Docs: Installing tools for authoring computational models

Wed, 28 Jan 2026 00:00:00 +0000

Before you install

If you are a coder planning on using ready4 to author computational models, then you may wish to install the ready4class, ready4fun and ready4pack libraries.

However, please note that none of these libraries are yet available as a production release. You should therefore understand the limitations of using ready4 software development releases before you make the decision to install this software. Although we use these authoring tools intensively to help us write highly standardised model modules, we feel that these tools are only likely to be helpful to others once much more comprehensive documentation and training resources become available. Without this training and support, these packages are unlikely to appear to be very user-friendly. Furthermore, the initial burden of complying with house-style, file-naming and directory structure requirements of these packages is only likely to be worthwhile if you plan on developing multiple ready4 module libraries. If you still think these tools could be useful to you, consider contacting us first to discuss what additional information may be most helpful to you.

Installation

As ready4class and ready4fun are bundled as dependencies of ready4pack, you can install all three from our GitHub organisation using one command.

devtools::install_github("ready4-dev/ready4pack")

Configuration

To use these computational model authoring tools, you will need to have set-up and appropriately configured your own accounts in:

GitHub (you will need write permissions to a GitHub organisation and to then enable GitHub actions and GitHub pages support for the repositories you create in that organisation);
Zenodo (you will need to have linked each GitHub repository used for your ready4 projects to your Zenodo account); and
Codecov (linked to your GitHub organisation).

The machine onto which you install ready4pack will also need to be securely storing your GitHub credentials (i.e. the value for the GITHUB_PAT token).

Try it out!

It should be noted that the development workflow supported by our computational model authoring tools is not yet well documented. We don’t recommend undertaking R package development with these tools until this has been rectified. However, if you still want to try these tools out, the best place to start is review the examples in the ready4class, ready4fun and ready4pack vignettes.

Docs: Dissemating citable, documented and quality assured model module libraries

Wed, 28 Jan 2026 00:00:00 +0000

This below section renders a vignette article from the ready4pack library. You can use the following links to:

view the vignette on the library website (adds useful hyperlinks to code blocks)
view the source file from that article, and;
edit its contents (requires a GitHub account).

library(ready4)
library(ready4fun)
library(ready4class)
library(ready4pack)

ready4pack is a toolkit for bundling collections of modules for computational health economic models authored with the ready4 framework as R packages that are:

Citable (with a Zenodo generated DOI and an algorithm generated CITATION file);
Community-minded (applying deprecation conventions supported by lifecycle);
Documented (applying a function self-documenting algorithm that extends sinew, deploying a GitHub pages hosted and pkgdown generated website and authoring PDF manuals stored in a GitHub Release via piggyback);
Internally consistent implementing automated checks to ensure consistency in naming conventions, etc;
Licensed (via a usethis generated GPL-3 license);
Quality assured (using continuous integration via GitHub actions and R-CMD-Check); and
Versioned (applying usethis version increments).

ready4pack extends ready4 framework tools for authoring module algorithms (ready4fun) and data structures (ready4class) and wraps functions from a number of third party R development workflow tools (such as devtools). ready4pack integrates these tools in a common workflow, while adding tools for authoring and documenting datasets to be shipped with model module R packages.

A combination of the ready4_pack_manifest class and author method are used to implement this workflow. This workflow has been used to author all public versions of the ready4 R packages available in the ready4 github repository.

Workflow

Manifest

The main class exported as part of ready4pack is readypack_manifest list based ready4 sub-module, that extends the ready4fun_manifest and ready4class_manifest sub-modules.

Typical usage

readypack_manifest sub-module is most efficiently created with the aid of the make_pt_ready4pack_manifest function and combines instances of the ready4fun_manifest and ready4class_constructor sub-modules.

x <- make_pt_ready4pack_manifest(ready4fun::ready4fun_manifest(),
                                 constructor_r3 = ready4class::ready4class_constructor()) %>%
  ready4pack_manifest()

The main method defined for readypack_manifest is author which extends the author method for ready4class_manifest to author a consistently documented R package.

## Not run
author(x)

Examples

Workflow example one

The program to author and document the ready4show package is relatively simple and authors:

the ready4show package CITATION, DESCRIPTION, LICENSE and README files;
all files in the ready4show package R directory;
the ready4show package website;
two versions of the ready4show package manual - a slimmed down version for end-users and a more detailed inventory of contents intended for developers;
an initial ready4show release for hosting supporting files, the creation of which will trigger archiving on Zenodo with a ready4show package DOI; and
an R-CMD-check continuous integration algorithm to be implemented each time a new version of ready4show is pushed to the main branch of the GitHub source code repository.

Workflow example two

The program to author and document the youthvars package is a bit more complex as it includes syntax to create package datasets. In addition to the package datasets, the algorithm creates content corresponding to the previous example, specifically:

the youthvars package CITATION, DESCRIPTION, LICENSE and README files;
all files in the youthvars package R directory;
the youthvars package website;
two versions of the youthvars package manual - a slimmed down version for end-users and a more detailed inventory of contents intended for developers;
an initial youthvars release for hosting supporting files, the creation of which will trigger archiving on Zenodo with a youthvars package DOI; and
an R-CMD-check continuous integration algorithm to be implemented each time a new version of youthvars is pushed to the main branch of the GitHub source code repository.

Future documentation

A more detailed guide to using ready4pack will be created in 2023.

ready4 – Software - libraries (ready4pack)