Showing 12 of total 12 results (show query)
ropensci
targets:Dynamic Function-Oriented 'Make'-Like Declarative Pipelines
Pipeline tools coordinate the pieces of computationally demanding analysis projects. The 'targets' package is a 'Make'-like pipeline tool for statistics and data science in R. The package skips costly runtime for tasks that are already up to date, orchestrates the necessary computation with implicit parallel computing, and abstracts files as R objects. If all the current output matches the current upstream code and data, then the whole pipeline is up to date, and the results are more trustworthy than otherwise. The methodology in this package borrows from GNU 'Make' (2015, ISBN:978-9881443519) and 'drake' (2018, <doi:10.21105/joss.00550>).
Maintained by William Michael Landau. Last updated 1 days ago.
data-sciencehigh-performance-computingmakepeer-reviewedpipeliner-targetopiareproducibilityreproducible-researchtargetsworkflow
978 stars 15.16 score 4.6k scripts 22 dependentsropensci
tarchetypes:Archetypes for Targets
Function-oriented Make-like declarative pipelines for Statistics and data science are supported in the 'targets' R package. As an extension to 'targets', the 'tarchetypes' package provides convenient user-side functions to make 'targets' easier to use. By establishing reusable archetypes for common kinds of targets and pipelines, these functions help express complicated reproducible pipelines concisely and compactly. The methods in this package were influenced by the 'targets' R package. by Will Landau (2018) <doi:10.21105/joss.00550>.
Maintained by William Michael Landau. Last updated 1 days ago.
data-sciencehigh-performance-computingpeer-reviewedpipeliner-targetopiareproducibilitytargetsworkflow
142 stars 11.27 score 1.7k scripts 10 dependentsropensci
jagstargets:Targets for JAGS Pipelines
Bayesian data analysis usually incurs long runtimes and cumbersome custom code. A pipeline toolkit tailored to Bayesian statisticians, the 'jagstargets' R package is leverages 'targets' and 'R2jags' to ease this burden. 'jagstargets' makes it super easy to set up scalable JAGS pipelines that automatically parallelize the computation and skip expensive steps when the results are already up to date. Minimal custom code is required, and there is no need to manually configure branching, so usage is much easier than 'targets' alone. For the underlying methodology, please refer to the documentation of 'targets' <doi:10.21105/joss.02959> and 'JAGS' (Plummer 2003) <https://www.r-project.org/conferences/DSC-2003/Proceedings/Plummer.pdf>.
Maintained by William Michael Landau. Last updated 4 months ago.
bayesianhigh-performance-computingjagsmaker-targetopiareproducibilityrjagsstatisticstargetscpp
10 stars 6.95 score 32 scriptsropensci
stantargets:Targets for Stan Workflows
Bayesian data analysis usually incurs long runtimes and cumbersome custom code. A pipeline toolkit tailored to Bayesian statisticians, the 'stantargets' R package leverages 'targets' and 'cmdstanr' to ease these burdens. 'stantargets' makes it super easy to set up scalable Stan pipelines that automatically parallelize the computation and skip expensive steps when the results are already up to date. Minimal custom code is required, and there is no need to manually configure branching, so usage is much easier than 'targets' alone. 'stantargets' can access all of 'cmdstanr''s major algorithms (MCMC, variational Bayes, and optimization) and it supports both single-fit workflows and multi-rep simulation studies. For the statistical methodology, please refer to 'Stan' documentation (Stan Development Team 2020) <https://mc-stan.org/>.
Maintained by William Michael Landau. Last updated 2 months ago.
bayesianhigh-performance-computingmaker-targetopiareproducibilitystanstatisticstargets
49 stars 6.85 score 180 scriptsropensci
geotargets:'Targets' Extensions for Geographic Spatial Formats
Provides extensions for various geographic spatial file formats, such as shape files and rasters. Currently provides support for the 'terra' geographic spatial formats. See the vignettes for worked examples, demonstrations, and explanations of how to use the various package extensions.
Maintained by Nicholas Tierney. Last updated 9 days ago.
geospatialpipeliner-targetopiarasterreproducibilityreproducible-researchtargetsvectorworkflow
73 stars 6.79 scoreropensci
gittargets:Data Version Control for the Targets Package
In computationally demanding data analysis pipelines, the 'targets' R package (2021, <doi:10.21105/joss.02959>) maintains an up-to-date set of results while skipping tasks that do not need to rerun. This process increases speed and increases trust in the final end product. However, it also overwrites old output with new output, and past results disappear by default. To preserve historical output, the 'gittargets' package captures version-controlled snapshots of the data store, and each snapshot links to the underlying commit of the source code. That way, when the user rolls back the code to a previous branch or commit, 'gittargets' can recover the data contemporaneous with that commit so that all targets remain up to date.
Maintained by William Michael Landau. Last updated 9 months ago.
data-sciencedata-version-controldata-versioningreproducibilityreproducible-researchtargetsworkflow
88 stars 5.99 score 11 scripts
daranzolin
sqltargets:'Targets' Extension for 'SQL' Queries
Provides an extension for 'SQL' queries as separate file within 'targets' pipelines. The shorthand creates two targets, the query file and the query result.
Maintained by David Ranzolin. Last updated 6 months ago.
39 stars 5.72 score 18 scripts
nyuglobalties
blueprintr:Automagically Document and Test Datasets Using Targets Or Drake
Documents and tests datasets in a reproducible manner so that data lineage is easier to comprehend for small to medium tabular data. Originally designed to aid data cleaning tasks for humanitarian research groups, specifically large-scale longitudinal studies.
Maintained by Patrick Anker. Last updated 9 months ago.
1 stars 3.40 score 7 scripts
tjmahr
notestar:Notebooks Using 'Targets' and 'Bookdown'
'Targets' is an R package for dependency and build management in data analysis projects. This package provides a set of targets and project infrastructure to create 'bookdown'-based notebooks using 'targets'.
Maintained by Tristan Mahr. Last updated 2 months ago.
bookdownknitrpandocrmarkdowntargets
30 stars 3.18 score 7 scripts
mps9506
bookdowntargets:Targets for bookdown pipeline
Provides a targets pipeline extension for bookdown projects. For the underlying methodology, please refer to the documentation of 'targets' <doi:10.21105/joss.02959>.
Maintained by Michael Schramm. Last updated 9 months ago.
2.00 score 3 scripts
robitalec
CSEE.reproducible.workflows.workshop:Workshop for CSEE 2023 On Reproducible Workflows In R
Developing a reproducible workflow in R using functions, targets and renv.
Maintained by Alec L. Robitaille. Last updated 2 years ago.
conflictedfunctionsprojectsrenvreproducibilitytargetstargets-pipeline
1 stars 1.70 scorerobitalec
preparelocs:Prepares Relocations For The WEEL
Prepares animal relocation datasets for the Wildlife Evolutionary Ecology Lab at Memorial University.
Maintained by Alec L. Robitaille. Last updated 1 years ago.
animalanimal-movementgpstargets
1.70 score