hardhat: Construct Modeling Packages (original) (raw)

Building modeling packages is hard. A large amount of effort generally goes into providing an implementation for a new method that is efficient, fast, and correct, but often less emphasis is put on the user interface. A good interface requires specialized knowledge about S3 methods and formulas, which the average package developer might not have. The goal of 'hardhat' is to reduce the burden around building new modeling packages by providing functionality for preprocessing, predicting, and validating input.

Version: 1.4.2
Depends: R (≥ 4.1)
Imports: cli (≥ 3.6.0), glue (≥ 1.6.2), rlang (≥ 1.1.0), sparsevctrs (≥ 0.2.0), tibble (≥ 3.2.1), vctrs (≥ 0.6.0)
Suggests: covr, crayon, devtools, knitr, Matrix, modeldata (≥ 0.0.2), recipes (≥ 1.0.5), rmarkdown (≥ 2.3), roxygen2, testthat (≥ 3.0.0), usethis (≥ 2.1.5), withr (≥ 3.0.0)
Published: 2025-08-20
DOI: 10.32614/CRAN.package.hardhat
Author: Hannah Frick ORCID iD [aut, cre], Davis Vaughan [aut], Max Kuhn [aut], Posit Software, PBC ROR ID [cph, fnd]
Maintainer: Hannah Frick
BugReports: https://github.com/tidymodels/hardhat/issues
License: MIT + file
URL: https://github.com/tidymodels/hardhat,https://hardhat.tidymodels.org
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: hardhat results

Documentation:

Downloads:

Reverse dependencies:

Reverse imports: accept, agua, applicable, baguette, brulee, card, censored, cuda.ml, dann, dials, healthyR.ts, important, ldmppr, lnmixsurv, modeltime, modeltime.resample, parsnip, probably, recipes, tabnet, tailor, text, themis, tidyclust, tidycmprsk, tidymodels, tune, vetiver, viralmodels, waywiser, workflows, workflowsets, yardstick
Reverse suggests: autostats, discrim, embed, healthyR.ai, mmrm, mrIML, orbital, shapr, textrecipes, tidysynthesis

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