File size: 3,781 Bytes
e4b9a7b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 | # -*- coding: utf-8 -*-
# SPDX-FileCopyrightText: 2016-2025 PyThaiNLP Project
# SPDX-FileType: SOURCE
# SPDX-License-Identifier: Apache-2.0
"""
Trie data structure.
Designed to be used for tokenizer's dictionary, but can be for other purposes.
"""
from typing import Iterable, Iterator, List, Union
class Trie(Iterable[str]):
class Node:
__slots__ = "end", "children"
def __init__(self):
self.end = False
self.children = {}
def __init__(self, words: Iterable[str]):
self.words = set(words)
self.root = Trie.Node()
for word in words:
self.add(word)
def add(self, word: str) -> None:
"""
Add a word to the trie.
Spaces in front of and following the word will be removed.
:param str text: a word
"""
word = word.strip()
self.words.add(word)
cur = self.root
for ch in word:
child = cur.children.get(ch)
if not child:
child = Trie.Node()
cur.children[ch] = child
cur = child
cur.end = True
def remove(self, word: str) -> None:
"""
Remove a word from the trie.
If the word is not found, do nothing.
:param str text: a word
"""
# remove from set first
if word not in self.words:
return
self.words.remove(word)
# then remove from nodes
parent = self.root
data = [] # track path to leaf
for ch in word:
child = parent.children[ch]
data.append((parent, child, ch))
parent = child
# remove the last one
child.end = False
# prune up the tree
for parent, child, ch in reversed(data):
if child.end or child.children:
break
del parent.children[ch] # remove from parent dict
def prefixes(self, text: str) -> List[str]:
"""
List all possible words from first sequence of characters in a word.
:param str text: a word
:return: a list of possible words
:rtype: List[str]
"""
res = []
cur = self.root
for i, ch in enumerate(text):
node = cur.children.get(ch)
if not node:
break
if node.end:
res.append(text[: i + 1])
cur = node
return res
def __contains__(self, key: str) -> bool:
return key in self.words
def __iter__(self) -> Iterator[str]:
yield from self.words
def __len__(self) -> int:
return len(self.words)
def dict_trie(dict_source: Union[str, Iterable[str], Trie]) -> Trie:
"""
Create a dictionary trie from a file or an iterable.
:param str|Iterable[str]|pythainlp.util.Trie dict_source: a path to
dictionary file or a list of words or a pythainlp.util.Trie object
:return: a trie object
:rtype: pythainlp.util.Trie
"""
trie = Trie([])
if isinstance(dict_source, str) and len(dict_source) > 0:
# dict_source is a path to dictionary text file
with open(dict_source, "r", encoding="utf8") as f:
_vocabs = f.read().splitlines()
trie = Trie(_vocabs)
elif isinstance(dict_source, Iterable) and not isinstance(
dict_source, str
):
# Note: Since Trie and str are both Iterable,
# so the Iterable check should be here, at the very end,
# because it has less specificality
trie = Trie(dict_source)
else:
raise TypeError(
"Type of dict_source must be pythainlp.util.Trie, "
"or Iterable[str], or non-empty str (path to source file)"
)
return trie
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