f = open('names_2.txt', 'r')
names_2 = f.read().split("\n") # List containing 10000 names
f.close()
duplicates = [] # Return the list of duplicates in this data structure
# Replace the nested for loops below with your improvements
# for name_1 in names_1:
# for name_2 in names_2:
# if name_1 == name_2:
# duplicates.append(name_1)
bst_node = BSTNode("") # implement a BST
for name_1 in names_1: # loop through all the names in names_1
bst_node.insert(name_1) # to insert each name in names_1
for name_2 in names_2: # loop through all the names in names_2
if bst_node.contains(
name_2
): # then see if the tree has (contains) the same names as names_2
duplicates.append(
name_2) # if it does, add (append) the name to the duplicated list
end_time = time.time()
print(f"{len(duplicates)} duplicates:\n\n{', '.join(duplicates)}\n\n")
print(f"runtime: {end_time - start_time} seconds")
# ---------- Stretch Goal -----------
# Python has built-in tools that allow for a very efficient approach to this problem
# What's the best time you can accomplish? Thare are no restrictions on techniques or data
# structures, but you may not import any additional libraries that you did not write yourself.
