Question

import glob
import os
import nltk.data
from nltk.sentiment.vader import SentimentIntensityAnalyzer
from nltk import sentiment
from nltk import word_tokenize

sid = SentimentIntensityAnalyzer()


tokenizer = nltk.data.load('tokenizers/punkt/english.pickle')


files = glob.glob(os.path.join(os.getcwd(), 'speeches', '*.txt'))


text = []

for file in files:
    #open the file and then call .read() to get the text

with open(file) as f:
        text.append(f.read())

sentences = tokenizer.tokenize(text)

并打印每个的极性分数。

for sentence in sentences:
        print(sentence,  file=open('sentiment1.txt', 'a'))
        scores = sid.polarity_scores(sentence)
        for key in sorted(scores):
                print('{0}: {1}, '.format(key, scores[key]), end='', file=open('sentiment1.txt', 'a'))
        print()

我在'speeches'文件夹中有五个文本文件已成功读取，但问题是输出文件（文本）是列表类型而不是字符串，而tokenize需要一个字符串或字节作为其参数。请帮我调整一下，因为我读过这可能是Python 3的一个问题。谢谢

Answer 1

# below is the sentiment analysis code written for sentence-level analysis
import glob
import os
import nltk.data
from nltk.sentiment.vader import SentimentIntensityAnalyzer
from nltk import sentiment
from nltk import word_tokenize
# Next, VADER is initialized so I can use it within the Python script
sid = SentimentIntensityAnalyzer()
# I will also initialize the 'english.pickle' function and give it a short 
# name
tokenizer = nltk.data.load('tokenizers/punkt/english.pickle')
#Each of the text file is listed from the folder speeches
files = glob.glob(os.path.join(os.getcwd(), 'speeches', '*.txt'))

text = []

#iterate over the list getting each file
for file in files:
#open the file and then call .read() to get the text
with open(file) as f:
    text=f.read()
sentences = tokenizer.tokenize(text)
for sentence in sentences:
    print(sentence,  file=open('sentiment1.txt', 'a'))
    scores = sid.polarity_scores(sentence)
    for key in sorted(scores):
            print('{0}: {1}, '.format(key, scores[key]), end='',  
                               file=open('sentiment1.txt', 'a'))

    print()

我已经测试了没有空列表的代码，因此不需要追加，但该方法只选择文件夹中的最后一个文本文件。我正在再次编写代码段，以便您可以清楚地看到我拥有的内容。感谢

Answer 2

如果将text初始化为空列表，并将五个输入文件的内容追加到text，则可以使用join()函数将这些文件粉碎成一个字符串供tokenizer.tokenize()使用：

text = []

for file in files:
    #open the file and then call .read() to get the text
    with open(file) as f:
        text.append(f.read())

text_str = "".join(text)   # or "\n".join(text)
sentences = tokenizer.tokenize(text_str)

或者，您可以将text初始化为空字符串，并依次连接每个文件的内容：

text = ""

for file in files:
    #open the file and then call .read() to get the text
    with open(file) as f:
        text += f.read()

sentences = tokenizer.tokenize(text)

我在标记从目录中读取的文件列表时遇到问题。以下是我的代码

2 个答案: