1.1 安装

pip install flashtext

 

1.2 使用例子

1.2.1 关键字提取

>>> from flashtext import KeywordProcessor>>> keyword_processor = KeywordProcessor()>>> # keyword_processor.add_keyword(
     
      , 
      
       )>>> keyword_processor.add_keyword('Big Apple', 'New York')>>> keyword_processor.add_keyword('Bay Area')>>> keywords_found = keyword_processor.extract_keywords('I love Big Apple and Bay Area.')>>> keywords_found>>> # ['New York', 'Bay Area']
      
     

 

1.2.2 关键字替换

>>> keyword_processor.add_keyword('New Delhi', 'NCR region')>>> new_sentence = keyword_processor.replace_keywords('I love Big Apple and new delhi.')>>> new_sentence>>> # 'I love New York and NCR region.'

 

1.2.3 区分大小写字母

>>> from flashtext import KeywordProcessor>>> keyword_processor = KeywordProcessor(case_sensitive=True)>>> keyword_processor.add_keyword('Big Apple', 'New York')>>> keyword_processor.add_keyword('Bay Area')>>> keywords_found = keyword_processor.extract_keywords('I love big Apple and Bay Area.')>>> keywords_found>>> # ['Bay Area']

 

1.2.4 关键字不清晰

>>> from flashtext import KeywordProcessor>>> keyword_processor = KeywordProcessor()>>> keyword_processor.add_keyword('Big Apple')>>> keyword_processor.add_keyword('Bay Area')>>> keywords_found = keyword_processor.extract_keywords('I love big Apple and Bay Area.')>>> keywords_found>>> # ['Big Apple', 'Bay Area']

 

1.2.5 同时添加多个关键词

>>> from flashtext import KeywordProcessor>>> keyword_processor = KeywordProcessor()>>> keyword_dict = {>>>     "java": ["java_2e", "java programing"],>>>     "product management": ["PM", "product manager"]>>> }>>> # {'clean_name': ['list of unclean names']}>>> keyword_processor.add_keywords_from_dict(keyword_dict)>>> # Or add keywords from a list:>>> keyword_processor.add_keywords_from_list(["java", "python"])>>> keyword_processor.extract_keywords('I am a product manager for a java_2e platform')>>> # output ['product management', 'java']

 

1.2.6 删除关键字

>>> from flashtext import KeywordProcessor>>> keyword_processor = KeywordProcessor()>>> keyword_dict = {>>>     "java": ["java_2e", "java programing"],>>>     "product management": ["PM", "product manager"]>>> }>>> keyword_processor.add_keywords_from_dict(keyword_dict)>>> print(keyword_processor.extract_keywords('I am a product manager for a java_2e platform'))>>> # output ['product management', 'java']>>> keyword_processor.remove_keyword('java_2e')>>> # you can also remove keywords from a list/ dictionary>>> keyword_processor.remove_keywords_from_dict({
   "product management": ["PM"]})>>> keyword_processor.remove_keywords_from_list(["java programing"])>>> keyword_processor.extract_keywords('I am a product manager for a java_2e platform')>>> # output ['product management']

 

有时候我们会将一些特殊符号作为字符边界，比如 空格，\ 等等。为了重新设定字边界，我们需要添加一些符号告诉算法，这是单词字符的一部分。

 

>>> from flashtext import KeywordProcessor>>> keyword_processor = KeywordProcessor()>>> keyword_processor.add_keyword('Big Apple')>>> print(keyword_processor.extract_keywords('I love Big Apple/Bay Area.'))>>> # ['Big Apple']>>> keyword_processor.add_non_word_boundary('/')>>> print(keyword_processor.extract_keywords('I love Big Apple/Bay Area.'))>>> # []