{diades.atlas}

A Shiny application to explore data.

Installation

remotes::install_github('inrae/diades.atlas')

Websites for validations :

• Package documentation : https://inrae.github.io/diades.atlas/
• Package documentation (development version) : https://inrae.github.io/diades.atlas/dev/
• Shiny App : https://connect.thinkr.fr/diadesatlasui18n/

Translation

All translations are stored in csv files in “inst/”. If there are corrections to be made, existing texts on the app to be translated, only these 3 files have to be modified:

• inst/translation_help.csv
• inst/translation_iucn.csv
• inst/translation.csv

After modifications in a branch, propose a Pull Request to the main branch:

• On the home page of the project, click on Pull Request
• Then on “New Pull Request”.
• In the “Compare Changes” section, choose your branch in the right drop-down menu “compare:”.
• Then “Create Pull Request”, twice.
• You can check in the ‘Files changed’ tab what you have changed.

Once the PR is accepted, the changes should appear in the app the next time it is deployed. There is nothing to do.

For more information, or for instructions on how to prepare the application for new languages or areas to be translated, refer to the “dev/translation.Rmd” file.

In all cases, developers will need to - have access to the PostGis database (see “Backend requirement” below) - follow the content of “dev/translation.Rmd” during each update.

Userguide

The userguide is included in English in “data-raw/userguide.Rmd”. This version is to be included in the vignettes to appear on the documentation website. Users can create other translations of this userguide.

• Copy the english Rmd file and change the name of the file
• Keep the images, but change the text for your language
• User can then knit the document as pdf_document.
• The translated Rmd file can stay in the “data-raw/” directory and be commit and push to GitHub

Retrieve package and develop

You can get this package and propose modifications of the code.

1. Clone in RStudio

• File > New Project > Version Control > Git
• Use URL: https://github.com/inrae/diades.atlas

2. In the RStudio “Git” Pane

• Create a “New branch” with your name

3. Define your credentials for the database

• Create a “.Renviron” file with usethis::edit_r_environ()
• Use the correct names and passwords to fill as below
• This file will stay on your computer

POSTGRES_DBNAME="diades"
POSTGRES_HOST="host-url"
POSTGRES_USER="username"
POSTGRES_PORT=5432
POSTGRES_PASS="user-password"

• Restart RStudio
• Verify these variables are correctly read

Sys.getenv("POSTGRES_USER")

4. You may need to install dependencies with the same packages than the developers

renv::restore()

{renv} may be tricky with multiple OS. Be kind.

5. Run pkgload::load_all() in the R Console

• This loads all existing functions stored in “R/” directory

6. Open a Rmd in “data-raw/” like “data-raw/be-page4-future.Rmd”

• You should be able to run it chunk by chunk
• Do not forget to close connection to the database at the end

7. You can test modifications of the code in “R/”

• After each modification, run pkgload::load_all() before testing in the Rmd

8. After each modification, it is necessary to run devtools::check()

Exploration of database out of Shiny application

You can use this package without opening the Shiny application.
See vignette “data-raw/aa-a-exploration_data.Rmd”

Test the application locally

To run the Shiny application on your computer, you need to meet the “Backend Requirements” (see the section below).
This means, at least, having access to the database: set your database connection information and your credentials as specified in section “PostGIS”.

You may need to update your package installation using:

renv::restore()

Then you can run in the R Console:

golem::run_dev()

Put in Production

Update Docker for deployment: https://gitlab.irstea.fr/diades/diades.atlas.deploy/

On https://gitlab.irstea.fr/diades/diades.atlas.deploy/, there are also details on how to test the docker-compose locally. At least try to build it locally before release.

docker build -t gitlab-registry.irstea.fr/diades/diades.atlas.deploy/app .

Backend requirement

PostGis

To update the translations or to run the shiny application locally, the PostGis database is required.

To be able to connect to a PostGis instance the user needs to define some golem config parameters and environment variables.

golem config parameters

Those are stored in inst/golem-config.yml and can be modified as such:

# database name
golem::amend_golem_config(
  "POSTGRES_DBNAME",
  "diades" # Changer ici le nom de la base de données
)
# database host URL
golem::amend_golem_config(
  "POSTGRES_HOST",
  "localhost"  # Changer ici l'URL de la base
)
# database port access
golem::amend_golem_config(
  "POSTGRES_PORT",
  "5432" # Changer ici le port
)

If you change these lines to set the real values, be sure to set them back with the examples below before commit, to avoid sending your credentials on Git.

Run the script below once, and you’ll be protected of sending your credentials accidentally.

usethis::use_git_hook(
      "pre-commit",
      script = c("#!/bin/bash
CONFIG=($(git diff --cached --name-only | grep -Ei '^inst/golem-config\\.yml$'))

if [[ ${#CONFIG[@]} == 1 ]]; then
  echo -e \"You added inst/golem-config.yml. Is that really what you want?\nYou may not want to commit your credentials.\nIf this is really what you want, use 'git commit --no-verify' to override this check.\"
  exit 1
fi
",
usethis:::render_template("readme-rmd-pre-commit.sh")
))

Environment variables

The POSTGRES_USER and POSTGRES_PASS must not be versioned with the app.

To avoid setting those environment variables every time you want to run the app, they should be saved in a local .Renviron file. To define one for your own copy of the project run this command:

usethis::edit_r_environ(scope = "project")

and add the following lines

# database username with Read access
POSTGRES_USER=diadesatlas_owner # Changer ici le username
# database password for the user
POSTGRES_PASS=thinkrpassword # Changer ici le password

Again make sure not to track this project .Renviron with git.

Dev - ThinkR PostGis DB

If you do not have direct access to the database, a copy can be used for development. Please refer to the doc in the {diadesdata} repo on ThinkR’s forge (restricted access): Section “Pull and Use”.

Checks

Verify connexion to database works
Whether you are connected to the development or the production database, this should work correctly

pkgload::load_all()
session <- new.env()
connect(session)
con <- get_con(session)

DBI::dbListTables(con)
DBI::dbDisconnect(con)

Dev - Mongo

To run the Shiny application locally in the same conditions as in production, it is better to have a Mongo database. For dev, you need to run the following on your machine:

docker run --name=mongo --rm -p 2811:27017 -e MONGO_INITDB_ROOT_USERNAME=Colin -e MONGO_INITDB_ROOT_PASSWORD=AsAboveSoBelow789123 mongo:4.0

Stop it at the end of your development process

docker kill mongo

If Mongo database is not available, a local temporary cache will be use in the RAM of your machine.

Dev - Data update requires update unit test expected outputs

If the database is updated, model outputs may change. It may be necessary to run simulation before unit tests.

source(here::here("data-raw/altas_simulation.R"))

Dev - update and include vignettes in the package

Vignettes are compiled manually by developers. Raw vignettes are stored in “data-raw”. Instructions to compile them are in the vignette itself.

However, they can all be prepared from this script:

remotes::install_local(upgrade = "never", force = TRUE)

file.copy(here::here("dev", "translation.Rmd"),
          here::here("data-raw", "translation.Rmd"))

all_vignettes <- c(
  "aa-a-exploration_data",
  "aa-data-exploration-and-preparation",
  "bb-page1-catch-bycatch",
  "bc-page2-present",
  "bd-page3-climate-change",
  "be-page4-future", 
  "translation",
  "userguide")

for (vignette_name in all_vignettes) {
  # vignette_name <- all_vignettes[6]
  vignette_file <- paste0(vignette_name, ".Rmd")
  
  rmarkdown::render(
    input = here::here(file.path("data-raw", vignette_file)),
    output_format = "rmarkdown::html_vignette",
    output_options = list(toc = TRUE),
    output_file = here::here(file.path("vignettes", vignette_file))
  )
  
  # Add header for title
  lines <- readLines(here::here(file.path("vignettes", vignette_file)))
  
  cat(
    glue::glue('---
title: ".{vignette_name}."
output: rmarkdown::html_vignette
vignette: >
  %\\VignetteIndexEntry{.{vignette_name}.}
  %\\VignetteEngine{knitr::rmarkdown}
  %\\VignetteEncoding{UTF-8}
---
', .open = ".{", .close = "}."),
lines,
sep = "\n", 
file = here::here(file.path("vignettes", vignette_file))
  )
}
file.remove(here::here("data-raw", "translation.Rmd"))

# Add unit tests report
# remotes::install_github("metrumresearchgroup/covrpage")
# You may need to run with interactive session.
# Do not know why...
# debugonce(covrpage::covrpage)
covrpage::covrpage(vignette = TRUE)
file.remove("tests/README.md")