In this blog post, Jannik will show you how to deploy your machine learning models as a REST API and how to make requests to the API from within your Python code.
In this blog post, Andre explains two approaches on how to secure a REST API: One works with nginx and the sub-request feature, the other implements the verification part in the API itself.
For all those, who are struggling with the (kind of weird) Johns Hopkins University COVID-19 case data CSV files, we’ve created a free API that makes it easy to integrate the latest worldwide COVID-19 data into your application.
Newman and Postman form a great team to test your REST API. I will give you a quick roundtrip through both tools and their interplay: define requests and tests, export them, and let them run with CLI and within Jenkins.
In this blog post, Stephan explains how to translate a simple R script, which transforms tables from wide to long format into a REST API with the R package Plumber and how to run it locally or with Docker.