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(This article was first published on <strong><a href="https://aghaynes.wordpress.com/2018/07/10/ropenscis-drake-package/"> R – Insights of a PhD</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>If you don’t know rOpenSci, then I recommend checking them out. They write a lot of really good packages for R. A relatively new seems to be <a rel="nofollow" href="https://github.com/ropensci/drake" target="_blank">drake</a>. I’ve not played with it yet, but it looks to be very useful at giving indications about which parts of an analysis are subject to changes, and only rerunning those parts to speed up redoing an analysis (envisage the overlays for some version control systems or dropbox that show the status of files, although it’s more complicated than that). Knitr has caching, which goes some way to handling this, but here you can see where outdated parts are in the scope of the entire analysis…</p>
<p>It looks like a super tool!<img data-orig-file="https://aghaynes.files.wordpress.com/2018/07/drake_dep.png?w=450&amp;h=344&amp;fit=568%2C344" data-orig-size="829,502" data-medium-file="https://aghaynes.files.wordpress.com/2018/07/drake_dep.png?w=450&amp;h=344&amp;fit=568%2C344?w=300" data-attachment-id="380" data-image-meta="{" data-image-description="" src="https://aghaynes.files.wordpress.com/2018/07/drake_dep.png?w=450&h=344&fit=568%2C344" data-permalink="https://aghaynes.wordpress.com/2018/07/10/ropenscis-drake-package/drake_dep/" data-large-file="https://aghaynes.files.wordpress.com/2018/07/drake_dep.png?w=450&amp;h=344&amp;fit=568%2C344?w=497" alt="drake_dep" data-image-title="drake_dep" sizes="(max-width: 568px) 100vw, 568px" data-comments-opened="1" class="wp-image-380" data-recalc-dims="1"></p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="https://aghaynes.wordpress.com/2018/07/10/ropenscis-drake-package/"> R – Insights of a PhD</a></strong>.</div>
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