Learn how to build a REST API with Python.

Become a Flask Developer

In this module, 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.

Building REST API with Python

## What are background tasks?
Often when you get a request from a client, you do not want your API to process that data completely, else you will have to send a confirmation as soon as you receive a request and process that data or operation in the background. In other words, these are useful for operations that need to happen after a request, but the client doesn't need to wait for the operation to get completed before receiving the response.
For example:
* **Email notifications sent after performing some action:** Connecting to an email server and then sending an email could be a slow (several seconds) process. We can return the response right away and send the email notification in the background.

* **Processing data:** Let's say you receive a file that must go through a file-processing operation. you can return the Accepted (`HTTP 202`) response and process the operation in the background.

You can easily implement this background processing in `FastAPI`. Let us see how we can achieve this.

## Implementing background tasks in `FastAPI`
You can define background tasks to be run after returning a response(kind-of confirmation).

Let us see the code now.

# What are background tasks?
Often when you get a request from a client, you do not want your API to process that data completely, else you will have to send a confirmation as soon as you receive a request and process that data or operation in the background. In other words, these are useful for operations that need to happen after a request, but the client doesn't need to wait for the operation to get completed before receiving the response.
For example:
* **Email notifications sent after performing some action:** Connecting to an email server and then sending an email could be a slow (several seconds) process. We can return the response right away and send the email notification in the background.

* **Processing data:** Let's say you receive a file that must go through a file-processing operation. you can return the Accepted (`HTTP 202`) response and process the operation in the background.

You can easily implement this background processing in `FastAPI`. Let us see how we can achieve this.

# Implementing background tasks in `FastAPI`
You can define background tasks to be run after returning a response(kind-of confirmation).

Let us see the code now.

Learn how to run background tasks and send an immediate response to the client using FastAPI.

Before We Begin

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

Conclusion

Appendix

Implement Background Tasks in FastAPI

What are background tasks?