Azure Blob storage is Microsoft's object storage solution for the cloud. Blob storage is optimized for storing massive amounts of unstructured data, such as text or binary data.
Blob storage is ideal for:
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Getting started PrerequisitesInstall the Azure Storage Blobs client library for Python with pip:
pip install azure-storage-blob
If you wish to create a new storage account, you can use the Azure Portal, Azure PowerShell, or Azure CLI:
# Create a new resource group to hold the storage account -
# if using an existing resource group, skip this step
az group create --name my-resource-group --location westus2
# Create the storage account
az storage account create -n my-storage-account-name -g my-resource-group
The Azure Storage Blobs client library for Python allows you to interact with three types of resources: the storage account itself, blob storage containers, and blobs. Interaction with these resources starts with an instance of a client. To create a client object, you will need the storage account's blob service account URL and a credential that allows you to access the storage account:
from azure.storage.blob import BlobServiceClient
service = BlobServiceClient(account_url="https://<my-storage-account-name>.blob.core.windows.net/", credential=credential)
You can find the storage account's blob service URL using the Azure Portal, Azure PowerShell, or Azure CLI:
# Get the blob service account url for the storage account
az storage account show -n my-storage-account-name -g my-resource-group --query "primaryEndpoints.blob"
The credential parameter may be provided in a number of different forms, depending on the type of authorization you wish to use:
To use an Azure Active Directory (AAD) token credential, provide an instance of the desired credential type obtained from the azure-identity library. For example, DefaultAzureCredential can be used to authenticate the client.
This requires some initial setup:
Use the returned token credential to authenticate the client:
from azure.identity import DefaultAzureCredential
from azure.storage.blob import BlobServiceClient
token_credential = DefaultAzureCredential()
blob_service_client = BlobServiceClient(
account_url="https://<my_account_name>.blob.core.windows.net",
credential=token_credential
)
To use a shared access signature (SAS) token, provide the token as a string. If your account URL includes the SAS token, omit the credential parameter. You can generate a SAS token from the Azure Portal under "Shared access signature" or use one of the generate_sas() functions to create a sas token for the storage account, container, or blob:
from datetime import datetime, timedelta
from azure.storage.blob import BlobServiceClient, generate_account_sas, ResourceTypes, AccountSasPermissions
sas_token = generate_account_sas(
account_name="<storage-account-name>",
account_key="<account-access-key>",
resource_types=ResourceTypes(service=True),
permission=AccountSasPermissions(read=True),
expiry=datetime.utcnow() + timedelta(hours=1)
)
blob_service_client = BlobServiceClient(account_url="https://<my_account_name>.blob.core.windows.net", credential=sas_token)
To use a storage account shared key (aka account key or access key), provide the key as a string. This can be found in the Azure Portal under the "Access Keys" section or by running the following Azure CLI command:
az storage account keys list -g MyResourceGroup -n MyStorageAccount
Use the key as the credential parameter to authenticate the client:
from azure.storage.blob import BlobServiceClient
service = BlobServiceClient(account_url="https://<my_account_name>.blob.core.windows.net", credential="<account_access_key>")
If you are using customized url (which means the url is not in this format <my_account_name>.blob.core.windows.net), please instantiate the client using the credential below:
from azure.storage.blob import BlobServiceClient
service = BlobServiceClient(account_url="https://<my_account_name>.blob.core.windows.net",
credential={"account_name": "<your_account_name>", "account_key":"<account_access_key>"})
To use anonymous public read access, simply omit the credential parameter.
Depending on your use case and authorization method, you may prefer to initialize a client instance with a storage connection string instead of providing the account URL and credential separately. To do this, pass the storage connection string to the client's from_connection_string class method:
from azure.storage.blob import BlobServiceClient
connection_string = "DefaultEndpointsProtocol=https;AccountName=xxxx;AccountKey=xxxx;EndpointSuffix=core.windows.net"
service = BlobServiceClient.from_connection_string(conn_str=connection_string)
The connection string to your storage account can be found in the Azure Portal under the "Access Keys" section or by running the following CLI command:
az storage account show-connection-string -g MyResourceGroup -n MyStorageAccount
The following components make up the Azure Blob Service:
The Azure Storage Blobs client library for Python allows you to interact with each of these components through the use of a dedicated client object.
ClientsFour different clients are provided to interact with the various components of the Blob Service:
get_container_client or get_blob_client methods.get_blob_client method.ContainerClient or BlobClient. It provides operations to acquire, renew, release, change, and break a lease on a specified resource.This library includes a complete async API supported on Python 3.5+. To use it, you must first install an async transport, such as aiohttp. See azure-core documentation for more information.
Async clients and credentials should be closed when they're no longer needed. These objects are async context managers and define async close methods.
Once you've initialized a Client, you can choose from the different types of blobs:
The following sections provide several code snippets covering some of the most common Storage Blob tasks, including:
Note that a container must be created before to upload or download a blob.
Create a containerCreate a container from where you can upload or download blobs.
from azure.storage.blob import ContainerClient
container_client = ContainerClient.from_connection_string(conn_str="<connection_string>", container_name="mycontainer")
container_client.create_container()
Use the async client to create a container
from azure.storage.blob.aio import ContainerClient
container_client = ContainerClient.from_connection_string(conn_str="<connection_string>", container_name="mycontainer")
await container_client.create_container()
Upload a blob to your container
from azure.storage.blob import BlobClient
blob = BlobClient.from_connection_string(conn_str="<connection_string>", container_name="mycontainer", blob_name="my_blob")
with open("./SampleSource.txt", "rb") as data:
blob.upload_blob(data)
Use the async client to upload a blob
from azure.storage.blob.aio import BlobClient
blob = BlobClient.from_connection_string(conn_str="<connection_string>", container_name="mycontainer", blob_name="my_blob")
with open("./SampleSource.txt", "rb") as data:
await blob.upload_blob(data)
Download a blob from your container
from azure.storage.blob import BlobClient
blob = BlobClient.from_connection_string(conn_str="<connection_string>", container_name="mycontainer", blob_name="my_blob")
with open("./BlockDestination.txt", "wb") as my_blob:
blob_data = blob.download_blob()
blob_data.readinto(my_blob)
Download a blob asynchronously
from azure.storage.blob.aio import BlobClient
blob = BlobClient.from_connection_string(conn_str="<connection_string>", container_name="mycontainer", blob_name="my_blob")
with open("./BlockDestination.txt", "wb") as my_blob:
stream = await blob.download_blob()
data = await stream.readall()
my_blob.write(data)
List the blobs in your container
from azure.storage.blob import ContainerClient
container = ContainerClient.from_connection_string(conn_str="<connection_string>", container_name="mycontainer")
blob_list = container.list_blobs()
for blob in blob_list:
print(blob.name + '\n')
List the blobs asynchronously
from azure.storage.blob.aio import ContainerClient
container = ContainerClient.from_connection_string(conn_str="<connection_string>", container_name="mycontainer")
blob_list = []
async for blob in container.list_blobs():
blob_list.append(blob)
print(blob_list)
Optional keyword arguments that can be passed in at the client and per-operation level.
Retry Policy configurationUse the following keyword arguments when instantiating a client to configure the retry policy:
retry_total=0 if you do not want to retry on requests. Defaults to 10.False.Use the following keyword arguments when instantiating a client to configure encryption:
'2.0' or '1.0' and the default value is '1.0'. Version 1.0 is deprecated, and it is highly recommended to use version 2.0.wrap_key(key)--wraps the specified key using an algorithm of the user's choice.get_key_wrap_algorithm()--returns the algorithm used to wrap the specified symmetric key.get_kid()--returns a string key id for this key-encryption-key.Other optional configuration keyword arguments that can be specified on the client or per-operation.
Client keyword arguments:
Per-operation keyword arguments:
headers={'CustomValue': value}Storage Blob clients raise exceptions defined in Azure Core.
This list can be used for reference to catch thrown exceptions. To get the specific error code of the exception, use the error_code attribute, i.e, exception.error_code.
This library uses the standard logging library for logging. Basic information about HTTP sessions (URLs, headers, etc.) is logged at INFO level.
Detailed DEBUG level logging, including request/response bodies and unredacted headers, can be enabled on a client with the logging_enable argument:
import sys
import logging
from azure.storage.blob import BlobServiceClient
# Create a logger for the 'azure.storage.blob' SDK
logger = logging.getLogger('azure.storage.blob')
logger.setLevel(logging.DEBUG)
# Configure a console output
handler = logging.StreamHandler(stream=sys.stdout)
logger.addHandler(handler)
# This client will log detailed information about its HTTP sessions, at DEBUG level
service_client = BlobServiceClient.from_connection_string("your_connection_string", logging_enable=True)
Similarly, logging_enable can enable detailed logging for a single operation, even when it isn't enabled for the client:
service_client.get_service_stats(logging_enable=True)
Get started with our Blob samples.
Several Storage Blobs Python SDK samples are available to you in the SDK's GitHub repository. These samples provide example code for additional scenarios commonly encountered while working with Storage Blobs:
blob_samples_container_access_policy.py (async version) - Examples to set Access policies:
blob_samples_hello_world.py (async version) - Examples for common Storage Blob tasks:
blob_samples_authentication.py (async version) - Examples for authenticating and creating the client:
blob_samples_service.py (async version) - Examples for interacting with the blob service:
blob_samples_containers.py (async version) - Examples for interacting with containers:
blob_samples_common.py (async version) - Examples common to all types of blobs:
blob_samples_directory_interface.py - Examples for interfacing with Blob storage as if it were a directory on a filesystem:
For more extensive documentation on Azure Blob storage, see the Azure Blob storage documentation on learn.microsoft.com.
ContributingThis project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.
When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
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