Configure your local environment for deploying Python web apps on Azure

This article walks you through setting up your local environment to develop Python web apps and deploy them to Azure. Your web app can be pure Python or use one of the common Python-based web frameworks like Django, Flask, or FastAPI.

Python web apps developed locally can be deployed to services such as Azure App Service, Azure Container Apps, or Azure Static Web Apps. There are many options for deployment. For example for App Service deployment, you can choose to deploy from code, a Docker container, or a Static Web App. If you deploy from code, you can deploy with Visual Studio Code, with the Azure CLI, from a local Git repository, or with GitHub actions. If you deploy in a Docker Container, you can do so from Azure Container Registry, Docker Hub, or any private registry.

Before continuing with this article, we suggest you review the Set up your dev environment for guidance on setting up your dev environment for Python and Azure. Below, we'll discuss setup and configuration specific to Python web app development.

After you get your local environment setup for Python web app development, you'll be ready to tackle these articles:

Working with Visual Studio Code

The Visual Studio Code integrated development environment (IDE) is an easy way to develop Python web apps and work with Azure resources that web apps use.


Make sure you have Python extension installed. For an overview of working with Python in VS Code, see Getting Started with Python in VS Code.

In VS code, you work with Azure resources through VS Code extensions. You can install extensions from the Extensions View or the key combination Ctrl+Shift+X. For Python web apps, you'll likely be working with one or more of the following extensions:

  • The Azure App Service extension enables you to interact with Azure App Service from within Visual Studio Code. App Service provides fully managed hosting for web applications including websites and web APIs.

  • The Azure Static Web Apps extension enables you to create Azure Static Web Apps directly from VS Code. Static Web Apps is serverless and a good choice for static content hosting.

  • If you plan on working with containers, then install:

    • The Docker extension to build and work with containers locally. For example, you can run a containerized Python web app on Azure App Service using Web Apps for Containers.

    • The Azure Container Apps extension to create and deploy containerized apps directly from Visual Studio Code.

  • There are other extensions such as the Azure Storage, Azure Databases, and Azure Resources extensions. You can always add these and other extensions as needed.

Extensions in Visual Studio Code are accessible as you would expect in a typical IDE interface and with rich keyword support using the VS Code command palette. To access the command palette, use the key combination Ctrl+Shift+P. The command palette is a good way to see all the possible actions you can take on an Azure resource. The screenshot below shows some of the actions for App Service.

A screenshot of the Visual Studio Code command palette for App Service.

Working with other IDEs

If you're working in another IDE that doesn't have explicit support for Azure, then you can use the Azure CLI to manage Azure resources. In the screenshot below, a simple Flask web app is open in the PyCharm IDE. The web app can be deployed to an Azure App Service using the az webapp up command. In the screenshot, the CLI command runs within the PyCharm embedded terminal emulator. If your IDE doesn't have an embedded emulator, your can use any terminal and the same command. The Azure CLI must be installed on your computer and be accessible in either case.

A screenshot of the PyCharm IDE with an Azure CLI command deploying a web app.

Azure CLI commands

When working locally with web apps using the Azure CLI commands, you'll typically work with the following commands:

Command Description
az webapp Manages web apps. Includes the subcommands create to create a web app and the up to create and deploy from a local workspace
az container app Manages Azure Container Apps.
az staticwebapp Manages Azure Static Web Apps.
az group Manages resource groups and template deployments. Use the subcommand create to a resource group to put your Azure resources in.
az appservice Manages App Service plans.
az config Managed Azure CLI configuration. To save keystrokes, you can define a default location or resource group that other commands use automatically.

Here's an example Azure CLI command to create a web app and associated resources, and deploy it to Azure in one command using az webapp up. Run the command in the root directory of your web app.

az webapp up \
    --runtime PYTHON:3.9 \
    --sku B1 \

For more about this example, see Quickstart: Deploy a Python (Django or Flask) web app to Azure App Service.

Keep in mind that for some of your Azure workflow you can also use the Azure CLI from an Azure Cloud Shell. Azure Cloud Shell is an interactive, authenticated, browser-accessible shell for managing Azure resources.

Azure SDK key packages

In your Python web apps, you can refer programmatically to Azure services using the Azure SDK for Python. This SDK is discussed extensively in the section Use the Azure libraries (SDK) for Python. In this section, we'll briefly mention some key packages of the SDK that you'll use in web development. And, we'll show an example around the best-practice for authenticating your code with Azure resources.

Below are some of the packages commonly used in web app development. You can install packages in your virtual environment directly with pip. Or put the Python package index (Pypi) name in your requirements.txt file.

SDK docs Install Python package index
Azure Identity pip install azure-identity azure-identity
Azure Storage Blobs pip install azure-storage-blob azure-storage-blob
Azure Cosmos DB pip install azure-cosmos azure-cosmos
Azure Key Vault Secrets pip install azure-keyvault-secrets azure-keyvault-secrets

The azure-identity package allows your web app to authenticate with Azure Active Directory (Azure AD). For authentication in your web app code, it's recommended that you use the DefaultAzureCredential in the azure-identity package. Here's an example of how to access Azure Storage. The pattern is similar for other Azure resources.

from azure.identity import DefaultAzureCredential
from import BlobServiceClient

azure_credential = DefaultAzureCredential()
blob_service_client = BlobServiceClient(

The DefaultAzureCredential will look in predefined locations for account information, for example, in environment variables, in the VS Code Account extension, or from the Azure CLI sign-in. For in-depth information on the DefaultAzureCredential logic, see Authenticate Python apps to Azure services by using the Azure SDK for Python.

Python-based web frameworks

In Python web app development, you often work with Python-based web frameworks. These frameworks provide functionality such page templates, session management, database access, and easy access to HTTP request and response objects. Frameworks enable you to avoid the need for you to have to reinvent the wheel for common functionality.

Three common Python web frameworks are Django, Flask, or FastAPI. These and other web frameworks can be used with Azure.

Below is an example of how you might get started quickly with these frameworks locally. Running these commands, you'll end up with an application, albeit a simple one that could be deployed to Azure. Run these commands inside a virtual environment.

Step 1: Download the frameworks with pip.

pip install Django

Step 2: Create a hello world app.

Create a sample project using the django-admin startproject command. The project includes a file that is the entry point for running the app.

django-admin startproject hello_world

Step 3: Run the code locally.

Django uses WSGI to run the app.

python hello_world\ runserver

Step 4: Browse the hello world app.

At this point, add a requirements.txt file and then you can deploy the web app to Azure or containerize it with Docker and then deploy it.

Next steps