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

## Implement logging in our *API*
We have already set up the *Application Insights* resource and installed the required package to connect to the service for logging the data. Now, let's make some changes in the code to do the logging operation. 

We will log three things:
* The text
* The sentiment of the overall text
* The key phrases from the overall text

Let us see the code now.

# Implement logging in our *API*
We have already set up the *Application Insights* resource and installed the required package to connect to the service for logging the data. Now, let's make some changes in the code to do the logging operation. 

We will log three things:
* The text
* The sentiment of the overall text
* The key phrases from the overall text

Let us see the code now.

Learn to perform logging using application insights  and Python.

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

Implement Logging in API Using Application Insights

Implement logging in our API