datahub/metadata-ingestion/examples/library/lineage_job_dataflow_new_api.py

from datahub.api.entities.datajob import DataFlow, DataJob
from datahub.emitter.rest_emitter import DatahubRestEmitter

# Create an emitter to the GMS REST API.

emitter = DatahubRestEmitter("http://localhost:8080")

jobFlow = DataFlow(env="prod", orchestrator="airflow", id="flow_new_api")
jobFlow.emit(emitter)

dataJob = DataJob(flow_urn=jobFlow.urn, id="job1")
dataJob.emit(emitter)
feat(ingest): airflow - add support to capture airflow executions, add high level dataflow jobs api to python sdk (#4615) Co-authored-by: Gabe Lyons <itsgabelyons@gmail.com> 2022-04-13 08:19:39 +02:00			`from datahub.api.entities.datajob import DataFlow, DataJob`
			`from datahub.emitter.rest_emitter import DatahubRestEmitter`

			`# Create an emitter to the GMS REST API.`

			`emitter = DatahubRestEmitter("http://localhost:8080")`

fix(sdk/dataflow): deprecate cluster and use env and platform_instance instead (#8201) Co-authored-by: mohdsiddique <mohdsiddiquebagwan@gmail.com> Co-authored-by: Harshal Sheth <hsheth2@gmail.com> 2023-06-16 02:36:28 +05:30			`jobFlow = DataFlow(env="prod", orchestrator="airflow", id="flow_new_api")`
feat(ingest): airflow - add support to capture airflow executions, add high level dataflow jobs api to python sdk (#4615) Co-authored-by: Gabe Lyons <itsgabelyons@gmail.com> 2022-04-13 08:19:39 +02:00			`jobFlow.emit(emitter)`

			`dataJob = DataJob(flow_urn=jobFlow.urn, id="job1")`
			`dataJob.emit(emitter)`