RestRserve

RestRserve is an R web API framework for building high-performance AND robust microservices and app backends. With Rserve backend on UNIX-like systems it is parallel by design. It will handle incoming requests in parallel - each request in a separate fork (all the credits should go to Simon Urbanek).

Quick start

Creating application is as simple as:

library(RestRserve)
app = Application$new()
app$add_get(
  path = "/hello", 
  FUN = function(request, response) {
    response$set_body("Hello from RestRserve")
  })
backend = BackendRserve$new()
backend$start(app, http_port = 8080)

Now you can type http://localhost:8080/hello in your favorite browser and see (surprisingly!) Hello from RestRserve.

Learn RestRserve

• follow quick start guide on http://restrserve.org/ for more details.
• check out "Articles" section on http://restrserve.org/
• browse examples on https://github.com/rexyai/RestRserve

Features

• Easy to install, small number of dependencies
• Fully featured http server with the support for URL encoded and multipart forms
• Build safe and secure applications - RestRserve supports https, provides building blocks for basic/token authentication
• Concise and intuitive syntax
• Raise meaningful http errors and allows to interrupt request handling from any place of the user code
• Comes with many examples - see inst/examples
• Saves you from boilerplate code:
  • automatically decodes request body from the common formats
  • automatically encodes response body to the common formats
  • automatically parses URI templates (such as /get/{item_id})
  • helps to expose OpenAPI and Swagger/Redoc/Rapidoc UI
• It is fast!

Installation

From source

remotes::install_github("rexyai/RestRserve")

Docker

Automated docker builds from docker-hub: https://hub.docker.com/r/rexyai/restrserve/

Contributing

Guidelines for filing issues / pull requests - CONTRIBUTING.md.

Acknowledgements

• Simon Urbanek (@s-u) for awesome Rserve and all the work on R itself and on his other packages
• Jeff Allen (@trestletech) for his work on Swagger UI in plumber (from where we took inspiration for our implementation)
• Brodie Gaslam (@brodieG) for help with understanding on how to get traceback from try-catch function calls. Also thanks Hadley Wickham (@hadley) for evaluate::try_capture_stack function which we use for this purpose.

Known limitations

• RestRserve is primarily tested on UNIX systems. While it works natively on Windows please don't expect it to be as performant as on UNIX-like systems. If you really want to use it on Windows - consider to try Windows Subsystem for Linux and report back.
• Keep in mind that every request is handled in a separate process (fork from a parent R session). While this feature allows to handle requests in parallel it also restricts reuse of certain objects which are not fork-safe (notably database connections, rJava objects, etc)

Related projects

• Rook
• FastRWeb
• opencpu
• plumber
• fiery
• jug (development discontinued)