Pre-release activities

.github/ISSUE_TEMPLATE/cran-release.yaml

@@ -0,0 +1,124 @@
+---
+name: 🎉 CRAN Release
+description: Template for release to CRAN
+title: "[Release]: <version>"
+labels: ["release"]
+assignees:
+  - KlaudiaBB
+  - cicdguy
+  - shajoezhu
+body:
+  - type: markdown
+    attributes:
+      value: |
+        ⚠️ Please do not link or mention any internal references in this issue. This includes internal URLs, intellectual property and references.
+  - type: textarea
+    id: blocked-by
+    attributes:
+      label: Blocked by
+      description: Any PRs or issues that this release is blocked by.
+      placeholder: Add a list of blocking PRs or issues here.
+      value: |
+        ### PRs
+
+        - [ ] PR 1
+
+        ### Issues
+
+        - [ ] Issue 1
+    validations:
+      required: true
+  - type: textarea
+    id: pre-release
+    attributes:
+      label: Pre-release
+      description: Pre-requisites that must be fulfilled before initiating the release process.
+      placeholder: Add your list of pre-requisites here.
+      value: |
+        - [ ] Make sure you adhere to CRAN submission policy: https://cran.r-project.org/web/packages/submission_checklist.html; https://cran.r-project.org/web/packages/policies.html.
+        - [ ] Make sure that high priority bugs (label "priority" + "bug") have been resolved before going into the release.
+        - [ ] Review old/hanging PRs before going into the release (Optional).
+        - [ ] Revisit R-package's lifecycle badges (Optional).
+        - [ ] Make sure that all upstream dependencies of this package that need to be submitted to CRAN were accepted before going into release activities.
+        - [ ] Make sure integration tests are green 2-3 days before the release. Look carefully through logs (check for warnings and notes).
+        - [ ] Decide what gets merged in before starting release activities.
+  - type: textarea
+    id: release
+    attributes:
+      label: Release
+      description: The steps to be taken in order to create a release.
+      placeholder: Steps to create a release.
+      value: |
+        ### Prepare the release
+
+        - [ ] Create a new release candidate branch
+          `git checkout -b release-candidate-vX.Y.Z`
+        - [ ] Update NEWS.md file: make sure it reflects a holistic summary of what has changed in the package.
+        - [ ] Remove the additional fields (`Remotes`) from the DESCRIPTION file where applicable.
+        - [ ] Make sure that the minimum dependency versions are updated in the DESCRIPTION file for the package and its reverse dependencies (Optional).
+          - [ ] Increase versioned dependency on {package name} to >=X.Y.Z (Optional).
+        - [ ] Commit your changes and create the PR on GitHub (add "[skip vbump]" in the PR title). Add all updates, commit, and push changes:
+          `# Make the necessary modifications to your files
+          # Stage the changes
+          git add <files your modified>
+          # Commit the changes
+          git commit -m "[skip vbump] <Your commit message>"
+          git push origin release-candidate-vX.Y.Z`
+
+        ### Test the release
+
+        - [ ] Execute the manual tests on Shiny apps that are deployed on various hosting providers (Posit connect and shinyapps.io) - track the results in GitHub issue (Applicable only for frameworks that use Shiny).
+        - [ ] Monitor integration tests, if integration fails, create priority issues on the board.
+        - [ ] Execute UAT tests (Optional).
+
+        ### CRAN submission
+
+        - [ ] Tag the update(s) as a release candidate vX.Y.Z-rc<iteration-number> (e.g. v0.5.3-rc1) on the release candidate branch (release-candidate-vX.Y.Z).
+          `# Create rc tag for submission for internal validation
+          git tag vX.Y.Z-rc<iteration number>
+          git push origin vX.Y.Z-rc<iteration number>`
+        - [ ] Build the package locally using the command:`R CMD build .` which will generate a .tar.gz file necessary for the CRAN submission.
+        - [ ] Submit the package to https://win-builder.r-project.org/upload.aspx for testing, for more details please see "Building and checking R source packages for Windows": https://win-builder.r-project.org/.
+        - [ ] Once tested, send the package that was built in the previous steps to CRAN via this form: https://cran.r-project.org/submit.html.
+        - [ ] Address CRAN feedback, tag the package vX.Y.Z-rc(n+1) and repeat the submission to CRAN whenever necessary.
+        - [ ] Get the package accepted and published on CRAN.
+
+        ### Tag the release
+
+        - [ ] If the additional fields were removed, add them back in a separate PR, and then merge the PR back to main (add "[skip vbump]" in the PR title). If nothing was removed just merge the PR you created in the "Prepare the release" section to 'main'. Note the commit hash of the merged commit. **Note:** additional commits might be added to the `main` branch by a bot or an automation - we do **NOT** want to tag this commit.
+
+        ### Make sure of the following before continuing
+
+        - [ ] CI checks are passing in GH before releasing the package.
+        - [ ] Shiny apps are deployable and there are no errors/warnings (Applicable only for frameworks that use Shiny).
+
+        - [ ] Create a git tag with the final version set to vX.Y.Z on the main branch. In order to do this:
+          1. Checkout the commit hash.
+          `git checkout <commit hash>`
+          2. Tag the hash with the release version (vX.Y.Z).
+          `git tag vX.Y.Z`
+          3. Push the tag to make the final release.
+          `git push origin vX.Y.Z`
+        - [ ] Update downstream package dependencies to (>=X.Y.Z) in {package name}.
+        Note: Once the release tag is created, the package is automatically published to internal repositories.
+  - type: textarea
+    id: post-release
+    attributes:
+      label: Post-release
+      description: The list of activities to be completed after the release.
+      placeholder: The steps that must be taken after the release.
+      value: |
+        - [ ] Ensure that CRAN checks are passing for the package.
+        - [ ] Make sure that the package is published to internal repositories.
+        - [ ] Make sure internal documentation is up to date.
+        - [ ] Review and update installation instructions for the package wherever needed (Optional).
+        - [ ] Update all integration tests to reference the new release.
+        - [ ] Announce the release on ________.
+  - type: textarea
+    id: decision-tree
+    attributes:
+      label: Decision tree
+      description: Any decision tree(s) that would aid release management
+      placeholder: Any decision tree(s) that would aid release management.
+      value: |
+        Click [here](https://github.com/insightsengineering/.github/blob/main/.github/ISSUE_TEMPLATE/RELEASE_DECISION_TREE.md) to see the release decision tree.

R/cdisc_data.R

@@ -26,8 +26,8 @@
 #' )
 #'
 #' data <- within(data, {
-#'   ADSL <- teal.data::example_cdisc_data("ADSL")
-#'   ADTTE <- teal.data::example_cdisc_data("ADTTE")
+#'   ADSL <- example_cdisc_data("ADSL")
+#'   ADTTE <- example_cdisc_data("ADTTE")
 #' })
 #'
 cdisc_data <- function(...,

R/deprecated.R

@@ -339,8 +339,9 @@ get_join_keys <- function(data) {
 }
 
 #' @rdname col_labels
-#' @inheritParams col_labels
-#' @param data a data.frame object
+#' @param data a `data.frame` object
+#' @param fill (`logical(1)`) boolean in case the `label` attribute does not exist if
+#'   `TRUE` the variable names is returned, otherwise `NA`.Default is `FALSE`.
 #' @export
 get_labels <- function(data, fill = TRUE) {
   lifecycle::deprecate_stop(

R/formatters_var_labels.R

@@ -1,12 +1,12 @@
-#' Get Label Attributes of Variables in a \code{data.frame}
+#' Get Label Attributes of Variables in a `data.frame`
 #'
-#' Variable labels can be stored as a \code{label} attribute for each variable.
+#' Variable labels can be stored as a `label` attribute for each variable.
 #' This functions returns a named character vector with the variable labels
 #' (empty sting if not specified)
 #'
-#' @param x a \code{data.frame} object
-#' @param fill boolean in case the \code{label} attribute does not exist if
-#'   \code{TRUE} the variable names is returned, otherwise \code{NA}
+#' @param x a `data.frame` object
+#' @param fill (`logical(1)`) boolean in case the `label` attribute does not exist if
+#'   `TRUE` the variable names is returned, otherwise `NA`.Default is `FALSE`.
 #'
 #' @source This function was taken 1-1 from
 #' \href{https://cran.r-project.org/package=formatters}{formatters} package, to reduce the complexity of
@@ -56,21 +56,21 @@ col_labels <- function(x, fill = FALSE) {
   labels
 }
 
-#' Set Label Attributes of All Variables in a \code{data.frame}
+#' Set Label Attributes of All Variables in a `data.frame`
 #'
-#' Variable labels can be stored as a \code{label} attribute for each variable.
-#' This functions sets all non-missing (non-NA) variable labels in a \code{data.frame}
+#' Variable labels can be stored as a `label` attribute for each variable.
+#' This functions sets all non-missing (non-NA) variable labels in a `data.frame`
 #'
 #' @inheritParams col_labels
-#' @param value new variable labels, \code{NA} removes the variable label
+#' @param value new variable labels, `NA` removes the variable label
 #'
 #' @source This function was taken 1-1 from
 #' \href{https://cran.r-project.org/package=formatters}{formatters} package, to reduce the complexity of
 #' the dependency tree.
 #'
 #' @seealso [col_labels()] [col_relabel()]
 #'
-#' @return modifies the variable labels of \code{x}
+#' @return modifies the variable labels of `x`
 #'
 #' @export
 #'
@@ -101,15 +101,15 @@ col_labels <- function(x, fill = FALSE) {
   x
 }
 
-#' Copy and Change Variable Labels of a \code{data.frame}
+#' Copy and Change Variable Labels of a `data.frame`
 #'
 #' Relabel a subset of the variables
 #'
 #' @inheritParams col_labels<-
 #' @param ... name-value pairs, where name corresponds to a variable name in
-#'   \code{x} and the value to the new variable label
+#'   `x` and the value to the new variable label
 #'
-#' @return a copy of \code{x} with changed labels according to \code{...}
+#' @return a copy of `x` with changed labels according to `...`
 #'
 #' @source This function was taken 1-1 from
 #' \href{https://cran.r-project.org/package=formatters}{formatters} package, to reduce the complexity of

R/join_keys-extract.R

@@ -181,7 +181,7 @@
 #' @rdname join_keys
 #'
 #' @order 1000
-#' @usage ## Prefered method is x[i, j] <- value
+#' @usage ## Preferred method is x[i, j] <- value
 #' x[[i]][[j]] <- value
 #'
 #' @section Functions:

R/join_keys-names.R

@@ -1,5 +1,9 @@
 #' The Names of an `join_keys` Object
 #' @inheritParams base::`names<-`
+#' @return For `names`, it returns `NULL` or a character vector containing the names of datasets.\cr
+#' For `names<-.join_keys`, it returns the updated 'join_keys' object with the keys modified.
+#' (Note that the value of names(x) <- value is that of the assignment,
+#' value, not the return value from the left-hand side.)
 #' @export
 `names<-.join_keys` <- function(x, value) {
   new_x <- unclass(x)

R/join_keys-parents.R

@@ -35,9 +35,9 @@ parents.join_keys <- function(x) {
 #' # Get parents of join_keys inside teal_data object ---
 #'
 #' td <- teal_data(
-#'   ADSL = teal.data::rADSL,
-#'   ADTTE = teal.data::rADTTE,
-#'   ADRS = teal.data::rADRS,
+#'   ADSL = rADSL,
+#'   ADTTE = rADTTE,
+#'   ADRS = rADRS,
 #'   join_keys = default_cdisc_join_keys[c("ADSL", "ADTTE", "ADRS")]
 #' )
 #' parents(td)
@@ -58,7 +58,7 @@ parents.teal_data <- function(x) {
 #' @export
 #' @examples
 #'
-#' # Assigment of parents ---
+#' # Assignment of parents ---
 #'
 #' jk <- join_keys(
 #'   join_key("ds1", "ds2", "id"),
@@ -111,7 +111,7 @@ parents.teal_data <- function(x) {
 #' @export
 #' @examples
 #'
-#' # Assigment of parents of join_keys inside teal_data object ---
+#' # Assignment of parents of join_keys inside teal_data object ---
 #'
 #' parents(td) <- list("ADTTE" = "ADSL") # replace existing
 #' parents(td)["ADRS"] <- "ADSL" # add new parent

R/teal_data-datanames.R

@@ -17,7 +17,9 @@
 #' td <- teal_data(iris = iris)
 #' td <- within(td, mtcars <- mtcars)
 #' datanames(td)
+#'
 #' datanames(td) <- c("iris", "mtcars")
+#' datanames(td)
 #'
 #' @name datanames
 #' @aliases datanames,teal_data-method

R/teal_data-get_code.R

@@ -16,6 +16,7 @@
 #' `expression` (`deparse = FALSE`).
 #' @return
 #' Either string or an expression representing code used to create the requested data sets.
+#'
 #' @examples
 #'
 #' tdata1 <- teal_data()

R/topological_sort.R

@@ -7,11 +7,6 @@
 #'
 #' @param graph (named `list`) list with node vector elements
 #' @keywords internal
-#'
-#' @examples
-#' teal.data:::topological_sort(list(A = c(), B = c("A"), C = c("B"), D = c("A")))
-#' teal.data:::topological_sort(list(D = c("A"), A = c(), B = c("A"), C = c("B")))
-#' teal.data:::topological_sort(list(D = c("A"), B = c("A"), C = c("B"), A = c()))
 topological_sort <- function(graph) {
   # compute in-degrees
   in_degrees <- list()

R/utils-get_code_dependency.R

@@ -70,6 +70,8 @@ extract_calls <- function(pd) {
   fix_comments(calls)
 }
 
+#' @keywords internal
+#' @noRd
 get_children <- function(pd, parent) {
   idx_children <- abs(pd$parent) == parent
   children <- pd[idx_children, c("token", "text", "id", "parent")]
@@ -82,6 +84,8 @@ get_children <- function(pd, parent) {
   }
 }
 
+#' @keywords internal
+#' @noRd
 fix_comments <- function(calls) {
   # If the first token is a COMMENT, then it belongs to the previous call.
   if (length(calls) >= 2) {

R/utils.R

@@ -12,20 +12,6 @@
 #'
 #' @param name `character, single or vector` name to check
 #' @keywords internal
-#'
-#' @examples
-#' teal.data:::check_simple_name("aas2df")
-#' teal.data:::check_simple_name("ADSL")
-#' teal.data:::check_simple_name("ADSLmodified")
-#' teal.data:::check_simple_name("ADSL_2")
-#' teal.data:::check_simple_name("a1")
-#' # the following fail
-#' \dontrun{
-#' teal.data:::check_simple_name("1a")
-#' teal.data:::check_simple_name("ADSL.modified")
-#' teal.data:::check_simple_name("ADSL_modified")
-#' teal.data:::check_simple_name("a1...")
-#' }
 check_simple_name <- function(name) {
   checkmate::assert_character(name, min.len = 1, any.missing = FALSE)
   if (!grepl("^[[:alpha:]][a-zA-Z0-9_]*$", name, perl = TRUE)) {

R/verify.R

@@ -24,32 +24,6 @@
 #' verify(tdata2)@verified
 #' tdata2@verified
 #'
-#' \dontrun{
-#' tdata3 <- teal_data()
-#' tdata3 <- within(tdata3, {
-#'   stop("error")
-#' })
-#' verify(tdata3)
-#'
-#'
-#' a <- 1
-#' b <- a + 2
-#' c <- list(x = 2)
-#' d <- 5
-#' tdata4 <- teal_data(
-#'   a = a, b = b, c = c, d = d,
-#'   code =
-#'     "
-#'     a <- 1
-#'     b <- a
-#'     c <- list(x = 2)
-#'     e <- 1
-#'     "
-#' )
-#' tdata4
-#' verify(tdata4)
-#' }
-#'
 #' @name verify
 #' @rdname verify
 #' @aliases verify,teal_data-method