cwordninja 2.0.4

Probabilistically split concatenated words using NLP based on English Wikipedia uni-gram frequencies.

C Word Ninja

Slice your munged together words! Seriously, Take anything, 'imateapot' for example, would become ['im', 'a', 'teapot']. Useful for humanizing stuff (like database tables when people don't like underscores).

This project is repackaging the excellent work from here: http://stackoverflow.com/a/11642687/2449774

cwordninja is rewritten using cython based on wordninja.

Usage

$ python
>>> import cwordninja
>>> cwordninja.split('derekanderson')
['derek', 'anderson']
>>> cwordninja.split('imateapot')
['im', 'a', 'teapot']
>>> cwordninja.split('heshotwhointhewhatnow')
['he', 'shot', 'who', 'in', 'the', 'what', 'now']
>>> cwordninja.split('thequickbrownfoxjumpsoverthelazydog')
['the', 'quick', 'brown', 'fox', 'jumps', 'over', 'the', 'lazy', 'dog']

Performance

It's super fast!

Code:

import cwordninja
import wordninja
import timeit

def a():
    cwordninja.split("derek anderson")

c_time = int(timeit.timeit(a, number=10000) * 1000)
print("cwordninja:", c_time, "ms")

def b():
    wordninja.split("derek anderson")

r_time = int(timeit.timeit(b, number=10000) * 1000)
print("wordninja:", r_time, "ms")

print(int(r_time / c_time), "x")

Result:

cwordninja: 2 ms
wordninja: 1507 ms
753 x

It can handle long strings:

>>> cwordninja.lsplit('wethepeopleoftheunitedstatesinordertoformamoreperfectunionestablishjusticeinsuredomestictranquilityprovideforthecommondefencepromotethegeneralwelfareandsecuretheblessingsoflibertytoourselvesandourposteritydoordainandestablishthisconstitutionfortheunitedstatesofamerica')
['we', 'the', 'people', 'of', 'the', 'united', 'states', 'in', 'order', 'to', 'form', 'a', 'more', 'perfect', 'union', 'establish', 'justice', 'in', 'sure', 'domestic', 'tranquility', 'provide', 'for', 'the', 'common', 'defence', 'promote', 'the', 'general', 'welfare', 'and', 'secure', 'the', 'blessings', 'of', 'liberty', 'to', 'ourselves', 'and', 'our', 'posterity', 'do', 'ordain', 'and', 'establish', 'this', 'constitution', 'for', 'the', 'united', 'states', 'of', 'america']

And scales well. (This string takes ~0.1ms to compute.)

How to Install

pip3 install cwordninja

Custom Language Models

#1 most requested feature! If you want to do something other than english (or want to specify your own model of english), this is how you do it.

>>> lm = cwordninja.LanguageModel('my_lang.txt.gz')
>>> lm.split('derek')
['der','ek']

Language files must be gziped text files with one word per line in decreasing order of probability.

If you want to make your model the default, set:

cwordninja.DEFAULT_LANGUAGE_MODEL = wordninja.LanguageModel('my_lang.txt.gz')