Pure Python 版オンライン形態素解析ツール Rakuten MA ref: http://qiita.com/yukinoi/items/925bc238185aa2fad8a7

file0.txt

from rakutenma import RakutenMA

rma = RakutenMA(phi=1024, c=0.007812)
rma.load("model_ja.json")
rma.hash_func = rma.create_hash_func(15)

print(rma.tokenize("うらにわにはにわにわとりがいる"))
print(rma.train_one(
       [["うらにわ","N-nc"],
        ["に","P-k"],
        ["は","P-rj"],
        ["にわ","N-n"],
        ["にわとり","N-nc"],
        ["が","P-k"],
        ["いる","V-c"]]))

file2.txt

$ time python rakutenma_benchmark.py 

real    0m5.143s
user    0m5.026s
sys 0m0.041s

$ time node rakutenma_benchmark.js

real    0m2.386s
user    0m2.265s
sys 0m0.042s

file3.txt

$ time python rakutenma_benchmark.py 

real    0m3.583s
user    0m3.573s
sys 0m0.009s

$ time node rakutenma_benchmark.js

real    0m1.852s
user    0m1.831s
sys 0m0.027s

file4.txt

$ time pypy3 test.py 

real    0m1.908s
user    0m1.859s
sys 0m0.042s

rakutenma_benchmark.js

var RakutenMA = require('./rakutenma');

var rma = new RakutenMA();
rma.featset = RakutenMA.default_featset_ja;

for (var i = 0; i < 1000; i++) {
    rma.tokenize("もう何も怖くない");
    rma.train_one(
        [["もう","F"],
         ["何","D"],
         ["も","P-rj"],
         ["怖く","A-c"],
         ["ない","X"]]);
}

rakutenma_benchmark.py

# -*- coding: utf-8 -*-
from rakutenma import RakutenMA

rma = RakutenMA()
for i in range(1000):
    rma.tokenize("もう何も怖くない")
    rma.train_one(
        [["もう","F"],
         ["何","D"],
         ["も","P-rj"],
         ["怖く","A-c"],
         ["ない","X"]])