![]() ![]() V1PodAffinity ( required_during_scheduling_ignored_during_execution = ), topology_key = ". V1NodeAffinity ( preferred_during_scheduling_ignored_during_execution = ) ] ), ) ] ), pod_affinity = k8s. V1Container ( name = "init-container", image = "ubuntu:16.04", env = init_environments, volume_mounts = init_container_volume_mounts, command =, args =, ) affinity = k8s. V1ContainerPort ( name = "http", container_port = 80 ) init_container_volume_mounts = init_environments = init_container = k8s. I have read that XCom is only made for sharing some metadata or flags between tasks and shouldnt be used for passing real data like for example a pandas dataframe. I know this is probably a very simple question but im kinda confused. V1PersistentVolumeClaimVolumeSource ( claim_name = "test-volume" ), ) port = k8s. Airflow - Handle XCOM inside a loop Ask Question Asked 2 years, 6 months ago Modified 2 years, 6 months ago Viewed 2k times 1 I have the following requirement. Airflow with Pandas Im new to Airflow, been studying for over a month now. ![]() V1Volume ( name = "test-volume", persistent_volume_claim = k8s. V1VolumeMount ( name = "test-volume", mount_path = "/root/mount_file", sub_path = None, read_only = True ) configmaps = volume = k8s. Secret_file = Secret ( "volume", "/etc/sql_conn", "airflow-secrets", "sql_alchemy_conn" ) secret_env = Secret ( "env", "SQL_CONN", "airflow-secrets", "sql_alchemy_conn" ) secret_all_keys = Secret ( "env", None, "airflow-secrets-2" ) volume_mount = k8s. Pushes an XCom without a specific target, just by returning it (pulledvalue2, tiNone) source Pull all previously pushed XComs and check if the pushed values match the pulled values.
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