PricingLoginStart free
Web Scraping & Bots · 课时

使用 BeautifulSoup 提取数据

使用 BeautifulSoup 解析 HTML 文档，并通过标签、类和 ID 提取特定数据项。

第 3 / 4 课12 个步骤

使用 BeautifulSoup 提取数据 是 CoddyKit 上的免费 Web Scraping & Bots 课时。 这是第 3 节课，共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 Web Scraping & Bots 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Web Scraping & Bots 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

BeautifulSoup: Your HTML Navigator

You've learned to fetch web page content using requests. But that content is just a big string of HTML!

BeautifulSoup is a Python library that helps you parse (understand) that HTML. It turns the raw HTML into a tree-like structure, making it easy to navigate and extract specific data.

Why Use a Parser?

Imagine trying to find a specific sentence in a book without page numbers or chapters. That's like trying to extract data from raw HTML strings!

BeautifulSoup gives structure to the HTML, allowing you to easily locate elements like headings, paragraphs, or links using their tags, classes, or IDs.

Creating a BeautifulSoup Object

First, you need to import the library and create a BeautifulSoup object. You pass your HTML content and specify a parser, usually 'html.parser'.

from bs4 import BeautifulSoup

html_doc = """<html><head><title>My Page</title></head><body><h1>Hello</h1><p>World</p></body></html>"""

soup = BeautifulSoup(html_doc, 'html.parser')

print(soup.prettify())

Finding Elements by Tag

The simplest way to find elements is by their HTML tag name. You can use soup.find() to get the first matching tag or soup.find_all() to get all matching tags.

  • find('tag_name'): Returns a single Tag object or None.
  • find_all('tag_name'): Returns a list of Tag objects.

Code: Finding Tags

Let's find the <title> and all <p> tags in our example HTML.

from bs4 import BeautifulSoup

html_doc = """<html><head><title>My Page</title></head><body><h1>Welcome!</h1><p class='intro'>This is an intro.</p><p>Another paragraph.</p></body></html>"""

soup = BeautifulSoup(html_doc, 'html.parser')

# Find the first title tag
title_tag = soup.find('title')
print(f"Title tag: {title_tag}")

# Find all paragraph tags
paragraph_tags = soup.find_all('p')
print(f"Paragraph tags found: {len(paragraph_tags)}")
for p in paragraph_tags:
    print(f" - {p.get_text()}")

Extracting Text and Attributes

Once you have a Tag object, you can easily get its text content or attribute values.

  • To get text: Use the .get_text() method.
  • To get attributes: Access them like a dictionary, e.g., tag['href'] or tag.get('href').

Code: Getting Text and Attributes

Let's extract the text from the <h1> and an attribute from a link.

from bs4 import BeautifulSoup

html_doc = """<html><body><h1 id='main-h1'>Hello CoddyKit</h1><a href='https://example.com' class='btn'>Visit Example</a></body></html>"""

soup = BeautifulSoup(html_doc, 'html.parser')

h1_tag = soup.find('h1')
print(f"H1 Text: {h1_tag.get_text()}")

link_tag = soup.find('a')
print(f"Link Text: {link_tag.get_text()}")
print(f"Link Href: {link_tag['href']}")
print(f"Link Class: {link_tag['class']}")

Finding Elements by Class

Web pages often use CSS classes to style and identify elements. BeautifulSoup lets you search for elements with a specific class using the class_ argument.

Why class_ and not class? Because class is a reserved keyword in Python!

Code: Finding by Class

Here's how to find paragraphs specifically marked with class="intro".

from bs4 import BeautifulSoup

html_doc = """<html><body><p class='intro'>Welcome message.</p><p>Normal text.</p><p class='intro'>Another intro.</p></body></html>"""

soup = BeautifulSoup(html_doc, 'html.parser')

intro_paragraphs = soup.find_all('p', class_='intro')

for p in intro_paragraphs:
    print(f"Found intro: {p.get_text()}")

Finding Elements by ID

HTML IDs are unique identifiers for elements within a page. You can target a specific element using its ID with the id argument.

Since IDs should be unique per page, find() is often sufficient when searching by ID.

Quick Check: Element Selection

Given the HTML snippet below, how would you extract the text 'Item 2'?

<div id="items">
  <span class="item-name">Item 1</span>
  <span class="item-name">Item 2</span>
  <span class="item-name">Item 3</span>
</div>
在交互式课程中回答

Recap: BeautifulSoup Basics

Great job! You've learned the fundamentals of extracting data using BeautifulSoup:

  • Initializing a BeautifulSoup object from HTML.
  • Finding elements by tag name using find() and find_all().
  • Extracting text content with .get_text() and attributes with tag['attr'].
  • Targeting elements precisely using CSS classes with class_.
  • Locating unique elements with IDs using id.

These methods are your building blocks for parsing web pages efficiently!

免费开始

用 AI 导师学习 Python — 免费

在浏览器中编写并运行真实代码，获得全天候 AI 导师的即时帮助，并在网页或应用中继续学习。

课程
12
课程
48
免费开始学习查看完整课程

常见问题解答

「使用 BeautifulSoup 提取数据」课时是免费的吗？

是的 — 「使用 BeautifulSoup 提取数据」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Web Scraping & Bots 课程的其余内容，请升级到 CoddyKit PRO。 Web Scraping & Bots 课程共包含 4 节课。

「使用 BeautifulSoup 提取数据」这节课中我会学到什么？

使用 BeautifulSoup 解析 HTML 文档，并通过标签、类和 ID 提取特定数据项。 你通过在浏览器中直接运行的动手代码来练习 Web Scraping & Bots，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Web Scraping & Bots 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Web Scraping & Bots 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。 这是第 3 节课，共 4 节。

「使用 BeautifulSoup 提取数据」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Web Scraping & Bots 课中编写并运行代码吗？

能。每节 Web Scraping & Bots 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

此课程中的所有课时

  1. 配置开发环境
  2. 使用 Requests 处理网址
  3. 使用 BeautifulSoup 提取数据
  4. 使用 CSS 选择器遍历 DOM
← 返回 Web Scraping & Bots