How to Create a REST API with Python and FastAPI Framework

Welcome! Let's take a look at "How to create a REST API with Python and FastAPI framework"🚀.

API is essential for building a multi-layer application structure, so choosing the right framework for your API can make the performance of your application robust.

FastAPI is a modern, fast (high-performance), a web framework for building APIs with Python 3.6+ based on standard Python type hints (source). It is written in Python with Starlette and Pydantic as a base. Big bull companies like Microsoft, Uber, Netflix, etc. have already started using FastAPI.

One of the reasons why I like FastAPI is because of the automatic interactive documentation. It will auto-generate Swagger documentation (not only Swagger but also Redoc) for you without any trouble of writing additional code.

Let's Begin Coding...

Prerequisites:

• Python 3.6+ (and how to use it😂)
• pip (if already installed then ignore)

Install FastAPI from pypi using pip, you also need to install an ASGI server.

 pip install fastapi 

 pip install uvicorn[standard] 

If you are familiar with the flask framework then it is very much similar to it, and if you are not then no worries. Once both are installed create a file app.py with the below code.

Let's run app.py with the below command

 uvicorn app:app --reload 

Adding --reload to the line will enable auto-refresh to your API whenever you save new changes. You can replace the left side app with your file/module name. For example, if you create a file as main.py then your command would be uvicorn main:app --reload.

Your API is running by now, and you can access it by going to http://localhost:8000/ from your browser. To see the documentation page of your API go to Swagger - http://localhost:8000/docs or Redoc - http://localhost:8000/redoc.

Understanding the above Code Example

After creating an instance you have defined data which is a list of dictionaries (i.e. fruits) to perform CRUD (Create Read Update and Delete) operations on it (Note: you can define your own data model or even use the database directly).

You have created an API that:

• Receives HTTP GET request in path  /  and  /fruits , returns welcome note and list of fruits respectively.
• Receives HTTP GET request in path  /find/fruits/{fruit_id}  and finds fruit with given fruit ID in URL. path parameter  fruit_id  should be an integer as you have defined in the function argument.

Why end here let's add more methods to the API

The above code has a body (BaseModel class) with Pydantic for the PUT and POST method. Now save this code and your API should auto-refresh, you can perform all the CRUD operations.

You can now try integrating the Postgres (or any other) database using SQAlchemy and make it a production-ready REST API but that would be a topic for the next blog.

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