Data structure and relevant algorithms for extremely fast prefix/fuzzy string searching in Python.

• val
• children
• parent
• depth

• Get Trie size:

trie.size

• Create Trie:

trie = Trie()

• Add key:

trie.add("test")

• Remove key:

trie.remove("test")

• Find key:

trie.find("test")

• Dfs search alphabets:

trie.dfs()

• Bfs search alphabets:

trie.bfs()

• Traverse all tree

trie.traverse()

• Prefix Search(if does not have this prefix, then return all value of tree)

trie.prefix_search("te")

• Fast test for valid prefix:

trie.has_key_with_prefix("t")

• get prefix of the word

trie.get_prefix("testing")  # 返回test

• Cmp tree

trie1 == trie2
trie1 > trie2
trie1 < trie2

• If item in trie

"test" in trie

• Most used alphabet(property)

trie.most_used_alphabet

• Least used alphabet(property)

trie.least_used_alphabet

• Alphabet count

trie.alphabet_count()

• Fuzzy search

trie.fuzzy_search('es')

• Longest word(property)

trie.longest_word

• Shortest word(property)

trie.shortest_word

• Testing Case(Big data)

SkyRover