Running a FastAPI App as an Azure Function

FastAPI is a modern, fast (high-performance), web framework for building APIs with Python 3.6+ based on standard Python type hints. Combining FastAPI with Azure Functions allows for scalable, serverless applications that can handle API requests efficiently. This blog will guide you through the process of setting up a FastAPI application as an Azure Function, covering usage, commands, and troubleshooting.

Prerequisites

Before you begin, ensure you have the following:

1. Python 3.6+ installed on your machine.
2. Azure CLI installed and configured.
3. VS Code with the Azure Functions extension installed.
4. Azure Functions Core Tools installed.

Step 1: Setting Up Your FastAPI Application

First, create a new directory for your project and navigate into it:

sh

mkdir fastapi-azure-function
cd fastapi-azure-function        

Next, create a virtual environment and activate it:

sh

python -m venv venv
source venv/bin/activate # On Windows, use `venv\Scripts\activate`        

Install FastAPI and Uvicorn (the ASGI server):

sh

pip install fastapi uvicorn        

Create a new file, “main.py”, and add the following FastAPI code:

python

from fastapi import FastAPI

app = FastAPI()

@app.get("/")
def read_root():
    return {"Hello": "World"}

@app.get("/items/{item_id}")
def read_item(item_id: int, q: str = None):
    return {"item_id": item_id, "q": q}        

Step 2: Creating an Azure Function Project

Initialize a new Azure Functions project in the same directory:

sh

func init . --python        

Add a new HTTP trigger function:

sh

func new --template "HTTP trigger" --name FastAPIFunction        

This command creates a new folder, “FastAPIFunction”, containing “__init__.py”?and function.json.

Step 3: Integrating FastAPI with Azure Functions

Replace the contents of “__init__.py”?with the following code:

sh

import logging
from fastapi import FastAPI
from fastapi.middleware.wsgi import WSGIMiddleware
import azure.functions as func

app = FastAPI()

@app.get("/")
def read_root():
    return {"Hello": "World"}

@app.get("/items/{item_id}")
def read_item(item_id: int, q: str = None):
    return {"item_id": item_id, "q": q}

def main(req: func.HttpRequest, context: func.Context) -> func.HttpResponse:
    return func.WsgiMiddleware(app.wsgi_app)(req, context)        

This code wraps the FastAPI application with WSGIMiddleware to handle HTTP requests through Azure Functions.

Step 4: Configuring Your Function

Edit “function.json” to match the following configuration:

sh

{
    "scriptFile": "__init__.py",
    "bindings": [
        {
            "authLevel": "function",
            "type": "httpTrigger",
            "direction": "in",
            "name": "req",
            "methods": ["get", "post"]
        },
        {
            "type": "http",
            "direction": "out",
            "name": "$return"
        }
    ]
}        

Step 5: Running Locally

To test your function locally, use the following command:

sh

func start        

You should see an output indicating the function host is running. Test the endpoints by navigating to https://localhost:7071/api/FastAPIFunction.

Step 6: Deploying to Azure

First, log in to your Azure account:

sh

az login        

Then, create a new function app in Azure:

sh

az functionapp create --resource-group <ResourceGroupName> --consumption-plan-location <Location> --runtime python --runtime-version 3.8 --functions-version 3 --name <FunctionAppName> --storage-account <StorageAccountName>        

Deploy your function app using the Azure CLI:

sh

func azure functionapp publish <FunctionAppName>        

Usage and Command Issues

Usage

Your FastAPI application is now running as an Azure Function. You can access it via the Azure Function URL, which can be found in the Azure portal under your function app's overview section.

Command Issues

1. Module Not Found Errors:?Ensure all dependencies are listed in requirements.txt. You can generate this file using:

sh

pip freeze > requirements.txt        

2. Azure CLI Login Issues:?If you encounter login issues, ensure that you have the correct permissions and that your Azure CLI is up to date.

3. Deployment Errors:?Ensure your resource group, storage account, and function app names are unique and correct.

Troubleshooting

Function Not Triggering

Ensure that your “function.json”?is correctly configured. Check the bindings and authorization levels.

Debugging Locally

Use the following command to start the Azure Function in debug mode:

sh

func host start --debug        

Logging and Monitoring

Azure Functions provide built-in logging. You can access logs in the Azure portal under the "Monitor" section of your function app. For more detailed logging, use the “logging”?module in Python:

python

import logging

logging.info("This is an info message")
logging.error("This is an error message")        

Performance Issues

If your FastAPI application experiences performance issues, consider the following:

• Increase Plan: Upgrade your Azure Function plan to a higher tier.
• Optimize Code: Profile and optimize your FastAPI application code.
• Caching: Implement caching mechanisms for frequently accessed data.

Conclusion

Deploying a FastAPI application as an Azure Function provides a scalable and efficient way to serve your API endpoints. By following the steps outlined in this guide, you can set up, configure, and deploy your application with ease. For any issues encountered during this process, the troubleshooting section provides solutions to common problems.

By leveraging the capabilities of Azure Functions and the performance of FastAPI, you can create robust and scalable applications. If you need further assistance or professional support, consider reaching out to Shiv Technolabs, a leading Python development company in Australia, specializing in serverless architecture and API development.

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