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import re
def extract_language_and_text_updated(speaker, dialogue):
# 使用正则表达式匹配<语言>标签和其后的文本
pattern_language_text = r"<(\S+?)>([^<]+)"
matches = re.findall(pattern_language_text, dialogue, re.DOTALL)
speaker = speaker[1:-1]
# 清理文本：去除两边的空白字符
matches_cleaned = [(lang.upper(), text.strip()) for lang, text in matches]
matches_cleaned.append(speaker)
return matches_cleaned
def validate_text(input_text):
# 验证说话人的正则表达式
pattern_speaker = r"(\[\S+?\])((?:\s*<\S+?>[^<\[\]]+?)+)"
# 使用re.DOTALL标志使.匹配包括换行符在内的所有字符
matches = re.findall(pattern_speaker, input_text, re.DOTALL)
# 对每个匹配到的说话人内容进行进一步验证
for _, dialogue in matches:
language_text_matches = extract_language_and_text_updated(_, dialogue)
if not language_text_matches:
return (
False,
"Error: Invalid format detected in dialogue content. Please check your input.",
)
# 如果输入的文本中没有找到任何匹配项
if not matches:
return (
False,
"Error: No valid speaker format detected. Please check your input.",
)
return True, "Input is valid."
def text_matching(text: str) -> list:
speaker_pattern = r"(\[\S+?\])(.+?)(?=\[\S+?\]|$)"
matches = re.findall(speaker_pattern, text, re.DOTALL)
result = []
for speaker, dialogue in matches:
result.append(extract_language_and_text_updated(speaker, dialogue))
return result
def cut_para(text):
splitted_para = re.split("[\n]", text) # 按段分
splitted_para = [
sentence.strip() for sentence in splitted_para if sentence.strip()
] # 删除空字符串
return splitted_para
def cut_sent(para):
para = re.sub("([。！;？\?])([^”’])", r"\1\n\2", para) # 单字符断句符
para = re.sub("(\.{6})([^”’])", r"\1\n\2", para) # 英文省略号
para = re.sub("(\…{2})([^”’])", r"\1\n\2", para) # 中文省略号
para = re.sub("([。！？\?][”’])([^，。！？\?])", r"\1\n\2", para)
para = para.rstrip() # 段尾如果有多余的\n就去掉它
return para.split("\n")
if __name__ == "__main__":
text = """
[说话人1]
[说话人2]<zh>你好吗？<jp>元気ですか？<jp>こんにちは，世界。<zh>你好吗？
[说话人3]<zh>谢谢。<jp>どういたしまして。
"""
text_matching(text)
# 测试函数
test_text = """
[说话人1]<zh>你好，こんにちは！<jp>こんにちは，世界。
[说话人2]<zh>你好吗？
"""
text_matching(test_text)
res = validate_text(test_text)
print(res)
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