ApifyDatasetLoader#

class langchain_community.document_loaders.apify_dataset.ApifyDatasetLoader[source]#

Bases: BaseLoader, BaseModel

Load datasets from Apify web scraping, crawling, and data extraction platform.

For details, see https://docs.apify.com/platform/integrations/langchain

Example

from langchain_community.document_loaders import ApifyDatasetLoader
from langchain_core.documents import Document

loader = ApifyDatasetLoader(
    dataset_id="YOUR-DATASET-ID",
    dataset_mapping_function=lambda dataset_item: Document(
        page_content=dataset_item["text"], metadata={"source": dataset_item["url"]}
    ),
)
documents = loader.load()

Initialize the loader with an Apify dataset ID and a mapping function.

Parameters:

dataset_id (str) – The ID of the dataset on the Apify platform.
dataset_mapping_function (Callable) – A function that takes a single dictionary (an Apify dataset item) and converts it to an instance of the Document class.

param apify_client: Any [Required]#: An instance of the ApifyClient class from the apify-client Python package.

param dataset_id: str [Required]#: The ID of the dataset on the Apify platform.

param dataset_mapping_function: Callable[[Dict], Document] [Required]#: A custom function that takes a single dictionary (an Apify dataset item) and converts it to an instance of the Document class.

async alazy_load() → AsyncIterator[Document]#

A lazy loader for Documents.

Return type:: AsyncIterator[Document]

async aload() → list[Document]#

Load data into Document objects.

Return type:: list[Document]

lazy_load() → Iterator[Document]#

A lazy loader for Documents.

Return type:: Iterator[Document]

load() → List[Document][source]#

Load documents.

Return type:: List[Document]

load_and_split(text_splitter: TextSplitter | None = None) → list[Document]#

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

Do not override this method. It should be considered to be deprecated!

Parameters:: text_splitter (Optional[TextSplitter]) – TextSplitter instance to use for splitting documents. Defaults to RecursiveCharacterTextSplitter.
Returns:: List of Documents.
Return type:: list[Document]

Examples using ApifyDatasetLoader