详细使用说明：http://textgrocery.readthedocs.io/zh/latest/index.html
TextGrocery是一个基于LibLinear和结巴分词的短文本分类工具，特点是高效易用，同时支持中文和英文语料。
需要安装：
pip install classifier
过程：
>>> from tgrocery import Grocery
# 新开张一个杂货铺（别忘了取名）
>>> grocery = Grocery('sample')
# 训练文本可以用列表传入
>>> train_src = [
('education', '名师指导托福语法技巧：名词的复数形式'),
... ('education', '中国高考成绩海外认可 是“狼来了”吗？'),
... ('sports', '图文：法网孟菲尔斯苦战进16强 孟菲尔斯怒吼'),
... ('sports', '四川丹棱举行全国长距登山挑战赛 近万人参与')
... ]
>>> grocery.train(train_src)
Building prefix dict from the default dictionary ...
Dumping model to file cache /tmp/jieba.cache
Loading model cost 1.125 seconds.
Prefix dict has been built succesfully.
*
optimization finished, #iter =
Objective value = -1.092381
nSV =
<tgrocery.Grocery object at 0x7f23cf243b50>
>>> grocery.save()
>>> new_grocery = Grocery('sample')
>>> new_grocery.load()
>>> new_grocery.predict('考生必读：新托福写作考试评分标准')
<tgrocery.base.GroceryPredictResult object at 0x4490d50>
>>> new_grocery.predict('考生必读：新托福写作考试评分标准')
<tgrocery.base.GroceryPredictResult object at 0x4490d90>
>>> result = new_grocery.predict('考生必读：新托福写作考试评分标准')
>>> print result
education
完毕。