Gain insights into building REST APIs with FastAPI, explore parallel processing in Python, and discover how to deploy APIs on Microsoft Azure with a CI/CD pipeline using GitHub.

Build a REST API Using Python and Deploy It to Microsoft Azure.png

fastapi-docker.tar.gz

FastAPI-test

Python3

In this course, you will learn how to build a REST API using a lighter web framework for Python, i.e., FastAPI. You will learn the basics of FastAPI and learn how to implement parallel processing in Python APIs.

Finally, you will deploy your API on Microsoft Azure and build a Continuous Integration/Continuous Development (CI/CD) Pipeline using Github.

Build a REST API Using Python and Deploy it to Microsoft Azure

# Create an application insights resource
Before moving to the core, let us first create the resource, and then use this resource to log some data from our *API*.

**Explanation**
* **Step 1:** Go to the [Azure Portal](https://portal.azure.com/), and search the *Application Insights* service. Click the one in the marketplace section to create a new service.

* **Step 2:** Fill in all the details to create the resource. Then, click on the "*Review + Create*" button.
* **Step 3:** If all the validations are passed, you will see a green tick. Then, click on the "*Create*" button.
* **Step 4:** Once your resource is deployed successfully, you can click on the "*Go to resource*" button.
* **Step 5:** You can view the dashboard of your deployed service now. You can see the *Instrumentation Key* on your dashboard. Copy it and save it somewhere as this will be the key required to connect to the *Application Insights* service.

# Install `opencensus-ext-azure` package
This is the package that will help us connect to our *Application Insights* resource and log some data to it. To install this, run the following command (*after activating your virtual environment*):
```
pip install opencensus-ext-azure
```
Once this is installed you can run the command below to update your `requirements.txt` file.
```
pip freeze > requirements.txt
```
> Remember to add the three packages required to deploy the `API` on *Azure App Services*.
> * `uvloop`
> * `httptools`
> * `gunicorn`

Your `requirements.txt` file should look something similar to the one shown below:

Learn and create an Azure application insights resource.

Overview of the Course

Building Blocks of an API in Python

Learn the Basics of FastAPI

Optical Character Recognition API Using Tesseract - Project 1

Cloud and Microsoft Azure Services

Text Analytics API Using Azure Cognitive Services - Project 2

Deploy the REST API on Microsoft Azure

Pop Quiz

Appendix

Create an Application Insights Resource

Create an application insights resource