geoplumber is an R package which enables data scientists and developers in general to develop scalable geospatial web applications. It is work in progress, and right now we consider it an R powered web application "framework". It utilizes plumber, which was designed for creating web APIs with R which is Swagger compliant. It supports React frontends at present (it may support other frontend frameworks such as VueJS in the future) and geographic data, building on sf.

In other words, geoplumber is a lightweight geographic data server, like a barebones version of GeoServer but with a smaller footprint (< 5MB rather than > 50MB download size) and easier installation, especially if you are already an R user. There is internal discussions on the choice of a spatial database (PostgreSQL, MongoDB etc) but the package is just too young for this.

It can be installed with the following command as it is not yet on CRAN:

devtools::install_github("ATFutures/geoplumber")
#> Downloading GitHub repo ATFutures/geoplumber@master
#> from URL https://api.github.com/repos/ATFutures/geoplumber/zipball/master
#> Installing geoplumber
#> Installing geojsonsf
...

geoplumber is built for Unix systems and Windows. Windows support is recent and package tests have only been run on Windows 10. If there are any issues please feel free to open a ticket on the issue tracker.

We have worked with Shiny and plumber and we consider ourselves experienced in ReactJS, too. In order to put together a web application powered at the backend with R and React at the front-end, there is a lot of setup and boilerplate to put together. This would be also correct for other front end stack such as Angular or VueJS.

As geoplumber uses both R and Node, currently R v3.4 is the minimum, we will do all we can to make it backward compatible both in R and node. As for node, whatever the needs of Facebook's create-react-app is. For instructions on installing node on your OS please refer to the NodeJS official docs. Currently geoplumber uses Facebook's create-react-app (CRA) npm package to deal with underlying app management (including building and running) to keep you up to date with updates. geoplumber will generally provide detailed installation instructions for all required npm packages, but if not, the following are minimally required:

sudo npm i -g create-react-app

The following are included by default, the versions are just from old .Rmd file. geoplumber updates these as the package is developed. Feel free to replace it with your own .json package definer as and when.

  "dependencies": {
    "create-react-app": "^1.5.2",       # main package to manage front end
    "enzyme": "^3.3.0",                 # test suite
    "enzyme-adapter-react-16": "^1.1.1",# test suite adapter for React
    "leaflet": "^1.3.1",                # main web map tool (future could be different)
    "prop-types": "^15.6.1",            # React bits and pieces
    "react": "^16.3.2",                 # React
    "react-bootstrap": "^0.32.1",       # bootstrap is current choice.
    "react-dom": "^16.3.2",             # React
    "react-leaflet": "^1.9.1",          # React wrapper around leaflet above
    "react-leaflet-control": "^1.4.1",  # React map control
    "react-router": "^4.3.1",           # React router (RR) (supporting multuplage, too)
    "react-router-dom": "^4.2.2",       # React dom for RR
    "react-scripts": "1.1.4",           # main package to manage front end
    "react-test-renderer": "^16.4.1",   # test suite
    "sinon": "^6.1.4"                   # test suite
  }

To create a new web application:

library(geoplumber)
gp_create("my_app")
#> Initializing project at: /Users/layik/code/geoplumber/my_app
#> To build/run app, set working directory to: my_app
#> Standard output from create-react-app above works.
#> You can run gp_ functions from directory: my_app
#> To build the front end run: gp_build()
#> To run the geoplumber app: gp_plumb()
#> Happy coding.

This will create a my_app folder at your current working directory. Suppose you started an R session from a folder with path /Users/ruser/, you will have /Users/ruser/my_app on your machine.

If you create an Rstudio project at /Users/ruser/my_app yourself, or an empty my_app directory, you can create a geoplumber app using: geoplumber::gp_create(".").

You can also give geoplumber a path including one ending with a new directory. Currently, geoplumber does not do any checks on this but the underlying CRA does.

You can then build the new project

library(geoplumber)
setwd("my_app")
gp_build() # the front end and create minified js files.
#> Running: npm run build
#> Looks like first run, installing npm packages...
#> Running: gp_npm_install()
#> Now trying to build: npm run build
#> Standard output from create-react-app above works.
#> To run the geoplumber app: gp_plumb()

Please note, gp_build() produces a production ready minifed front end. It does not have to be used everytime a little change is done to the front end, as the package is still very young, it does not have the proper development "serve" function which would use gp_plumb_front() but would have to also use gp_plumb() to serve the backend.

At this point, if you created an app using the above examples or set your working directory to a geoplumber app. You can then serve all endpoints and front end with one command: gp_plumb() # provide custom port if you wish, default is 8000

Then visit localhost:8000 to see your app.

Once the geoplumber app my_app has been created. It will have a create-react-app directory structure with an extra R folder to hold the backend R code. The React components, as they are in CRA apps, are in the src folder and ready to be customised and developed for your own purposes. So, a React developer could run npm start on the root directory and run the built in CRA development server which is what gp_plumb_front() does too.

Serve the geoplumber::traffic dataset (data.frame) at a "/api/data" endpoint, and view it on the front end.

The traffic dataset is from CDRC at University of Leeds which is traffic data locations for the larger traffic dataset.

To achive this copy the following endpoint/API to the clipboard of your machine. If you like to understand the function, you need to learn plumber package.

#' Serve geoplumber::traffic from /api/data
#' @get /api/data
get_traffic <- function(res) {
  geojson <- geojsonsf::sf_geojson(geoplumber::traffic)
  res$body <- geojson
  res
}

Then run (re-copied into clipboard just in case):

setwd("my_app")
old_clip <- clipr::read_clip()
# adding above to clipboard
 clipr::write_clip(c(
 "#' Serve geoplumber::traffic from /api/data",
 "#' @get /api/data",
 "get_traffic <- function(res) {",
 "  geojson <- geojsonsf::sf_geojson(geoplumber::traffic)",
 "  res$body <- geojson",
 "  res",
 "}"
 ))
 gp_endpoint_from_clip()
#> Clipboard contents: 
#> ------begin----
#> #' Serve geoplumber::traffic from /api/data
#> #' @get /api/data
#> get_traffic <- function(res) {
#>   geojson <- geojsonsf::sf_geojson(geoplumber::traffic)
#>   res$body <- geojson
#>   res
#> }
#> -----end-----
#> Success.
#> Please restart your server: gp_plumb()
#> Success.
#> Please restart your server: gp_plumb()
 clipr::write_clip(old_clip)

This has now added a new endpoint at: /api/data. To consume it, we can simply run:

setwd("my_app")
gp_add_geojson("/api/data") # param value is default
#> Remember to rebuild frontend: gp_build()
#> Success.

You can now see the data by running:

setwd("my_app")
gp_build() # build changes
gp_plumb()

CDRC London traffic data on geoplumber

You can also now see the raw JSON dataset at http://localhost:8000/api/data, and on a map on a browser view the map at http://localhost:8000.

We would like to see default University of Leeds uni_poly grow/shrink using sf::st_buffer() function. Here is a reproducible example (please take a look at the default plumber.R file in your my_app project):

gp_create(tolower(tempdir()))
cw <- setwd(tolower(tempdir()))
gp_is_wd_geoplumber()
gp_add_slider(
  min = 0.001,
  max = 0.01,
  step = 0.001
)
gp_change_file(
  path = "src/Welcome.js",
  what = '<GeoJSONComponent fetchURL={"http://localhost:8000/api/uol?grow=" + this.state.sliderInput} />
',
  pattern = '<GeoJSONComponent fetchURL="http://localhost:8000/api/uol" />',
  replace = TRUE,
  verbose = TRUE
)

Run the project (this time at tempdir() location) by:

gp_build() # build changes
gp_plumb()

Now you can see (latest version is slightly improved than following GIF):

geoplumber::uni\_poly grow/shrinking using sf::st\_buffer function on server side.

R package plumber comes with a default endpoint for documenting the API using Swagger. This is also available from geoplumber's /__swagger__/ path.

We follow a pattern of /api/ before the endpoints and without for other URL's. A new web app will have /api/helloworld and you can curl it:

curl localhost:8000/api/helloworld
#> {"msg":["The message is: 'nothing given'"]}

Tests currently only apply to very restricted components of full functionality.

devtools::test()