tests/testthat/test_Tracker.R

In signaux-faibles/MLlogr:

context("Test Tracker")

test_database <- "unittest_mllogr"
test_collection <- "test_generic_tracker"
test_tracker <- Tracker$new(
  database = test_database,
  collection = test_collection,
  control = list(id_columns = c("a", "b"))
  )


test_that("md5 works.", {
  expect_equal(
    md5(data.frame(a = c(1, 2, 1), b = c(5, 4, 3))),
    "063643d0f4958e0af2f1a17acb1038fb"
    )
  expect_equal(
    md5(data.frame(a = c(2, 1, 1), b = c(4, 3, 5))),
    "063643d0f4958e0af2f1a17acb1038fb"
    )
  expect_false(
    md5(data.frame(a = c(2, 1, 1), b = c(5, 4, 3))) ==
    "063643d0f4958e0af2f1a17acb1038fb"
    )
  })

test_tracker$set(
      experiment_name = "experiment_name",
      experiment_description = "experiment_description",
      model = list(a = 1, "2", 3),
      model_name = "model_name",
      model_parameters = "model_parameters",
      model_features = "model_features",
      model_target = "model_target",
      model_performance = "model_performance",
      resampling_strategy = "resampling_strategy",
      preprocessing_strategy = "preprocessing_strategy",
      train_val_test_shares = "train_val_test_shares",
      test_frame = data.frame(a = c(1, 2, 1), b = c(5, 4, 3))
      )

test_that("log works.", {
   dbconnection <- mongolite::mongo(
     db = test_tracker$database,
     collection = test_tracker$collection
     )
   dbconnection$remove("{}")
   test_tracker$log()
   test_log <- dbconnection$find("{}")
   expect_true("timestamp" %in% names(test_log))
   expect_true("uuid" %in% names(test_log))
   expect_equal(
     test_log[, names(test_log) != c("timestamp", "uuid")],

     structure(list(
       experiment_name = list("experiment_name"),
       experiment_description = list("experiment_description"),
       model = structure(list(
         a = list(1),
         `2` = list("2"),
         `3` = list(3)
       ), class = "data.frame", row.names = 1L),
       model_name = list("model_name"),
       model_parameters = list("model_parameters"),
       model_features = list("model_features"),
       model_target = list("model_target"),
       model_performance = list("model_performance"),
       resampling_strategy = list("resampling_strategy"),
       preprocessing_strategy = list("preprocessing_strategy"),
       train_val_test_shares = list("train_val_test_shares"),
       test_frame = list("063643d0f4958e0af2f1a17acb1038fb")
     ), class = "data.frame", row.names = 1L)

     )
      })