Searching for files using index tags is a common use case but the Azure documentation can be quite hard to grasp.
To search for blobs with specific tags in Azure Blob Storage using Python, you can use the
find_blobs_by_tags method from the Azure Storage SDK. It takes as a single parameter
filter_expression which can be used to query blobs with specific tags, container or name.
Here's an example of how to use
find_blobs_by_tags to search for blobs with specific tags
from azure.storage.blob import BlobServiceClient # Create a BlobServiceClient object blob_service_client = BlobServiceClient.from_connection_string("<your_connection_string>") # Get a reference to the container where your blobs are stored container_client = blob_service_client.get_container_client("<your_container_name>") # Use the find_blobs_by_tags method to search for blobs with a specific set of tags results = container_client.find_blobs_by_tags( "key1 = 'value1' and key2 = 'value2'" ) # Print the names of the blobs that were found for blob in results: print(blob["name"])
In this example, the
find_blobs_by_tags method is used to search for blobs that have the tags
key1 with a value of
key2 with a value of
find_blobs_by_tags returns a iterable response of
FilteredBlob objects. The return value is automatically paginated and you can control the number of
Blobs per page with the
results_per_page keyword argument. You can iterate the results by blob or by page using the iterator returned by the
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