Connectors & datasets

Python SDK reference for connectors and datasets — create, test, browse, and update connectors, then onboard, list, summarize, refresh, and delete datasets.

These methods manage data connectors and the datasets you onboard from them. They are available on both AlgentaClient and AsyncAlgentaClient (await the async calls). Connector metadata is passed as typed keyword arguments; dataset onboarding takes a request dict. For a full walkthrough see Connect a data source and the per-provider pages under Connectors.

Method reference

Method	Purpose
create_connector(*, name, connector_type, config=None, description=None, visibility=None)	Create a data connector (ConnectorInfo). Posts to /v1/connectors.
list_connectors(*, page=1, limit=200)	List connectors (ConnectorListResult). Reads /v1/connectors.
iter_connectors(*, page=1, limit=200, max_items=None)	Iterate connectors across pages, capped by max_items.
get_connector(connector_id)	Fetch one connector (ConnectorInfo). Reads /v1/connectors/{connector_id}.
update_connector(connector_id, *, name=None, description=None, visibility=None, config=None)	Update a connector's metadata or config (ConnectorInfo). Sends PATCH /v1/connectors/{connector_id}.
delete_connector(connector_id)	Delete a connector. Sends DELETE /v1/connectors/{connector_id}.
test_connector(connector_id)	Run a real connection test on a saved connector (ConnectorTestInfo). Posts to /v1/connectors/{connector_id}/test.
preview_test_connector(*, connector_type, config=None)	Test a connector config before saving it (ConnectorTestInfo). Posts to /v1/connectors/test.
browse_connector(connector_id)	List the tables a live connector exposes (ConnectorBrowseResult). Reads /v1/connectors/{connector_id}/browse.
preview_browse_connector(*, connector_type, config=None)	Browse a connector config before saving it (ConnectorBrowseResult). Posts to /v1/connectors/browse.
connect_data(request=None, **kwargs)	Onboard a connector selection (table or query) as a queryable dataset (DatasetConnectResult). Posts to /v1/data/connect.
list_datasets(*, page=1, limit=200, search=None, status=None, source_name=None, compact=False)	List datasets (DatasetListResult). Reads /v1/data.
iter_datasets(*, page=1, limit=200, max_items=None, search=None, status=None, source_name=None, compact=False)	Iterate datasets across pages, capped by max_items.
get_dataset(dataset_id)	Fetch dataset detail (DatasetDetailResult). Reads /v1/data/{dataset_id}.
get_dataset_summary(dataset_id)	Fetch a dataset's profiled schema summary (DatasetSummaryResult). Reads /v1/data/{dataset_id}/summary.
refresh_dataset(dataset_id)	Re-ingest a dataset from its source (DatasetConnectResult). Posts to /v1/data/{dataset_id}/refresh.
delete_dataset(dataset_id)	Delete a dataset (DatasetDeleteResult). Sends DELETE /v1/data/{dataset_id}.

Example: create a connector, test it, and browse tables

import os
from decision_engine import AlgentaClient

client = AlgentaClient(api_key=os.environ["ALGENTA_API_KEY"])

connector = client.create_connector(
    name="Analytics Warehouse",
    connector_type="snowflake",
    config={
        "account": "xy12345.eu-central-1",
        "user": "ANALYTICS",
        "password": os.environ["SNOWFLAKE_PASSWORD"],
        "warehouse": "COMPUTE_WH",
        "database": "SALES",
        "schema": "PUBLIC",
    },
)

test = client.test_connector(connector.id)
assert test.success, test.message

browse = client.browse_connector(connector.id)
print(browse.total, "tables")

Example: onboard a dataset and read its summary

import os
from decision_engine import AlgentaClient

client = AlgentaClient(api_key=os.environ["ALGENTA_API_KEY"])

result = client.connect_data(
    connection_type="database",
    provider="snowflake",
    dataset_name="sales_orders",
    connection_id="$CONNECTOR_ID",
    selection={"table": "PUBLIC.ORDERS"},
    visibility="private",
)
print(result.status, result.dataset_id)

summary = client.get_dataset_summary(result.dataset_id)
print(summary.row_count)

# Browse the full catalog.
datasets = client.list_datasets(search="orders", compact=True)
for dataset in datasets.datasets:
    print(dataset.dataset_id, dataset.name)

Related pages

Connect a data sourceSnowflakeSimulations & queries