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Extract/Replaces keywords in sentences.

Project description

Build Status Documentation Status Version license

This module can be used to replace keywords in sentences or extract keywords from sentences.

Installation

$ pip install flashtext

Usage

Extract keywords
>>> from flashtext.keyword import KeywordProcessor
>>> keyword_processor = KeywordProcessor()
>>> 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']
Replace keywords
>>> 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.'
Case Sensitive example
>>> from flashtext.keyword 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']
No clean name for Keywords
>>> from flashtext.keyword 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']
Add Multiple Keywords simultaneously
>>> from flashtext.keyword 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']
To Remove keywords
>>> from flashtext.keyword 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']

For detecting Word Boundary currently any character other than this \w [A-Za-z0-9_] is considered a word boundary.

To set or add characters as part of word characters
>>> from flashtext.keyword 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.'))
>>> # []

API doc

Documentation can be found at FlashText Read the Docs.

Test

$ git clone https://github.com/vi3k6i5/flashtext
$ cd flashtext
$ pip install pytest
$ python setup.py test

Build Docs

$ git clone https://github.com/vi3k6i5/flashtext
$ cd flashtext/docs
$ pip install sphinx
$ make html
$ # open _build/html/index.html in browser to view it locally

Why not Regex?

It’s a custom algorithm based on Aho-Corasick algorithm and Trie Dictionary.

Benchmark

To do the same with regex it will take a lot of time:

Docs count

# Keywords

Regex

flashtext

1.5 million

2K

16 hours

Not measured

2.5 million

10K

15 days

15 mins

The idea for this library came from the following StackOverflow question.

Contribute

License

The project is licensed under the MIT license.

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