Completed BFS-1

course.py

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+# Time Complexity : O(V+E) where v is number of course and E is number of dependencies
+# Space complexity :O(V+E)
+# Did this code successfully run on Leetcode : Yes
+# Any problem you faced while coding this : converting the logic of mapping the dependency of each course was hard it took time.
+
+# Your code here along with comments explaining your approach
+# Create an adjacency list linking prerequisites to their dependent courses and counting exactly how many prerequisites each course requires.
+# Scan the indegree array to find all courses that require no prerequisites and place them into a queue to process first.
+# Process courses from the queue and reduce the indegree of any dependent courses by 1, and add them to the queue. If all courses processed then return True else False.
+
+class Solution(object):
+    def canFinish(self, numCourses, prerequisites):
+        """
+        :type numCourses: int
+        :type prerequisites: List[List[int]]
+        :rtype: bool
+        """
+        indegree = [0] * numCourses
+        graph = {}
+
+        #mapping dependency of each course
+        for pre in prerequisites:
+            indegree[pre[0]] += 1
+            if pre[1] not in graph:
+                graph[pre[1]] = []
+            graph[pre[1]].append(pre[0])
+
+        count = 0
+        q = deque()
+
+        #add independent course to queue 
+        for i in range(0,numCourses):
+            if indegree[i] == 0:
+                q.append(i)
+                count += 1
+
+        if not q:
+            return False
+        if count == numCourses:
+            return True
+
+        # updating the q of dependency
+        while q:
+            curr = q.popleft()
+            dependency = graph.get(curr)
+            if dependency:
+                for course in dependency:
+                    indegree[course] -= 1
+                    if indegree[course] == 0:
+                        q.append(course)
+                        count += 1
+                        if count == numCourses:
+                            return True
+        return False

level_order.py

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+# Time Complexity : O(n)
+# Space complexity :O(n)
+# Did this code successfully run on Leetcode : Yes
+# Any problem you faced while coding this : Got confused while implementing call and storing list for each level.
+
+# Your code here along with comments explaining your approach
+# Creating a queue starting with the root node to keep track of nodes to visit.
+# Loop through the queue recording its current size to know exactly how many nodes belong to the current level.
+# Pop each node for that level from the front, save its value, and add its left and right children to the back of the queue to be processed in the next level.
+
+from collections import deque
+# Definition for a binary tree node.
+# class TreeNode(object):
+#     def __init__(self, val=0, left=None, right=None):
+#         self.val = val
+#         self.left = left
+#         self.right = right
+class Solution(object):
+    def levelOrder(self, root):
+        """
+        :type root: Optional[TreeNode]
+        :rtype: List[List[int]]
+        """
+        result = []
+
+        if root is None:
+            return []
+
+        q = deque([root])
+        while q:
+            size = len(q)
+            temp = []
+            for i in range(0,size):
+                curr = q.popleft()
+                temp.append(curr.val)
+                if curr.left:
+                    q.append(curr.left)
+                if curr.right:
+                    q.append(curr.right)
+            result.append(temp)
+        return result