High performance Trie and Ahocorasick automata (AC automata) for python
Project description
cyac
High performance Trie & Keyword Match & Replace Tool.
It's implemented by cython, and will be compiled to cpp. The trie data structure is cedar, which is an optimized double array trie. it supports Python2.7 and 3.4+. It supports pickle to dump and load.
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Quick Start
This module is written in cython. You need cython installed.
pip install cyac
Then create a Trie
>>> from cyac import Trie
>>> trie = Trie()
add/get/remove keyword
>>> trie.insert(u"哈哈") # return keyword id in trie, return -1 if doesn't exist
>>> trie.get(u"哈哈") # return keyword id in trie, return -1 if doesn't exist
>>> trie.remove(u"呵呵") # return keyword in trie
>>> trie[id] # return the word corresponding to the id
>>> trie[u"呵呵"] # similar to get but it will raise exeption if doesn't exist
>>> u"呵呵" in trie # test if the keyword is in trie
get all keywords
>>> for key, id_ in trie.items():
>>> print(key, id_)
prefix/ predict
>>> # return the string in the trie which starts with given string
>>> for id_ in trie.predict(u"呵呵"):
>>> print(id_)
>>> # return the prefix of given string which is in the trie.
>>> for id_, len_ in trie.prefix(u"呵呵"):
>>> print(id_, len_)
trie extract,replace
>>> python_id = trie.insert(u"python")
>>> trie.replace_longest("python", {python_id: u"hahah"}, set([ord(" ")])) # the second parameter is seperator. If you specify seperators. it only matches strings tween seperators. e.g. It won't match 'apython'
>>> for id_, start, end in trie.match_longest(u"python", set([ord(" ")])):
>>> print(id_, start, end)
Aho Corasick extract
>>> ac = AC.build([u"python", u"ruby"])
>>> for id, start, end in ac.match(u"python ruby"):
>>> print(id, start, end)
Export to File, then we can use mmap to load file, share data between processes.
>>> ac = AC.build([u"python", u"ruby"])
>>> ac.save("filename")
>>> ac.to_buff(buff_object)
Init from Python Buffer
>>> import mmap
>>> with open("filename", "r+b") as bf:
buff_object = mmap.mmap(bf.fileno(), 0)
>>> AC.from_buff(buff_object, copy=True) # it allocs new memory
>>> AC.from_buff(buff_object, copy=False) # it shares memory
Multi Process example
import mmap
from multiprocessing import Process
from cyac import AC
def get_mmap():
with open("random_data", "r+b") as bf:
buff_object = mmap.mmap(bf.fileno(), 0)
ac_trie = AC.from_buff(buff_object, copy=False)
# Do your aho searches here. "match" function is process safe.
processes_list = list()
for x in range(0, 6):
p = Process(
target=get_mmap,
)
p.start()
processes_list.append(p)
for p in processes_list:
p.join()
For more information about multiprocessing and memory analysis in cyac, see this issue.
Thread safety
The function "match" of the AC automaton is thread/process safe. It is possible to find matches in parrallel with a shared AC automaton, but not write/append patterns to it.
Performance
On Ubuntu 14.04.5/Intel(R) Core(TM) i7-4790K CPU @ 4.00GHz.
Trie
Compared With HatTrie, Horizon axis is token num. Vertical axis is used time(seconds).
Insert
Get
Remove
KeyWord Extract/Replace
Compared With flashText. Regular Expression is too slow in this task (See flashText's bench mark). Horizon axis is char num to be match. Vertical axis is used time(seconds).
Aho Corasick Algorithm
Compared With pyahocorasick, Horizon axis is char num to be match. Vertical axis is used time(seconds).
Unicode
>>> len(char.lower()) == len(char) # this is always true in python2, but not in python3
>>> len(u"İstanbul") != len(u"İstanbul".lower()) # in python3
In case insensitive matching, this library take care of the fact, and returns correct offset.
Run Test
python setup.py build
PYTHONPATH=$(pwd)/build/BUILD_DST python3 tests/test_all.py
PYTHONPATH=$(pwd)/build/BUILD_DST python3 bench/bench_*.py
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