langchain_community.document_loaders.hn.HNLoader¶

class langchain_community.document_loaders.hn.HNLoader(web_path: Union[str, Sequence[str]] = '', header_template: Optional[dict] = None, verify_ssl: bool = True, proxies: Optional[dict] = None, continue_on_failure: bool = False, autoset_encoding: bool = True, encoding: Optional[str] = None, web_paths: Sequence[str] = (), requests_per_second: int = 2, default_parser: str = 'html.parser', requests_kwargs: Optional[Dict[str, Any]] = None, raise_for_status: bool = False, bs_get_text_kwargs: Optional[Dict[str, Any]] = None, bs_kwargs: Optional[Dict[str, Any]] = None, session: Any = None)[source]¶

Load Hacker News data.

It loads data from either main page results or the comments page.

Initialize loader.

Parameters

  • web_paths – Web paths to load from.

  • requests_per_second – Max number of concurrent requests to make.

  • default_parser – Default parser to use for BeautifulSoup.

  • requests_kwargs – kwargs for requests

  • raise_for_status – Raise an exception if http status code denotes an error.

  • bs_get_text_kwargs – kwargs for beatifulsoup4 get_text

  • bs_kwargs – kwargs for beatifulsoup4 web page parsing

Attributes

web_path

Methods

__init__([web_path, header_template, ...])

Initialize loader.

aload()

Load text from the urls in web_path async into Documents.

fetch_all(urls)

Fetch all urls concurrently with rate limiting.

lazy_load()

Lazy load text from the url(s) in web_path.

load()

Get important HN webpage information.

load_and_split([text_splitter])

Load Documents and split into chunks.

load_comments(soup_info)

Load comments from a HN post.

load_results(soup)

Load items from an HN page.

scrape([parser])

Scrape data from webpage and return it in BeautifulSoup format.

scrape_all(urls[, parser])

Fetch all urls, then return soups for all results.
__init__(web_path: Union[str, Sequence[str]] = '', header_template: Optional[dict] = None, verify_ssl: bool = True, proxies: Optional[dict] = None, continue_on_failure: bool = False, autoset_encoding: bool = True, encoding: Optional[str] = None, web_paths: Sequence[str] = (), requests_per_second: int = 2, default_parser: str = 'html.parser', requests_kwargs: Optional[Dict[str, Any]] = None, raise_for_status: bool = False, bs_get_text_kwargs: Optional[Dict[str, Any]] = None, bs_kwargs: Optional[Dict[str, Any]] = None, session: Any = None) → None¶

Initialize loader.

Parameters

  • web_paths – Web paths to load from.

  • requests_per_second – Max number of concurrent requests to make.

  • default_parser – Default parser to use for BeautifulSoup.

  • requests_kwargs – kwargs for requests

  • raise_for_status – Raise an exception if http status code denotes an error.

  • bs_get_text_kwargs – kwargs for beatifulsoup4 get_text

  • bs_kwargs – kwargs for beatifulsoup4 web page parsing

aload() → List[Document]¶

Load text from the urls in web_path async into Documents.

async fetch_all(urls: List[str]) → Any¶

Fetch all urls concurrently with rate limiting.

lazy_load() → Iterator[Document]¶

Lazy load text from the url(s) in web_path.

load() → List[Document][source]¶

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

load_and_split(text_splitter: Optional[TextSplitter] = None) → List[Document]¶

Load Documents and split into chunks. Chunks are returned as Documents.

Parameters

text_splitter – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter.

Returns

List of Documents.

load_comments(soup_info: Any) → List[Document][source]¶

Load comments from a HN post.

load_results(soup: Any) → List[Document][source]¶

Load items from an HN page.

scrape(parser: Optional[str] = None) → Any¶

Scrape data from webpage and return it in BeautifulSoup format.

scrape_all(urls: List[str], parser: Optional[str] = None) → List[Any]¶

Fetch all urls, then return soups for all results.

Examples using HNLoader¶