Airbyte Shopify (Deprecated)
Note: This connector-specific loader is deprecated. Please use
AirbyteLoader
instead.
Airbyte is a data integration platform for ELT pipelines from APIs, databases & files to warehouses & lakes. It has the largest catalog of ELT connectors to data warehouses and databases.
This loader exposes the Shopify connector as a document loader, allowing you to load various Shopify objects as documents.
Installationβ
First, you need to install the airbyte-source-shopify
python package.
%pip install --upgrade --quiet airbyte-source-shopify
Exampleβ
Check out the Airbyte documentation page for details about how to configure the reader. The JSON schema the config object should adhere to can be found on Github: https://github.com/airbytehq/airbyte/blob/master/airbyte-integrations/connectors/source-shopify/source_shopify/spec.json.
The general shape looks like this:
{
"start_date": "<date from which to start retrieving records from in ISO format, e.g. 2020-10-20T00:00:00Z>",
"shop": "<name of the shop you want to retrieve documents from>",
"credentials": {
"auth_method": "api_password",
"api_password": "<your api password>"
}
}
By default all fields are stored as metadata in the documents and the text is set to an empty string. Construct the text of the document by transforming the documents returned by the reader.
from langchain_community.document_loaders.airbyte import AirbyteShopifyLoader
config = {
# your shopify configuration
}
loader = AirbyteShopifyLoader(
config=config, stream_name="orders"
) # check the documentation linked above for a list of all streams
API Reference:
Now you can load documents the usual way
docs = loader.load()
As load
returns a list, it will block until all documents are loaded.
To have better control over this process, you can also you the
lazy_load
method which returns an iterator instead:
docs_iterator = loader.lazy_load()
Keep in mind that by default the page content is empty and the metadata object contains all the information from the record. To create documents in a different, pass in a record_handler function when creating the loader:
from langchain_community.docstore.document import Document
def handle_record(record, id):
return Document(page_content=record.data["title"], metadata=record.data)
loader = AirbyteShopifyLoader(
config=config, record_handler=handle_record, stream_name="orders"
)
docs = loader.load()
API Reference:
Incremental loadsβ
Some streams allow incremental loading, this means the source keeps track of synced records and wonβt load them again. This is useful for sources that have a high volume of data and are updated frequently.
To take advantage of this, store the last_state
property of the loader
and pass it in when creating the loader again. This will ensure that
only new records are loaded.
last_state = loader.last_state # store safely
incremental_loader = AirbyteShopifyLoader(
config=config, stream_name="orders", state=last_state
)
new_docs = incremental_loader.load()