skip_on_cran()
skip_if_not_installed("stacks")
skip_if_not_installed("plumber")
library(plumber)
library(stacks)
data("tree_frogs", package = "stacks")
tree_test <- tree_frogs %>%
dplyr::select(-hatched, -latency, -clutch)
frog_reg <-
stacks() %>%
add_candidates(reg_res_lr) %>%
add_candidates(reg_res_sp) %>%
blend_predictions(penalty = 20) %>%
fit_members()
v <- vetiver_model(frog_reg, "frog-stack")
test_that("can print stacks model", {
expect_snapshot(v)
})
test_that("can predict stacks model", {
preds <- predict(v, tree_test[2:10,])
expect_s3_class(preds, "tbl_df")
expect_equal(mean(preds$.pred), 142, tolerance = 1)
})
test_that("can pin a stacks model", {
b <- board_temp()
vetiver_pin_write(b, v)
pinned <- pin_read(b, "frog-stack")
expect_equal(
pinned,
list(
model = bundle::bundle(butcher::butcher(frog_reg)),
prototype = vctrs::vec_ptype(tree_test)
)
)
expect_equal(
pin_meta(b, "frog-stack")$user$required_pkgs,
c("glmnet", "parsnip", "recipes", "stacks", "stats", "workflows")
)
})
test_that("default OpenAPI spec", {
v$metadata <- list(url = "potatoes")
p <- pr() %>% vetiver_api(v)
frog_spec <- p$getApiSpec()
expect_equal(frog_spec$info$description,
"A regression stacked ensemble with 3 members")
post_spec <- frog_spec$paths$`/predict`$post
expect_equal(names(post_spec), c("summary", "requestBody", "responses"))
expect_equal(as.character(post_spec$summary),
"Return predictions from model using 4 features")
get_spec <- frog_spec$paths$`/pin-url`$get
expect_equal(as.character(get_spec$summary),
"Get URL of pinned vetiver model")
})
test_that("create plumber.R for stacks", {
skip_on_cran()
b <- board_folder(path = tmp_dir)
vetiver_pin_write(b, v)
tmp <- tempfile()
vetiver_write_plumber(b, "frog-stack", file = tmp)
expect_snapshot(
cat(readr::read_lines(tmp), sep = "\n"),
transform = redact_vetiver
)
})
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