Run Predictions Inside the Database R package tidypredict version 1.1.0 CRAN Task View: ModelDeployment (https://CRAN.R-project.org/view=ModelDeployment) It parses a fitted 'R' model object, and returns a formula in 'Tidy Eval' code that calculates the predictions. It works with several databases back-ends because it leverages 'dplyr' and 'dbplyr' for the final 'SQL' translation of the algorithm. It currently supports lm(), glm(), randomForest(), ranger(), rpart(), earth(), xgb.Booster.complete(), lgb.Booster(), catboost.Model(), cubist(), and ctree() models. Software Depends: R (>= 3.6) Imports: cli, dplyr (>= 0.7), generics, jsonlite, knitr, purrr, rlang (>= 1.1.1), tibble, tidyr Suggests: bonsai, covr, Cubist (>= 0.5.1), DBI, dbplyr, earth (>= 5.1.2), glmnet, lightgbm, methods, mlbench, modeldata, nycflights13, parsnip, partykit, randomForest, ranger (>= 0.14.1), rpart (>= 4.1.0), rmarkdown, RSQLite, survival, testthat (>= 3.2.0), withr, xgboost, yaml Emil Hvitfeldt <emil.hvitfeldt@posit.co> Comprehensive R Archive Network (CRAN) Emil Hvitfeldt [aut, cre], Edgar Ruiz [aut], Max Kuhn [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=tidypredict/LICENSE) 2026-02-27 application/tgz https://CRAN.R-project.org/package=tidypredict doi:10.32614/CRAN.package.tidypredict