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精密な抽出のためのCSSセレクター

CSSセレクターを適用し、スタイルや属性に基づいて要素を特定してデータを抽出します。

「精密な抽出のためのCSSセレクター」はCoddyKit上の無料Web Scraping & Botsレッスンです。 これはレッスン2/4です。 下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。 これはWeb Scraping & Bots学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 Web Scraping & Botsコースには全4レッスンが含まれています。

このレッスンの一部はまだ翻訳されておらず、英語で表示されています。

What are CSS Selectors?

CSS selectors are patterns used to select elements on a web page. Think of them as precise instructions for finding specific pieces of information.

Web browsers use them to apply styles (CSS), and we'll use them to extract data efficiently.

Selectors for Data Extraction

In web scraping, CSS selectors provide a powerful way to pinpoint exactly the data you need from complex HTML.

  • They are often more concise than XPath.
  • Many developers are already familiar with CSS.
  • BeautifulSoup has excellent support for them.

Selecting by Tag Name

The simplest selector is the tag name. This selects all elements of that type.

For example, p selects all paragraph tags, and a selects all anchor (link) tags.

Example: To find all list items, you'd use li.

from bs4 import BeautifulSoup

html_doc = """
<html><body>
  <h1>My Title</h1>
  <p>First paragraph.</p>
  <ul>
    <li>Item 1</li>
    <li>Item 2</li>
  </ul>
</body></html>
"""
soup = BeautifulSoup(html_doc, 'html.parser')

# Select all 'p' tags
paragraphs = soup.select('p')
for p in paragraphs:
    print(p.get_text())

Class and ID Selectors

You can select elements based on their class or ID attributes. These are very common for styling and unique identification.

  • Class: Use a dot . before the class name (e.g., .product-title).
  • ID: Use a hash # before the ID name (e.g., #main-content). IDs should be unique!
from bs4 import BeautifulSoup

html_doc = """
<div id="header">Welcome</div>
<p class="intro">Hello there!</p>
<p class="intro">Another intro.</p>
"""
soup = BeautifulSoup(html_doc, 'html.parser')

header = soup.select_one('#header')
print("Header:", header.get_text())

intros = soup.select('.intro')
for p in intros:
    print("Intro:", p.get_text())

Selecting Nested Elements

To select elements that are inside other elements, you use a space between selectors. This is called a descendant selector.

It means "find an element (B) that is anywhere inside another element (A)".

Example: div p selects all <p> tags that are inside any <div> tag.

from bs4 import BeautifulSoup

html_doc = """
<div>
  <p>Inside div paragraph 1</p>
  <span>
    <p>Inside span inside div</p>
  </span>
</div>
<p>Outside div paragraph</p>
"""
soup = BeautifulSoup(html_doc, 'html.parser')

div_paragraphs = soup.select('div p')
for p in div_paragraphs:
    print(p.get_text())

Direct Children Only

Sometimes you only want elements that are direct children of another element, not just any descendant.

Use the greater than symbol > for this.

Example: ul > li selects all <li> tags that are direct children of a <ul> tag.

from bs4 import BeautifulSoup

html_doc = """
<div class="container">
  <p>Direct child P</p>
  <div>
    <p>Nested P (not direct)</p>
  </div>
</div>
"""
soup = BeautifulSoup(html_doc, 'html.parser')

direct_p = soup.select('.container > p')
for p in direct_p:
    print(p.get_text())

Selecting by Attributes

You can select elements based on their attributes and even their attribute values!

  • [attr]: Has the attribute (e.g., [href]).
  • [attr="value"]: Has attribute with exact value (e.g., [target="_blank"]).
  • [attr^="value"]: Attribute value starts with (e.g., [src^="data:"]).
  • [attr$="value"]: Attribute value ends with (e.g., [alt$="logo"]).
  • [attr*="value"]: Attribute value contains (e.g., [id*="item"]).
from bs4 import BeautifulSoup

html_doc = """
<a href="/about">About Us</a>
<a href="https://example.com/contact" target="_blank">Contact</a>
<img src="image.jpg" alt="product image">
"""
soup = BeautifulSoup(html_doc, 'html.parser')

# Select links with target="_blank"
external_links = soup.select('a[target="_blank"]')
for link in external_links:
    print("External:", link.get('href'))

# Select images with alt containing "image"
product_images = soup.select('img[alt*="image"]')
for img in product_images:
    print("Image:", img.get('src'))

Combining with Commas

To select elements that match any of several different selectors, you can separate them with a comma ,.

This is useful when you want to gather data from different types of elements or locations.

Example: h1, h2, h3 selects all heading tags of level 1, 2, or 3.

from bs4 import BeautifulSoup

html_doc = """
<h1>Main Heading</h1>
<p>Some text.</p>
<h2>Sub Heading</h2>
<div>Another div.</div>
"""
soup = BeautifulSoup(html_doc, 'html.parser')

headings = soup.select('h1, h2')
for h in headings:
    print(h.get_text())

Pseudo-classes for Position

CSS pseudo-classes allow selection based on state or position, not just attributes. For scraping, position-based ones are very useful.

  • :first-child: Selects the first child element.
  • :last-child: Selects the last child element.
  • :nth-of-type(n): Selects the Nth element of a specific type (e.g., li:nth-of-type(2) for the second list item).
from bs4 import BeautifulSoup

html_doc = """
<ul>
  <li>First item</li>
  <li>Second item</li>
  <li>Third item</li>
</ul>
"""
soup = BeautifulSoup(html_doc, 'html.parser')

first_item = soup.select_one('li:first-child')
print("First:", first_item.get_text())

second_item = soup.select_one('li:nth-of-type(2)')
print("Second:", second_item.get_text())

Practical CSS Selector Use

Let's combine what we've learned to extract specific data from a sample product listing.

We want the title and price of the first product.

from bs4 import BeautifulSoup

html_doc = """
<div class="product-list">
  <div class="product-card">
    <h3 class="product-title">Laptop X1</h3>
    <p class="product-price">$999.99</p>
    <button class="add-to-cart">Add</button>
  </div>
  <div class="product-card">
    <h3 class="product-title">Mouse Z2</h3>
    <p class="product-price">$29.99</p>
    <button class="add-to-cart">Add</button>
  </div>
</div>
"""
soup = BeautifulSoup(html_doc, 'html.parser')

# Select the first product card
first_product = soup.select_one('.product-card:first-of-type')

if first_product:
    title = first_product.select_one('.product-title')
    price = first_product.select_one('.product-price')
    print("Title:", title.get_text())
    print("Price:", price.get_text())
else:
    print("No product found.")

Quick Check on Selectors

Given the HTML below, what CSS selector would correctly select the text "Product Name 2"?

<div class="items">
  <div id="item-1">
    <span class="name">Product Name 1</span>
  </div>
  <div id="item-2">
    <span class="name">Product Name 2</span>
  </div>
  <p class="name">Other Name</p>
</div>

Recap: CSS Selectors

Great job! You've mastered the basics of CSS selectors for web scraping.

  • We learned to select by tag, class, and ID.
  • We explored descendant (space) and direct child (>) selectors.
  • You can filter by attributes ([attr="value"]) and use pseudo-classes like :first-child.
  • BeautifulSoup's .select() and .select_one() methods make using them easy in Python.

Next, we'll look into XPath for even more powerful selections!

よくある質問

「精密な抽出のためのCSSセレクター」レッスンは無料ですか?

はい。「精密な抽出のためのCSSセレクター」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し(組み込みコードエディタと24時間対応のAIチューター)、Web Scraping & Botsコースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 Web Scraping & Botsコースには全4レッスンが含まれています。

「精密な抽出のためのCSSセレクター」で何を学びますか?

CSSセレクターを適用し、スタイルや属性に基づいて要素を特定してデータを抽出します。 ブラウザで直接実行するハンズオンコードでWeb Scraping & Botsを演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。

Web Scraping & Botsを始めるのに経験は必要ですか?

事前経験は必要ありません。CoddyKitのWeb Scraping & Botsは初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。 これはレッスン2/4です。

「精密な抽出のためのCSSセレクター」レッスンにはどのくらい時間がかかりますか?

ほとんどのCoddyKitレッスンは約5~10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。

このWeb Scraping & Botsレッスンでコードを書いて実行できますか?

はい。すべてのWeb Scraping & Botsレッスンに組み込みコードエディタが含まれているため、ブラウザでリアルコードを書いて実行し、即座のAIフィードバックを取得できます。ローカル設定は不要です。

このコースのすべてのレッスン

  1. 複雑なHTML構造のナビゲーション
  2. 精密な抽出のためのCSSセレクター
  3. 堅牢な選択のためのXPath
  4. HTML テーブルからデータを抽出する
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