{"library":"apache-airflow-providers-apache-beam","type":"library","category":null,"description":"The `apache-airflow-providers-apache-beam` package provides operators and hooks to seamlessly integrate Apache Airflow with Apache Beam. Apache Beam is an open-source, unified model for defining both batch and streaming data-parallel processing pipelines. This provider enables Airflow users to define, schedule, and monitor Beam pipelines, which can then be executed by various Beam-supported backends such as Apache Flink, Apache Spark, or Google Cloud Dataflow. The provider follows a roughly 2-3 month minor release cadence, with patch releases issued on an as-needed basis.","language":"python","status":"active","version":"6.2.3","tags":["airflow","apache-beam","etl","data-processing","pipeline","gcp","dataflow"],"last_verified":"Sat May 23","install":[{"cmd":"pip install apache-airflow-providers-apache-beam","imports":["from airflow.providers.apache.beam.hooks.beam import ApacheBeamHook","from airflow.providers.apache.beam.operators.beam import BeamRunPythonPipelineOperator","from airflow.providers.apache.beam.operators.beam import BeamRunJavaPipelineOperator","from airflow.providers.apache.beam.operators.beam import BeamRunGoPipelineOperator"]},{"cmd":"pip install apache-airflow-providers-apache-beam[google]","imports":[]}],"homepage":null,"github":"https://github.com/apache/airflow","docs":"https://airflow.apache.org/docs/apache-airflow-providers-apache-beam/6.2.3","changelog":"https://airflow.apache.org/docs/apache-airflow-providers-apache-beam/6.2.3/changelog.html","pypi":"https://pypi.org/project/apache-airflow-providers-apache-beam/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":45.7,"avg_import_s":null,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/apache-airflow-providers-apache-beam/compatibility"}}