AI & MACHINE LEARNING PROGRAM • LEVEL 23 — CLASSICAL AI SEARCH
Search a Graph with DFS with Python
Learn search a graph with dfs with python with a short, executable Python example.
PROBLEM UNDERSTANDING
Input and expected output
No input required
['A', 'B', 'D', 'C']
COMPLETE PYTHON PROGRAM
Complete Python implementation
graph={'A':['B','C'],'B':['D'],'C':[],'D':[]}
stack,visited=['A'],[]
while stack:
node=stack.pop()
if node not in visited:
visited.append(node); stack.extend(reversed(graph[node]))
print(visited)CURRENT STEP
Select Start to walk through the important lines.
SELECTED LINE
No line selected
EXPECTED OUTPUT FOR THE SAMPLE
['A', 'B', 'D', 'C']
PROGRAM EXPLANATION
Algorithm and explanation
- Initialize the sample values used to search a graph with dfs.
- Process the data step by step using DFS and Graph search.
- Display the result for search a graph with dfs and compare it with the documented sample output.
This example of search a graph with dfs processes the sample values in a controlled iteration. It demonstrates DFS and Graph search and prints a deterministic result that can be checked against the sample output.
EFFICIENCY
Time and space complexity
O(V + E)
O(V)
DEBUGGING CHECKLIST
Common mistakes
For search a graph with dfs, keep the data shape and value types consistent with DFS.
Keep every dependent statement inside the correct indented Python block.
Verify the final DFS and Graph search result against the sample before trying new data.