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 value1
and key2
with a value of value2
.
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 by_page
function.
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