Running ‘testthat.R’ [91s/143s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(tidypredict)
  > 
  > test_check("tidypredict")
  [ FAIL 11 | WARN 1 | SKIP 10 | PASS 91 ]
  
  ══ Skipped tests ═══════════════════════════════════════════════════════════════
  • On CRAN (10)
  
  ══ Failed tests ════════════════════════════════════════════════════════════════
  ── Error ('test-earth.R:13:3'): Simple models ──────────────────────────────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_false(test_earth(age ~ sibsp + parch, data = etitanic)) at test-earth.R:13:2
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. ├─tidypredict (local) test_earth(age ~ sibsp + parch, data = etitanic)
    5. │ ├─tidypredict::tidypredict_test(earth::earth(...), df = .data) at test-earth.R:6:2
    6. │ └─tidypredict:::tidypredict_test.default(earth::earth(...), df = .data)
    7. │   └─tidypredict:::tidypredict_test_default(...)
    8. │     └─tidypredict::tidypredict_to_column(...)
    9. │       ├─tidypredict::tidypredict_fit(model)
   10. │       └─tidypredict:::tidypredict_fit.earth(model)
   11. │         ├─tidypredict::parse_model(model)
   12. │         └─tidypredict:::parse_model.earth(model)
   13. │           └─tidypredict:::mars_terms(model, is_glm)
   14. │             └─... %>% purrr::pluck("final")
   15. ├─purrr::pluck(., "final")
   16. │ └─purrr:::pluck_raw(.x, list2(...), .default = .default)
   17. ├─dplyr::summarize(...)
   18. ├─dplyr::group_by(., feature, feature_num)
   19. ├─dplyr::mutate(...)
   20. ├─dplyr::rowwise(.)
   21. ├─dplyr::left_join(., term_to_column, by = "term")
   22. ├─dplyr::arrange(., feature_num)
   23. ├─dplyr::mutate(...)
   24. ├─dplyr::right_join(., feature_coefs, by = "feature")
   25. └─dplyr:::right_join.data.frame(., feature_coefs, by = "feature")
   26.   └─dplyr:::join_mutate(...)
   27.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   28.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   29.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   30.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   31.           ├─base::withCallingHandlers(...)
   32.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-earth.R:19:3'): Less simple models w categorical vars ──────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_false(test_earth(age ~ ., data = etitanic)) at test-earth.R:19:2
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. ├─tidypredict (local) test_earth(age ~ ., data = etitanic)
    5. │ ├─tidypredict::tidypredict_test(earth::earth(...), df = .data) at test-earth.R:6:2
    6. │ └─tidypredict:::tidypredict_test.default(earth::earth(...), df = .data)
    7. │   └─tidypredict:::tidypredict_test_default(...)
    8. │     └─tidypredict::tidypredict_to_column(...)
    9. │       ├─tidypredict::tidypredict_fit(model)
   10. │       └─tidypredict:::tidypredict_fit.earth(model)
   11. │         ├─tidypredict::parse_model(model)
   12. │         └─tidypredict:::parse_model.earth(model)
   13. │           └─tidypredict:::mars_terms(model, is_glm)
   14. │             └─... %>% purrr::pluck("final")
   15. ├─purrr::pluck(., "final")
   16. │ └─purrr:::pluck_raw(.x, list2(...), .default = .default)
   17. ├─dplyr::summarize(...)
   18. ├─dplyr::group_by(., feature, feature_num)
   19. ├─dplyr::mutate(...)
   20. ├─dplyr::rowwise(.)
   21. ├─dplyr::left_join(., term_to_column, by = "term")
   22. ├─dplyr::arrange(., feature_num)
   23. ├─dplyr::mutate(...)
   24. ├─dplyr::right_join(., feature_coefs, by = "feature")
   25. └─dplyr:::right_join.data.frame(., feature_coefs, by = "feature")
   26.   └─dplyr:::join_mutate(...)
   27.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   28.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   29.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   30.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   31.           ├─base::withCallingHandlers(...)
   32.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-earth.R:25:3'): Models w degree work ───────────────────────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_false(...) at test-earth.R:25:2
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. ├─tidypredict (local) test_earth(age ~ sibsp + parch, data = etitanic, degree = 2)
    5. │ ├─tidypredict::tidypredict_test(earth::earth(...), df = .data) at test-earth.R:6:2
    6. │ └─tidypredict:::tidypredict_test.default(earth::earth(...), df = .data)
    7. │   └─tidypredict:::tidypredict_test_default(...)
    8. │     └─tidypredict::tidypredict_to_column(...)
    9. │       ├─tidypredict::tidypredict_fit(model)
   10. │       └─tidypredict:::tidypredict_fit.earth(model)
   11. │         ├─tidypredict::parse_model(model)
   12. │         └─tidypredict:::parse_model.earth(model)
   13. │           └─tidypredict:::mars_terms(model, is_glm)
   14. │             └─... %>% purrr::pluck("final")
   15. ├─purrr::pluck(., "final")
   16. │ └─purrr:::pluck_raw(.x, list2(...), .default = .default)
   17. ├─dplyr::summarize(...)
   18. ├─dplyr::group_by(., feature, feature_num)
   19. ├─dplyr::mutate(...)
   20. ├─dplyr::rowwise(.)
   21. ├─dplyr::left_join(., term_to_column, by = "term")
   22. ├─dplyr::arrange(., feature_num)
   23. ├─dplyr::mutate(...)
   24. ├─dplyr::right_join(., feature_coefs, by = "feature")
   25. └─dplyr:::right_join.data.frame(., feature_coefs, by = "feature")
   26.   └─dplyr:::join_mutate(...)
   27.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   28.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   29.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   30.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   31.           ├─base::withCallingHandlers(...)
   32.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-earth.R:35:3'): Most pmethods work ─────────────────────────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─base::lapply(...) at test-earth.R:35:2
    2. │ └─tidypredict (local) FUN(X[[i]], ...)
    3. │   ├─testthat::expect_false(...) at test-earth.R:38:6
    4. │   │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    5. │   │   └─rlang::eval_bare(expr, quo_get_env(quo))
    6. │   └─tidypredict (local) test_earth(age ~ sibsp + parch, data = etitanic, pmethod = x)
    7. │     ├─tidypredict::tidypredict_test(earth::earth(...), df = .data) at test-earth.R:6:2
    8. │     └─tidypredict:::tidypredict_test.default(earth::earth(...), df = .data)
    9. │       └─tidypredict:::tidypredict_test_default(...)
   10. │         └─tidypredict::tidypredict_to_column(...)
   11. │           ├─tidypredict::tidypredict_fit(model)
   12. │           └─tidypredict:::tidypredict_fit.earth(model)
   13. │             ├─tidypredict::parse_model(model)
   14. │             └─tidypredict:::parse_model.earth(model)
   15. │               └─tidypredict:::mars_terms(model, is_glm)
   16. │                 └─... %>% purrr::pluck("final")
   17. ├─purrr::pluck(., "final")
   18. │ └─purrr:::pluck_raw(.x, list2(...), .default = .default)
   19. ├─dplyr::summarize(...)
   20. ├─dplyr::group_by(., feature, feature_num)
   21. ├─dplyr::mutate(...)
   22. ├─dplyr::rowwise(.)
   23. ├─dplyr::left_join(., term_to_column, by = "term")
   24. ├─dplyr::arrange(., feature_num)
   25. ├─dplyr::mutate(...)
   26. ├─dplyr::right_join(., feature_coefs, by = "feature")
   27. └─dplyr:::right_join.data.frame(., feature_coefs, by = "feature")
   28.   └─dplyr:::join_mutate(...)
   29.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   30.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   31.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   32.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   33.           ├─base::withCallingHandlers(...)
   34.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-earth.R:47:3'): simple binomial works ──────────────────────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_false(...) at test-earth.R:47:2
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. ├─tidypredict (local) test_earth(...)
    5. │ ├─tidypredict::tidypredict_test(earth::earth(...), df = .data) at test-earth.R:6:2
    6. │ └─tidypredict:::tidypredict_test.default(earth::earth(...), df = .data)
    7. │   └─tidypredict:::tidypredict_test_default(...)
    8. │     └─tidypredict::tidypredict_to_column(...)
    9. │       ├─tidypredict::tidypredict_fit(model)
   10. │       └─tidypredict:::tidypredict_fit.earth(model)
   11. │         ├─tidypredict::parse_model(model)
   12. │         └─tidypredict:::parse_model.earth(model)
   13. │           └─tidypredict:::mars_terms(model, is_glm)
   14. │             └─... %>% purrr::pluck("final")
   15. ├─purrr::pluck(., "final")
   16. │ └─purrr:::pluck_raw(.x, list2(...), .default = .default)
   17. ├─dplyr::summarize(...)
   18. ├─dplyr::group_by(., feature, feature_num)
   19. ├─dplyr::mutate(...)
   20. ├─dplyr::rowwise(.)
   21. ├─dplyr::left_join(., term_to_column, by = "term")
   22. ├─dplyr::arrange(., feature_num)
   23. ├─dplyr::mutate(...)
   24. ├─dplyr::right_join(., feature_coefs, by = "feature")
   25. └─dplyr:::right_join.data.frame(., feature_coefs, by = "feature")
   26.   └─dplyr:::join_mutate(...)
   27.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   28.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   29.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   30.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   31.           ├─base::withCallingHandlers(...)
   32.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-earth.R:56:3'): complex binomial w/ degree works ───────────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_false(...) at test-earth.R:56:2
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. ├─tidypredict (local) test_earth(...)
    5. │ ├─tidypredict::tidypredict_test(earth::earth(...), df = .data) at test-earth.R:6:2
    6. │ └─tidypredict:::tidypredict_test.default(earth::earth(...), df = .data)
    7. │   └─tidypredict:::tidypredict_test_default(...)
    8. │     └─tidypredict::tidypredict_to_column(...)
    9. │       ├─tidypredict::tidypredict_fit(model)
   10. │       └─tidypredict:::tidypredict_fit.earth(model)
   11. │         ├─tidypredict::parse_model(model)
   12. │         └─tidypredict:::parse_model.earth(model)
   13. │           └─tidypredict:::mars_terms(model, is_glm)
   14. │             └─... %>% purrr::pluck("final")
   15. ├─purrr::pluck(., "final")
   16. │ └─purrr:::pluck_raw(.x, list2(...), .default = .default)
   17. ├─dplyr::summarize(...)
   18. ├─dplyr::group_by(., feature, feature_num)
   19. ├─dplyr::mutate(...)
   20. ├─dplyr::rowwise(.)
   21. ├─dplyr::left_join(., term_to_column, by = "term")
   22. ├─dplyr::arrange(., feature_num)
   23. ├─dplyr::mutate(...)
   24. ├─dplyr::right_join(., feature_coefs, by = "feature")
   25. └─dplyr:::right_join.data.frame(., feature_coefs, by = "feature")
   26.   └─dplyr:::join_mutate(...)
   27.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   28.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   29.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   30.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   31.           ├─base::withCallingHandlers(...)
   32.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-earth.R:66:3'): Most pmethods work ─────────────────────────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─base::lapply(...) at test-earth.R:66:2
    2. │ └─tidypredict (local) FUN(X[[i]], ...)
    3. │   └─tidypredict (local) test_earth(...) at test-earth.R:69:6
    4. │     ├─tidypredict::tidypredict_test(earth::earth(...), df = .data) at test-earth.R:6:2
    5. │     └─tidypredict:::tidypredict_test.default(earth::earth(...), df = .data)
    6. │       └─tidypredict:::tidypredict_test_default(...)
    7. │         └─tidypredict::tidypredict_to_column(...)
    8. │           ├─tidypredict::tidypredict_fit(model)
    9. │           └─tidypredict:::tidypredict_fit.earth(model)
   10. │             ├─tidypredict::parse_model(model)
   11. │             └─tidypredict:::parse_model.earth(model)
   12. │               └─tidypredict:::mars_terms(model, is_glm)
   13. │                 └─... %>% purrr::pluck("final")
   14. ├─purrr::pluck(., "final")
   15. │ └─purrr:::pluck_raw(.x, list2(...), .default = .default)
   16. ├─dplyr::summarize(...)
   17. ├─dplyr::group_by(., feature, feature_num)
   18. ├─dplyr::mutate(...)
   19. ├─dplyr::rowwise(.)
   20. ├─dplyr::left_join(., term_to_column, by = "term")
   21. ├─dplyr::arrange(., feature_num)
   22. ├─dplyr::mutate(...)
   23. ├─dplyr::right_join(., feature_coefs, by = "feature")
   24. └─dplyr:::right_join.data.frame(., feature_coefs, by = "feature")
   25.   └─dplyr:::join_mutate(...)
   26.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   27.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   28.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   29.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   30.           ├─base::withCallingHandlers(...)
   31.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-earth.R:81:3'): first degree earth model with different interfaces ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(tidypredict_fit(f_mod_1), iris) at test-earth.R:81:2
    2. ├─tidypredict::tidypredict_fit(f_mod_1)
    3. ├─tidypredict:::tidypredict_fit.earth(f_mod_1)
    4. │ ├─tidypredict::parse_model(model)
    5. │ └─tidypredict:::parse_model.earth(model)
    6. │   └─tidypredict:::mars_terms(model, is_glm)
    7. │     └─... %>% purrr::pluck("final")
    8. ├─purrr::pluck(., "final")
    9. │ └─purrr:::pluck_raw(.x, list2(...), .default = .default)
   10. ├─dplyr::summarize(...)
   11. ├─dplyr::group_by(., feature, feature_num)
   12. ├─dplyr::mutate(...)
   13. ├─dplyr::rowwise(.)
   14. ├─dplyr::left_join(., term_to_column, by = "term")
   15. ├─dplyr::arrange(., feature_num)
   16. ├─dplyr::mutate(...)
   17. ├─dplyr::right_join(., feature_coefs, by = "feature")
   18. └─dplyr:::right_join.data.frame(., feature_coefs, by = "feature")
   19.   └─dplyr:::join_mutate(...)
   20.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   21.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   22.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   23.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   24.           ├─base::withCallingHandlers(...)
   25.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-earth.R:94:3'): 2nd degree earth model with different interfaces ──
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─rlang::eval_tidy(tidypredict_fit(f_mod_2), iris) at test-earth.R:94:2
    2. ├─tidypredict::tidypredict_fit(f_mod_2)
    3. ├─tidypredict:::tidypredict_fit.earth(f_mod_2)
    4. │ ├─tidypredict::parse_model(model)
    5. │ └─tidypredict:::parse_model.earth(model)
    6. │   └─tidypredict:::mars_terms(model, is_glm)
    7. │     └─... %>% purrr::pluck("final")
    8. ├─purrr::pluck(., "final")
    9. │ └─purrr:::pluck_raw(.x, list2(...), .default = .default)
   10. ├─dplyr::summarize(...)
   11. ├─dplyr::group_by(., feature, feature_num)
   12. ├─dplyr::mutate(...)
   13. ├─dplyr::rowwise(.)
   14. ├─dplyr::left_join(., term_to_column, by = "term")
   15. ├─dplyr::arrange(., feature_num)
   16. ├─dplyr::mutate(...)
   17. ├─dplyr::right_join(., feature_coefs, by = "feature")
   18. └─dplyr:::right_join.data.frame(., feature_coefs, by = "feature")
   19.   └─dplyr:::join_mutate(...)
   20.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   21.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   22.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   23.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   24.           ├─base::withCallingHandlers(...)
   25.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-earth.R:115:3'): Tests with parsnip returns no alert ───────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─testthat::expect_false(...) at test-earth.R:115:2
    2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
    3. │   └─rlang::eval_bare(expr, quo_get_env(quo))
    4. ├─tidypredict::tidypredict_test(...)
    5. ├─tidypredict:::tidypredict_test.model_fit(...)
    6. │ ├─tidypredict::tidypredict_test(...)
    7. │ └─tidypredict:::tidypredict_test.default(...)
    8. │   └─tidypredict:::tidypredict_test_default(...)
    9. │     └─tidypredict::tidypredict_to_column(...)
   10. │       ├─tidypredict::tidypredict_fit(model)
   11. │       └─tidypredict:::tidypredict_fit.earth(model)
   12. │         ├─tidypredict::parse_model(model)
   13. │         └─tidypredict:::parse_model.earth(model)
   14. │           └─tidypredict:::mars_terms(model, is_glm)
   15. │             └─... %>% purrr::pluck("final")
   16. ├─purrr::pluck(., "final")
   17. │ └─purrr:::pluck_raw(.x, list2(...), .default = .default)
   18. ├─dplyr::summarize(...)
   19. ├─dplyr::group_by(., feature, feature_num)
   20. ├─dplyr::mutate(...)
   21. ├─dplyr::rowwise(.)
   22. ├─dplyr::left_join(., term_to_column, by = "term")
   23. ├─dplyr::arrange(., feature_num)
   24. ├─dplyr::mutate(...)
   25. ├─dplyr::right_join(., feature_coefs, by = "feature")
   26. └─dplyr:::right_join.data.frame(., feature_coefs, by = "feature")
   27.   └─dplyr:::join_mutate(...)
   28.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   29.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   30.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   31.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   32.           ├─base::withCallingHandlers(...)
   33.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  ── Error ('test-earth.R:163:3'): Model can be saved and re-loaded ──────────────
  Error in `vectbl_assign(x[[j]], i, recycled_value[[j]])`: DLL requires the use of native symbols
  Backtrace:
       ▆
    1. ├─yaml::write_yaml(parse_model(model), mp) at test-earth.R:163:2
    2. │ └─yaml::as.yaml(x, ...)
    3. ├─tidypredict::parse_model(model)
    4. ├─tidypredict:::parse_model.earth(model)
    5. │ └─tidypredict:::mars_terms(model, is_glm)
    6. │   └─... %>% purrr::pluck("final")
    7. ├─purrr::pluck(., "final")
    8. │ └─purrr:::pluck_raw(.x, list2(...), .default = .default)
    9. ├─dplyr::summarize(...)
   10. ├─dplyr::group_by(., feature, feature_num)
   11. ├─dplyr::mutate(...)
   12. ├─dplyr::rowwise(.)
   13. ├─dplyr::left_join(., term_to_column, by = "term")
   14. ├─dplyr::arrange(., feature_num)
   15. ├─dplyr::mutate(...)
   16. ├─dplyr::right_join(., feature_coefs, by = "feature")
   17. └─dplyr:::right_join.data.frame(., feature_coefs, by = "feature")
   18.   └─dplyr:::join_mutate(...)
   19.     ├─base::`[<-`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   20.     └─tibble:::`[<-.tbl_df`(`*tmp*`, new_rows, merge, value = `<tibble[,1]>`)
   21.       └─tibble:::tbl_subassign(x, i, j, value, i_arg, j_arg, substitute(value))
   22.         └─tibble:::tbl_subassign_row(xj, i, value, i_arg, value_arg, call)
   23.           ├─base::withCallingHandlers(...)
   24.           └─tibble:::vectbl_assign(x[[j]], i, recycled_value[[j]])
  
  [ FAIL 11 | WARN 1 | SKIP 10 | PASS 91 ]
  Error: Test failures
  Execution halted