finished stretch goal in names.py

Author: davidanagy

names/names.py

@@ -14,31 +14,50 @@
 
 # Replace the nested for loops below with your improvements
 
-# The runtime of the original code here was O(n^2)
+# --> The runtime of the original code here was O(n^2) <--
 # for name_1 in names_1:
 #     for name_2 in names_2:
 #         if name_1 == name_2:
 #             duplicates.append(name_1)
 
 # The below imports assume that the given folders contain the requisite
 # data structures.
+# import sys
+# sys.path.append('../../Data-Structures/binary_search_tree')
+# sys.path.append('../../Data-Structures/queue_and_stack')
+# sys.path.append('../../Data-Structures/doubly_linked_list')
+# from binary_search_tree import BinarySearchTree
+
+# # This has a runtime complexity of O(n log n), I think.
+# # It took about 0.1 seconds to run on my computer.
+# tree = BinarySearchTree(names_1[0])
+# for name_1 in names_1[1:]:
+#     tree.insert(name_1)
+# for name_2 in names_2:
+#     # The "contains" method checks if the value exists in the tree.
+#     # On average, its runtime is O(log n).
+#     if tree.contains(name_2):
+#         duplicates.append(name_2)
+
+# STRETCH SOLUTION
+# Basically I want to search names_1 for each name_2, and add to
+# "duplicates" if I find it.
+# The most efficient search with arrays is a Binary Search,
+# so I'll import my code for that.
 import sys
-sys.path.append('../../Data-Structures/binary_search_tree')
-sys.path.append('../../Data-Structures/queue_and_stack')
-sys.path.append('../../Data-Structures/doubly_linked_list')
-from binary_search_tree import BinarySearchTree
-
-# This has a runtime complexity of O(n log n), I think.
-# It took about 0.1 seconds to run on my computer.
-tree = BinarySearchTree(names_1[0])
-for name_1 in names_1[1:]:
-    tree.insert(name_1)
+sys.path.append('../../Sorting/src/searching')
+from searching import binary_search
+# To do a binary search, you first have to sort the search array.
+names_1.sort()
 for name_2 in names_2:
-    # The "contains" method checks if the value exists in the tree.
-    # On average, its runtime is O(log n).
-    if tree.contains(name_2):
+    # binary_search returns a -1 when the item isn't found,
+    # so append to duplicates whenever the result isn't -1.
+    if binary_search(names_1, name_2) != -1:
         duplicates.append(name_2)
 
+# The runtime for this ended up being about 0.8 seconds on my computer--
+# better than the Binary Search Tree!
+
 end_time = time.time()
 print (f"{len(duplicates)} duplicates:\n\n{', '.join(duplicates)}\n\n")
 print (f"runtime: {end_time - start_time} seconds")