Dynamically interact with the data lineage graph for your organization.
pip install grai-graph
You can now run deeper exploration and counterfactuals using the python library. First import the library, including graph, analysis and visualizations.
from grai_graph import graph, analysis, visualizations
You can now run several counterfactual analyses from the graph library. These allow you to see the downstream impact of changes before they impact your dashboards and jobs.
For instance maybe we wanted to find out all of the data which would be impacted by deleting the id column on the lineage_node table.
affected_nodes = analysis.test_delete_node(namespace='default', name='public.lineage_node.id') for node in affected_nodes: print(node.spec.name)
Or to test changing the data type from uuid to int.
nodes = analysis.test_type_change(namespace='default', name='public.lineage_node.id', new_type='int') for node in nodes: print(node.spec.name)
You can also determine what nodes are downstream from a particular node:
downstream_nodes = analysis.downstream_nodes(namespace='default', name='public.lineage_node.id') for node in downstream_nodes: print(node.spec.name)