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" <small><i>This notebook was prepared by [Donne Martin](https://github.com/donnemartin). Source and license info is on [GitHub](https://github.com/donnemartin/interactive-coding-challenges).</i></small> "
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" # Solution Notebook "
]
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" ## Problem: Determine whether there is a path between two nodes in a graph. \n " ,
" \n " ,
" * [Constraints](#Constraints) \n " ,
" * [Test Cases](#Test-Cases) \n " ,
" * [Algorithm](#Algorithm) \n " ,
" * [Code](#Code) \n " ,
" * [Unit Test](#Unit-Test) "
]
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" ## Constraints \n " ,
" \n " ,
" * Is the graph directed? \n " ,
" * Yes \n " ,
" * Can we assume we already have Graph and Node classes? \n " ,
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" * Yes \n " ,
" * Can we assume the inputs are valid? \n " ,
" * Yes \n " ,
" * Can we assume this fits memory? \n " ,
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" * Yes "
]
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" ## Test Cases \n " ,
" \n " ,
" Input: \n " ,
" * `add_edge(source, destination, weight)` \n " ,
" \n " ,
" ``` \n " ,
" graph.add_edge(0, 1, 5) \n " ,
" graph.add_edge(0, 4, 3) \n " ,
" graph.add_edge(0, 5, 2) \n " ,
" graph.add_edge(1, 3, 5) \n " ,
" graph.add_edge(1, 4, 4) \n " ,
" graph.add_edge(2, 1, 6) \n " ,
" graph.add_edge(3, 2, 7) \n " ,
" graph.add_edge(3, 4, 8) \n " ,
" ``` \n " ,
" \n " ,
" Result: \n " ,
" * search_path(start=0, end=2) -> True \n " ,
" * search_path(start=0, end=0) -> True \n " ,
" * search_path(start=4, end=5) -> False "
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" ## Algorithm \n " ,
" \n " ,
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" To determine if there is a path, we can use either breadth-first or depth-first search. \n " ,
" \n " ,
" Breadth-first search can also be used to determine the shortest path. Depth-first search is easier to implement with just straight recursion, but often results in a longer path. \n " ,
" \n " ,
" We ' ll use a breadth-first search approach: \n " ,
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" \n " ,
" * Add the start node to the queue and mark it as visited \n " ,
" * If the start node is the end node, return True \n " ,
" * While the queue is not empty \n " ,
" * Dequeue a node and visit it \n " ,
" * If the node is the end node, return True \n " ,
" * Iterate through each adjacent node \n " ,
" * If the node has not been visited, add it to the queue and mark it as visited \n " ,
" * Return False \n " ,
" \n " ,
" Complexity: \n " ,
" * Time: O(V + E), where V = number of vertices and E = number of edges \n " ,
" * Space: O(V + E) "
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" ## Code "
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" %r un ../graph/graph.py "
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" from collections import deque \n " ,
" \n " ,
" \n " ,
" def path_exists(start, end): \n " ,
" if start is None or end is None: \n " ,
" return False \n " ,
" if start is end: \n " ,
" return True \n " ,
" queue = deque() \n " ,
" queue.append(start) \n " ,
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" start.visit_state = State.visited \n " ,
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" while queue: \n " ,
" node = queue.popleft() \n " ,
" if node is end: \n " ,
" return True \n " ,
" for adj_node in node.adjacent: \n " ,
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" if adj_node.visit_state == State.unvisited: \n " ,
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" queue.append(adj_node) \n " ,
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" adj_node.visit_state = State.visited \n " ,
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" return False "
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" source " : [
" ## Unit Test "
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" Overwriting test_path_exists.py \n "
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" source " : [
" %% writefile test_path_exists.py \n " ,
" from nose.tools import assert_equal \n " ,
" \n " ,
" \n " ,
" class TestPathExists(object): \n " ,
" \n " ,
" def test_path_exists(self): \n " ,
" nodes = [] \n " ,
" graph = Graph() \n " ,
" for id in range(0, 6): \n " ,
" nodes.append(graph.add_node(id)) \n " ,
" graph.add_edge(0, 1, 5) \n " ,
" graph.add_edge(0, 4, 3) \n " ,
" graph.add_edge(0, 5, 2) \n " ,
" graph.add_edge(1, 3, 5) \n " ,
" graph.add_edge(1, 4, 4) \n " ,
" graph.add_edge(2, 1, 6) \n " ,
" graph.add_edge(3, 2, 7) \n " ,
" graph.add_edge(3, 4, 8) \n " ,
" \n " ,
" assert_equal(path_exists(nodes[0], nodes[2]), True) \n " ,
" assert_equal(path_exists(nodes[0], nodes[0]), True) \n " ,
" assert_equal(path_exists(nodes[4], nodes[5]), False) \n " ,
" \n " ,
" print( ' Success: test_path_exists ' ) \n " ,
" \n " ,
" \n " ,
" def main(): \n " ,
" test = TestPathExists() \n " ,
" test.test_path_exists() \n " ,
" \n " ,
" \n " ,
" if __name__ == ' __main__ ' : \n " ,
" main() "
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" Success: test_path_exists \n "
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" %r un -i test_path_exists.py "
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