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import regex as re | |
try: | |
from contants import config | |
except: | |
pass | |
langid_languages = ["af", "am", "an", "ar", "as", "az", "be", "bg", "bn", "br", "bs", "ca", "cs", "cy", "da", "de", | |
"dz", "el", | |
"en", "eo", "es", "et", "eu", "fa", "fi", "fo", "fr", "ga", "gl", "gu", "he", "hi", "hr", "ht", | |
"hu", "hy", | |
"id", "is", "it", "ja", "jv", "ka", "kk", "km", "kn", "ko", "ku", "ky", "la", "lb", "lo", "lt", | |
"lv", "mg", | |
"mk", "ml", "mn", "mr", "ms", "mt", "nb", "ne", "nl", "nn", "no", "oc", "or", "pa", "pl", "ps", | |
"pt", "qu", | |
"ro", "ru", "rw", "se", "si", "sk", "sl", "sq", "sr", "sv", "sw", "ta", "te", "th", "tl", "tr", | |
"ug", "uk", | |
"ur", "vi", "vo", "wa", "xh", "zh", "zu"] | |
def classify_language(text: str, target_languages: list = None) -> str: | |
try: | |
module = config.language_identification.language_identification_library.lower() | |
except: | |
module = "langid" | |
if not target_languages: | |
target_languages = None | |
if module == "fastlid" or module == "fasttext": | |
from fastlid import fastlid, supported_langs | |
classifier = fastlid | |
if target_languages is not None: | |
target_languages = [lang for lang in target_languages if lang in supported_langs] | |
fastlid.set_languages = target_languages | |
elif module == "langid": | |
import langid | |
classifier = langid.classify | |
if target_languages is not None: | |
target_languages = [lang for lang in target_languages if lang in langid_languages] | |
langid.set_languages(target_languages) | |
else: | |
raise ValueError(f"Wrong LANGUAGE_IDENTIFICATION_LIBRARY in config.py") | |
lang = classifier(text)[0] | |
return lang | |
# def classify_zh_ja(text: str) -> str: | |
# for idx, char in enumerate(text): | |
# unicode_val = ord(char) | |
# | |
# # 检测日语字符 | |
# if 0x3040 <= unicode_val <= 0x309F or 0x30A0 <= unicode_val <= 0x30FF: | |
# return "ja" | |
# | |
# # 检测汉字字符 | |
# if 0x4E00 <= unicode_val <= 0x9FFF: | |
# # 检查周围的字符 | |
# next_char = text[idx + 1] if idx + 1 < len(text) else None | |
# | |
# if next_char and (0x3040 <= ord(next_char) <= 0x309F or 0x30A0 <= ord(next_char) <= 0x30FF): | |
# return "ja" | |
# | |
# return "zh" | |
def split_alpha_nonalpha(text, mode=1): | |
""" | |
Splits the input text based on the specified mode. | |
Parameters: | |
- text (str): The input text to be split. | |
- mode (int): The mode for splitting (1 or 2). | |
- Mode 1: Splits based on the pattern - Chinese/Japanese followed by English or vice versa. | |
- Mode 2: Splits based on the pattern - Chinese/Japanese followed by English/digit or vice versa. | |
Returns: | |
- list: A list of substrings after the split. | |
""" | |
if mode == 1: | |
pattern = r'(?<=[\u4e00-\u9fff\u3040-\u30FF\d\s])(?=[\p{Latin}])|(?<=[\p{Latin}\s])(?=[\u4e00-\u9fff\u3040-\u30FF\d])' | |
elif mode == 2: | |
pattern = r'(?<=[\u4e00-\u9fff\u3040-\u30FF\s])(?=[\p{Latin}\d])|(?<=[\p{Latin}\d\s])(?=[\u4e00-\u9fff\u3040-\u30FF])' | |
else: | |
raise ValueError("Invalid mode. Supported modes are 1 and 2.") | |
return re.split(pattern, text) | |
if __name__ == "__main__": | |
text = "这是一个测试文本" | |
print(classify_language(text)) | |
# print(classify_zh_ja(text)) # "zh" | |
text = "これはテストテキストです" | |
print(classify_language(text)) | |
# print(classify_zh_ja(text)) # "ja" | |