docs(r): 📝 renv notes

r/environments.md

@@ -0,0 +1,57 @@
+# R environments
+
+## How to set-up renv for reproducible research
+
+Create `DESCRIPTION` file e.g.
+
+```
+Title: quarto_huang_2019
+Depends: 
+    R (>= 3.7)
+Imports:
+    knitr (==1.47),
+    rmarkdown (==2.27),
+    remotes (==2.5.0),
+    tiff (==0.1-12)
+```
+
+Then start new empty environment with `renv::init(bare=TRUE)`.
+
+When initialising, you should be prompted to only install from the `DESCRIPTION` - select yes to this. Otherwise, run the command yourself: `renv::settings$snapshot.type("explicit")`.
+
+You can then install the packages from DESCRIPTION by running `renv::install()`, and then create the lock file by running `renv::snapshot`.
+
+If you make any changes to the packages and versions, simply modified the `DESCRIPTION` file and then run `renv::install()` followed by `renv::snapshot`.
+
+If you run into issues where it cannot find a specific package/version, this may be due to the formatting of the version number. For example, for the package `tiff`:
+
+* `tiff` - installs latest version (0.1.12)
+* `tiff (==0.1.11)` - cannot find package
+* `tiff (==0.1-11)` - installs older version (0.1.11)
+
+The error was due to how those versions are formatted on CRAN, as you can see on the [tiff archive](https://cran.r-project.org/src/contrib/Archive/tiff/).
+
+## Basic renv commands
+
+To start new project environment, creating .RProfile: `renv::init()`  
+To save state of project library to lockfile renv.lock: `renv::snapshot()`  
+To return to environment in lockfile:  `renv::restore()`  
+
+## Binder
+
+Created using instructions from [here](https://ajstewartlang.github.io/23_introduction_to_binder/slides/23_introduction_to_binder.pdf) and [here](https://github.com/binder-examples/r).  
+
+1. Create runtime.txt file with R version  
+2. Create install.R file with package installations  
+3. Navigate to https://mybinder.org/, paste in GitHub repository, set to "URL to open (optional)" and type in "rstudio", then launch  
+
+## Rough notes
+
+R -
+\begin{itemize}
+    \item Renv
+    \item Posit Public Package Manager - can use Snapshot (earliest is Oct 2017, and 5 most recent versions of R), for Linux can install binary packages (which is much quicker, as usually R installs from source rather than binary unlike for Windows and Mac which makes it really slow) - \href{https://packagemanager.posit.co/client/#/repos/cran/setup}{source 1}, \href{https://docs.posit.co/faq/p3m-faq/#frequently-asked-questions}{source 2}
+    \item Groundhog - can go back to R 3.2 and April 2015 (and apparently can patch to go earlier) - \href{https://www.brodrigues.co/blog/2023-01-12-repro_r/}{source 1}
+    \item miniCRAN - \href{https://learn.microsoft.com/en-us/sql/machine-learning/package-management/create-a-local-package-repository-using-minicran?view=sql-server-ver16}{source 1}
+    \item Docker - requires license for non-academic (e.g. NHS) use - but Podman can drop in as replacement. To do development inside a container isn't natively supported by RStudio but can use RStudioServer via Rocker. By default, it runs in ephemeral mode - any code created or saved is lost when close - but you can use volume argument to mount local folders - \href{https://towardsdatascience.com/running-rstudio-inside-a-container-e9db5e809ff8}{source 1}
+\end{itemize}

r/general.md

@@ -4,19 +4,10 @@
 :hidden: True
 
 self
+environments
 packages
 ```
 
-R -
-\begin{itemize}
-    \item Renv
-    \item Posit Public Package Manager - can use Snapshot (earliest is Oct 2017, and 5 most recent versions of R), for Linux can install binary packages (which is much quicker, as usually R installs from source rather than binary unlike for Windows and Mac which makes it really slow) - \href{https://packagemanager.posit.co/client/#/repos/cran/setup}{source 1}, \href{https://docs.posit.co/faq/p3m-faq/#frequently-asked-questions}{source 2}
-    \item Groundhog - can go back to R 3.2 and April 2015 (and apparently can patch to go earlier) - \href{https://www.brodrigues.co/blog/2023-01-12-repro_r/}{source 1}
-    \item miniCRAN - \href{https://learn.microsoft.com/en-us/sql/machine-learning/package-management/create-a-local-package-repository-using-minicran?view=sql-server-ver16}{source 1}
-    \item Docker - requires license for non-academic (e.g. NHS) use - but Podman can drop in as replacement. To do development inside a container isn't natively supported by RStudio but can use RStudioServer via Rocker. By default, it runs in ephemeral mode - any code created or saved is lost when close - but you can use volume argument to mount local folders - \href{https://towardsdatascience.com/running-rstudio-inside-a-container-e9db5e809ff8}{source 1}
-\end{itemize}
-
-
 ## Function setting default inputs  
 If default input is different to the input name, you won't have an issue. If it's the same you'll have an error.  
 ```
@@ -58,17 +49,6 @@ for (i in seq_along(output[[1]])){
 }
 ```
 
-## Reproducible environment: renv  
-To start new project environment, creating .RProfile: `renv::init()`  
-To save state of project library to lockfile renv.lock: `renv::snapshot()`  
-To return to environment in lockfile:  `renv::restore()`  
-
-## Reproducible environment: binder
-Created using instructions from [here](https://ajstewartlang.github.io/23_introduction_to_binder/slides/23_introduction_to_binder.pdf) and [here](https://github.com/binder-examples/r).  
-1. Create runtime.txt file with R version  
-2. Create install.R file with package installations  
-3. Navigate to https://mybinder.org/, paste in GitHub repository, set to "URL to open (optional)" and type in "rstudio", then launch  
-
 ## Linting
 ```
 install.packages("lintr")