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Key Features
Allows customizing artifact names from the SDK in one of two ways.
# Method 1: Use the decorator@op(outputs=['sklearn model', 'churn predictions'])deftrain_and_predict_churn(features):
# ...returnmodel, predictions# Method 2: Use .set_name()@opdeftrain_model(features):
# ...returnmodel# ...model=train_model(features)
model.set_name('churn model')
Enhancements
Allows providing filepath to ServiceAccount key file when connecting to BigQuery from Aqueduct SDK.
Improves form validation when connecting Databricks integration.
Throughout the SDK, enables references to workflows using workflow name in addition to workflow ID.
Puts upper bounds on Python package dependencies to prevent unexpected regressions (e.g., recent issues caused by SQLAlchemy 2.0).
Bugfixes
Fixes bug where errors were not being properly handled when an operator had multiple outputs. This was occurring because the return value didn't have the expected length.