r = requests.get('https://www.yelp.com/biz/social-brew-cafe-pyrmont') soup = BeautifulSoup(r.text, 'html.parser') regex = re.compile('.*comment.*') results = soup.find_all('p', {'class':regex}) reviews = [result.text for result in results] import numpy as np import pandas as pd df = pd.DataFrame(np.array(reviews), columns=['review']) df['review'].iloc[0] def sentiment_score(review): tokens = tokenizer.encode(review, return_tensors='pt') result = model(tokens) return int(torch.argmax(result.logits))+1 sentiment_score(df['review'].iloc[1]) df['sentiment'] = df['review'].apply(lambda x: sentiment_score(x[:512])) print(df) print(df['review'].iloc[3]) 解释
时间: 2024-04-15 21:24:48 浏览: 33
这段代码是爬取一个网页上的评论,并对评论进行情感分析。首先,使用requests库获取网页的内容。然后,使用BeautifulSoup库解析网页内容。接着,使用正则表达式找到所有包含评论的`<p>`标签。然后,将这些评论存储在一个DataFrame中,并取出第一个评论进行情感分析。情感分析的函数`sentiment_score`使用了一个预训练的模型,并将评论转换为tokens后输入模型,得到情感分析的结果。最后,将情感分析结果存储在DataFrame中,并打印出整个DataFrame和第四条评论。
相关问题
以下代码爬取的内容是乱码,什么原因?from bs4 import BeautifulSoup import requests if name == 'main': url = 'https://www.pincai.com/article/2320333.htm' response = requests.get(url).text soup = BeautifulSoup(response, 'lxml')。帮我修改好代码
以下是修改后的代码:
```python
from bs4 import BeautifulSoup
import requests
if __name__ == '__main__':
url = 'https://www.pincai.com/article/2320333.htm'
response = requests.get(url)
response.encoding = 'utf-8'
soup = BeautifulSoup(response.text, 'lxml')
# 在这里可以继续处理网页内容
```
对于乱码问题,我在代码中添加了 `response.encoding = 'utf-8'` 来指定网页的编码为UTF-8,以确保正确解析网页内容。另外,我将 `response.text` 传递给 `BeautifulSoup` 来处理,以获取正确的解析结果。
现在你可以继续处理 `soup` 对象中的网页内容了。如果还有其他问题,请随时提问。
优化这段代码import requests from bs4 import BeautifulSoup url = "https://www.gupang.com/202305/64619.html" response = requests.get(url) soup = BeautifulSoup(response.content, "html.parser") title = soup.find("h1", class_="title").text content = soup.find("div", class_="content").text print(title) print(content)
可以使用以下方法进行优化:
1. 添加异常处理,以防止请求失败或解析失败导致程序崩溃:
```python
import requests
from bs4 import BeautifulSoup
url = "https://www.gupang.com/202305/64619.html"
try:
response = requests.get(url)
response.raise_for_status() # 抛出异常,如果请求失败
except requests.exceptions.RequestException as e:
print(e)
sys.exit(1)
soup = BeautifulSoup(response.content, "html.parser")
try:
title = soup.find("h1", class_="title").text
content = soup.find("div", class_="content").text
except AttributeError as e:
print(e)
sys.exit(1)
print(title)
print(content)
```
2. 使用`with`语句来管理资源,以确保在使用完文件或网络连接后自动释放资源:
```python
import requests
from bs4 import BeautifulSoup
url = "https://www.gupang.com/202305/64619.html"
try:
with requests.get(url) as response:
response.raise_for_status()
soup = BeautifulSoup(response.content, "html.parser")
title = soup.find("h1", class_="title").text
content = soup.find("div", class_="content").text
except (requests.exceptions.RequestException, AttributeError) as e:
print(e)
sys.exit(1)
print(title)
print(content)
```
这种方法可以避免手动关闭连接或文件,而且代码更加简洁。
相关推荐
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![pdf](https://img-home.csdnimg.cn/images/20210720083512.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)