Non-recursive DFS Posted:
Depth-first search (DFS) is a powerful algorithm. The recursive DFS algorithm is probably the easiest to understand, and most of the time it is good enough.
In some problems, the recursion stack gets very large. This can easily blow the stack limit in Python. Fortunately, there is a simple way to make the algorithm iterative.
Recursive DFS implementations sometimes ignore the pre or post numbering of the vertexes, because they aren't needed – the work is done in the recursive call. Those numbers are key to the iterative algorithm.
The main idea of the recursive algorithm is to visit every vertex, and at each visit:
- Set the pre-order number.
- Visit all unvisited children.
- Set the post-order number.
In a recursive algorithm, we can also do some work before visiting the child vertexes, while visiting them, or after.
The pre-order and post-order numbers are the key to making DFS iterative. We will use an explicit stack for this algorithm.
First, we add the starting vertex to the stack. Then, while the stack is non-empty, we pop the last vertex off of the stack and do the following:
- If the vertex has a post-order number, skip it.
- Otherwise, if the vertex has a pre-order number, we are in the post-child step.
- Set the post-order number and do any post processing.
- Otherwise, we are now visiting the vertex for the first time.
- Set the pre-order number.
- Add the vertex back to the stack.
- Add all of its unvisited children to the stack.
Let's informally check if this makes sense.
- A vertex is added to the stack only if it has not been visited (pre-order is not set), or while it is being visited, before its children are added to the stack. (3a and 3b)
- A vertex only hits step 3 once. After step 3, it has a pre-order number, so the next time the vertex is processed, it will go to step 2.
- The vertex only makes it to step 2 after its children have been processed.
- So, step 2 is the post-order step.
Finally, here is some code
1 class DFS(object): 2 def __init__(self,adj): 3 self.adj = adj 4 self.N = len(adj) 5 self.pre = [-1 for x in adj] 6 self.post = [-1 for x in adj] 7 self.pre_count = 0 8 self.post_count = 0 9 10 def dfs(self, i): 11 stack = [i] 12 while stack: 13 u = stack.pop() 14 if self.post[u] > -1: 15 continue 16 elif self.pre[u] > - 1: 17 self.post[u] = self.post_count 18 self.post_count += 1 19 else: 20 stack.append(u) 21 self.pre[u] = self.pre_count 22 self.pre_count += 1 23 for v in self.adj[u]: 24 if self.pre[v] == -1: 25 stack.append(v)
This code only handles starting a search tree from a specific vertex. To search the entire graph, the dfs method needs to be called for every vertex. That order is up to the caller. Pre-order or post-order steps can be added to this code, or it could be generalized to provide hooks for sub-classes to use.