Quickstart: Create a chat room with Azure Functions and SignalR Service using Python
Azure SignalR Service lets you easily add real-time functionality to your application. Azure Functions is a serverless platform that lets you run your code without managing any infrastructure. In this quickstart, learn how to use SignalR Service and Functions to build a serverless, real-time chat application.
This quickstart can be run on macOS, Windows, or Linux.
Make sure you have a code editor such as Visual Studio Code installed.
Install the Azure Functions Core Tools (version 2.7.1505 or higher) to run Python Azure Function apps locally.
Azure Functions requires Python 3.6 or 3.7.
Log in to Azure
Sign in to the Azure portal at https://portal.azure.com/ with your Azure account.
Create an Azure SignalR Service instance
Your application will connect to a SignalR Service instance in Azure.
Select the New button found on the upper left-hand corner of the Azure portal. In the New screen, type SignalR Service in the search box and press enter.
Select SignalR Service from the search results, then select Create.
Enter the following settings.
Setting Suggested value Description Resource name Globally unique name Name that identifies your new SignalR Service instance. Valid characters are
Subscription Your subscription The subscription under which this new SignalR Service instance is created. Resource Group myResourceGroup Name for the new resource group in which to create your SignalR Service instance. Location West US Choose a region near you. Pricing tier Free Try Azure SignalR Service for free. Unit count Not applicable Unit count specifies how many connections your SignalR Service instance can accept. It is only configurable in the Standard tier. Service mode Serverless For use with Azure Functions or REST API.
Select Create to start deploying the SignalR Service instance.
After the instance is deployed, open it in the portal and locate its Settings page. Change the Service Mode setting to Serverless only if you are using Azure SignalR Service through Azure Functions binding or REST API. Leave it in Classic or Default otherwise.
Clone the sample application
While the service is deploying, let's switch to working with code. Clone the sample app from GitHub, set the SignalR Service connection string, and run the application locally.
Open a git terminal window. Change to a folder where you want to clone the sample project.
Run the following command to clone the sample repository. This command creates a copy of the sample app on your computer.
git clone https://github.com/Azure-Samples/signalr-service-quickstart-serverless-chat.git
Configure and run the Azure Function app
In the browser where the Azure portal is opened, confirm the SignalR Service instance you deployed earlier was successfully created by searching for its name in the search box at the top of the portal. Select the instance to open it.
Select Keys to view the connection strings for the SignalR Service instance.
Select and copy the primary connection string.
In your code editor, open the src/chat/python folder in the cloned repository.
To locally develop and test Python functions, you must work in a Python 3.6 or 3.7 environment. Run the following commands to create and activate a virtual environment named
Linux or macOS:
python3.7 -m venv .venv source .venv/bin/activate
py -3.7 -m venv .venv .venv\scripts\activate
Rename local.settings.sample.json to local.settings.json.
In local.settings.json, paste the connection string into the value of the AzureSignalRConnectionString setting. Save the file.
Python functions are organized into folders. In each folder are two files: function.json defines the bindings that are used in the function, and __init__.py is the body of the function. There are two HTTP triggered functions in this function app:
- negotiate - Uses the SignalRConnectionInfo input binding to generate and return valid connection information.
- messages - Receives a chat message in the request body and uses the SignalR output binding to broadcast the message to all connected client applications.
In the terminal with the virtual environment activated, ensure that you are in the src/chat/python folder. Install the necessary Python packages using PIP.
python -m pip install -r requirements.txt
Run the function app.
Run the web application
There is a sample single page web application hosted in GitHub for your convenience. Open your browser to https://azure-samples.github.io/signalr-service-quickstart-serverless-chat/demo/chat-v2/.
The source of the HTML file is located at /docs/demo/chat-v2/index.html.
When prompted for the function app base URL, enter
Enter a username when prompted.
The web application calls the GetSignalRInfo function in the function app to retrieve the connection information to connect to Azure SignalR Service. When the connection is complete, the chat message input box appears.
Type a message and press enter. The application sends the message to the SendMessage function in the Azure Function app, which then uses the SignalR output binding to broadcast the message to all connected clients. If everything is working correctly, the message should appear in the application.
Open another instance of the web application in a different browser window. You will see that any messages sent will appear in all instances of the application.
Because the HTML page is served using HTTPS, but the local Azure Functions runtime is using HTTP by default, your browser (such as Firefox) may enforce a mixed-content policy that blocks the requests from the web page to your functions. To solve this, use a browser that does not have this restriction or start a local HTTP server such as http-server in the /docs/demo/chat-v2 directory. Ensure the origin is added to the
CORS setting in local.settings.json.
Clean up resources
If you're not going to continue to use this app, delete all resources created by this quickstart with the following steps so you don't incur any charges:
In the Azure portal, select Resource groups on the far left, and then select the resource group you created. Alternatively, you may use the search box to find the resource group by its name.
In the window that opens, select the resource group, and then click Delete resource group.
In the new window, type the name of the resource group to delete, and then click Delete.
In this quickstart, you built and ran a real-time serverless application in VS Code. Next, learn more about how to deploy Azure Functions from VS Code.