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Non-Overlapping Aho-Corasick Python extension, for Python 2 (str and unicode) and Python 3
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JDonner/NoAho
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Non-Overlapping Aho-Corasick Trie Features: - 'short' and 'long' (longest matching key) searches, both one-off and iteration over all non-overlapping keyword matches in some text. - Works with both unicode and str in Python 2, and unicode in Python 3. NOTE: As everything is simply single UCS4 / UTF-32 codepoints under the hood, all substrings and input unicode must be normalized, ie any separate modifying marks must be folded into each codepoint. See: http://stackoverflow.com/questions/16467479/normalizing-unicode Or, theoretically, you could put into the tree all forms of the keywords you expect to see in your text. - Allows you to associate an arbitrary Python object payload with each keyword, and supports dict operations len(), [], and 'in' for the keywords (though no del or traversal). - Does the 'compilation' (generation of Aho-Corasick failure links) of the trie on-demand, ie you could mix adding keywords and searching text, freely, but mostly it just relieves you of worrying about compiling. - Can be used commercially, it's under the minimal, MIT license (if you somehow need a different license, ask me, I mean for it to be used). Anti-Features: - Will not find overlapped keywords (eg given keywords 'abc' and 'cdef', will not find 'cdef' in 'abcdef'. Any full Aho-Corasick implementation would give you both. The package 'Acora' is an alternative package for this use. (noaho can be relatively easily modified to be a normal Aho-Corasick, but it wasn't what I personally needed.) - Lacking overlap, find[all]_short is kind of useless. - Lacks key iteration and deletion from the mapping (dict) protocol. - Memory leaking untested (one run under valgrind turned up nothing, but it wasn't extensive). - No /testcase/ for unicode in Python 2 (did manual test however) Unicode chars represented as ucs4, and, each character has its own hashtable, so it's relatively memory-heavy (see 'Ways to Reduce Memory Use' below). - Requires a C++ compiler (C++98 support is enough). Bug reports and patches welcome of course! To build and install, use either pip install noaho or # Python 2 python2 setup.py install # (or ... build, and copy the .so to where you want it) pip install or # Python 3 python3 setup.py install # (or ... build, and copy the .so to where you want it) API: from noaho import NoAho trie = NoAho() 'text' below applies to str and unicode in Python 2, or unicode in Python 3 (all there is) trie.add(key_text, optional payload) (key_start, key_end, key_value) = trie.find_short(text_to_search) (key_start, key_end, key_value) = trie.find_long(text_to_search) (key_start, key_end, key_value) = trie.findall_short(text_to_search) (key_start, key_end, key_value) = trie.findall_long(text_to_search) # keyword = text_to_search[key_start:key_end] trie['keyword] = key_value key_value = trie.find_long(text_to_search) assert len(trie) assert keyword in trie Examples: >>> a = NoAho() >>> a.add('ms windows') >>> a.add('ms windows 2000', "this is canonical") >>> a.add('windows', None) >>> a.add('windows 2000') >>> a['apple'] = None >>> text = 'windows 2000 ms windows 2000 windows' >>> for k in a.findall_short(text): ... print text[k[0]:k[1]] ... windows ms windows windows >>> for k in a.findall_long(text): ... print text[k[0]:k[1]] ... windows 2000 ms windows 2000 windows Mapping (dictionary) methods: trie = NoAho() trie['apple'] = apple_handling_function trie['orange'] = Orange() trie.add('banana') # payload will be None trie['pear'] # will give key error assert isinstance(trie['orange'], Orange) assert 'banana' in trie len(trie) # No del; # no iteration over keys The 'find[all]_short' forms are named as long and awkwardly as they are, to leave plain 'find[all]' free if overlapping matches are ever implemented. For the fullest spec of what the code will and will not do, check out test-noaho.py (run it with: python[3] test-noaho.py) Untested: whether the payload handling is complete, ie that there are no memory leaks. It should be correct though. Regenerating the Python Wrapper: - Needs a C++ compiler (C++98 is fine) and Cython. You do not need to rebuild the Cython wrapper (the generated noaho.cpp), but if you want to make changes to the module itself, there is a script: test-all-configurations.sh which will, with minor configuration tweaking, rebuild and test against both python 2 and 3. It requires you to have a Cython tarball in the top directory. Note that the python you used to install Cython should be the same as the one you use to do the regeneration, because the regeneration setup includes a module Cython.Distutils, from the installation. Cython generates python-wrapper noaho.cpp from noaho.pyx (be careful to distinguish it from the misnamed array-aho.* (it uses hash tables), which is the original C++ code). Ways to Reduce Memory Use: One of its aims is to handle Unicode, which means you have to accommodate a huge branching factor, thus the hashtable (a full array would be out of the question). Ways to attack memory size might be, to either force very conservative hashtable growth, or, once the trie is complete (in 'compile', say) go through the tree and replace the hashtables with just-the-right-size arrays - linear scan / binary search should be fast enough if small enough, and take less memory. If you're willing to do a linear scan at that point, you could switch to UTF-8, too, saving quite a bit of memory. Danny Yoo's original code I think just started out as arrays and would grow to hashtables when needed. Also, if all you need is ASCII, you could re-define AC_CHAR_TYPE to be 'char'. I've tried to be careful to use AC_CHAR_TYPE consistently, but you'd probably want to go through the code to make sure if you're going to rely on this. Python 3 uses Unicode internally though and would do a lot of conversions anyway. Otherwise, I don't trust my knowledge of Unicode enough to try to play games with storing fewer bits. In the Hopper: I have a case-insensitive version (the easiest thing is just to downcase everything you add or search for in noaho.pyx), and, one that will only yield keywords at word boundaries, thanks to Python's unicode character classes. (However, this second is a bit raw, and you can do it manually anyway.)
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