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Diffstat (limited to 'scratch/deepmind/part_two/mesh-message.py')
-rw-r--r-- | scratch/deepmind/part_two/mesh-message.py | 183 |
1 files changed, 183 insertions, 0 deletions
diff --git a/scratch/deepmind/part_two/mesh-message.py b/scratch/deepmind/part_two/mesh-message.py new file mode 100644 index 000000000000..a265296ab066 --- /dev/null +++ b/scratch/deepmind/part_two/mesh-message.py @@ -0,0 +1,183 @@ +import unittest +from collections import deque +from heapq import heappush, heappop + + +################################################################################ +# InterviewCake.com +################################################################################ +# construct_path :: Map String String -> String -> String -> [String] +def construct_path(paths, beg, end): + """ + Reconstruct the path from `beg` to `end`. + """ + result = [] + current = end + + print(paths) + print(beg, end) + print('-----') + while current: + result.append(current) + current = paths[current] + + result.reverse() + return result + + +def get_path_ic(graph, beg, end): + """ + InterviewCake uses a dictionary and back-tracking to store and reconstruct + the path instead of storing the path as state on each node. + This reduces the memory costs. See get_path_bft for an example of this less + optimal solution. + """ + if beg not in graph: + raise Exception('Origin node absent from graph.') + + if end not in graph: + raise Exception('Destination node absent from graph.') + + q = deque() + q.append(beg) + paths = {beg: None} + + while q: + node = q.popleft() + + if node == end: + print(graph) + return construct_path(paths, beg, end) + + for x in graph[node]: + if x not in paths: + paths[x] = node + q.append(x) + + return None + + +################################################################################ +# Per-node state +################################################################################ +def get_path_bft(graph, beg, end): + """ + Here we find the shortest path from `beg` to `end` in `graph` by doing a BFT + from beg to end and storing the path state alongside each node in the queue. + """ + if beg not in graph: + raise Exception('Origin node absent from graph.') + + if end not in graph: + raise Exception('Destination node absent from graph.') + + q = deque() + seen = set() + q.append([beg]) + + while q: + path = q.popleft() + node = path[-1] + seen.add(node) + + if node == end: + return path + + for x in graph[node]: + if x not in seen: + q.append(path + [x]) + + +################################################################################ +# Dijkstra's Algorithm +################################################################################ +def get_path(graph, beg, end): + """ + Here we find the shortest path using Dijkstra's algorithm, which is my + favorite solution. + """ + if beg not in graph: + raise Exception( + 'The origin node, {}, is not present in the graph'.format(beg)) + + if end not in graph: + raise Exception( + 'The origin node, {}, is not present in the graph'.format(end)) + + q = [] + seen = set() + heappush(q, (1, [beg])) + + while q: + weight, path = heappop(q) + node = path[-1] + seen.add(node) + + if node == end: + return path + + for x in graph[node]: + if x not in seen: + heappush(q, (weight + 1, path + [x])) + + return None + + +# Tests +class Test(unittest.TestCase): + def setUp(self): + self.graph = { + 'a': ['b', 'c', 'd'], + 'b': ['a', 'd'], + 'c': ['a', 'e'], + 'd': ['b', 'a'], + 'e': ['c'], + 'f': ['g'], + 'g': ['f'], + } + + def test_two_hop_path_1(self): + actual = get_path(self.graph, 'a', 'e') + expected = ['a', 'c', 'e'] + self.assertEqual(actual, expected) + + def test_two_hop_path_2(self): + actual = get_path(self.graph, 'd', 'c') + expected = ['d', 'a', 'c'] + self.assertEqual(actual, expected) + + def test_one_hop_path_1(self): + actual = get_path(self.graph, 'a', 'c') + expected = ['a', 'c'] + self.assertEqual(actual, expected) + + def test_one_hop_path_2(self): + actual = get_path(self.graph, 'f', 'g') + expected = ['f', 'g'] + self.assertEqual(actual, expected) + + def test_one_hop_path_3(self): + actual = get_path(self.graph, 'g', 'f') + expected = ['g', 'f'] + self.assertEqual(actual, expected) + + def test_zero_hop_path(self): + actual = get_path(self.graph, 'a', 'a') + expected = ['a'] + self.assertEqual(actual, expected) + + def test_no_path(self): + actual = get_path(self.graph, 'a', 'f') + expected = None + self.assertEqual(actual, expected) + + def test_start_node_not_present(self): + with self.assertRaises(Exception): + get_path(self.graph, 'h', 'a') + + def test_end_node_not_present(self): + with self.assertRaises(Exception): + get_path(self.graph, 'a', 'h') + + +unittest.main(verbosity=2) |