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.
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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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.
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.
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:
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 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.
Application requests to Azure Blob Storage must be authorized. Using the DefaultAzureCredential class provided by the Azure Identity client library is the recommended approach for implementing passwordless connections to Azure services in your code, including Blob Storage.
You can also authorize requests to Azure Blob Storage by using the account access key. However, this approach should be used with caution. Developers must be diligent to never expose the access key in an unsecure location. Anyone who has the access key is able to authorize requests against the storage account, and effectively has access to all the data. DefaultAzureCredential offers improved management and security benefits over the account key to allow passwordless authentication. Both options are demonstrated in the following example.
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.
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.
When developing locally, make sure that the user account that is accessing blob data has the correct permissions. You'll need Storage Blob Data Contributor to read and write blob data. To assign yourself this role, you'll need to be assigned the User Access Administrator role, or another role that includes the Microsoft.Authorization/roleAssignments/write action. You can assign Azure RBAC roles to a user using the Azure portal, Azure CLI, or Azure PowerShell. You can learn more about the available scopes for role assignments on the scope overview page.
In this scenario, you'll assign permissions to your user account, scoped to the storage account, to follow the Principle of Least Privilege. This practice gives users only the minimum permissions needed and creates more secure production environments.
In most cases it will take a minute or two for the role assignment to propagate in Azure, but in rare cases it may take up to eight minutes. If you receive authentication errors when you first run your code, wait a few moments and try again.
To assign a role at the resource level using the Azure CLI, you first must retrieve the resource id using the az storage account show command. You can filter the output properties using the --query parameter.
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.
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.
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.
In the storage account menu pane, under Security + networking, select Access keys. Here, you can view the account access keys and the complete connection string for each key.
In the key1 section, locate the Connection string value. Select the Copy to clipboard icon to copy the connection string. You'll add the connection string value to an environment variable in the next section.
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 with your actual connection string.
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 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.
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.
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.
I've been able to create a storage account, then a container, than a blob storing a .csv file. I've successfully been able to download the .csv file from Azure itself and using Python as well via the azure-storage package. This is to confirm that external sources (i.e. Python) are able to import/export blobs. The .csv stores a numeric table with header in the first row.
This code will connect to your storage account, download the CSV file from the specified container and blob, and read the contents of the CSV file into a pandas DataFrame. You can then work with the data in the DataFrame as needed.
Now I have my Azure function (written in Python running) and I implement step 2 using Azure blob storage. See attached flow for example. Basically, in my Flow, it will create a blob (write the data to Azure blob) and send a http request to trigger my Azure Funtion which reads the Azure blob and do the processing there.
- get file content from Azure Blob: I am able to get the file content. However, it is in binary format. How should I parse this binary format and select certain columns (e.g., emails column in my processed data)
I would recommend to write another Azure function that accepts BLOB as parameter and returns required fields like email address. Then from Power Automate Flow, you can call this function and use the fields. This will be relatively simpler option than exploring ways to convert Blob to file and then read data from Power Automate.
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