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5 min Azure Functions compute with powershell 3

Last updated on January 28, 2023

Jump to Most used commands and quick guide

Deployment technologies in Azure Functions

Deployment technologies in Azure Functions | Microsoft Learn

Create a Python function in Azure from the command line

Create a Python function from the command line – Azure Functions | Microsoft Learn

Check environment, after all prerequisites is installed.

Prerequisite check

Powershell is used for a code

# Check that the Azure Functions Core Tools version is 4.x.
func --version
# Verify version 5.0 or later
(Get-Module -ListAvailable Az).Version
# Sign in to Azure and verify an active subscription
Connect-AzAccount
# Check your Python version reports 3.9.x, 3.8.x, or 3.7.x.
python --version

Could create a env

Create a local function project

PS C:\giti2022not> mkdir azfunctionsrepo
PS C:\giti2022not> cd .\azfunctionsrepo\

PS C:\giti2022not\azfunctionsrepo> func init LocalFunctionQA --python
PS C:\giti2022not\azfunctionsrepo> cd .\LocalFunctionQA\

This folder contains various files for the project, including configuration files named local.settings.json and host.json. Because local.settings.json can contain secrets downloaded from Azure, the file is excluded from source control by default in the .gitignore file.

Add a function

Add a function to your project by using the following command, where the –name argument is the unique name of your function (HttpExample) and the –template argument specifies the function’s trigger (HTTP).

func new --name coinfun01qa --template "HTTP trigger" --authlevel "anonymous"

func new creates a subfolder matching the function name that contains a code file appropriate to the project’s chosen language and a configuration file named function.json.

Get the list of templates by using the following command:

func templates list -l python

init.py
init.py contains a main() Python function that’s triggered according to the configuration in function.json.

function.json
function.json is a configuration file that defines the input and output bindings for the function, including the trigger type.

If desired, you can change scriptFile to invoke a different Python file.

Run the function locally

func start

The powershell output has the URL and logs the requests.

http://localhost:7071/api/coinfun01qa

Visit the URL

Ctrl+c for quit

Change the init.py

Lets change the init.py so we can start coding.

import logging

import azure.functions as func

# clean template
def main(req: func.HttpRequest) -> func.HttpResponse:
    logging.info('Python HTTP trigger function processed a request.')
    clean_template = "Welcome to clean template"

    return func.HttpResponse(clean_template,mimetype="text/json", status_code=200)

run func start and visit the URL again.

Create supporting Azure resources for your function

Before you can deploy your function code to Azure, you need to create three resources:

  • A resource group, which is a logical container for related resources.
  • A storage account, which maintains the state and other information about your projects.
  • A function app, which provides the environment for executing your function code. A function app maps to your local function project and lets you group functions as a logical unit for easier management, deployment, and sharing of resources.

Create a rg named rg-wecoinfun01qa in we

Create a storage account named staccwecoinfun01qa in we, standard LRS

Create a function app named, coinfun01qa, code Python 3.9, we, Linux, consumption, in the rg we created above and with the sta we created above. Select yes to application insight new (coinfun01qa). Disable continuous deployment now.

Now we have the following in rg-wecoinfun01qa:

(Log analytics is outside, hm)

Deploy the function project to Azure

func azure functionapp publish coinfun01qa

Much output, local had higher Python version that 3.9, this is the essential

Now go to Azure and copy the URL and visit it.

https://coinfun01qa.azurewebsites.net/api/coinfun01qa

Verify in Azure or just look in metrics
Run the following command to view near real-time streaming logs in Application Insights in the Azure portal.

func azure functionapp logstream coinfun01qa --browser

Now we are done and can start to code more and deploy, remember to update requirements.txt if you add some libs with pip.

Import a new class

Deploy locally, then deploy to Azure.

To debug start

func start --verbose

logging default

logging.info etc will come in the Powershell output

Most used commands and quick guide

# New function after cd to dir
func new --name coinfun01qa --template "HTTP trigger" --authlevel "anonymous"

# Start
func start
# Ctrl+c for quit

# Debug
func start --verbose

Create resources in Powershell (then workspace and all will be in same rg)

New-AzResourceGroup -Name rg-wecoinfunc01qa -Location 'West Europe'

New-AzStorageAccount -ResourceGroupName rg-wecoinfun01qa -Name staccwecoinfun01qa -SkuName Standard_LRS -Location 'West Europe'

New-AzFunctionApp -Name coinfun01qa -ResourceGroupName rg-wecoinfun01qa -StorageAccountName staccwecoinfun01qa -FunctionsVersion 4 -RuntimeVersion 3.9 -Runtime python -Location 'West Europe'

# OS type is default linux

Edit the quota for fileshare

# Deploy after cd to location for coinfun01qa
func azure functionapp publish coinfun01qa

Stream logs

Stream execution logs in Azure Functions | Microsoft Learn

Do a request to URL, and view in Portal, stop and start and so on.

Publish without seeing changes? (Maybe good to test local first)

But view the log stream after visit the URL 1-3 times

Choose level

View the code in portal

We can vie the code and files in the portal but since it is published with VSC, we cannot edit, we do that locally and then deploy.

Bonus: Using managed identity

Quickstart: Azure Queue Storage client library for Python – Azure Storage | Microsoft Learn

Connect to a queue from the function using managed identity

Create the queue in the same st account

Then code

NOTE: Remember to update requirements.txt

from azure.identity import DefaultAzureCredential
from azure.storage.queue import QueueServiceClient, QueueClient, QueueMessage


class StorageQueue:

    def __init__(self):
        self.queue_client = None

    def connect_queue(self):
        try:
            logging.info("Azure Queue storage, trying to connect")
            # Quickstart code goes here
            account_url = "https://your-storage-account.queue.core.windows.net"
            default_credential = DefaultAzureCredential()
            self.queue_client = QueueClient(account_url, queue_name="your-queue-name" ,credential=default_credential)
            logging.info("Azure Queue storage, connection success")
        except Exception as ex:
            logging.error(ex)
        return self.queue_client

    def send_msg(self,message):
        self.connect_queue()
        try:
            self.queue_client.send_message(message)
            logging.info("Sent msg to Azure Queue storage")
        except Exception as ex:
            logging.error(ex)

Enable system assigned to the function.

On the st account, add the function app.

The Principle of Least Privilege states that a subject should be given only those privileges needed for it to complete its task

Visit ULR and the queue is updated with msg:

Logic app is timer

Add a HTTP logic app and run it every x hour

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