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 the `requirements.txt` file
We have created successfully the `API` in the previous chapter. Now is the time to push it on GitHub. We are doing this because we will be connecting this repository to *Azure App Services* for CI/CD. 

Before doing that, we need to take one important step. We need to create a `requirements.txt` file that will contain the dependencies required to run our `API`. Follow the steps below to create the file:
* Activate your virtual environment.

* Go to your project folder.
* Run the command shown below:
   ```
   pip freeze > requirements.txt
    ```
* It will create a `requirements.txt` file in your current directory. Your directory structure should look something like this:
    ```
   ./text-analytics-api
       |- main.py
       |- utils.py
       |- requirements.txt
    ```
* Later on we are going to deploy the API on Azure using the same repository, and hence, we need to manually add some packages in the `requirements.txt` file. You need to add the following text at the end of your `requirements.txt` file:
   ```
   uvloop
   httptools
   gunicorn==20.0.4
   ```
   * `uvloop`: It implements all the `asyncio` event loop APIs. This will only be required if you are deploying on a Linux machine.
   * `httptools`: It is a Python binding for the nodejs `HTTP` parser. This will only be required if you are deploying on a Linux machine.

   * `gunicorn`: Gunicorn *'Green Unicorn'* is a Python `WSGI` `HTTP` Server for UNIX. This will only be required if you are deploying on a Linux machine.
   

You can verify your `requirements.txt` file by checking its content as shown below:


Learn to create a Github repository and push the OCR API to your remote Github repository using the GIT commands discussed earlier

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

Push the API to Github

Create the `requirements.txt` file

Pop Quiz

Push the API to Github

Create the requirements.txt file

Create the `requirements.txt` file