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Tutorial: Python function with Azure Queue Storage as trigger

  • Άρθρο

In this tutorial, you learn how to configure a Python function with Storage Queue as trigger by completing the following tasks.

  • Use Visual Studio Code to create a Python function project.
  • Use Visual Studio Code to run the function locally.
  • Use the Azure CLI to create a connection between Azure Function and Storage Queue with Service Connector.
  • Use Visual Studio to deploy your function.

An overview of the function project components in this tutorial:

Project Component Selection / Solution
Source Service Azure Function
Target Service Azure Storage Queue
Function Binding Storage Queue as Trigger
Local Project Auth Type Connection String
Cloud Function Auth Type Connection String

Warning

Microsoft recommends that you use the most secure authentication flow available. The authentication flow described in this procedure requires a very high degree of trust in the application, and carries risks that are not present in other flows. You should only use this flow when other more secure flows, such as managed identities, aren't viable.

Prerequisites

Create a Python function project

Follow the tutorial to create a local Azure Functions project, and provide the following information at the prompts:

Prompt Selection
Select a language Choose Python. (v1 programming language model)
Select a Python interpreter to create a virtual environment Choose your preferred Python interpreter. If an option isn't shown, type in the full path to your Python binary.
Select a template for your project's first function Choose Azure Queue Storage trigger.
Provide a function name Enter QueueStorageTriggerFunc.
Select setting from "local.settings.json" Choose Create new local app settings, which lets you select your Storage Account and provide your queue name that works as the trigger.

You created a Python function project with Azure Storage Queue as trigger. The local project connects to Azure Storage using the connection string saved into the local.settings.json file. Finally, the main function in __init__.py file of the function can consume the connection string with the help of the Function Binding defined in the function.json file.

Run the function locally

Follow the tutorial to run the function locally and verify the trigger.

  1. Select the storage account as you chose when creating the Azure Function resource if you're prompted to connect to storage. This value is used for Azure Function's runtime, and it isn't necessarily the same as the storage account you use for the trigger.
  2. To start the function locally, press <kbd>F5 </kbd> or select the Run and Debug icon in the left-hand side Activity bar.
  3. To verify the trigger works properly, keep the function running locally and open the Storage Queue pane in Azure portal, select Add message and provide a test message. You should see the function is triggered and processed as a queue item in your Visual Studio Code terminal.

Create a connection using Service Connector

In last step, you verified the function project locally. Now you'll learn how to configure the connection between the Azure Function and Azure Storage Queue in the cloud, so that your function can be triggered by the storage queue after being deployed to the cloud.

  1. Open the function.json file in your local project, change the value of the connection property in bindings to be AZURE_STORAGEQUEUE_CONNECTIONSTRING.
  2. Run the following Azure CLI command to create a connection between your Azure Function and your Azure storage account.
az functionapp connection create storage-queue --source-id "<your-function-resource-id>" --target-id "<your-storage-queue-resource-id>" --secret
  • --source-id format: /subscriptions/{subscription}/resourceG roups/{source_resource_group}/providers/Microsoft.Web/sites/{site}
  • --target-id format: /subscriptions/{subscription}/resourceGroups/{target_resource_group}/providers/Microsoft.Storage/storageAccounts/{account}/queueServices/default

This step creates a Service Connector resource that configures an AZURE_STORAGEQUEUE_CONNECTIONSTRING variable in the function's App Settings. The function binding runtime uses it to connect to the storage, so that the function can accept triggers from the storage queue. For more information, go to how Service Connector helps Azure Functions connect to services.

Deploy your function to Azure

Now you can deploy your function to Azure and verify the storage queue trigger works.

  1. Follow this Azure Functions tutorial to deploy your function to Azure.
  2. Open the Storage Queue pane in the Azure portal, select Add message and provide a test message. You should see the function is triggered and processed as a queue item in your function logs.

Troubleshoot

If there are any errors related with the storage host, such as No such host is known (<acount-name>.queue.core.windows.net:443), check whether the connection string you use to connect to Azure Storage contains the queue endpoint or not. If it doesn't, go to Azure Storage in the Azure portal, copy the connection string from the Access keys pane, and replace the values.

If this error happens when you start the project locally, check the local.settings.json file.

If this error happens when you deploy your function to cloud (in this case, Function deployment usually fails on Syncing triggers ), check your Function's App Settings.

Clean up resources

If you're not going to continue to use this project, delete the Function App resource you created earlier.

  1. In the Azure portal, open the Function App resource and select Delete.
  2. Enter the app name and select Delete to confirm.

Next steps

Read the articles below to learn more about Service Connector concepts and how it helps Azure Functions connect to services.

Learn about Service Connector concepts

Use Service Connector to connect Azure Functions to other cloud services