azurefunctionblobevent

Azure Function Blob Storage event Python example

This folder contains a Python application example that handles Functions on Microsoft Azure.

It handles an Azure Function that responds to a Blob Storage event (trigger) when a blob appears in a blob storage.

Requirements

• You must have a Microsoft Azure subscription.

• To develop functions app with Python, you must have the following installed:

  • Python 3
  • Azure CLI
  • Azure Functions Core Tools Version 3.x

• The code was written for:

  • Python 3

• Azure Functions Core Tools Version 3.x

  Azure Functions Core Tools lets you develop and test your functions on your local computer from the command prompt or terminal. Your local functions can connect to live Azure services, and you can debug your functions on your local computer using the full Functions runtime. You can even deploy a function app to your Azure subscription.

  Version 3.x/2.x: Supports either version 3.x or 2.x of the Azure Functions runtime. These versions support Windows, macOS, and Linux and use platform-specific package managers or npm for installation.

  Azure Functions Core Tools currently depends on either the Azure CLI or Azure PowerShell for authenticating with your Azure account. This means that you must install one of these tools to be able to publish to Azure from Azure Functions Core Tools.

  Version 3.x/2.x of the tools uses the Azure Functions runtime that is built on .NET Core. This version is supported on all platforms .NET Core supports, including Windows, macOS, and Linux.

  Install version 3.x of the Core Tools on your local computer:

  • For Windows:

    1. Download and run the Core Tools installer, based on your version of Windows:

       • v3.x - Windows 64-bit (Recommended. Visual Studio Code debugging requires 64-bit.)
       • v3.x - Windows 32-bit

    2. If you don't plan to use extension bundles, install the .NET Core 3.x SDK for Windows.

  • For MacOS:

    1. Install Homebrew, if it's not already installed.

    2. Install the Core Tools package:

       brew tap azure/functions
       brew install azure-functions-core-tools@3
       # if upgrading on a machine that has 2.x installed
       brew link --overwrite azure-functions-core-tools@3

    3. If you don't plan to use extension bundles, install the .NET Core 3.x SDK for macOS.

Using the code

• Create the Azure Funtion project and the Azure Function (Boilerplate code).

  This step is only necessary when you want to create an Azure Function from scratch.

  The Azure Functions Core Tools help you to create the boilerplate code for the Azure Funtion project and the Azure Function:

  • Create an Azure Functions project.

    In the terminal window or from a command prompt, navigate to an empty folder for your project, and run the following command:

    func init azurefunctionblobevent

    In version 3.x/2.x, when you run the command you must choose a runtime for your project.

    Select python

    Then, the project is created with these files:

    • host.json - JSON configuration file for the Function App.
    • local.settings.json - It stores app settings, connection strings, and settings used by local development tools. Settings in the local.settings.json file are used only when you are running projects locally.
    • requirements.txt - File with python dependencies.

    Because local.settings.json can contain secrets downloaded from Azure, the file is excluded from source control by default in the .gitignore file.

  • Create the Azure Function.

    In the terminal window or from a command prompt, move to the folder for your project, and run the following command:

    func new

    Select Azure Blob Storage trigger

    Select the name BlobTrigger.

    Then, the function BlobTrigger is created successfully from the Blob trigger template.

    The BlobTrigger folder content is:

    • __init__.py - Code of the function.
    • function.json - Configuration of the function.

• Create a Storage Account for the input source.

  You must create the Storage Account, using the Azure console. The storage account must be a StorageV2 (general purpose v2) account kind. Create a blob container with the samples-workitems name in this Storage Account.

• Create the Function App.

  1. You must create a Storage Account for the Function App, using the Azure console.

  2. You must create the Function App. You can create it in two ways:

     • Using the Azure console.

     • Using the Azure CLI tool:

       You create the Azure Function App by executing the command:

       az functionapp create --functions-version 3 --resource-group <RESOURCE_GROUP> --os-type Linux --consumption-plan-location westeurope --runtime python --name <FUNCTION_APP> --storage-account <STORAGE_ACCOUNT>

       In the previous command, replace with the proper:

       • <RESOURCE_GROUP> - Resource group name.
       • <FUNCTION_APP> - Function App name.
       • <STORAGE_ACCOUNT>- Storage Account name.

• Configure the Azure Function.

  1. You must configurate the function.json file:

     • Defining the connection with a variable MY_STORAGE_IN for the in binding:

       "connection": "MY_STORAGE_IN"

     The name variable, in the function.json file, will hold the name of the file found in the blob container, while myblob variable will hold the actual contents of the file.

  2. You must configure the connection string for trigger in the local.settings.json file when running locally.

     You must define the MY_STORAGE_IN variable in the local.settings.json file:

     "MY_STORAGE_IN": "DefaultEndpointsProtocol=https;AccountName=<STORAGE_ACCOUNT_IN>;AccountKey=<ACCOUNT_KEY_IN>;EndpointSuffix=core.windows.net",

     Replace with the proper:

     • <STORAGE_ACCOUNT_IN> - Storage Account name for input source.
     • <ACCOUNT_KEY_IN> - Account Key of the Storage Account for input source.

     You must define the AzureWebJobsStorage variable in the local.settings.json file:

     "AzureWebJobsStorage": "DefaultEndpointsProtocol=https;AccountName=<STORAGE_ACCOUNT_NAME>;AccountKey=<STORAGE_ACCOUNT_KEY>;EndpointSuffix=core.windows.net",

     Replace with the proper:

     • <STORAGE_ACCOUNT_NAME> - Name of the Storage Account.
     • <STORAGE_ACCOUNT_KEY> - Key of the Storage Account.

• Run your function project locally.

  You can run your function locally.

  Enter the following command to run your function app:

  func start

  The runtime will waiting for a blob event (trigger).

  Upload a file to the blob storage container in the storage account.

  You should see the next message in the log:

  Python blob trigger function processed blob
  Blob Name: samples-workitems/<FILE_NAME>
  Blob Size: <XX> bytes

  To stop debugging, use Ctrl-C in the terminal.

• Deploy the Azure Function to Azure.

  The deploy process to Azure Functions uses account credentials from the Azure CLI. Log in with the Azure CLI before continuing.

  az login

  To publish your local code to a function app in Azure, use the publish command:

  func azure functionapp publish <FUNCTION_APP>

  When the deploy is complete, you see the URL that you can use to access your Azure Function App:

  Deployment successful.
  Remote build succeeded!
  Syncing triggers...
  Functions in <FUNCTION_APP>:
      BlobTrigger - [blobTrigger]

• Configure the connection string for trigger Blob in the Function App.

  You must configure the connection strings or secrets for trigger, input map to values in the application settings for the Function App when running in Azure.

  You can make that in two ways:

  • Using the Azure console.

    Go to your Function App.

    Select: Settings > Configuration > Application settings

    Set the setting MY_STORAGE_IN name to: DefaultEndpointsProtocol=https;AccountName=<STORAGE_ACCOUNT_IN>;AccountKey=<ACCOUNT_KEY_IN>;EndpointSuffix=core.windows.net

  • Using the Azure CLI

    az functionapp config appsettings set --name MyFunctionApp --resource-group MyResourceGroup --settings "MY_STORAGE_IN=DefaultEndpointsProtocol=https;AccountName=<STORAGE_ACCOUNT_IN>;AccountKey=<ACCOUNT_KEY_IN>;EndpointSuffix=core.windows.net"

  In both cases, replace with the proper:

  • <STORAGE_ACCOUNT_IN>- Storage Account name for input source.
  • <ACCOUNT_KEY_IN> - Account Key of the Storage Account for input source.

• Test the function.

  Upload a file to the source blob storage container in the storage account.

  You should see the next message in the log:

  Python blob trigger function processed blob
  Blob Name: samples-workitems/<FILE_NAME>
  Blob Size: <XX> bytes