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Recursive URL

The RecursiveUrlLoader lets you recursively scrape all child links from a root URL and parse them into Documents.

Overview​

Integration details​

ClassPackageLocalSerializableJS support
RecursiveUrlLoaderlangchain_community✅❌✅

Loader features​

SourceDocument Lazy LoadingNative Async Support
RecursiveUrlLoader✅❌

Setup​

Credentials​

No credentials are required to use the RecursiveUrlLoader.

Installation​

The RecursiveUrlLoader lives in the langchain-community package. There's no other required packages, though you will get richer default Document metadata if you have `beautifulsoup4 installed as well.

%pip install -qU langchain-community beautifulsoup4

Instantiation​

Now we can instantiate our document loader object and load Documents:

from langchain_community.document_loaders import RecursiveUrlLoader

loader = RecursiveUrlLoader(
    "https://docs.python.org/3.9/",
    # max_depth=2,
    # use_async=False,
    # extractor=None,
    # metadata_extractor=None,
    # exclude_dirs=(),
    # timeout=10,
    # check_response_status=True,
    # continue_on_failure=True,
    # prevent_outside=True,
    # base_url=None,
    # ...
)
API Reference:RecursiveUrlLoader

Load​

Use .load() to synchronously load into memory all Documents, with one Document per visited URL. Starting from the initial URL, we recurse through all linked URLs up to the specified max_depth.

Let's run through a basic example of how to use the RecursiveUrlLoader on the Python 3.9 Documentation.

docs = loader.load()
docs[0].metadata
/Users/bagatur/.pyenv/versions/3.9.1/lib/python3.9/html/parser.py:170: XMLParsedAsHTMLWarning: It looks like you're parsing an XML document using an HTML parser. If this really is an HTML document (maybe it's XHTML?), you can ignore or filter this warning. If it's XML, you should know that using an XML parser will be more reliable. To parse this document as XML, make sure you have the lxml package installed, and pass the keyword argument `features="xml"` into the BeautifulSoup constructor.
  k = self.parse_starttag(i)
{'source': 'https://docs.python.org/3.9/',
 'content_type': 'text/html',
 'title': '3.9.19 Documentation',
 'language': None}

Great! The first document looks like the root page we started from. Let's look at the metadata of the next document

docs[1].metadata
{'source': 'https://docs.python.org/3.9/using/index.html',
 'content_type': 'text/html',
 'title': 'Python Setup and Usage — Python 3.9.19 documentation',
 'language': None}

That url looks like a child of our root page, which is great! Let's move on from metadata to examine the content of one of our documents

print(docs[0].page_content[:300])

<!DOCTYPE html>

<html xmlns="http://www.w3.org/1999/xhtml">
  <head>
    <meta charset="utf-8" /><title>3.9.19 Documentation</title><meta name="viewport" content="width=device-width, initial-scale=1.0">
    
    <link rel="stylesheet" href="_static/pydoctheme.css" type="text/css" />
    <link rel=

That certainly looks like HTML that comes from the url https://docs.python.org/3.9/, which is what we expected. Let's now look at some variations we can make to our basic example that can be helpful in different situations.

Lazy loading​

If we're loading a large number of Documents and our downstream operations can be done over subsets of all loaded Documents, we can lazily load our Documents one at a time to minimize our memory footprint:

pages = []
for doc in loader.lazy_load():
    pages.append(doc)
    if len(pages) >= 10:
        # do some paged operation, e.g.
        # index.upsert(page)

        pages = []
/var/folders/4j/2rz3865x6qg07tx43146py8h0000gn/T/ipykernel_73962/2110507528.py:6: XMLParsedAsHTMLWarning: It looks like you're parsing an XML document using an HTML parser. If this really is an HTML document (maybe it's XHTML?), you can ignore or filter this warning. If it's XML, you should know that using an XML parser will be more reliable. To parse this document as XML, make sure you have the lxml package installed, and pass the keyword argument `features="xml"` into the BeautifulSoup constructor.
  soup = BeautifulSoup(html, "lxml")

In this example we never have more than 10 Documents loaded into memory at a time.

Adding an Extractor​

By default the loader sets the raw HTML from each link as the Document page content. To parse this HTML into a more human/LLM-friendly format you can pass in a custom extractor method:

import re

from bs4 import BeautifulSoup


def bs4_extractor(html: str) -> str:
    soup = BeautifulSoup(html, "lxml")
    return re.sub(r"\n\n+", "\n\n", soup.text).strip()


loader = RecursiveUrlLoader("https://docs.python.org/3.9/", extractor=bs4_extractor)
docs = loader.load()
print(docs[0].page_content[:200])
/var/folders/td/vzm913rx77x21csd90g63_7c0000gn/T/ipykernel_10935/1083427287.py:6: XMLParsedAsHTMLWarning: It looks like you're parsing an XML document using an HTML parser. If this really is an HTML document (maybe it's XHTML?), you can ignore or filter this warning. If it's XML, you should know that using an XML parser will be more reliable. To parse this document as XML, make sure you have the lxml package installed, and pass the keyword argument `features="xml"` into the BeautifulSoup constructor.
  soup = BeautifulSoup(html, "lxml")
/Users/isaachershenson/.pyenv/versions/3.11.9/lib/python3.11/html/parser.py:170: XMLParsedAsHTMLWarning: It looks like you're parsing an XML document using an HTML parser. If this really is an HTML document (maybe it's XHTML?), you can ignore or filter this warning. If it's XML, you should know that using an XML parser will be more reliable. To parse this document as XML, make sure you have the lxml package installed, and pass the keyword argument `features="xml"` into the BeautifulSoup constructor.
  k = self.parse_starttag(i)
``````output
3.9.19 Documentation

Download
Download these documents
Docs by version

Python 3.13 (in development)
Python 3.12 (stable)
Python 3.11 (security-fixes)
Python 3.10 (security-fixes)
Python 3.9 (securit

This looks much nicer!

You can similarly pass in a metadata_extractor to customize how Document metadata is extracted from the HTTP response. See the API reference for more on this.

API reference​

These examples show just a few of the ways in which you can modify the default RecursiveUrlLoader, but there are many more modifications that can be made to best fit your use case. Using the parameters link_regex and exclude_dirs can help you filter out unwanted URLs, aload() and alazy_load() can be used for aynchronous loading, and more.

For detailed information on configuring and calling the RecursiveUrlLoader, please see the API reference: https://python.langchain.com/api_reference/community/document_loaders/langchain_community.document_loaders.recursive_url_loader.RecursiveUrlLoader.html.

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