471 remove CodeClass from FilteredData

NEWS.md

@@ -1,4 +1,4 @@
-# teal.slice 0.4.0.9022
+# teal.slice 0.4.0.9023
 
 ### Miscellaneous
 
@@ -27,6 +27,7 @@
 * Setting filters using a list is now deprecated. Use `teal_slices` and `teal_slice` instead.
 * Removed `CDISCFilteredData` and `CDISCFilteredDataset` and implementing `JoinKeys` handling in their parent classes (`FilteredData` and `DefaultFilteredDataset`).
 * Specifying set of filterable columns is done through `include_varnames` and `exclude_varnames` in `teal_slices`. Specifying `attr(, "filterable")` is hard deprecated.
+* Removed private fields `$code` and `$check` from `FilteredData` class and made appropriate changes to constructor and `init_filtered_data`.
 
 # teal.slice 0.3.0
 

R/FilteredData-utils.R

@@ -60,12 +60,10 @@ init_filtered_data.TealData <- function(x, # nolint
 
 #' @keywords internal
 #' @export
-init_filtered_data.default <- function(x, join_keys = teal.data::join_keys(), code = NULL, check = FALSE) { # nolint
+init_filtered_data.default <- function(x, join_keys = teal.data::join_keys(), code, check) { # nolint
   checkmate::assert_list(x, any.missing = FALSE, names = "unique")
-  checkmate::assert_class(code, "CodeClass", null.ok = TRUE)
   checkmate::assert_class(join_keys, "join_keys")
-  checkmate::assert_flag(check)
-  FilteredData$new(x, join_keys = join_keys, code = code, check = check)
+  FilteredData$new(x, join_keys = join_keys)
 }
 
 #' Validate dataset arguments

R/FilteredData.R

@@ -68,20 +68,11 @@ FilteredData <- R6::R6Class( # nolint
     #'   should named elements containing `data.frame` or `MultiAssayExperiment`.
     #'   Names of the list will serve as `dataname`.
     #' @param join_keys (`join_keys` or NULL) see [`teal.data::join_keys()`].
-    #' @param code (`CodeClass` or `NULL`) see [`teal.data::CodeClass`].
-    #' @param check (`logical(1)`) whether data has been check against reproducibility.
     #'
-    initialize = function(data_objects, join_keys = teal.data::join_keys(), code = NULL, check = FALSE) {
+    initialize = function(data_objects, join_keys = teal.data::join_keys()) {
       checkmate::assert_list(data_objects, any.missing = FALSE, min.len = 0, names = "unique")
       # Note the internals of data_objects are checked in set_dataset
       checkmate::assert_class(join_keys, "join_keys")
-      checkmate::assert_class(code, "CodeClass", null.ok = TRUE)
-      checkmate::assert_flag(check)
-
-      self$set_check(check)
-      if (!is.null(code)) {
-        self$set_code(code)
-      }
 
       self$set_join_keys(join_keys)
       child_parent <- sapply(
@@ -210,21 +201,6 @@ FilteredData <- R6::R6Class( # nolint
       private$get_filtered_dataset(dataname)$get_call()
     },
 
-    #' @description
-    #' Gets the R preprocessing code string that generates the unfiltered datasets.
-    #'
-    #' @param dataname (`character(1)`) name(s) of dataset(s)
-    #'
-    #' @return (`character(1)`) deparsed code
-    #'
-    get_code = function(dataname = self$datanames()) {
-      if (!is.null(private$code)) {
-        paste0(private$code$get_code(dataname), collapse = "\n")
-      } else {
-        paste0("# No pre-processing code provided")
-      }
-    },
-
     #' @description
     #' Gets filtered or unfiltered dataset.
     #'
@@ -241,15 +217,6 @@ FilteredData <- R6::R6Class( # nolint
       if (filtered) data() else data
     },
 
-    #' @description
-    #' Returns whether the datasets in the object has undergone a reproducibility check.
-    #'
-    #' @return `logical`
-    #'
-    get_check = function() {
-      private$.check
-    },
-
     #' @description
     #' Gets metadata for a given dataset.
     #'
@@ -375,34 +342,6 @@ FilteredData <- R6::R6Class( # nolint
       invisible(self)
     },
 
-    #' @description
-    #' Sets whether the datasets in the object have undergone a reproducibility check.
-    #'
-    #' @param check (`logical`) whether datasets have undergone reproducibility check
-    #'
-    #' @return (`self`)
-    #'
-    set_check = function(check) {
-      checkmate::assert_flag(check)
-      private$.check <- check
-      invisible(self)
-    },
-
-    #' @description
-    #' Sets the R preprocessing code for single dataset.
-    #'
-    #' @param code (`CodeClass`)\cr
-    #'   preprocessing code that can be parsed to generate the unfiltered datasets
-    #'
-    #' @return (`self`)
-    #'
-    set_code = function(code) {
-      checkmate::assert_class(code, "CodeClass")
-      logger::log_trace("FilteredData$set_code setting code")
-      private$code <- code
-      invisible(self)
-    },
-
     # Functions useful for restoring from another dataset ----
 
     #' @description
@@ -1071,12 +1010,6 @@ FilteredData <- R6::R6Class( # nolint
     # activate/deactivate filter panel
     filter_panel_active = TRUE,
 
-    # whether the datasets had a reproducibility check
-    .check = FALSE,
-
-    # preprocessing code used to generate the unfiltered datasets as a string
-    code = NULL,
-
     # `reactive` containing teal_slices that can be selected; only active in module-specific mode
     available_teal_slices = NULL,
 

R/zzz.R

@@ -43,6 +43,7 @@
   plotly::plot_ly
   shinycssloaders::withSpinner
   shinyWidgets::pickerOptions
+  teal.data::datanames
   teal.widgets::optionalSelectInput
 }
 

inst/WORDLIST

@@ -1,11 +1,11 @@
+cloneable
 Forkers
+funder
 Hoffmann
 MultiAssayExperiment
-UI
-cloneable
-funder
 programmatically
 repo
 reproducibility
 subclasses
 subtype
+UI

tests/testthat/test-FilteredData.R

@@ -22,50 +22,6 @@ testthat::test_that("constructor accepts join_keys to be join_keys or NULL", {
   )
 })
 
-testthat::test_that("constructor accepts code to be CodeClass or NULL", {
-  mockcodeclass <- R6::R6Class(classname = "CodeClass")
-  testthat::expect_no_error(
-    FilteredData$new(list(iris = list(dataset = iris)), code = mockcodeclass$new())
-  )
-  testthat::expect_no_error(
-    FilteredData$new(list(iris = list(dataset = iris)), code = NULL)
-  )
-  testthat::expect_error(
-    FilteredData$new(list(iris = list(dataset = iris)), code = list(), "Assertion on 'code' failed")
-  )
-})
-
-testthat::test_that("constructor accepts check to be a flag", {
-  testthat::expect_no_error(
-    FilteredData$new(list(iris = list(dataset = iris)), check = TRUE)
-  )
-  testthat::expect_error(
-    FilteredData$new(list(iris = list(dataset = iris)), check = NULL, "Assertion on 'check' failed")
-  )
-  testthat::expect_error(
-    FilteredData$new(list(iris = list(dataset = iris)), check = logical(0), "Assertion on 'check' failed")
-  )
-})
-
-testthat::test_that("FilteredData preserves the check field when check is TRUE", {
-  code <- teal.data:::CodeClass$new()$set_code("df_1 <- data.frame(x = 1:10)")
-
-  filtered_data <- FilteredData$new(
-    list("df_1" = list(dataset = data.frame(x = 1:10))),
-    code = code,
-    check = FALSE
-  )
-  testthat::expect_false(filtered_data$get_check())
-
-  filtered_data <- FilteredData$new(
-    list("df_1" = list(dataset = data.frame(x = 1:10))),
-    code = code,
-    check = TRUE
-  )
-  testthat::expect_true(filtered_data$get_check())
-})
-
-
 # datanames ----
 testthat::test_that("filtered_data$datanames returns character vector of datasets names", {
   dataset <- list(dataset = iris)
@@ -207,23 +163,6 @@ testthat::test_that("get_metadata returns metadata if dataset exists", {
 })
 
 
-# get_code ----
-testthat::test_that("get_code returns the code passed to CodeClass$set_code", {
-  code <- teal.data:::CodeClass$new()
-  code$set_code("'preprocessing code'", "iris")
-  filtered_data <- FilteredData$new(
-    list(iris = list(dataset = head(iris))),
-    code = code
-  )
-  testthat::expect_equal(filtered_data$get_code(), "\"preprocessing code\"")
-})
-
-testthat::test_that("get_code returns a string when FilteredData has no code", {
-  filtered_data <- FilteredData$new(data_objects = list())
-  testthat::expect_identical(filtered_data$get_code(), "# No pre-processing code provided")
-})
-
-
 # get_call ----
 testthat::test_that("get_call returns a NULL if no filters applied", {
   datasets <- FilteredData$new(