spaCy/spacy/lang/th/__init__.py

69 lines
1.7 KiB
Python

from typing import Set, Dict, Callable, Any
from thinc.api import Config
from .stop_words import STOP_WORDS
from .lex_attrs import LEX_ATTRS
from ...language import Language
from ...tokens import Doc
from ...util import DummyTokenizer, registry
DEFAULT_CONFIG = """
[nlp]
lang = "th"
stop_words = {"@language_data": "spacy.th.stop_words"}
lex_attr_getters = {"@language_data": "spacy.th.lex_attr_getters"}
[nlp.tokenizer]
@tokenizers = "spacy.ThaiTokenizer.v1"
[nlp.vocab_data]
@language_data = "spacy-lookups-data"
lang = ${nlp:lang}
tables = ["lexeme_norm"]
"""
@registry.language_data("spacy.th.stop_words")
def stop_words() -> Set[str]:
return STOP_WORDS
@registry.language_data("spacy.th.lex_attr_getters")
def lex_attr_getters() -> Dict[int, Callable[[str], Any]]:
return LEX_ATTRS
@registry.tokenizers("spacy.ThaiTokenizer.v1")
def create_thai_tokenizer():
def thai_tokenizer_factory(nlp):
return ThaiTokenizer(nlp)
return thai_tokenizer_factory
class ThaiTokenizer(DummyTokenizer):
def __init__(self, nlp: Language) -> None:
try:
from pythainlp.tokenize import word_tokenize
except ImportError:
raise ImportError(
"The Thai tokenizer requires the PyThaiNLP library: "
"https://github.com/PyThaiNLP/pythainlp"
)
self.word_tokenize = word_tokenize
self.vocab = nlp.vocab
def __call__(self, text: str) -> Doc:
words = list(self.word_tokenize(text))
spaces = [False] * len(words)
return Doc(self.vocab, words=words, spaces=spaces)
class Thai(Language):
lang = "th"
default_config = Config().from_str(DEFAULT_CONFIG)
__all__ = ["Thai"]