These functions use the connection to Microsoft Planner set up with connect_planner().
planner_browse(account = connect_planner())
planner_bucket_create(bucket_name, account = connect_planner())
planner_buckets_list(account = connect_planner(), plain = FALSE)
planner_task_create(
title,
description = NULL,
startdate = NULL,
duedate = NULL,
requested_by = NULL,
priority = read_secret("planner.default.priority"),
checklist_items = NULL,
categories = NULL,
assigned = NULL,
bucket_name = read_secret("planner.default.bucket"),
attachment_urls = NULL,
account = connect_planner(),
project_number = planner_highest_project_id() + 1
)
planner_task_update(
task,
title = NULL,
description = NULL,
startdate = NULL,
duedate = NULL,
priority = NULL,
checklist_items = NULL,
categories = NULL,
categories_keep = FALSE,
assigned = NULL,
assigned_keep = FALSE,
bucket_name = NULL,
percent_completed = NULL,
attachment_urls = NULL,
account = connect_planner()
)
planner_tasks_list(
account = connect_planner(),
plain = FALSE,
include_completed = TRUE
)
planner_task_search(
search_term = ".*",
limit = 50,
include_completed = TRUE,
include_description = FALSE,
account = connect_planner()
)
planner_task_find(task, account = connect_planner())
planner_categories_list(account = connect_planner())
planner_retrieve_project_id(task, account = connect_planner())
planner_task_request_validation(
task,
category_text = read_secret("planner.label.authorise"),
account = connect_planner()
)
planner_task_validate(
task,
category_text = read_secret("planner.label.authorised"),
account = connect_planner()
)
planner_create_project_from_path(
path,
projects_path = read_secret("projects.path"),
account = connect_planner(),
title = basename(path),
...
)
planner_user_property(
user,
team_name = read_secret("team.name"),
account = connect_planner(),
property = "id",
as_list = FALSE
)
planner_highest_project_id(
task = read_secret("planner.dummy.project"),
account = connect_planner()
)
# S3 method for ms_object
as.data.frame(
x,
row.names = NULL,
optional = FALSE,
account = connect_planner(),
...
)
# S3 method for ms_object
as_tibble(x, account = connect_planner(), ...)a Microsoft 365 account to use for looking up properties. This has to be an object as returned by connect_planner() or via AzureGraph::create_graph_login()$get_group(name)$get_plan(plan_title).
name of the bucket
return as plain names, not as Azure objects
title of the task
a description for the task. A vector of length > 1 will be added as one text separated by white lines.
a date to use as start date, use FALSE to remove it
a date to use as due date, use FALSE to remove it
name of the person(s) who requested the task, this will be added as first line to description
a priority to set. Can be ranged between 0 (highest) and 10 (lowest), or: "urgent" or "dringend" for 1, "important" or "belangrijk" for 3, "medium" or "gemiddeld" or FALSE for 5, "low" or "laag" for 9. Priorities cannot be removed - the default setting is 5.
character vector of checklist items
names of categories to add, can be multiple, but must exactly match existing category names
names of members within the plan - use NULL to not add members in planner_task_create(), and use FALSE to remove all existing members in planner_task_update()
URLs to add as attachment, can be named characters to give the URLs a title. If they are Excel, PowerPoint or Word files, a preview will be shown on the task.
the new project number to assign. Use NULL or FALSE to not assign a project number. Defaults to the currently highest project ID + 1.
exact task ID or title, will be searched with %like%
add categories that are set in categories instead of replacing them, defaults to FALSE
add members that are set in assigned instead of replacing them, defaults to FALSE
percentage of task completion between 0-100
also search completed tasks
search term, can contain a regular expression. When searching for project numbers (such as "p201 - Some text", or "p201" or "201"), only titles will be searched for the project number.
maximum number of tasks to show
also search the description, which requires additional queries and lowers speed
text of the category to use
location of the folder that has to be converted to a project. This folder will be renamed to contain the new project number.
location of the folder that contains all department projects
arguments passed on to planner_task_create()
a user name, mail adress, or Certe login name
name of the team, can be left blank to connect to an individual planner
property to return, can be "id", "name" or "mail"
return the full list of members as list, split into Eigenaars (Owners) / Leden (Members). This ignores user.
an ms_object
NULL or a character vector giving the row
names for the data frame. Missing values are not allowed.
logical. If TRUE, setting row names and
converting column names (to syntactic names: see
make.names) is optional. Note that all of R's
base package as.data.frame() methods use
optional only for column names treatment, basically with the
meaning of data.frame(*, check.names = !optional).
See also the make.names argument of the matrix method.
planner_task_search() searches the title and description using case-insensitive regular expressions and returns an ms_plan_task object. In interactive mode and with multiple hits, a menu will be shown to pick from.
planner_task_find() searches task title or ID, and returns an ms_plan_task object. It is used internally b a lot of planner_* functions, very fast, and does not support interactive use.
planner_retrieve_project_id() retrieves the p-number from the task title and returns it as integer.
Use planner_create_project_from_path() to convert any folder (and any location) to a project folder, by (1) assigning a project number, (2) creating a Planner task and (3) moving the old folder to the department's projects folder.
planner_highest_project_id() retrieves the currently highest project ID from the dummy project.
Using as.data.frame() or as_tibble() on an ms_object, such as ms_plan_task, will return the properties and details of the object as a data.frame. For transforming many ms_objects to a data.frame, use as.data.frame() or as_tibble() in lapply() and bind the list of objects together. For example, this retrieves a tibble with the properties and details of all tasks:
library(dplyr)
planner_tasks_list() |>
lapply(as_tibble) |>
bind_rows()
# also works for other 'ms_object's, such as 'ms_channel':
teams_channels_list(plain = FALSE) |>
lapply(as_tibble) |>
bind_rows()