## BFS searching shortest path
Well done! Now, let's implement a method that helps us to find the length of shortest path between two vertices, i. e. minimum number of edges to reach `end` vertice from `start`.

You should store the length of the way from `start` to `curr` node, and you can do it by modifying `visited` array: `visited[i]` equals: 
 - -1, if `i` not visited yet

 - 0, if `i` is visited as first node

 - 1, if `i` is a neighbor of node, that has mark `0`

 - k, if `i` is a neighbor of node with mark k-1 etc. 

This way, you'll store the distance between `start` and `current` node, like at the example:



This mini-course introduces the BFS Algorithm. It requires understanding the graph theory on base level, and Python programming language knowledge. This course is built on implementing step-by-step solutions and using `Graph` class implementation, so you have to understand Python OOP minimally. You have to be able to implement an algorithm by pseudocode.

Meet the BFS example and code, that you'll improve during the course.

Let's upgrade your code to make it faster and consistent.

Apply your knowledge to solve some algorithmic problems.

Shortest Path in Graph

BFS searching shortest path

Shortest Path in Graph

BFS searching shortest path