feat: Add advanced link head extraction with three-layer scoring system (#1)
Squashed commit from feature/link-extractor branch implementing comprehensive link analysis: - Extract HTML head content from discovered links with parallel processing - Three-layer scoring: Intrinsic (URL quality), Contextual (BM25), and Total scores - New LinkExtractionConfig class for type-safe configuration - Pattern-based filtering for internal/external links - Comprehensive documentation and examples
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@@ -23,6 +23,8 @@ from .utils import (
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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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@@ -944,6 +946,72 @@ class WebScrapingStrategy(ContentScrapingStrategy):
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# Update the links dictionary with unique links
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links["internal"] = list(internal_links_dict.values())
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links["external"] = list(external_links_dict.values())
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# Extract head content for links if configured
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link_extraction_config = kwargs.get("link_extraction_config")
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if link_extraction_config is not None:
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try:
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import asyncio
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from .link_extractor import LinkExtractor
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from .models import Links, Link
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verbose = link_extraction_config.verbose
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if verbose:
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self._log("info", "Starting link head extraction for {internal} internal and {external} external links",
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params={"internal": len(links["internal"]), "external": len(links["external"])}, tag="LINK_EXTRACT")
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# Convert dict links to Link objects
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internal_links = [Link(**link_data) for link_data in links["internal"]]
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external_links = [Link(**link_data) for link_data in links["external"]]
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links_obj = Links(internal=internal_links, external=external_links)
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# Create a config object for LinkExtractor
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class TempCrawlerRunConfig:
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def __init__(self, link_config, score_links):
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self.link_extraction_config = link_config
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self.score_links = score_links
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config = TempCrawlerRunConfig(link_extraction_config, kwargs.get("score_links", False))
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# Extract head content (run async operation in sync context)
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async def extract_links():
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async with LinkExtractor(self.logger) as extractor:
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return await extractor.extract_link_heads(links_obj, config)
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# Run the async operation
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try:
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# Check if we're already in an async context
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loop = asyncio.get_running_loop()
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# If we're in an async context, we need to run in a thread
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import concurrent.futures
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with concurrent.futures.ThreadPoolExecutor() as executor:
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future = executor.submit(asyncio.run, extract_links())
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updated_links = future.result()
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except RuntimeError:
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# No running loop, we can use asyncio.run directly
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updated_links = asyncio.run(extract_links())
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# Convert back to dict format
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links["internal"] = [link.dict() for link in updated_links.internal]
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links["external"] = [link.dict() for link in updated_links.external]
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if verbose:
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successful_internal = len([l for l in updated_links.internal if l.head_extraction_status == "valid"])
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successful_external = len([l for l in updated_links.external if l.head_extraction_status == "valid"])
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self._log("info", "Link head extraction completed: {internal_success}/{internal_total} internal, {external_success}/{external_total} external",
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params={
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"internal_success": successful_internal,
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"internal_total": len(updated_links.internal),
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"external_success": successful_external,
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"external_total": len(updated_links.external)
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}, tag="LINK_EXTRACT")
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else:
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self._log("info", "Link head extraction completed successfully", tag="LINK_EXTRACT")
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except Exception as e:
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self._log("error", f"Link head extraction failed: {str(e)}", tag="LINK_EXTRACT")
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# Continue with original links if extraction fails
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# # Process images using ThreadPoolExecutor
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imgs = body.find_all("img")
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@@ -1037,6 +1105,7 @@ class LXMLWebScrapingStrategy(WebScrapingStrategy):
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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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@@ -1056,6 +1125,25 @@ class LXMLWebScrapingStrategy(WebScrapingStrategy):
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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"] = float('inf')
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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"] = float('inf')
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is_external = is_external_url(normalized_href, base_domain)
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if is_external:
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@@ -1491,6 +1579,33 @@ class LXMLWebScrapingStrategy(WebScrapingStrategy):
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base_domain = get_base_domain(url)
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# Extract page context for link scoring (if enabled) - do this BEFORE any removals
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page_context = None
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if kwargs.get("score_links", False):
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try:
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# Extract title
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title_elements = doc.xpath('//title')
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page_title = title_elements[0].text_content() if title_elements else ""
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# Extract headlines
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headlines = []
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for tag in ['h1', 'h2', 'h3']:
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elements = doc.xpath(f'//{tag}')
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for el in elements:
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text = el.text_content().strip()
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if text:
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headlines.append(text)
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headlines_text = ' '.join(headlines)
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# Extract meta description
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meta_desc_elements = doc.xpath('//meta[@name="description"]/@content')
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meta_description = meta_desc_elements[0] if meta_desc_elements else ""
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# Create page context
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page_context = extract_page_context(page_title, headlines_text, meta_description, url)
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except Exception:
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page_context = {} # Fail gracefully
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# Early removal of all images if exclude_all_images is set
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# This is more efficient in lxml as we remove elements before any processing
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if kwargs.get("exclude_all_images", False):
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@@ -1579,6 +1694,7 @@ class LXMLWebScrapingStrategy(WebScrapingStrategy):
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media,
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internal_links_dict,
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external_links_dict,
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page_context=page_context,
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base_domain=base_domain,
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**kwargs,
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)
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@@ -1623,14 +1739,84 @@ class LXMLWebScrapingStrategy(WebScrapingStrategy):
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method="html",
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with_tail=False,
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).strip()
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# Create links dictionary in the format expected by LinkExtractor
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links = {
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"internal": list(internal_links_dict.values()),
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"external": list(external_links_dict.values()),
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}
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# Extract head content for links if configured
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link_extraction_config = kwargs.get("link_extraction_config")
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if link_extraction_config is not None:
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try:
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import asyncio
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from .link_extractor import LinkExtractor
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from .models import Links, Link
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verbose = link_extraction_config.verbose
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if verbose:
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self._log("info", "Starting link head extraction for {internal} internal and {external} external links",
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params={"internal": len(links["internal"]), "external": len(links["external"])}, tag="LINK_EXTRACT")
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# Convert dict links to Link objects
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internal_links = [Link(**link_data) for link_data in links["internal"]]
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external_links = [Link(**link_data) for link_data in links["external"]]
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links_obj = Links(internal=internal_links, external=external_links)
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# Create a config object for LinkExtractor
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class TempCrawlerRunConfig:
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def __init__(self, link_config, score_links):
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self.link_extraction_config = link_config
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self.score_links = score_links
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config = TempCrawlerRunConfig(link_extraction_config, kwargs.get("score_links", False))
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# Extract head content (run async operation in sync context)
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async def extract_links():
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async with LinkExtractor(self.logger) as extractor:
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return await extractor.extract_link_heads(links_obj, config)
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# Run the async operation
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try:
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# Check if we're already in an async context
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loop = asyncio.get_running_loop()
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# If we're in an async context, we need to run in a thread
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import concurrent.futures
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with concurrent.futures.ThreadPoolExecutor() as executor:
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future = executor.submit(asyncio.run, extract_links())
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updated_links = future.result()
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except RuntimeError:
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# No running loop, we can use asyncio.run directly
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updated_links = asyncio.run(extract_links())
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# Convert back to dict format
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links["internal"] = [link.dict() for link in updated_links.internal]
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links["external"] = [link.dict() for link in updated_links.external]
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if verbose:
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successful_internal = len([l for l in updated_links.internal if l.head_extraction_status == "valid"])
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successful_external = len([l for l in updated_links.external if l.head_extraction_status == "valid"])
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self._log("info", "Link head extraction completed: {internal_success}/{internal_total} internal, {external_success}/{external_total} external",
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params={
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"internal_success": successful_internal,
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"internal_total": len(updated_links.internal),
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"external_success": successful_external,
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"external_total": len(updated_links.external)
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}, tag="LINK_EXTRACT")
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else:
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self._log("info", "Link head extraction completed successfully", tag="LINK_EXTRACT")
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except Exception as e:
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self._log("error", f"Error during link head extraction: {str(e)}", tag="LINK_EXTRACT")
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# Continue with original links if head extraction fails
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return {
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"cleaned_html": cleaned_html,
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"success": success,
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"media": media,
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"links": {
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"internal": list(internal_links_dict.values()),
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"external": list(external_links_dict.values()),
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},
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"links": links,
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"metadata": meta,
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}
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