title	titleSuffix	description	author	ms.author	ms.date	ms.topic	ms.service	ms.devlang	ms.custom	ai-usage	zone_pivot_groups
Quickstart: Azure Blob Storage client library for Python	Azure Storage	In this quickstart, you learn how to use the Azure Blob Storage client library for Python to create a container and a blob in Blob (object) storage. Next, you learn how to download the blob to your local computer, and how to list all of the blobs in a container.	pauljewellmsft	pauljewell	09/13/2024	quickstart	azure-blob-storage	python	devx-track-python, mode-api, passwordless-python, ai-video-demo, devx-track-extended-azdevcli	ai-assisted	azure-blob-storage-quickstart-options

Quickstart: Azure Blob Storage client library for Python

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Note

The Build from scratch option walks you step by step through the process of creating a new project, installing packages, writing the code, and running a basic console app. This approach is recommended if you want to understand all the details involved in creating an app that connects to Azure Blob Storage. If you prefer to automate deployment tasks and start with a completed project, choose Start with a template.

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Note

The Start with a template option uses the Azure Developer CLI to automate deployment tasks and starts you off with a completed project. This approach is recommended if you want to explore the code as quickly as possible without going through the setup tasks. If you prefer step by step instructions to build the app, choose Build from scratch.

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Get started with the Azure Blob Storage client library for Python to manage blobs and containers.

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In this article, you follow steps to install the package and try out example code for basic tasks.

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In this article, you use the Azure Developer CLI to deploy Azure resources and run a completed console app with just a few commands.

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API reference documentation | Library source code | Package (PyPi) | Samples

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This video shows you how to start using the Azure Blob Storage client library for Python.

[!VIDEO f663a554-96ca-4bc3-b3b1-48376a7efbdf]

The steps in the video are also described in the following sections.

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Prerequisites

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Azure account with an active subscription - create an account for free
Azure Storage account - create a storage account
Python 3.8+

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Azure subscription - create one for free
Python 3.8+
Azure Developer CLI

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Setting up

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This section walks you through preparing a project to work with the Azure Blob Storage client library for Python.

Create the project

Create a Python application named blob-quickstart.

In a console window (such as PowerShell or Bash), create a new directory for the project:
```
mkdir blob-quickstart
```
Switch to the newly created blob-quickstart directory:
```
cd blob-quickstart
```

Install the packages

From the project directory, install packages for the Azure Blob Storage and Azure Identity client libraries using the pip install command. The azure-identity package is needed for passwordless connections to Azure services.

pip install azure-storage-blob azure-identity

Set up the app framework

From the project directory, follow steps to create the basic structure of the app:

Open a new text file in your code editor.
Add import statements, create the structure for the program, and include basic exception handling, as shown below.
Save the new file as blob_quickstart.py in the blob-quickstart directory.

:::code language="python" source="~/azure-storage-snippets/blobs/quickstarts/python/app-framework-qs.py":::

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With Azure Developer CLI installed, you can create a storage account and run the sample code with just a few commands. You can run the project in your local development environment, or in a DevContainer.

Initialize the Azure Developer CLI template and deploy resources

From an empty directory, follow these steps to initialize the azd template, provision Azure resources, and get started with the code:

Clone the quickstart repository assets from GitHub and initialize the template locally:
```
azd init --template blob-storage-quickstart-python
```
You'll be prompted for the following information:
- Environment name: This value is used as a prefix for all Azure resources created by Azure Developer CLI. The name must be unique across all Azure subscriptions and must be between 3 and 24 characters long. The name can contain numbers and lowercase letters only.
Log in to Azure:
```
azd auth login
```
Provision and deploy the resources to Azure:
```
azd up
```
You'll be prompted for the following information:
- Subscription: The Azure subscription that your resources are deployed to.
- Location: The Azure region where your resources are deployed.
The deployment might take a few minutes to complete. The output from the azd up command includes the name of the newly created storage account, which you'll need later to run the code.

Run the sample code

At this point, the resources are deployed to Azure and the code is almost ready to run. Follow these steps to install packages, update the name of the storage account in the code, and run the sample console app:

Install packages: In the local directory, install packages for the Azure Blob Storage and Azure Identity client libraries using the following command: pip install azure-storage-blob azure-identity
Update the storage account name: In the local directory, edit the file named blob_quickstart.py. Find the <storage-account-name> placeholder and replace it with the actual name of the storage account created by the azd up command. Save the changes.
Run the project: Execute the following command to run the app: python blob_quickstart.py.
Observe the output: This app creates a test file in your local data folder and uploads it to a container in the storage account. The example then lists the blobs in the container and downloads the file with a new name so that you can compare the old and new files.

To learn more about how the sample code works, see Code examples.

When you're finished testing the code, see the Clean up resources section to delete the resources created by the azd up command.

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Object model

Azure Blob Storage is optimized for storing massive amounts of unstructured data. Unstructured data is data that doesn't adhere to a particular data model or definition, such as text or binary data. Blob storage offers three types of resources:

The storage account
A container in the storage account
A blob in the container

The following diagram shows the relationship between these resources:

Use the following Python classes to interact with these resources:

BlobServiceClient: The BlobServiceClient class allows you to manipulate Azure Storage resources and blob containers.
ContainerClient: The ContainerClient class allows you to manipulate Azure Storage containers and their blobs.
BlobClient: The BlobClient class allows you to manipulate Azure Storage blobs.

Code examples

These example code snippets show you how to do the following tasks with the Azure Blob Storage client library for Python:

Authenticate to Azure and authorize access to blob data
Create a container
Upload blobs to a container
List the blobs in a container
Download blobs
Delete a container

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Note

The Azure Developer CLI template includes a file with sample code already in place. The following examples provide detail for each part of the sample code. The template implements the recommended passwordless authentication method, as described in the Authenticate to Azure section. The connection string method is shown as an alternative, but isn't used in the template and isn't recommended for production code.

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Authenticate to Azure and authorize access to blob data

[!INCLUDE storage-quickstart-passwordless-auth-intro]

Passwordless (Recommended)

DefaultAzureCredential supports multiple authentication methods and determines which method should be used at runtime. This approach enables your app to use different authentication methods in different environments (local vs. production) without implementing environment-specific code.

The order and locations in which DefaultAzureCredential looks for credentials can be found in the Azure Identity library overview.

For example, your app can authenticate using your Azure CLI sign-in credentials with when developing locally. Your app can then use a managed identity once it has been deployed to Azure. No code changes are required for this transition.

Assign roles to your Microsoft Entra user account

[!INCLUDE assign-roles]

Sign in and connect your app code to Azure using DefaultAzureCredential

You can authorize access to data in your storage account using the following steps:

Make sure you're authenticated with the same Microsoft Entra account you assigned the role to on your storage account. You can authenticate via the Azure CLI, Visual Studio Code, or Azure PowerShell.

Azure CLI

Sign-in to Azure through the Azure CLI using the following command:
```
az login
```
Visual Studio Code

You'll need to install the Azure CLI to work with DefaultAzureCredential through Visual Studio Code.

On the main menu of Visual Studio Code, navigate to Terminal > New Terminal.

Sign-in to Azure through the Azure CLI using the following command:
```
az login
```
PowerShell

Sign-in to Azure using PowerShell via the following command:
```
Connect-AzAccount
```
To use DefaultAzureCredential, make sure that the azure-identity package is installed, and the class is imported:
```
from azure.identity import DefaultAzureCredential
from azure.storage.blob import BlobServiceClient
```
Add this code inside the try block. When the code runs on your local workstation, DefaultAzureCredential uses the developer credentials of the prioritized tool you're logged into to authenticate to Azure. Examples of these tools include Azure CLI or Visual Studio Code.

:::code language="python" source="~/azure-storage-snippets/blobs/quickstarts/python/blob-quickstart.py" id="Snippet_CreateServiceClientDAC":::
Make sure to update the storage account name in the URI of your BlobServiceClient object. The storage account name can be found on the overview page of the Azure portal.

:::image type="content" source="./media/storage-quickstart-blobs-python/storage-account-name.png" alt-text="A screenshot showing how to find the storage account name.":::

[!NOTE] When deployed to Azure, this same code can be used to authorize requests to Azure Storage from an application running in Azure. However, you'll need to enable managed identity on your app in Azure. Then configure your storage account to allow that managed identity to connect. For detailed instructions on configuring this connection between Azure services, see the Auth from Azure-hosted apps tutorial.

Connection String

A connection string includes the storage account access key and uses it to authorize requests. Always be careful to never expose the keys in an unsecure location.

Note

To authorize data access with the storage account access key, you'll need permissions for the following Azure RBAC action: Microsoft.Storage/storageAccounts/listkeys/action. The least privileged built-in role with permissions for this action is Reader and Data Access, but any role which includes this action will work.

[!INCLUDE retrieve credentials]

Configure your storage connection string

After you copy the connection string, write it to a new environment variable on the local machine running the application. To set the environment variable, open a console window, and follow the instructions for your operating system. Replace <yourconnectionstring> with your actual connection string.

Windows:

setx AZURE_STORAGE_CONNECTION_STRING "<yourconnectionstring>"

After you add the environment variable in Windows, you must start a new instance of the command window.

Linux:

export AZURE_STORAGE_CONNECTION_STRING="<yourconnectionstring>"

The code below retrieves the connection string for the storage account from the environment variable created earlier, and uses the connection string to construct a service client object.

Add this code inside the try block:

# Retrieve the connection string for use with the application. The storage
# connection string is stored in an environment variable on the machine
# running the application called AZURE_STORAGE_CONNECTION_STRING. If the environment variable is
# created after the application is launched in a console or with Visual Studio,
# the shell or application needs to be closed and reloaded to take the
# environment variable into account.
connect_str = os.getenv('AZURE_STORAGE_CONNECTION_STRING')

# Create the BlobServiceClient object
blob_service_client = BlobServiceClient.from_connection_string(connect_str)

Important

The account access key should be used with caution. If your account access key is lost or accidentally placed in an insecure location, your service may become vulnerable. Anyone who has the access key is able to authorize requests against the storage account, and effectively has access to all the data. DefaultAzureCredential provides enhanced security features and benefits and is the recommended approach for managing authorization to Azure services.

Create a container

Create a new container in your storage account by calling the create_container method on the blob_service_client object. In this example, the code appends a GUID value to the container name to ensure that it's unique.

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Add this code to the end of the try block:

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:::code language="python" source="~/azure-storage-snippets/blobs/quickstarts/python/blob-quickstart.py" id="Snippet_CreateContainer":::

To learn more about creating a container, and to explore more code samples, see Create a blob container with Python.

Important

Container names must be lowercase. For more information about naming containers and blobs, see Naming and Referencing Containers, Blobs, and Metadata.

Upload blobs to a container

Upload a blob to a container using upload_blob. The example code creates a text file in the local data directory to upload to the container.

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Add this code to the end of the try block:

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:::code language="python" source="~/azure-storage-snippets/blobs/quickstarts/python/blob-quickstart.py" id="Snippet_UploadBlobs":::

To learn more about uploading blobs, and to explore more code samples, see Upload a blob with Python.

List the blobs in a container

List the blobs in the container by calling the list_blobs method. In this case, only one blob has been added to the container, so the listing operation returns just that one blob.

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Add this code to the end of the try block:

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:::code language="python" source="~/azure-storage-snippets/blobs/quickstarts/python/blob-quickstart.py" id="Snippet_ListBlobs":::

To learn more about listing blobs, and to explore more code samples, see List blobs with Python.

Download blobs

Download the previously created blob by calling the download_blob method. The example code adds a suffix of "DOWNLOAD" to the file name so that you can see both files in local file system.

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Add this code to the end of the try block:

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:::code language="python" source="~/azure-storage-snippets/blobs/quickstarts/python/blob-quickstart.py" id="Snippet_DownloadBlobs":::

To learn more about downloading blobs, and to explore more code samples, see Download a blob with Python.

Delete a container

The following code cleans up the resources the app created by removing the entire container using the delete_container method. You can also delete the local files, if you like.

The app pauses for user input by calling input() before it deletes the blob, container, and local files. Verify that the resources were created correctly before they're deleted.

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Add this code to the end of the try block:

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:::code language="python" source="~/azure-storage-snippets/blobs/quickstarts/python/blob-quickstart.py" id="Snippet_CleanUp":::

To learn more about deleting a container, and to explore more code samples, see Delete and restore a blob container with Python.

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Run the code

This app creates a test file in your local folder and uploads it to Azure Blob Storage. The example then lists the blobs in the container, and downloads the file with a new name. You can compare the old and new files.

Navigate to the directory containing the blob_quickstart.py file, then execute the following python command to run the app:

python blob_quickstart.py

The output of the app is similar to the following example (UUID values omitted for readability):

Azure Blob Storage Python quickstart sample

Uploading to Azure Storage as blob:
        quickstartUUID.txt

Listing blobs...
        quickstartUUID.txt

Downloading blob to
        ./data/quickstartUUIDDOWNLOAD.txt

Press the Enter key to begin clean up

Deleting blob container...
Deleting the local source and downloaded files...
Done

Before you begin the cleanup process, check your data folder for the two files. You can compare them and observe that they're identical.

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Clean up resources

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After you've verified the files and finished testing, press the Enter key to delete the test files along with the container you created in the storage account. You can also use Azure CLI to delete resources.

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When you're done with the quickstart, you can clean up the resources you created by running the following command:

azd down

You'll be prompted to confirm the deletion of the resources. Enter y to confirm.

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Next step

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storage-quickstart-blobs-python.md

storage-quickstart-blobs-python.md

Quickstart: Azure Blob Storage client library for Python

Prerequisites

Setting up

Create the project

Install the packages

Set up the app framework

Initialize the Azure Developer CLI template and deploy resources

Run the sample code

Object model

Code examples

Authenticate to Azure and authorize access to blob data

Passwordless (Recommended)

Assign roles to your Microsoft Entra user account

Sign in and connect your app code to Azure using DefaultAzureCredential

Azure CLI

Visual Studio Code

PowerShell

Connection String

Configure your storage connection string

Create a container

Upload blobs to a container

List the blobs in a container

Download blobs

Delete a container

Run the code

Clean up resources

Next step

Files

storage-quickstart-blobs-python.md

Latest commit

History

storage-quickstart-blobs-python.md

File metadata and controls

Quickstart: Azure Blob Storage client library for Python

Prerequisites

Setting up

Create the project

Install the packages

Set up the app framework

Initialize the Azure Developer CLI template and deploy resources

Run the sample code

Object model

Code examples

Authenticate to Azure and authorize access to blob data

Passwordless (Recommended)

Assign roles to your Microsoft Entra user account

Sign in and connect your app code to Azure using DefaultAzureCredential

Azure CLI

Visual Studio Code

PowerShell

Connection String

Configure your storage connection string

Create a container

Upload blobs to a container

List the blobs in a container

Download blobs

Delete a container

Run the code

Clean up resources

Next step