Overview

This is a very simple REST API created using plumber package in R, that serves predictions on car prices based on mileage, engine displacement and year of manufacture.

Step Invloved

The process can be broken down into three steps, each presented as a separate script:

1. Building a multiple linear regression model and saving it as an rds file
2. Turning the R model into a RESTFUL API, using the plumber package
3. Calling the API

Anatomy of an API

• Host (fixed) e.g. https://api.hostname.com/

• Endpoint (varied) e.g. https://api.hostname.com/endpoint

  • Endpoints are like a function
  • Determines what will happen

• Parameters (optional) e.g. https://api.hostname.com/endpoint/?param=value

  • Think of these like function arguments
  • Addresses varying parts of a request

Anatomy of a Plumber API

• Uses roxygen-like commenting #* to document

• #* is followed by tags

• Tags look like @tagName

• End points are defined by the appropriate method tag and endpoint name e.g. @get /predict

• Endpoint functionality is defined by an unassigned function immediately following the endpoint name

• Code outside of a function can be considered global

Reference

1. https://github.com/JosiahParry/deploying-r-models

2. https://www.youtube.com/watch?v=w4yHEQWct20&t=2s&ab_channel=JosiahParry