Hunter Smith - Sprint-Challenge--Data-Structures-Python

Data_Structures_Answers.md

@@ -1,18 +1,20 @@
 Add your answers to the questions below.
 
 1. What is the runtime complexity of your `depth_first_for_each` method?
-
+O(n) , it runs through each node
 2. What is the space complexity of your `depth_first_for_each` function?
-
+O(n)
 3. What is the runtime complexity of your `breadth_first_for_each` method?
-
+O(n)
 4. What is the space complexity of your `breadth_first_for_each` method?
-
+O(n)
 
 5. What is the runtime complexity of the provided code in `names.py`?
+O(n^2) since it is looping through each element of each list to compare to each element of the other
 
 6. What is the space complexity of the provided code in `names.py`?
-
+O(n)
 7. What is the runtime complexity of your optimized code in `names.py`?
-
+O(n)
 8. What is the space complexity of your optimized code in `names.py`?
+O(n)

README.md

@@ -1,5 +1,5 @@
 # Sprint Challenge: Data Structures
-
+Hunter Smith
 In this week's Sprint you implemented some classic and fundamental data structures and learned about how to go about evaluating their respective runtimes and performance. This Sprint Challenge aims to assess your comfort with these topics through exercises that build on the data structures you implemented and the algorithmic intuition you've started to build up.
 
 ## Instructions

names/names.py

@@ -11,10 +11,14 @@
 f.close()
 
 duplicates = []
-for name_1 in names_1:
-    for name_2 in names_2:
-        if name_1 == name_2:
-            duplicates.append(name_1)
+# for name_1 in names_1:
+#     for name_2 in names_2:
+#         if name_1 == name_2:
+#             duplicates.append(name_1)
+a_set = set(names_1)
+b_set = set(names_2)
+if (a_set & b_set):
+    duplicates.append(repr(a_set & b_set))
 
 end_time = time.time()
 print (f"{len(duplicates)} duplicates:\n\n{', '.join(duplicates)}\n\n")

search/binary_search_tree.py

@@ -5,10 +5,25 @@ def __init__(self, value):
     self.right = None
 
   def depth_first_for_each(self, cb):
-    pass    
+    cb(self.value)
+    if self.left != None:
+      self.left.depth_first_for_each(cb)
+    if self.right != None:
+      self.right.depth_first_for_each(cb)
+    return
+
 
   def breadth_first_for_each(self, cb):
-    pass
+    nodes = [self]
+    #while loop going through every node
+    while len(nodes) > 0:
+      current = nodes.pop(0)
+      cb(current.value)
+      if current.left != None:
+        nodes.append(current.left)
+      if current.right != None:
+        nodes.append(current.right)
+
 
   def insert(self, value):
     new_tree = BinarySearchTree(value)