Python 如何确保BeautifulSoup不将逗号视为制表符

我已经创建了一个抓取代码，从本地报纸网站获取信息。当前代码存在两个问题

当它检索段落数据并将其保存到CSV时。它将“，”识别为中断，并将相关数据保存在相邻单元格中。我该如何阻止这种情况发生

我希望他们将刮取的信息排成一行。i、 e段落、标题、网络链接

代码如下

from bs4 import BeautifulSoup as soup
from urllib.request import urlopen as uReq

page_url = "https://neweralive.na/today/"

ne_url = "https://neweralive.na/posts/"

uClient = uReq(page_url)

page_soup = soup(uClient.read(), "html.parser")
uClient.close()


containers = page_soup.findAll("article", {"class": "post-item"})

filename = "newera.csv"
headers = "paragraph,title,link\n"

f = open(filename, "w")
f.write(headers)

for container in containers:
    paragraph_container = container.findAll("p", {"class": "post-excerpt"})
    paragraph = paragraph_container[0].text

    title_container = container.findAll("h3", {"class": "post-title"})
    title = title_container[0].text
    weblink = ne_url + title_container[0].a["href"]

    f.write(paragraph + "," + title + "," + weblink + "\n")

f.close()

可以使用编写格式良好的CSV，并在需要的字符串（例如，包含逗号的字符串）周围加引号

在此期间，我重构了您的代码以使用可重用函数：

• get\u soup\u from\u url（）

  下载一个url并从中获得一个漂亮的组合

• parse\u today\u page（）

  是一个生成器函数，它可以遍历这道汤并返回每篇文章的目录
• 主代码现在只在打开的文件上使用

  csv.DictWriter

  ；解析的dict打印到控制台以便于调试，并馈送到CSV编写器以进行输出

生成的CSV最终看起来像

paragraph,title,link
"The mayor of Helao Nafidi, Elias Nghipangelwa, has expressed disappointment after Covid-19 relief food was stolen and sold by two security officers entrusted to guard the warehouse where the food was stored.","Guards arrested for theft of relief food",https://neweralive.na/posts/posts/guards-arrested-for-theft-of-relief-food
"Government has decided to construct 1 200 affordable homes, starting Thursday this week.","Govt to construct  1 200 low-cost houses",https://neweralive.na/posts/posts/govt-to-construct-1-200-low-cost-houses
...

---

您可以使用pandas模块轻松地将dataframe表转换为csv

import pandas as pd
from bs4 import BeautifulSoup as soup
from urllib.request import urlopen as uReq

page_url = "https://neweralive.na/today/"

ne_url = "https://neweralive.na/posts/"

uClient = uReq(page_url)

page_soup = soup(uClient.read(), "html.parser")

uClient.close()

containers = page_soup.findAll("article", {"class": "post-item"})

filename = "newera.csv"

rows = []  # Initialize list of list which is converted to dataframe.

for container in containers:

    paragraph_container = container.findAll("p", {"class": "post-excerpt"})
    paragraph = paragraph_container[0].text

    title_container = container.findAll("h3", {"class": "post-title"})
    title = title_container[0].text
    weblink = ne_url + title_container[0].a["href"]
    
    rows.append([paragraph, title, weblink])  # each row is appended 

df = pd.DataFrame(rows, columns = ["paragraph","title","link"])  # col-name is headers 

df.to_csv(filename, index=None)

---

这个世界上有英雄。非常感谢。大家好-哇，这太棒了，我喜欢这个解决方案-这是一个python中的cristal clear csv示例。非常感谢！这是一项绝对不需要熊猫的任务。我同意。亲爱的Shimo-非常感谢你展示了我们与熊猫的选择和可能性-我喜欢它-拥有我们所拥有的各种方式和路径的想法。这使得Python如此强大！所以，谢谢你用你的想法把盘子钉起来

import pandas as pd
from bs4 import BeautifulSoup as soup
from urllib.request import urlopen as uReq

page_url = "https://neweralive.na/today/"

ne_url = "https://neweralive.na/posts/"

uClient = uReq(page_url)

page_soup = soup(uClient.read(), "html.parser")

uClient.close()

containers = page_soup.findAll("article", {"class": "post-item"})

filename = "newera.csv"

rows = []  # Initialize list of list which is converted to dataframe.

for container in containers:

    paragraph_container = container.findAll("p", {"class": "post-excerpt"})
    paragraph = paragraph_container[0].text

    title_container = container.findAll("h3", {"class": "post-title"})
    title = title_container[0].text
    weblink = ne_url + title_container[0].a["href"]
    
    rows.append([paragraph, title, weblink])  # each row is appended 

df = pd.DataFrame(rows, columns = ["paragraph","title","link"])  # col-name is headers 

df.to_csv(filename, index=None)