targets-minimal
workflowr
| targets-minimal | workflowr | |
|---|---|---|
| 1 | 2 | |
| 56 | 807 | |
| - | 0.9% | |
| 0.0 | 5.4 | |
| about 2 years ago | 2 months ago | |
| R | R | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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targets-minimal
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Should you always rerun your entire script when reopening an R project?
Will has a GitHub repo in his own profile that is pretty minimal: https://github.com/wlandau/targets-minimal
workflowr
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How do you manage results, plots, etc.?
I would start by saying "bioinformatics world" is a very broad term. Most of it does not involve managing multiple models, which is what MLflow seems to be for. Most work is cleaning the data and interpreting the results, which is highly project-specific. Something like workflowr is generally more appropriate, but even that is an overkill for most people.
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Restructuring a large R project. Need advice on how to wire up file paths and associated objects.
Targets stores all your data serialised on disk, and only loads them in as needed by the dependencies. For a standardised folder structure, you can take inspiration from workflowr.
What are some alternatives?
bruceR - 📦 BRoadly Useful Convenient and Efficient R functions that BRing Users Concise and Elegant R data analyses.
targets - Function-oriented Make-like declarative workflows for R
targets-tutorial - Short course on the targets R package
box - Write reusable, composable and modular R code
deps - Dependency Management with roxygen-style Comments
reprex - Render bits of R code for sharing, e.g., on GitHub or StackOverflow.
blogdown - Create Blogs and Websites with R Markdown
data-science-development-project-template - A logical, reasonably standardized, but flexible project structure for doing and sharing data science research work while developing a software tool.
webR-quarto-demos - Experiments with generating a standalone Quarto Document using Web R
namer - R package :package: for labelling chunks of RMarkdown files! :boom: