Shellinford is an implementation of a Wavelet Matrix/Tree succinct data structure for document retrieval.

It is based on shellinford C++ library.

NOTE: This module requires C++11 compiler

$ pip install shellinford

>>> import shellinford
>>> fm = shellinford.FMIndex()

• shellinford.Shellinford([use_wavelet_tree=True, filename=None])
  • When given a filename, Shellinford loads FM-index data from the file

>>> fm.build(['Milky Holmes', 'Sherlock "Sheryl" Shellingford', 'Milky'], 'milky.fm')

• build([docs, filename])
  • When given a filename, Shellinford stores FM-index data to the file

>>> for doc in fm.search('Milky'):
>>>     print('doc_id:', doc.doc_id)
>>>     print('count:', doc.count)
>>>     print('text:', doc.text)
doc_id: 0
count: [1]
text: Milky Holmes
doc_id: 2
count: [1]
text: Milky

>>> for doc in fm.search(['Milky', 'Holmes']):
>>>     print('doc_id:', doc.doc_id)
>>>     print('count:', doc.count)
>>>     print('text:', doc.text)
doc_id: 1
count: [1]
text: Milky Holmes

• search(query, [_or=False, ignores=[]])
  • If _or = True, then "OR" search is executed, else "AND" search
  • Given ignores, "NOT" search is also executed
  • NOTE: The search function is available after FM-index is built or loaded

>>> fm.count('Milky'):
2

>>> fm.count(['Milky', 'Holmes']):
1

• count(query, [_or=False])
  • If _or = True, then "OR" search is executed, else "AND" search
  • NOTE: The count function is available after FM-index is built or loaded
  • This function is slightly faster than the search function

>>> fm.push_back('Baritsu')

• push_back(doc)
  • NOTE: A document added by this method is not available to search until build

>>> fm.read('milky_holmes.fm')

• read(path)

>>> fm.write('milky_holmes.fm')

• write(path)

>>> 'baritsu' in fm

• Wrapper code is licensed under the New BSD License.
• Bundled shellinford C++ library (c) 2012 echizen_tm is licensed under the New BSD License.