feat: add docs website
This commit is contained in:
parent
f0ec2e4942
commit
576125d377
1 changed files with 683 additions and 3 deletions
24
docs/containers/index.qmd
Normal file
24
docs/containers/index.qmd
Normal file
|
|
@ -0,0 +1,24 @@
|
|||
---
|
||||
title: Containers
|
||||
---
|
||||
|
||||
The [rocker](https://hub.docker.com/u/rocker) project provides container images for R since several years.
|
||||
Since recently, the images are multi-arch, i.e. `arm64` is supported alongside `amd64`.
|
||||
|
||||
Yet, other distributions than Ubuntu are missing and don't use the devXY binaries out of the box.
|
||||
To simplify running containers that make use of the devXY R binaries implicitly, the following images are provided:
|
||||
|
||||
- [devxygmbh/r-alpine](https://hub.docker.com/r/devxygmbh/r-alpine)
|
||||
- [devxygmbh/r-ubuntu](https://hub.docker.com/r/devxygmbh/r-ubuntu)
|
||||
|
||||
These have the devXY repositories configured by default and can be used efficiently without further configuration changes.
|
||||
|
||||
In contrast to the minimal `rocker/r-ver` images, the `r-ubuntu` images contain a few additional system libraries which are essential for troublefree R usage.
|
||||
|
||||
The following screencast shows how quickly the `r-alpine` image can be used to install the full {tidyverse} package universe in just under 30s:
|
||||
|
||||
<div style="padding:59.12% 0 0 0;position:relative;"><iframe src="https://player.vimeo.com/video/1035389676?badge=0&autopause=0&player_id=0&app_id=58479" frameborder="0" allow="autoplay; fullscreen; picture-in-picture; clipboard-write" style="position:absolute;top:0;left:0;width:100%;height:100%;" title="Alpine package binaries: Install tidyverse"></iframe></div><script src="https://player.vimeo.com/api/player.js"></script>
|
||||
|
||||
::: {.callout-note}
|
||||
The performance of this screencast (and your local experience) depends on a few factors: local download speed, cached binaries in the CDN, proximity to a local edge node of the CDN and your CPU performance and finally the `Ncpus` option in R, defining how many installations are performed in parallel (by default 1).
|
||||
:::
|
||||
Loading…
Reference in a new issue