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Example Airflow DAG that senses blob(s) in Azure Blob Storage.

This DAG relies on the following OS environment variables

* CONTAINER_NAME - The container under which to look for the blob.
* BLOB_NAME - The name of the blob to match.
* PREFIX - The blob with the specified prefix to match.

from __future__ import annotations

import os
from datetime import datetime

from airflow.models import DAG
from import WasbBlobSensor, WasbPrefixSensor

[docs]CONTAINER_NAME = os.environ.get("CONTAINER_NAME", "example-container-name")
[docs]BLOB_NAME = os.environ.get("BLOB_NAME", "example-blob-name")
[docs]PREFIX = os.environ.get("PREFIX", "example-prefix")
with DAG( "example_wasb_sensors", start_date=datetime(2022, 8, 8), catchup=False, tags=["example"], ) as dag: # [START wasb_blob_sensor]
[docs] azure_wasb_sensor = WasbBlobSensor( container_name=CONTAINER_NAME, blob_name=BLOB_NAME, task_id="wasb_sense_blob", )
# [END wasb_blob_sensor] # [START wasb_prefix_sensor] azure_wasb_prefix_sensor = WasbPrefixSensor( container_name=CONTAINER_NAME, prefix=PREFIX, task_id="wasb_sense_prefix", ) # [END wasb_prefix_sensor] from tests.system.utils import get_test_run # noqa: E402 # Needed to run the example DAG with pytest (see: tests/system/
[docs]test_run = get_test_run(dag)

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