c2c4d42be4
The remove_empty_elements_fast() method was removing whitespace-only span elements inside <pre> and <code> tags, causing import statements like "import torch" to become "importtorch". Now skips elements inside code blocks where whitespace is significant.
914 lines
35 KiB
Python
914 lines
35 KiB
Python
import re
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from itertools import chain
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from abc import ABC, abstractmethod
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from typing import Dict, Any, Optional
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from bs4 import BeautifulSoup
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import asyncio
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import requests
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from .config import (
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MIN_WORD_THRESHOLD,
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IMAGE_DESCRIPTION_MIN_WORD_THRESHOLD,
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IMAGE_SCORE_THRESHOLD,
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ONLY_TEXT_ELIGIBLE_TAGS,
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IMPORTANT_ATTRS,
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SOCIAL_MEDIA_DOMAINS,
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)
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from bs4 import NavigableString, Comment
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from bs4 import PageElement, Tag
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from urllib.parse import urljoin
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from requests.exceptions import InvalidSchema
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from .utils import (
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extract_metadata,
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normalize_url,
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is_external_url,
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get_base_domain,
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extract_metadata_using_lxml,
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extract_page_context,
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calculate_link_intrinsic_score,
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)
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from lxml import etree
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from lxml import html as lhtml
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from typing import List
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from .models import ScrapingResult, MediaItem, Link, Media, Links
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import copy
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# Pre-compile regular expressions for Open Graph and Twitter metadata
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OG_REGEX = re.compile(r"^og:")
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TWITTER_REGEX = re.compile(r"^twitter:")
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DIMENSION_REGEX = re.compile(r"(\d+)(\D*)")
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# Function to parse srcset
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def parse_srcset(s: str) -> List[Dict]:
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if not s:
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return []
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variants = []
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for part in s.split(","):
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part = part.strip()
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if not part:
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continue
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parts = part.split()
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if len(parts) >= 1:
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url = parts[0]
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width = (
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parts[1].rstrip("w").split('.')[0]
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if len(parts) > 1 and parts[1].endswith("w")
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else None
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)
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variants.append({"url": url, "width": width})
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return variants
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# Function to parse image height/width value and units
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def parse_dimension(dimension):
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if dimension:
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# match = re.match(r"(\d+)(\D*)", dimension)
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match = DIMENSION_REGEX.match(dimension)
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if match:
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number = int(match.group(1))
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unit = match.group(2) or "px" # Default unit is 'px' if not specified
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return number, unit
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return None, None
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# Fetch image file metadata to extract size and extension
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def fetch_image_file_size(img, base_url):
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# If src is relative path construct full URL, if not it may be CDN URL
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img_url = urljoin(base_url, img.get("src"))
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try:
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response = requests.head(img_url)
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if response.status_code == 200:
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return response.headers.get("Content-Length", None)
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else:
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print(f"Failed to retrieve file size for {img_url}")
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return None
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except InvalidSchema:
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return None
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finally:
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return
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class ContentScrapingStrategy(ABC):
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@abstractmethod
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def scrap(self, url: str, html: str, **kwargs) -> ScrapingResult:
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pass
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@abstractmethod
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async def ascrap(self, url: str, html: str, **kwargs) -> ScrapingResult:
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pass
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class LXMLWebScrapingStrategy(ContentScrapingStrategy):
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"""
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LXML-based implementation for fast web content scraping.
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This is the primary scraping strategy in Crawl4AI, providing high-performance
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HTML parsing and content extraction using the lxml library.
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Note: WebScrapingStrategy is now an alias for this class to maintain
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backward compatibility.
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"""
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def __init__(self, logger=None):
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self.logger = logger
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self.DIMENSION_REGEX = re.compile(r"(\d+)(\D*)")
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self.BASE64_PATTERN = re.compile(r'data:image/[^;]+;base64,([^"]+)')
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def _log(self, level, message, tag="SCRAPE", **kwargs):
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"""Helper method to safely use logger."""
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if self.logger:
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log_method = getattr(self.logger, level)
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log_method(message=message, tag=tag, **kwargs)
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def scrap(self, url: str, html: str, **kwargs) -> ScrapingResult:
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"""
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Main entry point for content scraping.
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Args:
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url (str): The URL of the page to scrape.
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html (str): The HTML content of the page.
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**kwargs: Additional keyword arguments.
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Returns:
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ScrapingResult: A structured result containing the scraped content.
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"""
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actual_url = kwargs.get("redirected_url", url)
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raw_result = self._scrap(actual_url, html, **kwargs)
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if raw_result is None:
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return ScrapingResult(
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cleaned_html="",
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success=False,
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media=Media(),
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links=Links(),
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metadata={},
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)
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# Convert media items
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media = Media(
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images=[
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MediaItem(**img)
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for img in raw_result.get("media", {}).get("images", [])
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if img
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],
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videos=[
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MediaItem(**vid)
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for vid in raw_result.get("media", {}).get("videos", [])
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if vid
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],
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audios=[
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MediaItem(**aud)
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for aud in raw_result.get("media", {}).get("audios", [])
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if aud
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],
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tables=raw_result.get("media", {}).get("tables", [])
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)
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# Convert links
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links = Links(
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internal=[
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Link(**link)
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for link in raw_result.get("links", {}).get("internal", [])
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if link
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],
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external=[
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Link(**link)
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for link in raw_result.get("links", {}).get("external", [])
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if link
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],
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)
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return ScrapingResult(
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cleaned_html=raw_result.get("cleaned_html", ""),
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success=raw_result.get("success", False),
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media=media,
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links=links,
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metadata=raw_result.get("metadata", {}),
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)
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async def ascrap(self, url: str, html: str, **kwargs) -> ScrapingResult:
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"""
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Main entry point for asynchronous content scraping.
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Args:
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url (str): The URL of the page to scrape.
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html (str): The HTML content of the page.
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**kwargs: Additional keyword arguments.
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Returns:
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ScrapingResult: A structured result containing the scraped content.
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"""
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return await asyncio.to_thread(self.scrap, url, html, **kwargs)
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def process_element(self, url, element: lhtml.HtmlElement, **kwargs) -> Dict[str, Any]:
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"""
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Process an HTML element.
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How it works:
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1. Check if the element is an image, video, or audio.
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2. Extract the element's attributes and content.
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3. Process the element based on its type.
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4. Return the processed element information.
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Args:
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url (str): The URL of the page containing the element.
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element (lhtml.HtmlElement): The HTML element to process.
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**kwargs: Additional keyword arguments.
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Returns:
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dict: A dictionary containing the processed element information.
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"""
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media = {"images": [], "videos": [], "audios": [], "tables": []}
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internal_links_dict = {}
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external_links_dict = {}
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self._process_element(
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url, element, media, internal_links_dict, external_links_dict, **kwargs
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)
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return {
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"media": media,
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"internal_links_dict": internal_links_dict,
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"external_links_dict": external_links_dict,
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}
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def _process_element(
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self,
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url: str,
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element: lhtml.HtmlElement,
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media: Dict[str, List],
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internal_links_dict: Dict[str, Any],
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external_links_dict: Dict[str, Any],
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page_context: dict = None,
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**kwargs,
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) -> bool:
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base_domain = kwargs.get("base_domain", get_base_domain(url))
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exclude_domains = set(kwargs.get("exclude_domains", []))
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# Process links
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try:
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base_element = element.xpath("//head/base[@href]")
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if base_element:
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base_href = base_element[0].get("href", "").strip()
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if base_href:
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url = base_href
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except Exception as e:
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self._log("error", f"Error extracting base URL: {str(e)}", "SCRAPE")
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pass
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for link in element.xpath(".//a[@href]"):
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href = link.get("href", "").strip()
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if not href:
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continue
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try:
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normalized_href = normalize_url(
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href, url,
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preserve_https=kwargs.get('preserve_https_for_internal_links', False),
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original_scheme=kwargs.get('original_scheme')
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)
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link_data = {
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"href": normalized_href,
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"text": link.text_content().strip(),
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"title": link.get("title", "").strip(),
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"base_domain": base_domain,
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}
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# Add intrinsic scoring if enabled
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if kwargs.get("score_links", False) and page_context is not None:
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try:
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intrinsic_score = calculate_link_intrinsic_score(
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link_text=link_data["text"],
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url=normalized_href,
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title_attr=link_data["title"],
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class_attr=link.get("class", ""),
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rel_attr=link.get("rel", ""),
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page_context=page_context
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)
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link_data["intrinsic_score"] = intrinsic_score
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except Exception:
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# Fail gracefully - assign default score
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link_data["intrinsic_score"] = 0
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else:
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# No scoring enabled - assign infinity (all links equal priority)
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link_data["intrinsic_score"] = 0
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is_external = is_external_url(normalized_href, base_domain)
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if is_external:
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link_base_domain = get_base_domain(normalized_href)
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link_data["base_domain"] = link_base_domain
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if (
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kwargs.get("exclude_external_links", False)
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or link_base_domain in exclude_domains
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):
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link.getparent().remove(link)
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continue
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if normalized_href not in external_links_dict:
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external_links_dict[normalized_href] = link_data
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else:
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if normalized_href not in internal_links_dict:
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internal_links_dict[normalized_href] = link_data
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except Exception as e:
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self._log("error", f"Error processing link: {str(e)}", "SCRAPE")
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continue
|
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# Process images
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images = element.xpath(".//img")
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total_images = len(images)
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for idx, img in enumerate(images):
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src = img.get("src") or ""
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img_domain = get_base_domain(src)
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# Decide if we need to exclude this image
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# 1) If its domain is in exclude_domains, remove.
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# 2) Or if exclude_external_images=True and it's an external domain, remove.
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if (img_domain in exclude_domains) or (
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kwargs.get("exclude_external_images", False)
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and is_external_url(src, base_domain)
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):
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parent = img.getparent()
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if parent is not None:
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parent.remove(img)
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continue
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# Otherwise, process the image as usual.
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try:
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processed_images = self.process_image(
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img, url, idx, total_images, **kwargs
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)
|
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if processed_images:
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media["images"].extend(processed_images)
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except Exception as e:
|
|
self._log("error", f"Error processing image: {str(e)}", "SCRAPE")
|
|
|
|
# Process videos and audios
|
|
for media_type in ["video", "audio"]:
|
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for elem in element.xpath(f".//{media_type}"):
|
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media_info = {
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"src": elem.get("src"),
|
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"alt": elem.get("alt"),
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"type": media_type,
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"description": self.find_closest_parent_with_useful_text(
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elem, **kwargs
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),
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}
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media[f"{media_type}s"].append(media_info)
|
|
|
|
# Process source tags within media elements
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for source in elem.xpath(".//source"):
|
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if src := source.get("src"):
|
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media[f"{media_type}s"].append({**media_info, "src": src})
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|
|
|
# Clean up unwanted elements
|
|
if kwargs.get("remove_forms", False):
|
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for form in element.xpath(".//form"):
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form.getparent().remove(form)
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|
|
|
if excluded_tags := kwargs.get("excluded_tags", []):
|
|
for tag in excluded_tags:
|
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for elem in element.xpath(f".//{tag}"):
|
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elem.getparent().remove(elem)
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|
|
|
if excluded_selector := kwargs.get("excluded_selector", ""):
|
|
try:
|
|
for elem in element.cssselect(excluded_selector):
|
|
elem.getparent().remove(elem)
|
|
except Exception:
|
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pass # Invalid selector
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|
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|
return True
|
|
|
|
def find_closest_parent_with_useful_text(
|
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self, element: lhtml.HtmlElement, **kwargs
|
|
) -> Optional[str]:
|
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image_description_min_word_threshold = kwargs.get(
|
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"image_description_min_word_threshold", IMAGE_DESCRIPTION_MIN_WORD_THRESHOLD
|
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)
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|
current = element
|
|
while current is not None:
|
|
if (
|
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current.text
|
|
and len(current.text_content().split())
|
|
>= image_description_min_word_threshold
|
|
):
|
|
return current.text_content().strip()
|
|
current = current.getparent()
|
|
return None
|
|
|
|
def flatten_nested_elements(self, element: lhtml.HtmlElement) -> lhtml.HtmlElement:
|
|
"""Flatten nested elements of the same type in LXML tree"""
|
|
if len(element) == 1 and element.tag == element[0].tag:
|
|
return self.flatten_nested_elements(element[0])
|
|
|
|
for child in element:
|
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child_idx = element.index(child)
|
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flattened_child = self.flatten_nested_elements(child)
|
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if flattened_child is not child: # Only replace if actually flattened
|
|
element[child_idx] = flattened_child
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|
|
|
return element
|
|
|
|
def process_image(
|
|
self, img: lhtml.HtmlElement, url: str, index: int, total_images: int, **kwargs
|
|
) -> Optional[List[Dict]]:
|
|
# Quick validation checks
|
|
style = img.get("style", "")
|
|
alt = img.get("alt", "")
|
|
src = img.get("src", "")
|
|
data_src = img.get("data-src", "")
|
|
srcset = img.get("srcset", "")
|
|
data_srcset = img.get("data-srcset", "")
|
|
|
|
if "display:none" in style:
|
|
return None
|
|
|
|
parent = img.getparent()
|
|
if parent.tag in ["button", "input"]:
|
|
return None
|
|
|
|
parent_classes = parent.get("class", "").split()
|
|
if any(
|
|
"button" in cls or "icon" in cls or "logo" in cls for cls in parent_classes
|
|
):
|
|
return None
|
|
|
|
# If src is in class or alt, likely an icon
|
|
if (src and any(c in src for c in ["button", "icon", "logo"])) or (
|
|
alt and any(c in alt for c in ["button", "icon", "logo"])
|
|
):
|
|
return None
|
|
|
|
# Score calculation
|
|
score = 0
|
|
if (width := img.get("width")) and width.isdigit():
|
|
score += 1 if int(width) > 150 else 0
|
|
if (height := img.get("height")) and height.isdigit():
|
|
score += 1 if int(height) > 150 else 0
|
|
if alt:
|
|
score += 1
|
|
score += index / total_images < 0.5
|
|
|
|
# Check formats in all possible sources
|
|
image_formats = {"jpg", "jpeg", "png", "webp", "avif", "gif"}
|
|
detected_format = None
|
|
for url in [src, data_src, srcset, data_srcset]:
|
|
if url:
|
|
format_matches = [fmt for fmt in image_formats if fmt in url.lower()]
|
|
if format_matches:
|
|
detected_format = format_matches[0]
|
|
score += 1
|
|
break
|
|
|
|
if srcset or data_srcset:
|
|
score += 1
|
|
|
|
if picture := img.xpath("./ancestor::picture[1]"):
|
|
score += 1
|
|
|
|
if score <= kwargs.get("image_score_threshold", IMAGE_SCORE_THRESHOLD):
|
|
return None
|
|
|
|
# Process image variants
|
|
unique_urls = set()
|
|
image_variants = []
|
|
base_info = {
|
|
"alt": alt,
|
|
"desc": self.find_closest_parent_with_useful_text(img, **kwargs),
|
|
"score": score,
|
|
"type": "image",
|
|
"group_id": index,
|
|
"format": detected_format,
|
|
}
|
|
|
|
def add_variant(src: str, width: Optional[str] = None):
|
|
if src and not src.startswith("data:") and src not in unique_urls:
|
|
unique_urls.add(src)
|
|
variant = {**base_info, "src": src}
|
|
if width:
|
|
variant["width"] = width
|
|
image_variants.append(variant)
|
|
|
|
# Add variants from different sources
|
|
add_variant(src)
|
|
add_variant(data_src)
|
|
|
|
for srcset_attr in [srcset, data_srcset]:
|
|
if srcset_attr:
|
|
for source in parse_srcset(srcset_attr):
|
|
add_variant(source["url"], source["width"])
|
|
|
|
# Handle picture element
|
|
if picture:
|
|
for source in picture[0].xpath(".//source[@srcset]"):
|
|
if source_srcset := source.get("srcset"):
|
|
for src_data in parse_srcset(source_srcset):
|
|
add_variant(src_data["url"], src_data["width"])
|
|
|
|
# Check framework-specific attributes
|
|
for attr, value in img.attrib.items():
|
|
if (
|
|
attr.startswith("data-")
|
|
and ("src" in attr or "srcset" in attr)
|
|
and "http" in value
|
|
):
|
|
add_variant(value)
|
|
|
|
return image_variants if image_variants else None
|
|
|
|
def remove_empty_elements_fast(self, root, word_count_threshold=5):
|
|
"""
|
|
Remove elements that fall below the desired word threshold in a single pass from the bottom up.
|
|
Skips non-element nodes like HtmlComment and bypasses certain tags that are allowed to have no content.
|
|
"""
|
|
bypass_tags = {
|
|
"a",
|
|
"img",
|
|
"br",
|
|
"hr",
|
|
"input",
|
|
"meta",
|
|
"link",
|
|
"source",
|
|
"track",
|
|
"wbr",
|
|
"tr",
|
|
"td",
|
|
"th",
|
|
}
|
|
|
|
for el in reversed(list(root.iterdescendants())):
|
|
if not isinstance(el, lhtml.HtmlElement):
|
|
continue
|
|
|
|
if el.tag in bypass_tags:
|
|
continue
|
|
|
|
# Skip elements inside <pre> or <code> tags where whitespace is significant
|
|
# This preserves whitespace-only spans (e.g., <span class="w"> </span>) in code blocks
|
|
is_in_code_block = False
|
|
ancestor = el.getparent()
|
|
while ancestor is not None:
|
|
if ancestor.tag in ("pre", "code"):
|
|
is_in_code_block = True
|
|
break
|
|
ancestor = ancestor.getparent()
|
|
|
|
if is_in_code_block:
|
|
continue
|
|
|
|
text_content = (el.text_content() or "").strip()
|
|
if (
|
|
len(text_content.split()) < word_count_threshold
|
|
and not el.getchildren()
|
|
):
|
|
parent = el.getparent()
|
|
if parent is not None:
|
|
parent.remove(el)
|
|
|
|
return root
|
|
|
|
def remove_unwanted_attributes_fast(
|
|
self, root: lhtml.HtmlElement, important_attrs=None, keep_data_attributes=False
|
|
) -> lhtml.HtmlElement:
|
|
"""
|
|
Removes all attributes from each element (including root) except those in `important_attrs`.
|
|
If `keep_data_attributes=True`, also retain any attribute starting with 'data-'.
|
|
|
|
Returns the same root element, mutated in-place, for fluent usage.
|
|
"""
|
|
if important_attrs is None:
|
|
important_attrs = set(IMPORTANT_ATTRS)
|
|
|
|
# If you want to handle the root as well, use 'include_self=True'
|
|
# so you don't miss attributes on the top-level element.
|
|
# Manually include the root, then all its descendants
|
|
for el in chain((root,), root.iterdescendants()):
|
|
# We only remove attributes on HtmlElement nodes, skip comments or text nodes
|
|
if not isinstance(el, lhtml.HtmlElement):
|
|
continue
|
|
|
|
old_attribs = dict(el.attrib)
|
|
new_attribs = {}
|
|
|
|
for attr_name, attr_val in old_attribs.items():
|
|
# If it's an important attribute, keep it
|
|
if attr_name in important_attrs:
|
|
new_attribs[attr_name] = attr_val
|
|
# Or if keep_data_attributes is True and it's a 'data-*' attribute
|
|
elif keep_data_attributes and attr_name.startswith("data-"):
|
|
new_attribs[attr_name] = attr_val
|
|
|
|
# Clear old attributes and set the filtered set
|
|
el.attrib.clear()
|
|
el.attrib.update(new_attribs)
|
|
|
|
return root
|
|
|
|
|
|
def _scrap(
|
|
self,
|
|
url: str,
|
|
html: str,
|
|
word_count_threshold: int = MIN_WORD_THRESHOLD,
|
|
css_selector: str = None,
|
|
target_elements: List[str] = None,
|
|
**kwargs,
|
|
) -> Dict[str, Any]:
|
|
if not html:
|
|
return None
|
|
|
|
success = True
|
|
try:
|
|
doc = lhtml.document_fromstring(html)
|
|
# Match BeautifulSoup's behavior of using body or full doc
|
|
# body = doc.xpath('//body')[0] if doc.xpath('//body') else doc
|
|
body = doc
|
|
|
|
base_domain = get_base_domain(url)
|
|
|
|
# Extract page context for link scoring (if enabled) - do this BEFORE any removals
|
|
page_context = None
|
|
if kwargs.get("score_links", False):
|
|
try:
|
|
# Extract title
|
|
title_elements = doc.xpath('//title')
|
|
page_title = title_elements[0].text_content() if title_elements else ""
|
|
|
|
# Extract headlines
|
|
headlines = []
|
|
for tag in ['h1', 'h2', 'h3']:
|
|
elements = doc.xpath(f'//{tag}')
|
|
for el in elements:
|
|
text = el.text_content().strip()
|
|
if text:
|
|
headlines.append(text)
|
|
headlines_text = ' '.join(headlines)
|
|
|
|
# Extract meta description
|
|
meta_desc_elements = doc.xpath('//meta[@name="description"]/@content')
|
|
meta_description = meta_desc_elements[0] if meta_desc_elements else ""
|
|
|
|
# Create page context
|
|
page_context = extract_page_context(page_title, headlines_text, meta_description, url)
|
|
except Exception:
|
|
page_context = {} # Fail gracefully
|
|
|
|
# Early removal of all images if exclude_all_images is set
|
|
# This is more efficient in lxml as we remove elements before any processing
|
|
if kwargs.get("exclude_all_images", False):
|
|
for img in body.xpath('//img'):
|
|
if img.getparent() is not None:
|
|
img.getparent().remove(img)
|
|
|
|
# Add comment removal
|
|
if kwargs.get("remove_comments", False):
|
|
comments = body.xpath("//comment()")
|
|
for comment in comments:
|
|
comment.getparent().remove(comment)
|
|
|
|
# Handle tag-based removal first
|
|
excluded_tags = set(kwargs.get("excluded_tags", []) or [])
|
|
if excluded_tags:
|
|
for tag in excluded_tags:
|
|
for element in body.xpath(f".//{tag}"):
|
|
if element.getparent() is not None:
|
|
element.getparent().remove(element)
|
|
|
|
# Handle CSS selector-based exclusion
|
|
excluded_selector = kwargs.get("excluded_selector", "")
|
|
if excluded_selector:
|
|
try:
|
|
for element in body.cssselect(excluded_selector):
|
|
if element.getparent() is not None:
|
|
element.getparent().remove(element)
|
|
except Exception as e:
|
|
self._log(
|
|
"error", f"Error with excluded CSS selector: {str(e)}", "SCRAPE"
|
|
)
|
|
|
|
# Extract metadata before any content filtering
|
|
try:
|
|
meta = extract_metadata_using_lxml(
|
|
"", doc
|
|
) # Using same function as BeautifulSoup version
|
|
except Exception as e:
|
|
self._log("error", f"Error extracting metadata: {str(e)}", "SCRAPE")
|
|
meta = {}
|
|
|
|
content_element = None
|
|
if target_elements:
|
|
try:
|
|
for_content_targeted_element = []
|
|
for target_element in target_elements:
|
|
for_content_targeted_element.extend(body.cssselect(target_element))
|
|
content_element = lhtml.Element("div")
|
|
content_element.extend(copy.deepcopy(for_content_targeted_element))
|
|
except Exception as e:
|
|
self._log("error", f"Error with target element detection: {str(e)}", "SCRAPE")
|
|
return None
|
|
else:
|
|
content_element = body
|
|
|
|
# Remove script and style tags
|
|
for tag in ["script", "style", "link", "meta", "noscript"]:
|
|
for element in body.xpath(f".//{tag}"):
|
|
if element.getparent() is not None:
|
|
element.getparent().remove(element)
|
|
|
|
# Handle social media and domain exclusions
|
|
kwargs["exclude_domains"] = set(kwargs.get("exclude_domains", []))
|
|
if kwargs.get("exclude_social_media_links", False):
|
|
kwargs["exclude_social_media_domains"] = set(
|
|
kwargs.get("exclude_social_media_domains", [])
|
|
+ SOCIAL_MEDIA_DOMAINS
|
|
)
|
|
kwargs["exclude_domains"].update(kwargs["exclude_social_media_domains"])
|
|
|
|
# Process forms if needed
|
|
if kwargs.get("remove_forms", False):
|
|
for form in body.xpath(".//form"):
|
|
if form.getparent() is not None:
|
|
form.getparent().remove(form)
|
|
|
|
# Process content
|
|
media = {"images": [], "videos": [], "audios": [], "tables": []}
|
|
internal_links_dict = {}
|
|
external_links_dict = {}
|
|
|
|
self._process_element(
|
|
url,
|
|
body,
|
|
media,
|
|
internal_links_dict,
|
|
external_links_dict,
|
|
page_context=page_context,
|
|
base_domain=base_domain,
|
|
**kwargs,
|
|
)
|
|
|
|
# Extract tables using the table extraction strategy if provided
|
|
if 'table' not in excluded_tags:
|
|
table_extraction = kwargs.get('table_extraction')
|
|
if table_extraction:
|
|
# Pass logger to the strategy if it doesn't have one
|
|
if not table_extraction.logger:
|
|
table_extraction.logger = self.logger
|
|
# Extract tables using the strategy
|
|
extracted_tables = table_extraction.extract_tables(body, **kwargs)
|
|
media["tables"].extend(extracted_tables)
|
|
|
|
# Handle only_text option
|
|
if kwargs.get("only_text", False):
|
|
for tag in ONLY_TEXT_ELIGIBLE_TAGS:
|
|
for element in body.xpath(f".//{tag}"):
|
|
if element.text:
|
|
new_text = lhtml.Element("span")
|
|
new_text.text = element.text_content()
|
|
if element.getparent() is not None:
|
|
element.getparent().replace(element, new_text)
|
|
|
|
# Clean base64 images
|
|
for img in body.xpath(".//img[@src]"):
|
|
src = img.get("src", "")
|
|
if self.BASE64_PATTERN.match(src):
|
|
img.set("src", self.BASE64_PATTERN.sub("", src))
|
|
|
|
# Remove empty elements
|
|
self.remove_empty_elements_fast(body, 1)
|
|
|
|
# Remove unneeded attributes
|
|
self.remove_unwanted_attributes_fast(
|
|
body, keep_data_attributes=kwargs.get("keep_data_attributes", False)
|
|
)
|
|
|
|
# Generate output HTML
|
|
cleaned_html = lhtml.tostring(
|
|
# body,
|
|
content_element,
|
|
encoding="unicode",
|
|
pretty_print=True,
|
|
method="html",
|
|
with_tail=False,
|
|
).strip()
|
|
|
|
# Create links dictionary in the format expected by LinkPreview
|
|
links = {
|
|
"internal": list(internal_links_dict.values()),
|
|
"external": list(external_links_dict.values()),
|
|
}
|
|
|
|
# Extract head content for links if configured
|
|
link_preview_config = kwargs.get("link_preview_config")
|
|
if link_preview_config is not None:
|
|
try:
|
|
import asyncio
|
|
from .link_preview import LinkPreview
|
|
from .models import Links, Link
|
|
|
|
verbose = link_preview_config.verbose
|
|
|
|
if verbose:
|
|
self._log("info", "Starting link head extraction for {internal} internal and {external} external links",
|
|
params={"internal": len(links["internal"]), "external": len(links["external"])}, tag="LINK_EXTRACT")
|
|
|
|
# Convert dict links to Link objects
|
|
internal_links = [Link(**link_data) for link_data in links["internal"]]
|
|
external_links = [Link(**link_data) for link_data in links["external"]]
|
|
links_obj = Links(internal=internal_links, external=external_links)
|
|
|
|
# Create a config object for LinkPreview
|
|
class TempCrawlerRunConfig:
|
|
def __init__(self, link_config, score_links):
|
|
self.link_preview_config = link_config
|
|
self.score_links = score_links
|
|
|
|
config = TempCrawlerRunConfig(link_preview_config, kwargs.get("score_links", False))
|
|
|
|
# Extract head content (run async operation in sync context)
|
|
async def extract_links():
|
|
async with LinkPreview(self.logger) as extractor:
|
|
return await extractor.extract_link_heads(links_obj, config)
|
|
|
|
# Run the async operation
|
|
try:
|
|
# Check if we're already in an async context
|
|
loop = asyncio.get_running_loop()
|
|
# If we're in an async context, we need to run in a thread
|
|
import concurrent.futures
|
|
with concurrent.futures.ThreadPoolExecutor() as executor:
|
|
future = executor.submit(asyncio.run, extract_links())
|
|
updated_links = future.result()
|
|
except RuntimeError:
|
|
# No running loop, we can use asyncio.run directly
|
|
updated_links = asyncio.run(extract_links())
|
|
|
|
# Convert back to dict format
|
|
links["internal"] = [link.dict() for link in updated_links.internal]
|
|
links["external"] = [link.dict() for link in updated_links.external]
|
|
|
|
if verbose:
|
|
successful_internal = len([l for l in updated_links.internal if l.head_extraction_status == "valid"])
|
|
successful_external = len([l for l in updated_links.external if l.head_extraction_status == "valid"])
|
|
self._log("info", "Link head extraction completed: {internal_success}/{internal_total} internal, {external_success}/{external_total} external",
|
|
params={
|
|
"internal_success": successful_internal,
|
|
"internal_total": len(updated_links.internal),
|
|
"external_success": successful_external,
|
|
"external_total": len(updated_links.external)
|
|
}, tag="LINK_EXTRACT")
|
|
else:
|
|
self._log("info", "Link head extraction completed successfully", tag="LINK_EXTRACT")
|
|
|
|
except Exception as e:
|
|
self._log("error", f"Error during link head extraction: {str(e)}", tag="LINK_EXTRACT")
|
|
# Continue with original links if head extraction fails
|
|
|
|
return {
|
|
"cleaned_html": cleaned_html,
|
|
"success": success,
|
|
"media": media,
|
|
"links": links,
|
|
"metadata": meta,
|
|
}
|
|
|
|
except Exception as e:
|
|
self._log("error", f"Error processing HTML: {str(e)}", "SCRAPE")
|
|
# Create error message in case of failure
|
|
error_body = lhtml.Element("div")
|
|
# Use etree.SubElement rather than lhtml.SubElement
|
|
error_div = etree.SubElement(error_body, "div", id="crawl4ai_error_message")
|
|
error_div.text = f"""
|
|
Crawl4AI Error: This page is not fully supported.
|
|
|
|
Error Message: {str(e)}
|
|
|
|
Possible reasons:
|
|
1. The page may have restrictions that prevent crawling.
|
|
2. The page might not be fully loaded.
|
|
|
|
Suggestions:
|
|
- Try calling the crawl function with these parameters:
|
|
magic=True,
|
|
- Set headless=False to visualize what's happening on the page.
|
|
|
|
If the issue persists, please check the page's structure and any potential anti-crawling measures.
|
|
"""
|
|
cleaned_html = lhtml.tostring(
|
|
error_body, encoding="unicode", pretty_print=True
|
|
)
|
|
return {
|
|
"cleaned_html": cleaned_html,
|
|
"success": False,
|
|
"media": {
|
|
"images": [],
|
|
"videos": [],
|
|
"audios": [],
|
|
"tables": []
|
|
},
|
|
"links": {"internal": [], "external": []},
|
|
"metadata": {},
|
|
}
|
|
|
|
|
|
# Backward compatibility alias
|
|
WebScrapingStrategy = LXMLWebScrapingStrategy
|