Crawl Result

The CrawlResult class is the heart of Crawl4AI's output, encapsulating all the data extracted from a crawling session. This class contains various fields that store the results of the web crawling and extraction process. Let's break down each field and see what it holds. 🎉

Class Definition

class CrawlResult(BaseModel):
    url: str
    html: str
    success: bool
    cleaned_html: Optional[str] = None
    media: Dict[str, List[Dict]] = {}
    links: Dict[str, List[Dict]] = {}
    screenshot: Optional[str] = None
    markdown: Optional[str] = None
    extracted_content: Optional[str] = None
    metadata: Optional[dict] = None
    error_message: Optional[str] = None

Fields Explanation

url: str

The URL that was crawled. This field simply stores the URL of the web page that was processed.

html: str

The raw HTML content of the web page. This is the unprocessed HTML source as retrieved by the crawler.

success: bool

A flag indicating whether the crawling and extraction were successful. If any error occurs during the process, this will be False.

cleaned_html: Optional[str]

The cleaned HTML content of the web page. This field holds the HTML after removing unwanted tags like <script>, <style>, and others that do not contribute to the useful content.

media: Dict[str, List[Dict]]

A dictionary containing lists of extracted media elements from the web page. The media elements are categorized into images, videos, and audios. Here’s how they are structured:

  • Images: Each image is represented as a dictionary with src (source URL) and alt (alternate text).
  • Videos: Each video is represented similarly with src and alt.
  • Audios: Each audio is represented with src and alt.
media = {
    'images': [
        {'src': 'image_url1', 'alt': 'description1', "type": "image"},
        {'src': 'image_url2', 'alt': 'description2', "type": "image"}
    ],
    'videos': [
        {'src': 'video_url1', 'alt': 'description1', "type": "video"}
    ],
    'audios': [
        {'src': 'audio_url1', 'alt': 'description1', "type": "audio"}
    ]
}

A dictionary containing lists of internal and external links extracted from the web page. Each link is represented as a dictionary with href (URL) and text (link text).

  • Internal Links: Links pointing to the same domain.
  • External Links: Links pointing to different domains.
links = {
    'internal': [
        {'href': 'internal_link1', 'text': 'link_text1'},
        {'href': 'internal_link2', 'text': 'link_text2'}
    ],
    'external': [
        {'href': 'external_link1', 'text': 'link_text1'}
    ]
}

screenshot: Optional[str]

A base64-encoded screenshot of the web page. This field stores the screenshot data if the crawling was configured to take a screenshot.

markdown: Optional[str]

The content of the web page converted to Markdown format. This is useful for generating clean, readable text that retains the structure of the original HTML.

extracted_content: Optional[str]

The content extracted based on the specified extraction strategy. This field holds the meaningful content blocks extracted from the web page, ready for your AI and data processing needs.

metadata: Optional[dict]

A dictionary containing metadata extracted from the web page, such as title, description, keywords, and other meta tags.

error_message: Optional[str]

If an error occurs during crawling, this field will contain the error message, helping you debug and understand what went wrong. 🚨

Example Usage

Here's a quick example to illustrate how you might use the CrawlResult in your code:

from crawl4ai import WebCrawler

# Create the WebCrawler instance
crawler = WebCrawler()

# Run the crawler on a URL
result = crawler.run(url="https://www.example.com")

# Check if the crawl was successful
if result.success:
    print("Crawl succeeded!")
    print("URL:", result.url)
    print("HTML:", result.html[:100])  # Print the first 100 characters of the HTML
    print("Cleaned HTML:", result.cleaned_html[:100])
    print("Media:", result.media)
    print("Links:", result.links)
    print("Screenshot:", result.screenshot)
    print("Markdown:", result.markdown[:100])
    print("Extracted Content:", result.extracted_content)
    print("Metadata:", result.metadata)
else:
    print("Crawl failed with error:", result.error_message)

With this setup, you can easily access all the valuable data extracted from the web page and integrate it into your applications. Happy crawling! 🕷️🤖