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# orderly1
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[](https://www.repostatus.org/#active)
[](https://github.com/vimc/orderly1/actions)
[](https://codecov.io/github/vimc/orderly1?branch=master)
[](https://www.codefactor.io/repository/github/vimc/orderly1)
[](https://cran.r-project.org/package=orderly)
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> [!WARNING]
> This is an archived copy of the original version of orderly, version 1, available as a package `orderly1`. The information below is for historical reference, and the package is available for use with historical orderly source repositories. New projects should use [`orderly` version 2](https://mrc-ide.github.io/orderly/); see the [migration guide](https://mrc-ide.github.io/orderly/articles/migrating.html) for possible next steps.
> 1. an attendant in a hospital responsible for the non-medical care of patients and the maintenance of order and cleanliness.
> 2. a soldier who carries orders or performs minor tasks for an officer.
<!-- introduction -->
## Workflows with `orderly1`
In the [MRC Centre for Global Infectious Disease Analysis](https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis) we use `orderly1` on three major projects:
- The [Vaccine Impact Modelling Consortium](https://www.vaccineimpact.org/)
- Our part of the response to the 2018-2020 Ebola outbreak in the Democratic Republic of Congo
- [Our part](https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/) of the response to the 2019-2020 2019-nCoV-SARS/COVID-19 pandemic
The workflows we have developed here are oriented towards collaborative groups of researchers - other workflows are possible (indeed `orderly1` is also designed to support a _decentralised_ workflow, though this has not been used in practice yet).
In these projects we have a group of researchers who develop and test analyses locally. These are developed on a [branch in git](https://git-scm.com/book/en/v2/Git-Branching-Basic-Branching-and-Merging) and then run on a centralised _staging environment_ (a duplicate of our production environment). The code and outputs are reviewed with the help of [GitHub's "Pull requests"](https://help.github.com/en/articles/about-pull-requests) and then the reports are run on our production environment.
Interaction with the remote environments is achieved using an [HTTP API](https://github.com/vimc/montagu-reporting-api) which `orderly1` itself transparently uses, so that reports can be run remotely, [directly from R](https://www.vaccineimpact.org/orderly/reference/orderly_run_remote.html). The remote systems also include an interactive web interface that can be used to explore and download versions of analyses, as well as run new ones.
## Internal database schema
`orderly1` has a database, which should be the preferred way of querying the report archive from other programs. The schema is programmatically described at [`inst/database/schema.yml`](inst/database/schema.yml) and automatically generated database documentation is available [here](https://www.vaccineimpact.org/orderly/schema/).
## Testing
There is a set of regression tests that require the reference data. Enable these by running the script `./scripts/copy_reference` which creates data in `tests/testthat/reference`
## RStudio addins
There are [addins](https://github.com/vimc/orderly.rstudio) available to help with development workflows.
See docs at [orderly.rstudio](https://github.com/vimc/orderly.rstudio#setup) for setup and usage instructions.
## Installation
Install `orderly` from our R universe with
```r
install.packages(
"orderly1",
repos = c("https://vimc.r-universe.dev", "https://cloud.r-project.org"))
```
## License
MIT © Imperial College of Science, Technology and Medicine