Create a new FM-index instance

>>> 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

Build FM-index

>>> 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

Search word from FM-index

>>> 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

Add a document

>>> fm.push_back('Baritsu')

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

Read FM-index from a binary file

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

• read(path)

Write FM-index binary to a file

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

• write(path)

0.3 (2014-11-24)

• “OR” search and “NOT” search are available in FMIndex.search().
• FMIndex.size and FMIndex.docsize are available as property

0.2 (2014-03-28)

“AND” search is available by giving Sequence (list, tuple, etc.) FMIndex.search()

0.1 (2014-03-11)

First release.