Source code for airflow.providers.google.cloud.utils.openlineage

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"""This module contains code related to OpenLineage and lineage extraction."""
from __future__ import annotations

from typing import TYPE_CHECKING, Any

from openlineage.client.facet import (
    ColumnLineageDatasetFacet,
    ColumnLineageDatasetFacetFieldsAdditional,
    ColumnLineageDatasetFacetFieldsAdditionalInputFields,
    DocumentationDatasetFacet,
    SchemaDatasetFacet,
    SchemaField,
)

if TYPE_CHECKING:
    from google.cloud.bigquery.table import Table
    from openlineage.client.run import Dataset


[docs]def get_facets_from_bq_table(table: Table) -> dict[Any, Any]: """Get facets from BigQuery table object.""" facets = { "schema": SchemaDatasetFacet( fields=[ SchemaField(name=field.name, type=field.field_type, description=field.description) for field in table.schema ] ), "documentation": DocumentationDatasetFacet(description=table.description or ""), } return facets
[docs]def get_identity_column_lineage_facet( field_names: list[str], input_datasets: list[Dataset], ) -> ColumnLineageDatasetFacet: """ Get column lineage facet. Simple lineage will be created, where each source column corresponds to single destination column in each input dataset and there are no transformations made. """ if field_names and not input_datasets: raise ValueError("When providing `field_names` You must provide at least one `input_dataset`.") column_lineage_facet = ColumnLineageDatasetFacet( fields={ field: ColumnLineageDatasetFacetFieldsAdditional( inputFields=[ ColumnLineageDatasetFacetFieldsAdditionalInputFields( namespace=dataset.namespace, name=dataset.name, field=field ) for dataset in input_datasets ], transformationType="IDENTITY", transformationDescription="identical", ) for field in field_names } ) return column_lineage_facet

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