如何读取文件并避免在 python 中强制出现 unicode 错误？

Question

我正在读取两个文件 (trainfile, testfile)，然后我想用 word_vectorizer 对它们进行 vecrize，问题是我可能没有以正确的方式读取文件，这就是我尝试过的：

# -- coding: utf-8 --
import codecs

from sklearn.feature_extraction.text import CountVectorizer
from sklearn.naive_bayes import MultinomialNB
import os, sys


with open('/Users/user/Desktop/train.txt', 'r') as trainfile:
    contenido_del_trainfile= trainfile.read()
    print contenido_del_trainfile

with open('/Users/user/Desktop/test.txt', 'r') as testfile:
    contenido_del_testfile= testfile.read()
    print contenido_del_testfile


print "\nThis is the training corpus:\n", contenido_del_trainfile
print "\nThis is the test corpus:\n", contenido_del_testfile



train = []

word_vectorizer = CountVectorizer(analyzer='word')

trainset = word_vectorizer.fit_transform(codecs.open(trainfile,'r','utf8'))
print word_vectorizer.get_feature_names()

这是输出：

TypeError: coercing to Unicode: need string or buffer, file found

如何以正确的方式读取文件以打印如下内容：

[u'word',... ,u'word']

Answer 1

codecs.open 断言，您提供的是文件路径，而不是文件本身。

所以，而不是

trainset = word_vectorizer.fit_transform(codecs.open(trainfile,'r','utf8'))

做

trainset = word_vectorizer.fit_transform(codecs.open('/Users/user/Desktop/train.txt','r','utf8'))