A Python implementation of the Rapid Automatic Keyword Extraction (RAKE) algorithm as described in: Rose, S., Engel, D., Cramer, N., & Cowley, W. (2010). Automatic Keyword Extraction from Individual Documents. In M. W. Berry & J. Kogan (Eds.), Text Mining: Theory and Applications: John Wiley & Sons.

The source code is released under the MIT License.

• Complete rewrite of the Rake class.
  • Cleaned up code by using tools from python's collections lib (Counter and defaultdict)
  • Methods now exist inside the Rake class, no need for them to be exposed outside (though they can still be called if need be
  • Rewrote the existing string tokenizer based on the process listed in the original paper (ie. "First, the document text is split into an array of words by the specified word delimiters. This array is then split into sequences of contiguous words at phrase delimiters and stop word positions.")
  • Uses the fox stopword list by default, since it returns results more similar to the abstract used as an example in the original paper, and the smart stopword list is overkill
  • Rake.run() can now take a tokenized list of words as input for alternative tokenizer use
  • Rake.run() now returns a sorted list of namedtuple KeywordScores, sorted by overall score and also containing sum_deg and sum_freq metrics. These can also be accessed via the Rake.keyword_scores attribute after a call to Rake.run()
  • Rake.word_scores is a class attribute that returns a sorted list of namedtuple WordScores, sorted by overall score and containing deg and freq metrics, available after calling Rake.run()
• Package should be almost ready to install from pypi or github (thanks to @tomaspinho and @fabinvf)

• Develop some tests and make sure we're legit
• Add adjoining features functionality (two potential keywords split by a stopword) aneesha#8

Dependencies for development are specified in the dev-requirements.txt file. You can install them with pip install -r dev-requirements.txt. You can run the tests with py.test tests after the requirements are installed.