Source code for

from typing import Any, List

from langchain_core.documents import Document

from langchain_community.document_loaders.web_base import WebBaseLoader

[docs]class HNLoader(WebBaseLoader): """Load `Hacker News` data. It loads data from either main page results or the comments page."""
[docs] def load(self) -> List[Document]: """Get important HN webpage information. HN webpage components are: - title - content - source url, - time of post - author of the post - number of comments - rank of the post """ soup_info = self.scrape() if "item" in self.web_path: return self.load_comments(soup_info) else: return self.load_results(soup_info)
[docs] def load_comments(self, soup_info: Any) -> List[Document]: """Load comments from a HN post.""" comments ="tr[class='athing comtr']") title = soup_info.select_one("tr[id='pagespace']").get("title") return [ Document( page_content=comment.text.strip(), metadata={"source": self.web_path, "title": title}, ) for comment in comments ]
[docs] def load_results(self, soup: Any) -> List[Document]: """Load items from an HN page.""" items ="tr[class='athing']") documents = [] for lineItem in items: ranking = lineItem.select_one("span[class='rank']").text link = lineItem.find("span", {"class": "titleline"}).find("a").get("href") title = lineItem.find("span", {"class": "titleline"}).text.strip() metadata = { "source": self.web_path, "title": title, "link": link, "ranking": ranking, } documents.append( Document( page_content=title, link=link, ranking=ranking, metadata=metadata ) ) return documents