Azure Blob Storage SDK for Python

Client library for Azure Blob Storage — object storage for unstructured data.

Installation

pip install azure-storage-blob azure-identity

Environment Variables

AZURE_STORAGE_ACCOUNT_NAME=<your-storage-account>

Or use full URL

AZURE_STORAGE_ACCOUNT_URL=https://<account>.blob.core.windows.net

Authentication

from azure.identity import DefaultAzureCredential from azure.storage.blob import BlobServiceClient

credential = DefaultAzureCredential() account_url = "https://<account>.blob.core.windows.net"

blob_service_client = BlobServiceClient(account_url, credential=credential)

Client Hierarchy

Client Purpose Get From

BlobServiceClient

Account-level operations Direct instantiation

ContainerClient

Container operations blob_service_client.get_container_client()

BlobClient

Single blob operations container_client.get_blob_client()

Core Workflow

Create Container

container_client = blob_service_client.get_container_client("mycontainer") container_client.create_container()

Upload Blob

From file path

blob_client = blob_service_client.get_blob_client( container="mycontainer", blob="sample.txt" )

with open("./local-file.txt", "rb") as data: blob_client.upload_blob(data, overwrite=True)

From bytes/string

blob_client.upload_blob(b"Hello, World!", overwrite=True)

From stream

import io stream = io.BytesIO(b"Stream content") blob_client.upload_blob(stream, overwrite=True)

Download Blob

blob_client = blob_service_client.get_blob_client( container="mycontainer", blob="sample.txt" )

To file

with open("./downloaded.txt", "wb") as file: download_stream = blob_client.download_blob() file.write(download_stream.readall())

To memory

download_stream = blob_client.download_blob() content = download_stream.readall() # bytes

Read into existing buffer

stream = io.BytesIO() num_bytes = blob_client.download_blob().readinto(stream)

List Blobs

container_client = blob_service_client.get_container_client("mycontainer")

List all blobs

for blob in container_client.list_blobs(): print(f"{blob.name} - {blob.size} bytes")

List with prefix (folder-like)

for blob in container_client.list_blobs(name_starts_with="logs/"): print(blob.name)

Walk blob hierarchy (virtual directories)

for item in container_client.walk_blobs(delimiter="/"): if item.get("prefix"): print(f"Directory: {item['prefix']}") else: print(f"Blob: {item.name}")

Delete Blob

blob_client.delete_blob()

Delete with snapshots

blob_client.delete_blob(delete_snapshots="include")

Performance Tuning

Configure chunk sizes for large uploads/downloads

blob_client = BlobClient( account_url=account_url, container_name="mycontainer", blob_name="large-file.zip", credential=credential, max_block_size=4 * 1024 * 1024, # 4 MiB blocks max_single_put_size=64 * 1024 * 1024 # 64 MiB single upload limit )

Parallel upload

blob_client.upload_blob(data, max_concurrency=4)

Parallel download

download_stream = blob_client.download_blob(max_concurrency=4)

SAS Tokens

from datetime import datetime, timedelta, timezone from azure.storage.blob import generate_blob_sas, BlobSasPermissions

sas_token = generate_blob_sas( account_name="<account>", container_name="mycontainer", blob_name="sample.txt", account_key="<account-key>", # Or use user delegation key permission=BlobSasPermissions(read=True), expiry=datetime.now(timezone.utc) + timedelta(hours=1) )

Use SAS token

blob_url = f"https://<account>.blob.core.windows.net/mycontainer/sample.txt?{sas_token}"

Blob Properties and Metadata

Get properties

properties = blob_client.get_blob_properties() print(f"Size: {properties.size}") print(f"Content-Type: {properties.content_settings.content_type}") print(f"Last modified: {properties.last_modified}")

Set metadata

blob_client.set_blob_metadata(metadata={"category": "logs", "year": "2024"})

Set content type

from azure.storage.blob import ContentSettings blob_client.set_http_headers( content_settings=ContentSettings(content_type="application/json") )

Async Client

from azure.identity.aio import DefaultAzureCredential from azure.storage.blob.aio import BlobServiceClient

async def upload_async(): credential = DefaultAzureCredential()

async with BlobServiceClient(account_url, credential=credential) as client:
    blob_client = client.get_blob_client("mycontainer", "sample.txt")
    
    with open("./file.txt", "rb") as data:
        await blob_client.upload_blob(data, overwrite=True)

Download async

async def download_async(): async with BlobServiceClient(account_url, credential=credential) as client: blob_client = client.get_blob_client("mycontainer", "sample.txt")

    stream = await blob_client.download_blob()
    data = await stream.readall()

Best Practices

• Use DefaultAzureCredential instead of connection strings

• Use context managers for async clients

• Set overwrite=True explicitly when re-uploading

• Use max_concurrency for large file transfers

• Prefer readinto() over readall() for memory efficiency

• Use walk_blobs() for hierarchical listing

• Set appropriate content types for web-served blobs