many Archive Team projects, both ongoing and completed. Thanks to the generous providing of disk space by the Internet Archive, multi-terabyte datasets can be made available, as well as in use by the Wayback Machine, providing a path back to lost websites and work.
Our collection has grown to the point of having sub-collections for the type of data we acquire. If you are seeking to browse the contents of these collections, the Wayback Machine is the best first stop. Otherwise, you are free to dig into the stacks to see what you may find.
The Archive Team Panic Downloads are full pulldowns of currently extant websites, meant to serve as emergency backups for needed sites that are in danger of closing, or which will be missed dearly if suddenly lost due to hard drive crashes or server failures.
Question 1
What is a heap?
A data structure that stores data in a binary tree structure
A collection of data elements stored in an unordered manner
A stack data structure with additional constraints
A sorted collection of data elements
Question 2
Which of the following is the correct way to create a heap in Python?
heap = []
heap = [1, 2, 3, 4]
from heapq import heapify; heapify([1, 2, 3, 4])
heap = {1: 'a', 2: 'b', 3: 'c'}
Question 3
What is the time complexity of inserting an element into a heap?
O(log n)
O(n)
O(1)
O(n log n)
Question 4
Which of the following is the correct way to add an element to a heap?
heap.append(5)
heap.insert(5)
from heapq import heappush; heappush(heap, 5)
heap.add(5)
Question 5
What is the time complexity of removing the smallest element from a heap?
O(log n)
O(n)
O(1)
O(n log n)
Question 6
Which of the following is the correct way to remove the smallest element from a heap?
heap.pop()
heap.remove(0)
from heapq import heappop; heappop(heap)
heap.delete_min()
Question 7
What is the time complexity of finding the smallest element in a heap?
O(log n)
O(n)
O(1)
O(n log n)
Question 8
Which of the following is the correct way to find the smallest element in a heap?
heap[0]
min(heap)
from heapq import heappush; heappush(heap, 5)
heap.peek()
Question 9
How to get the smallest element from a heap without removing it?
heap[0]
peek_heap(heap)
heap_peak(heap)
heappop(heap)
Question 10
What is the advantage of using a heap over other data structures?
Faster insertion and removal of elements
Faster searching of elements
Requires less memory
None of the above
There are 10 questions to complete.
