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Merge pull request #63 from Boehringer-Ingelheim/299890-remove-groupings-on-start
299890 remove groupings on start
2 parents ae3bf20 + 6188db1 commit f187a04

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‎DESCRIPTION‎

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Package: dv.manager
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Type: Package
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Title: DaVinci Module Manager
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Version: 2.1.12-9000
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Version: 2.1.13-9000
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Authors@R: c(person("Boehringer-Ingelheim Pharma GmbH & Co.KG", role = c("cph", "fnd")),
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person('Luis', 'Morís Fernández', email = '[email protected]', role = c('cre', 'aut')),
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person('Sorin', 'Voicu', email = '[email protected]', role = c('aut')))

‎NEWS.md‎

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# dv.manager 2.1.13-9000
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- Ungroups all datasets and transform into `data.frame`
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# dv.manager 2.1.12-9000
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- Refactors UI

‎R/run_app.R‎

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@@ -69,7 +69,12 @@ run_app <- function(data = NULL,
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config <- list()
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config[["module_info"]] <- check_resolved_modules(process_module_list(module_list))
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# The automatic mapping will influence reporting when it is implemented in the future
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config[["data"]] <- char_vars_to_factor_vars_dataset_lists(check_data(dataset_lists))
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config[["data"]] <- local({
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check_data(dataset_lists)
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d <- char_vars_to_factor_vars_dataset_lists(dataset_lists)
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d <- ungroup2df_datasets_dataset_lists(d)
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d
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})
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config[["filter_data"]] <- check_filter_data(filter_data, dataset_lists)
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config[["filter_key"]] <- check_filter_key(filter_key, dataset_lists)
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config[["startup_msg"]] <- check_startup_msg(startup_msg)

‎R/utils_preproc.R‎

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@@ -45,3 +45,35 @@ char_vars_to_factor_vars_dataset_lists <- function(dataset_lists) { # nolintr
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}
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dataset_lists
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}
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decorate_ungroup2df_datasets_dataset_list <- function(f) { # nolintr
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function() {
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ungroup2df_datasets_dataset_list(f())
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}
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}
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ungroup2df_datasets_dataset_list <- function(dataset_list) { # nolintr
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dataset_names <- names(dataset_list)
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for (dataset_name in dataset_names) {
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dataset_list[[dataset_name]] <- as.data.frame( # Transform to base::data.frame, discards tibble related classes...
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dplyr::ungroup(dataset_list[[dataset_name]])
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)
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}
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dataset_list
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}
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ungroup2df_datasets_dataset_lists <- function(dataset_lists) { # nolintr
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dataset_list_names <- names(dataset_lists)
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for (dataset_list_name in dataset_list_names) {
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dataset_list <- dataset_lists[[dataset_list_name]]
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if (is.function(dataset_list)) {
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ungrouped_dataset_list <- decorate_ungroup2df_datasets_dataset_list(dataset_list)
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} else if (is.list(dataset_list)) {
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ungrouped_dataset_list <- ungroup2df_datasets_dataset_list(dataset_list)
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} else {
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stop("Unknown type")
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}
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dataset_lists[[dataset_list_name]] <- ungrouped_dataset_list
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}
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dataset_lists
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}

‎inst/validation/specs.R‎

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@@ -34,7 +34,7 @@ fs_spec <- specs_list(
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"selected_dataset_name_access" = "Modules will have access to the name of the selected dataset",
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"module_name_access" = "Modules will have access to its name and the name of the other modules",
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"modification_dates_access" = "Modules will have access to the earliest and latest modification dates of all the data tables.",
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"module_tab_switching" = "dv.manager allows programatically switching from one module tab to another",
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"module_tab_switching" = "dv.manager allows programatically switching from one module tab to another",
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"SSO_authentication_option" = "dv.manager provides the option to enable the authentication of App Users with SSO to access the app.",
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"empty_datasets" = "dv.manager supports datasets with 0 rows"
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)
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"dispatchers" = "- dispatchers: A dispatcher function that simplifies the acces to datasets from the module invocation in the module list.",
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"SSO_login_option" = "module manager offers the option of providing an SSO login. For this the app uses the AzureAuth package.",
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"AzureAuth_integration" = "module manager just passes the information to AzureAuth therefore no development testing is done at this level, as it requires an Azure AD in place and it is not available at build time in Jenkins.",
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"data_reloading" = "Module Manager allows reloading the data after a given amount of time. The data_reload parameter will be specified by the App Creator."
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"data_reloading" = "Module Manager allows reloading the data after a given amount of time. The data_reload parameter will be specified by the App Creator."
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)
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tab_group <- list(
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)
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preprocessing <- list(
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"char_to_factor_mapping" = "Module manager will automatically map character columns into factors for all the variables in all the datasets loaded in the app"
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"char_to_factor_mapping" = "Module manager will automatically map character columns into factors for all the variables in all the datasets loaded in the app",
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"ungroup_datasets" = "Module manager will automatically ungroup datasets",
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"tibble2df" = "Module manager will automatically transform tibble in data.frames"
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)
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specs <- c(

‎tests/testthat/test-utils-preproc.R‎

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@@ -52,10 +52,11 @@ local({
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test_that("char_vars_to_factor_vars respect lables" |>
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vdoc[["add_spec"]](c(specs$preprocessing$char_to_factor_mapping)), {
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r <- char_vars_to_factor_vars_dataset(dl)
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expect_identical(attr(e1[["char_var1"]], "label"), "char_var1_label")
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expect_identical(attr(r[["ds1"]][["char_var1"]], "label"), "char_var1_label")
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})
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test_that("decorate_char_vars_to_factor_vars_dataset_list decorates a functions that returns a list of data.frames and transforms character variables into factor variables", { # nolintr
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test_that("decorate_char_vars_to_factor_vars_dataset_list decorates a functions that returns a list of data.frames and transforms character variables into factor variables" |>
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vdoc[["add_spec"]](c(specs$preprocessing$char_to_factor_mapping)), { # nolintr
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f <- function() dl
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dec_f <- decorate_char_vars_to_factor_vars_dataset_list(f)
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e <- edl
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expect_identical(r[["config"]][["data"]][["dl2"]]()[["ds2"]], expected_dataset_lists[["dl2"]]()[["ds2"]])
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})
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})
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local({
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d <- data.frame(
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num = 1,
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fac = factor(c("fa"))
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)
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attr(d[["num"]], "label") <- "num_label"
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attr(d[["fac"]], "label") <- "fac_label"
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d1 <- dplyr::group_by(d, .data[["num"]])
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d2 <- tibble::as_tibble(d)
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d3 <- d
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dl <- list(ds1 = d1, ds2 = d2, ds3 = d3)
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edl <- list(ds1 = d, ds2 = d, ds3 = d)
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dataset_lists <- list(
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dl1 = dl,
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dl2 = function() dl
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)
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expected_dataset_lists <- list(
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dl1 = edl,
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dl2 = function() edl
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)
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test_that("ungroup2df_datasets_dataset_list ungroups and transforms into data.frames datasets in a dataset_list" |>
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vdoc[["add_spec"]](c(specs$preprocessing$ungroup_datasets, specs$preprocessing$tibble2df)), {
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r <- ungroup2df_datasets_dataset_list(dl)
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expect_identical(r, edl)
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})
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test_that("decorate_ungroup2df_datasets_dataset_list decorates a functions that returns a list of data.frames and ungroups and transforms into data.frames all datasets in the list" |>
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vdoc[["add_spec"]](c(specs$preprocessing$ungroup_datasets, specs$preprocessing$tibble2df)), { # nolintr
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f <- function() dl
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dec_f <- decorate_ungroup2df_datasets_dataset_list(f)
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e <- edl
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expect_identical(dec_f(), e)
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})
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test_that("ungroup2df_datasets_dataset_lists applies decorators and transformations to dataset_lists" |>
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vdoc[["add_spec"]](c(specs$preprocessing$ungroup_datasets, specs$preprocessing$tibble2df)), {
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r <- ungroup2df_datasets_dataset_lists(dataset_lists)
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expect_identical(r[["dl1"]][["ds1"]], expected_dataset_lists[["dl1"]][["ds1"]])
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expect_identical(r[["dl1"]][["ds2"]], expected_dataset_lists[["dl1"]][["ds2"]])
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expect_identical(r[["dl2"]]()[["ds1"]], expected_dataset_lists[["dl2"]]()[["ds1"]])
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expect_identical(r[["dl2"]]()[["ds2"]], expected_dataset_lists[["dl2"]]()[["ds2"]])
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})
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test_that("character variables are transformed into factors during run_app calls" |>
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vdoc[["add_spec"]](c(specs$preprocessing$ungroup_datasets, specs$preprocessing$tibble2df)), {
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r <- suppressMessages(
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suppressWarnings(
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run_app(dataset_lists, module_list = list(), filter_data = "ds1", filter_key = "num", .launch = FALSE)
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)
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)
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expect_identical(r[["config"]][["data"]][["dl1"]][["ds1"]], expected_dataset_lists[["dl1"]][["ds1"]])
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expect_identical(r[["config"]][["data"]][["dl1"]][["ds2"]], expected_dataset_lists[["dl1"]][["ds2"]])
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expect_identical(r[["config"]][["data"]][["dl2"]]()[["ds1"]], expected_dataset_lists[["dl2"]]()[["ds1"]])
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expect_identical(r[["config"]][["data"]][["dl2"]]()[["ds2"]], expected_dataset_lists[["dl2"]]()[["ds2"]])
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})
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})

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