Clear Understanding of Depth-First Search Algorithm and Its Python Implementation

Clear Understanding of Depth-First Search Algorithm and Its Python Implementation

Clear Understanding of Depth-First Search Algorithm and Its Python Implementation: Graph Algorithm. Learn with Clear Visualizations. Also learn a common mistake that people make in Depth-first search algorithm

This is one of the widely used and very popular graph search algorithms. To understand this algorithm, think of a maze. What we do when have to solve a maze? We take a route, keep going till we find a dead end. After hitting the dead end, we take a backtrack and keep coming until we see a path we did not try before. Take that new route. Again keep going till we find a dead end. Take a backtrack again….

The depth-first search works almost in the same way. Using this type of backtracking process. From the starting point, it travels until it finds no more paths to follow. Then takes a backtrack and comes back to a point that has unexplored paths. It keeps doing that until finished traveling all the nodes and edges.

That was just the easiest way I could introduce the depth-first search. I will explain it in more detail later.

Why Depth-Firth Search is Important?

The depth-first search has a wide range of use cases.

  1. Solving a maze or puzzle as I described above
  2. Scheduling a problem
  3. Cycle detection in a graph
  4. Network analysis
  5. Mapping routes
  6. Topological sorting

And many more. The depth-first search is also the base for many other complex algorithms.

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