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| 1 | +# Time: ctor: O(n * l), n is the number of products |
| 2 | +# , l is the average length of product name |
| 3 | +# suggest: O(l^2) |
| 4 | +# Space: O(t), t is the number of nodes in trie |
| 5 | + |
| 6 | +import collections |
| 7 | + |
| 8 | + |
| 9 | +class TrieNode(object): |
| 10 | + |
| 11 | + def __init__(self): |
| 12 | + self.__TOP_COUNT = 3 |
| 13 | + self.leaves = collections.defaultdict(TrieNode) |
| 14 | + self.infos = [] |
| 15 | + |
| 16 | + def insert(self, words, i): |
| 17 | + curr = self |
| 18 | + for c in words[i]: |
| 19 | + curr = curr.leaves[c] |
| 20 | + curr.add_info(words, i) |
| 21 | + |
| 22 | + def add_info(self, words, i): |
| 23 | + self.infos.append(i) |
| 24 | + self.infos.sort(key=lambda x: words[x]) |
| 25 | + if len(self.infos) > self.__TOP_COUNT: |
| 26 | + self.infos.pop() |
| 27 | + |
| 28 | + |
| 29 | +class Solution(object): |
| 30 | + def suggestedProducts(self, products, searchWord): |
| 31 | + """ |
| 32 | + :type products: List[str] |
| 33 | + :type searchWord: str |
| 34 | + :rtype: List[List[str]] |
| 35 | + """ |
| 36 | + trie = TrieNode() |
| 37 | + for i in xrange(len(products)): |
| 38 | + trie.insert(products, i) |
| 39 | + result = [[] for _ in xrange(len(searchWord))] |
| 40 | + for i, c in enumerate(searchWord): |
| 41 | + if c not in trie.leaves: |
| 42 | + break |
| 43 | + trie = trie.leaves[c] |
| 44 | + result[i] = map(lambda x: products[x], trie.infos) |
| 45 | + return result |
| 46 | + |
| 47 | + |
| 48 | +# Time: ctor: O(n * l * log(n * l)), n is the number of products |
| 49 | +# , l is the average length of product name |
| 50 | +# suggest: O(l^2) |
| 51 | +# Space: O(t), t is the number of nodes in trie |
| 52 | +class TrieNode2(object): |
| 53 | + |
| 54 | + def __init__(self): |
| 55 | + self.__TOP_COUNT = 3 |
| 56 | + self.leaves = collections.defaultdict(TrieNode2) |
| 57 | + self.infos = [] |
| 58 | + |
| 59 | + def insert(self, words, i): |
| 60 | + curr = self |
| 61 | + for c in words[i]: |
| 62 | + curr = curr.leaves[c] |
| 63 | + curr.add_info(i) |
| 64 | + |
| 65 | + def add_info(self, i): |
| 66 | + if len(self.infos) == self.__TOP_COUNT: |
| 67 | + return |
| 68 | + self.infos.append(i) |
| 69 | + |
| 70 | + |
| 71 | +class Solution2(object): |
| 72 | + def suggestedProducts(self, products, searchWord): |
| 73 | + """ |
| 74 | + :type products: List[str] |
| 75 | + :type searchWord: str |
| 76 | + :rtype: List[List[str]] |
| 77 | + """ |
| 78 | + products.sort() |
| 79 | + trie = TrieNode2() |
| 80 | + for i in xrange(len(products)): |
| 81 | + trie.insert(products, i) |
| 82 | + result = [[] for _ in xrange(len(searchWord))] |
| 83 | + for i, c in enumerate(searchWord): |
| 84 | + if c not in trie.leaves: |
| 85 | + break |
| 86 | + trie = trie.leaves[c] |
| 87 | + result[i] = map(lambda x: products[x], trie.infos) |
| 88 | + return result |
| 89 | + |
| 90 | + |
| 91 | +# Time: ctor: O(n * l * log(n * l)), n is the number of products |
| 92 | +# , l is the average length of product name |
| 93 | +# suggest: O(l^2 * n) |
| 94 | +# Space: O(n * l) |
| 95 | +import bisect |
| 96 | + |
| 97 | + |
| 98 | +class Solution3(object): |
| 99 | + def suggestedProducts(self, products, searchWord): |
| 100 | + """ |
| 101 | + :type products: List[str] |
| 102 | + :type searchWord: str |
| 103 | + :rtype: List[List[str]] |
| 104 | + """ |
| 105 | + products.sort() # Time: O(n * l * log(n * l)) |
| 106 | + result = [] |
| 107 | + prefix = "" |
| 108 | + for i, c in enumerate(searchWord): # Time: O(l) |
| 109 | + prefix += c |
| 110 | + start = bisect.bisect_left(products, prefix) # Time: O(log(n * l)) |
| 111 | + new_products = [] |
| 112 | + for j in xrange(start, len(products)): # Time: O(n * l) |
| 113 | + if not (i < len(products[j]) and products[j][i] == c): |
| 114 | + break |
| 115 | + new_products.append(products[j]) |
| 116 | + products = new_products |
| 117 | + result.append(products[:3]) |
| 118 | + return result |
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