The basic idea

A plugin is provided by a package, possibly it will be the only thing that a package provides. The plugin name must (currently) be the same as the package name. The only functions that the package needs to call are orderly::orderly_plugin and orderly::orderly_plugin_register which create and register the plugin, respectively.

To make a plugin available for an orderly project, two new bits of configuration may be present in orderly_config.json - one declares the plugin will be used, the other configures the plugin.

To use a plugin for an individual report, functions from the plugin should be used, which configure and use the plugin.

Finally, we can save information back into the final orderly metadata about what the plugin did.

With the yaml-less design of orderly (see vignette("migrating") if you are familiar with orderly1), the line between a plugin and just package code is fairly blurred, but reasons for writing a plugin are typically that you want to make something easier in reports, and you want that action reflected in the orderly metadata.

An example

As an example, we’ll implement a stripped down version of the database plugin that inspired this work (see `orderly.db for a fuller implementation). To make this work we need functions:

• …that process additional fields in orderly_config.json that describe where to find the database
• …that can be called from an orderly file that access the database
• …that can add metadata to the final orderly metadata about what was done

We’ll start with the report side of things, describing what we want to happen, then work on the implementation.

Here is the directory structure of our minimal project

## .
## ├── orderly_config.json
## └── src
##     └── example
##         └── example.R

The orderly_config.json file contains the information shared by all possible uses of the plugin - in the case the connection information for the database:

{
  "minimum_orderly_version": "1.99.90",
  "plugins": {
    "example.db": {
      "path": "/tmp/RtmpBVLQ2N/file24a4c439daf1ee"
    }
  }
}

Our plugin is called example.db and is listed within the plugins section, along with its configuration; in this case indicating the path where the SQLite file can be loaded from.

The example.R file contains information about use of the database for this specific report; in this case, making the results of the query SELECT * from mtcars WHERE cyl == 4 against the database available as some R object dat

dat <- example.db::query("SELECT * FROM mtcars WHERE cyl == 4")
orderly::orderly_artefact(description = "Summary of data", "data.rds")

saveRDS(summary(dat), "data.rds")

Normally, we imagine some calculation here but this is kept minimal for the purpose of demonstration.

To implement this we need to:

1. create a package
2. write a function to handle the configuration in orderly_config.json
3. write a function query() used in example.R to do the query itself

## .
## ├── DESCRIPTION
## ├── NAMESPACE
## └── R
##     └── plugin.R

Package: example.db
Version: 0.0.1
License: CC0
Title: Orderly Database Example Plugin
Description: Simple example of an orderly plugin.
Authors@R: person('Orderly Authors', role = c('aut', 'cre'),
    email = 'email@example.com')
Imports: orderly

db_config <- function(data, filename) {
  data
}

query <- function(sql) {
  ctx <- orderly::orderly_plugin_context("example.db")
  dbname <- ctx$config$path
  con <- DBI::dbConnect(RSQLite::SQLite(), dbname)
  on.exit(DBI::dbDisconnect(con))
  DBI::dbGetQuery(con, sql)
}

.onLoad <- function(...) {
  orderly::orderly_plugin_register(
    name = "example.db",
    config = db_config)
}

db_config <- function(data, filename) {
  data
}

query <- function(sql) {
  ctx <- orderly::orderly_plugin_context("example.db")
  dbname <- ctx$config$path
  con <- DBI::dbConnect(RSQLite::SQLite(), dbname)
  on.exit(DBI::dbDisconnect(con))
  DBI::dbGetQuery(con, sql)
}

.onLoad <- function(...) {
  orderly::orderly_plugin_register(
    name = "example.db",
    config = db_config)
}

export(query)

pkgload::load_all()

## ℹ Loading example.db

library(orderly)
orderly_run("example", root = path_root)
## ℹ Starting packet 'example' `20251008-130626-e2d52613` at 2025-10-08 14:06:26.891156
## > dat <- example.db::query("SELECT * FROM mtcars WHERE cyl == 4")
## > orderly::orderly_artefact(description = "Summary of data", "data.rds")
## > saveRDS(summary(dat), "data.rds")
## ✔ Finished running 'example.R'
## ℹ Finished 20251008-130626-e2d52613 at 2025-10-08 14:06:26.932295 (0.04113913 secs)
## [1] "20251008-130626-e2d52613"

Making the plugin more robust

The plugin above is fairly fragile because it does not do any validation on the input data from orderly_config.json. This is fairly annoying to do in practice, but a little effort will make the experience for a user better because they will be able to debug incorrect configuration more effectively.

In our case, we expect a single key-value pair in orderly_config.json with the key being path and the value being the path to a SQLite database. We can easily expand our configuration function to report better back to the user when they misconfigure the plugin:

db_config <- function(data, filename) {
  if (!is.list(data) || is.null(names(data)) || length(data) == 0) {
    stop("Expected a JSON object for orderly_config.json:example.db")
  }
  if (length(data$path) != 1 || !is.character(data$path)) {
    stop("Expected a string for orderly_config.json:example.db:path")
  }
  if (!file.exists(data$path)) {
    stop(sprintf(
      "The database '%s' does not exist (orderly_config:example.db:path)",
      data$path))
  }
  data
}

This should do an acceptable job of preventing poor input while suggesting to the user where they might look within the configuration to fix it. Note that we return the configuration data here, and you can augment (or otherwise change) this data as you need.

Saving metadata about what the plugin did

Nothing about what the plugin does is saved into the report metadata unless you save it. Partly this is because the orderly source file, which is saved into the final directory, serves as some sort of record. However, you probably want to know something about the data that you returned here. For example we might want to save

• the query string so that later we can query it without having to read and process the orderly source file
• some statistics about the size of the data (e.g., the number of rows returned, or the columns)
• perhaps some summary of the content such as a hash so that we can see if the content has changed between different versions of a report

To save metadata, use the function orderly::orderly_plugin_add_metadata; this takes as arguments your plugin name, any string you like to structure the saved metadata (here we’ll use query) and whatever data you want to save:

query <- function(sql) {
  ctx <- orderly::orderly_plugin_context("example.db")
  dbname <- ctx$config$path
  con <- DBI::dbConnect(RSQLite::SQLite(), dbname)
  on.exit(DBI::dbDisconnect(con))
  d <- DBI::dbGetQuery(con, sql)
  info <- list(sql = sql, rows = nrow(d), cols = names(d))
  orderly::orderly_plugin_add_metadata("example.db", "query", info)
  d
}

This function is otherwise the same as the minimal version above.

We also need to provide a serialisation function to ensure that the metadata is saved as expected. Because we saved our metadata under the key query, we will get a list back with an element query and then an unnamed list with as many elements as there were query calls in a given report.

db_serialise <- function(data) {
  for (i in seq_along(data$query)) {
    # Always save cols as a vector, even if length 1:
    data$query[[i]]$cols <- I(data$query[[i]]$cols)
  }
  jsonlite::toJSON(data$query, auto_unbox = TRUE)
}

Here, we ensure that everything except cols that is length 1 (which will be everything) gets turned into a scalar (so 1 not [1]) and then serialise with jsonlite::toJSON with auto_unbox as TRUE.

Taking this a step further, we can also specify a schema that this metadata will conform to

{
    "$schema": "http://json-schema.org/draft-07/schema#",

    "type": "array",
    "items": {
        "type": "object",
        "properties": {
            "sql": {
                "type": "string"
            },
            "rows": {
                "type": "number"
            },
            "cols": {
                "type": "array",
                "items": {
                    "type": "string"
                }
            }
        },
        "required": ["sql", "rows", "cols"],
        "additionalProperties": false
    }
}

We save this file as inst/schema.json within the package (any path within inst is fine, just adapt the schema path in the call to orderly_plugin_register below).

Finally, we can also add a deserialisation hook to convert the loaded metadata into a nice data.frame:

Now, when we register the plugin, we provide the path to this schema, along with the serialisation and deserialisation functions:

.onLoad <- function(...) {
  orderly::orderly_plugin_register(
    name = "example.db",
    config = db_config,
    serialise = db_serialise,
    deserialise = db_deserialise,
    schema = "schema.json")
}

Now, when the orderly metadata is saved (just before running the script part of a report) we will validate output that was passed into orderly::orderly_plugin_add_metadata against the schema, if jsonvalidate is installed and if the R option orderly.schema_validate is set to TRUE (e.g., by running options(orderly.schema_validate = TRUE), see vignette("details")).

Our final package has structure:

## .
## ├── archive
## │   └── example
## │       └── 20251008-130626-e2d52613
## │           ├── data.rds
## │           └── example.R
## ├── draft
## │   └── example
## ├── orderly_config.json
## └── src
##     └── example
##         └── example.R

The DESCRIPTION file and NAMESPACE are unchanged from above, and the schema is shown just above.

The plugin.R file contains the code collected from above:

db_config <- function(data, filename) {
  if (!is.list(data) || is.null(names(data)) || length(data) == 0) {
    stop("Expected a JSON object for orderly_config.json:example.db")
  }
  if (length(data$path) != 1 || !is.character(data$path)) {
    stop("Expected a string for orderly_config.json:example.db:path")
  }
  if (!file.exists(data$path)) {
    stop(sprintf(
      "The database '%s' does not exist (orderly_config:example.db:path)",
      data$path))
  }
  data
}

query <- function(sql) {
  ctx <- orderly::orderly_plugin_context("example.db")
  dbname <- ctx$config$path
  con <- DBI::dbConnect(RSQLite::SQLite(), dbname)
  on.exit(DBI::dbDisconnect(con))
  d <- DBI::dbGetQuery(con, sql)
  info <- list(sql = sql, rows = nrow(d), cols = names(d))
  orderly::orderly_plugin_add_metadata("example.db", "query", info)
  d
}

.onLoad <- function(...) {
  orderly::orderly_plugin_register(
    name = "example.db",
    config = db_config,
    serialise = db_serialise,
    deserialise = db_deserialise,
    schema = "schema.json")
}

(this code could be in any .R file in the package, or across several).

id <- orderly_run("example", root = path_root)
## ℹ Starting packet 'example' `20251008-130627-423fb4f5` at 2025-10-08 14:06:27.263721
## > dat <- example.db::query("SELECT * FROM mtcars WHERE cyl == 4")
## > orderly::orderly_artefact(description = "Summary of data", "data.rds")
## > saveRDS(summary(dat), "data.rds")
## ✔ Finished running 'example.R'
## ℹ Finished 20251008-130627-423fb4f5 at 2025-10-08 14:06:27.297384 (0.03366232 secs)
meta <- orderly_metadata(id, root = path_root)
meta$custom$example.db
##                                   sql rows         cols
## 1 SELECT * FROM mtcars WHERE cyl == 4   11 mpg, cyl....

Potential uses

Our need for this functionality is similar to this example - pulling out the database functionality from the original version of orderly into something that is more independent, as it turns out to be useful only in a fraction of orderly use-cases. We can imagine other potential uses though, such as:

• Non-DBI-based database data extraction, or customised routines for pulling data from a database
• Download files from some shared location just before use (e.g., SharePoint, OneDrive, AWS). The orderly_config.json would contain account connection details and the orderly source file would contain mapping between the remote data/files and local files. Rather than writing to the environment as we do above, use the path argument to copy files into the correct place.
• Pull data from some web API just before running

These all follow the same basic pattern of requiring some configuration in order to be able to connect to the resource service, some specification of what resources are to be fetched, and some action to actually fetch the resource and put it into place.