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.

.lintr

@@ -1,5 +1,6 @@
 linters: linters_with_defaults(
   line_length_linter = line_length_linter(120),
   cyclocomp_linter = NULL,
-  object_usage_linter = NULL
+  object_usage_linter = NULL,
+  indentation_linter = NULL
   )

NEWS.md

@@ -59,7 +59,7 @@
 ### Bug fixes
 
 * Fixed an error where the `RangeFilterState` produced an error when using `bootstrap 4`.
-* Fixed a bug that caused the range slider to omit values selected programmatically through the filter API.
+* Fixed a bug that caused the range slider to omit values selected via filter API.
 * Fixed a bug where setting incorrect values for Date and Date time ranges caused the app to crash.
 
 ### Miscellaneous

R/FilterPanelAPI.R

@@ -14,7 +14,7 @@
 #'
 #' @examples
 #' library(teal.slice)
-#' fd <- teal.slice::init_filtered_data(list(iris = list(dataset = iris)))
+#' fd <- init_filtered_data(list(iris = list(dataset = iris)))
 #' fpa <- FilterPanelAPI$new(fd)
 #'
 #' # get the actual filter state --> empty named list

R/FilterState-utils.R

@@ -19,37 +19,8 @@
 #' }
 #' @param ... additional arguments to be saved as a list in `private$extras` field
 #'
-#' @keywords internal
-#'
-#' @examples
-#' filter_state <- teal.slice:::init_filter_state(
-#'   x = c(1:10, NA, Inf),
-#'   x_reactive = reactive(c(1:10, NA, Inf)),
-#'   slice = teal_slice(
-#'     varname = "x",
-#'     dataname = "dataname"
-#'   ),
-#'   extract_type = "matrix"
-#' )
-#'
-#' shiny::isolate(filter_state$get_call())
-#' app <- shinyApp(
-#'   ui = fluidPage(
-#'     filter_state$ui(id = "app"),
-#'     verbatimTextOutput("call")
-#'   ),
-#'   server = function(input, output, session) {
-#'     filter_state$server("app")
-#'
-#'     output$call <- renderText(
-#'       deparse1(filter_state$get_call(), collapse = "\n")
-#'     )
-#'   }
-#' )
-#' if (interactive()) {
-#'   shinyApp(app$ui, app$server)
-#' }
 #' @return `FilterState` object
+#' @keywords internal
 init_filter_state <- function(x,
                               x_reactive = reactive(NULL),
                               slice,
@@ -239,12 +210,6 @@ init_filter_state_expr <- function(slice) {
 #'              set to NULL to omit adding the alpha channel
 #'
 #' @return Named `character(1)` containing a hexadecimal color representation.
-#'
-#' @examples
-#' teal.slice:::fetch_bs_color("primary")
-#' teal.slice:::fetch_bs_color("danger", 0.35)
-#' teal.slice:::fetch_bs_color("danger", "80")
-#'
 #' @keywords internal
 #'
 fetch_bs_color <- function(color, alpha = NULL) {

R/FilterStateChoices.R

@@ -4,104 +4,6 @@
 #' @docType class
 #' @keywords internal
 #'
-#'
-#' @examples
-#' filter_state <- teal.slice:::ChoicesFilterState$new(
-#'   x = c(LETTERS, NA),
-#'   slice = teal_slice(varname = "x", dataname = "data")
-#' )
-#' shiny::isolate(filter_state$get_call())
-#' filter_state$set_state(
-#'   teal_slice(
-#'     dataname = "data",
-#'     varname = "x",
-#'     selected = "A",
-#'     keep_na = TRUE
-#'   )
-#' )
-#' shiny::isolate(filter_state$get_call())
-#'
-#' # working filter in an app
-#' library(shiny)
-#' library(shinyjs)
-#'
-#' data_choices <- c(sample(letters[1:4], 100, replace = TRUE), NA)
-#' attr(data_choices, "label") <- "lowercase letters"
-#' fs <- teal.slice:::ChoicesFilterState$new(
-#'   x = data_choices,
-#'   slice = teal_slice(
-#'     dataname = "data", varname = "variable", selected = c("a", "c"), keep_na = TRUE
-#'   )
-#' )
-#'
-#' ui <- fluidPage(
-#'   useShinyjs(),
-#'   teal.slice:::include_css_files(pattern = "filter-panel"),
-#'   teal.slice:::include_js_files(pattern = "count-bar-labels"),
-#'   column(4, div(
-#'     h4("ChoicesFilterState"),
-#'     fs$ui("fs")
-#'   )),
-#'   column(4, div(
-#'     h4("Condition (i.e. call)"), # display the subsetting call generated by this FilterState
-#'     textOutput("condition_choices"), br(),
-#'     h4("Unformatted state"), # display raw filter state
-#'     textOutput("unformatted_choices"), br(),
-#'     h4("Formatted state"), # display human readable filter state
-#'     textOutput("formatted_choices"), br()
-#'   )),
-#'   column(4, div(
-#'     h4("Programmatic filter control"),
-#'     actionButton("button1_choices", "set drop NA", width = "100%"), br(),
-#'     actionButton("button2_choices", "set keep NA", width = "100%"), br(),
-#'     actionButton("button3_choices", "set selection: a, b", width = "100%"), br(),
-#'     actionButton("button4_choices", "deselect all", width = "100%"), br(),
-#'     actionButton("button0_choices", "set initial state", width = "100%"), br()
-#'   ))
-#' )
-#'
-#' server <- function(input, output, session) {
-#'   fs$server("fs")
-#'   output$condition_choices <- renderPrint(fs$get_call())
-#'   output$formatted_choices <- renderText(fs$format())
-#'   output$unformatted_choices <- renderPrint(fs$get_state())
-#'   # modify filter state programmatically
-#'   observeEvent(
-#'     input$button1_choices,
-#'     fs$set_state(
-#'       teal_slice(dataname = "data", varname = "variable", keep_na = FALSE)
-#'     )
-#'   )
-#'   observeEvent(
-#'     input$button2_choices,
-#'     fs$set_state(
-#'       teal_slice(dataname = "data", varname = "variable", keep_na = TRUE)
-#'     )
-#'   )
-#'   observeEvent(
-#'     input$button3_choices,
-#'     fs$set_state(
-#'       teal_slice(dataname = "data", varname = "variable", selected = c("a", "b"))
-#'     )
-#'   )
-#'   observeEvent(
-#'     input$button4_choices,
-#'     fs$set_state(
-#'       teal_slice(dataname = "data", varname = "variable", selected = character(0), keep_na = TRUE)
-#'     )
-#'   )
-#'   observeEvent(
-#'     input$button0_choices,
-#'     fs$set_state(
-#'       teal_slice(dataname = "data", varname = "variable", selected = c("a", "c"), keep_na = TRUE)
-#'     )
-#'   )
-#' }
-#'
-#' if (interactive()) {
-#'   shinyApp(ui, server)
-#' }
-#'
 ChoicesFilterState <- R6::R6Class( # nolint
   "ChoicesFilterState",
   inherit = FilterState,