Aveek Das
Deploy to Azure

Deploy Python apps to Azure Functions using Visual Studio Code

July 10, 2020 by

In this article, we are going to build a small python application and deploy it to Azure Functions. The development and the deployment will be done using the Visual Studio (VS) Code. As you might be aware, VS Code is one of the most widely used and preferred code editors for programmers. It is a cross-platform tool, which means you can install this tool on any operating system of your choice, starting from Windows, Linux, or Mac OS.

What makes the VS Code so unique and popular is that there are tons of custom extensions that are developed by the community. These extensions are leveraged and can be extended the default behavior of the code editor as you want.

Pre-requisites for app development

Assuming that this article is for a beginner, I will start by listing out all the possible pre-requisites that you need to have in order to deploy your code to Azure Functions from Visual Studio Code.

  • Python executable – First things first, since in this article, we are going to learn how to deploy python apps, we need to have the python executable installed in our system. You can head over to https://www.python.org/ and download Python for your operating system
  • Visual Studio Code – Yes, as we are going to use Visual Studio Code as the code editor and build our app using the same, you need to get this installed and running on your machine as well. Visual Studio Code is a cross-platform tool, and you can get it installed on any operating system. Download Visual Studio Code by visiting http://code.visualstudio.com/
  • Python Extension for Visual Studio Code – By default, when you install Visual Studio Code, you do not have the option to execute python files directly. You need to install an additional extension provided by Microsoft to support working with python files. Download this extension from the marketplace by visiting https://marketplace.visualstudio.com/items?itemName=ms-python.python
  • Azure Functions Extension for Visual Studio Code – In order to be able to deploy your code to Azure Functions, you need to install the extension as well. You can install the same by visiting https://marketplace.visualstudio.com/items?itemName=ms-azuretools.vscode-azurefunctions
  • Azure Functions Core Tools – In order to debug and run your functions locally, you need to set up Azure Functions Core Tools as well. You can follow how to install this tool from the official documentation
  • A valid Azure Account – You also need to have an Azure account up and running for this. Visit https://portal.azure.com to create your account

Once you are done with installing all the pre-requisites as mentioned above, you should be good to start with it. Now, the Visual Studio Code looks something like this.

Functions Icon Added in VS Code

Figure 1 – Azure Icon Added in VS Code

As you can see, an icon for using the Azure Services appears on the left-hand pane. Use this panel to sign-in to your Azure account to proceed forward.

Creating the project locally

Now that we are able to set up our environment for development let us go ahead and create a new project. Start by clicking on the New Project icon under Azure Functions in the panel and browse a directory to start with.

Create new project

Figure 2 – Create a new project

Once you have specified the folder for the project, the next step is to choose the programming language that you want to start with. For the sake of this tutorial, I am going to go ahead and choose Python.

Choosing the Language

Figure 3 – Choosing the Language

In the next step, you need to tell the Visual Studio Code, wherein the binary file for the Python. In this step, the VS Code will create a virtual environment for the project and run the python file inside it.

Selecting Python Interpreter

Figure 4 – Selecting Python Interpreter

In the next step, you will be prompted with a choice to select a template to begin with. Templates help you to do the heavy lifting in your application, and you just need to focus on your code. It is absolutely fine if you want to write your own code from scratch, but to keep things simpler and sweet, I am going to select the HTTP Trigger template.

Selecting the template

Figure 5 – Selecting the template

Now, we have selected our environment and also defined a template that we would like to use. The next step is to add a name to our function. Please note that your Azure Function on the Azure portal will also be created using this name.

Function Name

Figure 6 – Function Name

The penultimate step here is to select the authorization level for your Azure function. Although in a production application, there will be securities and authentication involved, for our tutorial, we will go with the Anonymous authentication.

Selecting Authentication Level

Figure 7 – Selecting Authentication Level

Once the app is created, you can see something like this on your screen.

Function created

Figure 8 – Function created

Debugging the function locally

Now that our function is ready, we can debug it locally to test if it is working as expected. To debug, click on the debug icon, and select Debug (Attach to Python Functions) or press F5 on your keyboard.

Debug the function locally

Figure 9 – Debug the function locally

As soon as you start debugging, you can see the terminal window is displayed, and the function is hosted locally on a URL. You can open this URL on a browser window. Click to open this URL on the browser.

URL for localhost

Figure 10 – URL for localhost

In the browser, you can see something like this.

Function response

Figure 11 – Function response

You can modify the URL and append “?name=aveek” at the end of the query to test if it is working fine.

Function response

Figure 12 – Function response

Now that the function is running as expected on our local, we can go ahead and deploy it on Azure Functions.

Deploying the function to Azure

To deploy your code to the Function App, click on the Deploy icon, as shown in the figure below.

Deploy to Azure

Figure 13 – Deploy to Azure

You will be prompted with the following two options. I am going to choose the first option with basic settings.

Creating the Function App

Figure 14 – Creating the Function App

In the following steps, provide a unique name of the Function App that you want and specify the version of Python. You might also need to provide the name of the region under which you would like the resources to be created in Azure. It might take some time to build up the resources on the cloud, and you can grab some coffee while the function is being deployed.

Function App Name

Figure 15 – Function App Name

You can see that the function has been deployed successfully and up for our use. Head over and click the URL that you can see and open it on the browser.

Function App Deployed

Figure 16 – Function App Deployed

As you might have guessed, the function is now deployed to Azure and works as expected.

Functions Work well

Figure 17 – Azure Functions Work well


In this article, we have seen how to develop python applications using Visual Studio Code locally. I have also explained how we can deploy the same applications to Azure Functions directly from VS Code editor. This is a great way to quickly deploy your app to the cloud without having to leave the code editor. You can easily build your apps locally and verify them. Once these apps are verified in local, you can quickly publish it to the cloud with the help of just a few clicks. This really helps to save a lot of time for the developers and help them focus on the code rather than deploying the changes.

Table of contents

Setting up Visual Studio Code for Python Development
How to debug Python scripts in Visual Studio Code
Deploy Python apps to Azure Functions using Visual Studio Code
Getting started with Amazon S3 and Python
Getting started with Pandas in Python
Working with Pandas Dataframes in Python
Exploring databases in Python using Pandas
Best practices to follow while programming in Python
Exporting data with Pandas in Python
Create REST APIs in Python using Flask
Working with JSON data in Python
Understanding *args and *kwargs arguments in Python

Aveek Das
Azure, Python, Visual Studio

About Aveek Das

Aveek is an experienced Data and Analytics Engineer, currently working in Dublin, Ireland. His main areas of technical interest include SQL Server, SSIS/ETL, SSAS, Python, Big Data tools like Apache Spark, Kafka, and cloud technologies such as AWS/Amazon and Azure. He is a prolific author, with over 100 articles published on various technical blogs, including his own blog, and a frequent contributor to different technical forums. In his leisure time, he enjoys amateur photography mostly street imagery and still life. Some glimpses of his work can be found on Instagram. You can also find him on LinkedIn View all posts by Aveek Das