Connect Azure Functions to Azure Storage using command line tools

Before you begin, you must complete the article, Quickstart: Create an Azure Functions project from the command line. If you already cleaned up resources at the end of that article, go through the steps again to recreate the function app and related resources in Azure.

Before you begin, you must complete the article, Quickstart: Create an Azure Functions project from the command line. If you already cleaned up resources at the end of that article, go through the steps again to recreate the function app and related resources in Azure.

Before you begin, you must complete the article, Quickstart: Create an Azure Functions project from the command line. If you already cleaned up resources at the end of that article, go through the steps again to recreate the function app and related resources in Azure.

Before you begin, you must complete the article, Quickstart: Create an Azure Functions project from the command line. If you already cleaned up resources at the end of that article, go through the steps again to recreate the function app and related resources in Azure.

Before you begin, you must complete the article, Quickstart: Create an Azure Functions project from the command line. If you already cleaned up resources at the end of that article, go through the steps again to recreate the function app and related resources in Azure.

Before you begin, you must complete the article, Quickstart: Create an Azure Functions project from the command line. If you already cleaned up resources at the end of that article, go through the steps again to recreate the function app and related resources in Azure.

Register binding extensions

Except for HTTP and timer triggers, bindings are implemented as extension packages. Run the following dotnet add package command in the Terminal window to add the Storage extension package to your project.

dotnet add package Microsoft.Azure.Functions.Worker.Extensions.Storage.Queues --prerelease

dotnet add package Microsoft.Azure.WebJobs.Extensions.Storage 

Now, you can add the storage output binding to your project.

Add an output binding definition to the function

Although a function can have only one trigger, it can have multiple input and output bindings, which lets you connect to other Azure services and resources without writing custom integration code.

When using the Node.js v4 programming model, binding attributes are defined directly in the ./src/functions/HttpExample.js file. From the previous quickstart, your file already contains an HTTP binding defined by the app.http method.

const { app } = require('@azure/functions');

app.http('httpTrigger', {
  methods: ['GET', 'POST'],
  authLevel: 'anonymous',
  handler: async (request, context) => {
    try {
      context.log(`Http function processed request for url "${request.url}"`);

      const name = request.query.get('name') || (await request.text());
      context.log(`Name: ${name}`);

      if (!name) {
        return { status: 404, body: 'Not Found' };
      }

      return { body: `Hello, ${name}!` };
    } catch (error) {
      context.log(`Error: ${error}`);
      return { status: 500, body: 'Internal Server Error' };
    }
  },
});

When using the Node.js v4 programming model, binding attributes are defined directly in the ./src/functions/HttpExample.js file. From the previous quickstart, your file already contains an HTTP binding defined by the app.http method.

import {
  app,
  HttpRequest,
  HttpResponseInit,
  InvocationContext,
} from '@azure/functions';

export async function httpTrigger1(
  request: HttpRequest,
  context: InvocationContext,
): Promise<HttpResponseInit> {
  context.log(`Http function processed request for url "${request.url}"`);

  const name = request.query.get('name') || (await request.text()) || 'world';

  return { body: `Hello, ${name}!` };
}

app.http('httpTrigger1', {
  methods: ['GET', 'POST'],
  authLevel: 'anonymous',
  handler: httpTrigger1,
});

You declare these bindings in the function.json file in your function folder. From the previous quickstart, your function.json file in the HttpExample folder contains two bindings in the bindings collection:

When using the Python v2 programming model, binding attributes are defined directly in the function_app.py file as decorators. From the previous quickstart, your function_app.py file already contains one decorator-based binding:

import azure.functions as func
import logging

app = func.FunctionApp()

@app.function_name(name="HttpTrigger1")
@app.route(route="hello", auth_level=func.AuthLevel.ANONYMOUS)

The route decorator adds HttpTrigger and HttpOutput binding to the function, which enables your function be triggered when http requests hit the specified route.

To write to an Azure Storage queue from this function, add the queue_output decorator to your function code:

@app.queue_output(arg_name="msg", queue_name="outqueue", connection="AzureWebJobsStorage")

In the decorator, arg_name identifies the binding parameter referenced in your code, queue_name is name of the queue that the binding writes to, and connection is the name of an application setting that contains the connection string for the Storage account. In quickstarts you use the same storage account as the function app, which is in the AzureWebJobsStorage setting (from local.settings.json file). When the queue_name doesn't exist, the binding creates it on first use.

"bindings": [
  {
    "authLevel": "function",
    "type": "httpTrigger",
    "direction": "in",
    "name": "Request",
    "methods": [
      "get",
      "post"
    ]
  },
  {
    "type": "http",
    "direction": "out",
    "name": "Response"
  }
]

To write to an Azure Storage queue:

• Add an extraOutputs property to the binding configuration

  {
      methods: ['GET', 'POST'],
      extraOutputs: [sendToQueue], // add output binding to HTTP trigger
      authLevel: 'anonymous',
      handler: () => {}
  }
  

• Add a output.storageQueue function above the app.http call

  const sendToQueue: StorageQueueOutput = output.storageQueue({
    queueName: 'outqueue',
    connection: 'AzureWebJobsStorage',
  });
  

The second binding in the collection is named res. This http binding is an output binding (out) that is used to write the HTTP response.

To write to an Azure Storage queue from this function, add an out binding of type queue with the name msg, as shown in the code below:

    {
      "authLevel": "function",
      "type": "httpTrigger",
      "direction": "in",
      "name": "Request",
      "methods": [
        "get",
        "post"
      ]
    },
    {
      "type": "http",
      "direction": "out",
      "name": "Response"
    },
    {
      "type": "queue",
      "direction": "out",
      "name": "msg",
      "queueName": "outqueue",
      "connection": "AzureWebJobsStorage"
    }
  ]
}

For a queue type, you must specify the name of the queue in queueName and provide the name of the Azure Storage connection (from local.settings.json file) in connection.

In a C# project, the bindings are defined as binding attributes on the function method. Specific definitions depend on whether your app runs in-process (C# class library) or in an isolated worker process.

public class MultiResponse
{
    [QueueOutput("outqueue",Connection = "AzureWebJobsStorage")]
    public string[] Messages { get; set; }
    public HttpResponseData HttpResponse { get; set; }
}

[Queue("outqueue"),StorageAccount("AzureWebJobsStorage")] ICollector<string> msg,

[FunctionName("HttpExample")]
public static async Task<IActionResult> Run(
    [HttpTrigger(AuthorizationLevel.Anonymous, "get", "post", Route = null)] HttpRequest req, 
    [Queue("outqueue"),StorageAccount("AzureWebJobsStorage")] ICollector<string> msg, 
    ILogger log)

In a Java project, the bindings are defined as binding annotations on the function method. The function.json file is then autogenerated based on these annotations.

Browse to the location of your function code under src/main/java, open the Function.java project file, and add the following parameter to the run method definition:

@QueueOutput(name = "msg", queueName = "outqueue", connection = "AzureWebJobsStorage") OutputBinding<String> msg

The msg parameter is an OutputBinding<T> type, which represents a collection of strings. These strings are written as messages to an output binding when the function completes. In this case, the output is a storage queue named outqueue. The connection string for the Storage account is set by the connection method. You pass the application setting that contains the Storage account connection string, rather than passing the connection string itself.

The run method definition must now look like the following example:

@FunctionName("HttpTrigger-Java")
public HttpResponseMessage run(
        @HttpTrigger(name = "req", methods = {HttpMethod.GET, HttpMethod.POST}, authLevel = AuthorizationLevel.FUNCTION)  
        HttpRequestMessage<Optional<String>> request, 
        @QueueOutput(name = "msg", queueName = "outqueue", connection = "AzureWebJobsStorage") 
        OutputBinding<String> msg, final ExecutionContext context) {
    ...
}

Update HttpExample\function_app.py to match the following code, add the msg parameter to the function definition and msg.set(name) under the if name: statement:

import azure.functions as func
import logging

app = func.FunctionApp(http_auth_level=func.AuthLevel.ANONYMOUS)

@app.route(route="HttpExample")
@app.queue_output(arg_name="msg", queue_name="outqueue", connection="AzureWebJobsStorage")
def HttpExample(req: func.HttpRequest, msg: func.Out [func.QueueMessage]) -> func.HttpResponse:
    logging.info('Python HTTP trigger function processed a request.')

    name = req.params.get('name')
    if not name:
        try:
            req_body = req.get_json()
        except ValueError:
            pass
        else:
            name = req_body.get('name')

    if name:
        msg.set(name)
        return func.HttpResponse(f"Hello, {name}. This HTTP triggered function executed successfully.")
    else:
        return func.HttpResponse(
             "This HTTP triggered function executed successfully. Pass a name in the query string or in the request body for a personalized response.",
             status_code=200
        )

The msg parameter is an instance of the azure.functions.Out class. The set method writes a string message to the queue. In this case, it's the name passed to the function in the URL query string.

Add code that uses the output binding object on context.extraOutputs to create a queue message. Add this code before the return statement.

context.extraOutputs.set(sendToQueue, [msg]);

At this point, your function could look as follows:

const { app, output } = require('@azure/functions');

const sendToQueue = output.storageQueue({
  queueName: 'outqueue',
  connection: 'AzureWebJobsStorage',
});

app.http('HttpExample', {
  methods: ['GET', 'POST'],
  authLevel: 'anonymous',
  extraOutputs: [sendToQueue],
  handler: async (request, context) => {
    try {
      context.log(`Http function processed request for url "${request.url}"`);

      const name = request.query.get('name') || (await request.text());
      context.log(`Name: ${name}`);

      if (name) {
        const msg = `Name passed to the function ${name}`;
        context.extraOutputs.set(sendToQueue, [msg]);
        return { body: msg };
      } else {
        context.log('Missing required data');
        return { status: 404, body: 'Missing required data' };
      }
    } catch (error) {
      context.log(`Error: ${error}`);
      return { status: 500, body: 'Internal Server Error' };
    }
  },
});

Add code that uses the output binding object on context.extraOutputs to create a queue message. Add this code before the return statement.

context.extraOutputs.set(sendToQueue, [msg]);

At this point, your function could look as follows:

import {
  app,
  output,
  HttpRequest,
  HttpResponseInit,
  InvocationContext,
  StorageQueueOutput,
} from '@azure/functions';

const sendToQueue: StorageQueueOutput = output.storageQueue({
  queueName: 'outqueue',
  connection: 'AzureWebJobsStorage',
});

export async function HttpExample(
  request: HttpRequest,
  context: InvocationContext,
): Promise<HttpResponseInit> {
  try {
    context.log(`Http function processed request for url "${request.url}"`);

    const name = request.query.get('name') || (await request.text());
    context.log(`Name: ${name}`);

    if (name) {
      const msg = `Name passed to the function ${name}`;
      context.extraOutputs.set(sendToQueue, [msg]);
      return { body: msg };
    } else {
      context.log('Missing required data');
      return { status: 404, body: 'Missing required data' };
    }
  } catch (error) {
    context.log(`Error: ${error}`);
    return { status: 500, body: 'Internal Server Error' };
  }
}

app.http('HttpExample', {
  methods: ['GET', 'POST'],
  authLevel: 'anonymous',
  handler: HttpExample,
});

Add code that uses the Push-OutputBinding cmdlet to write text to the queue using the msg output binding. Add this code before you set the OK status in the if statement.

$outputMsg = $name
Push-OutputBinding -name msg -Value $outputMsg

At this point, your function must look as follows:

using namespace System.Net

# Input bindings are passed in via param block.
param($Request, $TriggerMetadata)

# Write to the Azure Functions log stream.
Write-Host "PowerShell HTTP trigger function processed a request."

# Interact with query parameters or the body of the request.
$name = $Request.Query.Name
if (-not $name) {
    $name = $Request.Body.Name
}

if ($name) {
    # Write the $name value to the queue, 
    # which is the name passed to the function.
    $outputMsg = $name
    Push-OutputBinding -name msg -Value $outputMsg

    $status = [HttpStatusCode]::OK
    $body = "Hello $name"
}
else {
    $status = [HttpStatusCode]::BadRequest
    $body = "Please pass a name on the query string or in the request body."
}

# Associate values to output bindings by calling 'Push-OutputBinding'.
Push-OutputBinding -Name Response -Value ([HttpResponseContext]@{
    StatusCode = $status
    Body = $body
})

Now, you can use the new msg parameter to write to the output binding from your function code. Add the following line of code before the success response to add the value of name to the msg output binding.

msg.setValue(name);

When you use an output binding, you don't have to use the Azure Storage SDK code for authentication, getting a queue reference, or writing data. The Functions runtime and queue output binding do those tasks for you.

Your run method must now look like the following example:

public HttpResponseMessage run(
        @HttpTrigger(name = "req", methods = {HttpMethod.GET, HttpMethod.POST}, authLevel = AuthorizationLevel.ANONYMOUS) 
        HttpRequestMessage<Optional<String>> request, 
        @QueueOutput(name = "msg", queueName = "outqueue", 
        connection = "AzureWebJobsStorage") OutputBinding<String> msg, 
        final ExecutionContext context) {
    context.getLogger().info("Java HTTP trigger processed a request.");

    // Parse query parameter
    String query = request.getQueryParameters().get("name");
    String name = request.getBody().orElse(query);

    if (name == null) {
        return request.createResponseBuilder(HttpStatus.BAD_REQUEST)
        .body("Please pass a name on the query string or in the request body").build();
    } else {
        // Write the name to the message queue. 
        msg.setValue(name);

        return request.createResponseBuilder(HttpStatus.OK).body("Hello, " + name).build();
    }
}

Update the tests

Because the archetype also creates a set of tests, you need to update these tests to handle the new msg parameter in the run method signature.

Browse to the location of your test code under src/test/java, open the Function.java project file, and replace the line of code under //Invoke with the following code:

@SuppressWarnings("unchecked")
final OutputBinding<String> msg = (OutputBinding<String>)mock(OutputBinding.class);
final HttpResponseMessage ret = new Function().run(req, msg, context);

In the LocalFunctionsProj folder, use the func azure functionapp publish command to redeploy the project, replacing<APP_NAME> with the name of your app.

func azure functionapp publish <APP_NAME>

In the local project folder, use the following Maven command to republish your project:

mvn azure-functions:deploy

• Examples of complete Function projects in C#.

• Azure Functions C# developer reference

• Examples of complete Function projects in JavaScript.

• Azure Functions JavaScript developer guide

• Examples of complete Function projects in TypeScript.

• Azure Functions TypeScript developer guide

• Examples of complete Function projects in Python.

• Azure Functions Python developer guide

• Examples of complete Function projects in PowerShell.

• Azure Functions PowerShell developer guide