this script resmbels a quick intro to googles word2vec wrapper

word2vec_hello_world.py

#!/usr/bin/python
#this script resmbels a quick intro to googles word2vec wrapper found in https://github.com/danielfrg/word2vec
#you can download text8 from :http://mattmahoney.net/dc/text8.zip
#word2vec description :https://code.google.com/archive/p/word2vec/

import time
import word2vec
from math import sqrt

def euclidean_distance(x,y):
    'returns euclidean distance bettwen 2 vectors'
    return sqrt(sum(pow(a-b,2) for a, b in zip(x, y)))

#Save text in bin with vectors
word2vec.word2vec('text8', 'text8.bin', size=100, verbose=True)

#load a model
t2=time.time()
model=word2vec.load('text8.bin')
print 'Model Loaded in {0}S '.format(round(time.time()-t2, 3))

eng_vec=model.get_vector('english')
eng=model.get_word(eng_vec)

print "Similarity of 'irish' and 'english' {0}".format(euclidean_distance(model.get_vector('irish'),model.get_vector('english')))
print "Similarity of 'french' and 'english' {0}".format(euclidean_distance(model.get_vector('french'),model.get_vector('english')))

print "Similarity of 'stanza' and 'english' {0}".format(euclidean_distance(model.get_vector('hello'),model.get_vector('english')))
print "Similarity of 'play' and 'hello' {0}".format(euclidean_distance(model.get_vector('play'),model.get_vector('hello')))