Package 'projmgr'

Description

Opens browser to relevant parts of GitHub API documentation to learn more about field definitions and formatting. Inspired by similar browse_ functions included in the usethis package.

Usage

browse_docs(
  action = c("get", "post"),
  object = c("milestone", "issue", "issue event", "issue comment", "repo labels")
)

Arguments

Value

Returns URL in non-interactive session or launches browser to docs in interactive session

Examples

## Not run: 
browse_docs('get', 'milestone')

## End(Not run)

Description

Opens browser to GitHub issues for a given repo. Inspired by similar browse_ functions included in the usethis package.

Usage

browse_issues(repo_ref, number = "")

Arguments

Value

Returns URL in non-interactive session or launches browser to docs in interactive session

Examples

## Not run: 
my_repo <- create_repo_ref("repo_owner", "repo")
browse_issues(my_repo)

## End(Not run)

Description

Opens browser to GitHub milestones for a given repo. Inspired by similar browse_ functions included in the usethis package.

Usage

browse_milestones(repo_ref, number = "")

Arguments

Value

Returns URL in non-interactive session or launches browser to docs in interactive session

Examples

## Not run: 
my_repo <- create_repo_ref("repo_owner", "repo")
browse_milestones(my_repo)

## End(Not run)

Description

Opens browser to a given GitHub repo. Inspired by similar browse_ functions included in the usethis package.

Usage

browse_repo(repo_ref)

Arguments

Value

Returns URL in non-interactive session or launches browser to docs in interactive session

Examples

## Not run: 
my_repo <- create_repo_ref("repo_owner", "repo")
browse_repo(my_repo)

## End(Not run)

Description

Check for valid credentials and repo permissions

Usage

check_credentials(ref)

Arguments

Value

Prints GitHub username as determined by credentials (if valid) and repo-level permissions (if any), else throws 401 Unauthorized error.

Examples

## Not run: 
experigit <- create_repo_ref('emilyriederer', 'experigit')
check_authentication(experigit)

## End(Not run)

Description

Basic wrapper around curl::has_internet()

Usage

check_internet()

Value

Returns TRUE is connected to internet and false otherwise

See Also

Other check: check_rate_limit()

Examples

## Not run: 
check_internet()

## End(Not run)

Description

Source: copied from httr vignette "Best practices for API packages" by Hadley Wickham

Usage

check_rate_limit(ref)

Arguments

Value

Informative message on requests remaining and reset time

See Also

Other check: check_internet()

Examples

## Not run: 
experigit <- create_repo_ref('emilyriederer', 'experigit')
check_rate_limit(experigit)

## End(Not run)

Description

This function constructs a list of needed information to send API calls to a specific GitHub repository. Specifically, it stores information on the repository's name and owner, the type (whether or not Enterprise GitHub), and potentially credentials to authenticate.

Usage

create_repo_ref(
  repo_owner,
  repo_name,
  is_enterprise = FALSE,
  hostname = "",
  identifier = ""
)

Arguments

Details

Note that this package can be used for GET requests on public repositories without any authentication (resulting in a lower rate limit.) To do this, simply pass any string into identifier that is not an environment variable already defined for your system (e.g. accessible through Sys.getenv("MY_VAR"))

Value

List of repository reference information and credentials

Examples

## Not run: 
myrepo <- create_repo_ref('emilyriederer', 'myrepo')

## End(Not run)

Description

In addition to information returned by GitHub API, appends field "number" for the issue number to which the returned comments correspond.

Usage

get_issue_comments(ref, number, ...)

Arguments

Value

Content of GET request as list

See Also

Other issues: get_issue_events(), get_issues(), parse_issue_comments(), parse_issue_events(), parse_issues(), post_issue_update(), post_issue(), report_discussion(), report_progress(), viz_waterfall()

Other comments: parse_issue_comments(), report_discussion()

Examples

## Not run: 
myrepo <- create_repo_ref('emilyriederer', 'myrepo')
comments_res <- get_issue_comments(myrepo, number = 1)
comments <- parse_issue_comments(comments_res)

## End(Not run)

Description

In addition to information returned by GitHub API, appends field "number" for the issue number to which the returned events correspond.

Usage

get_issue_events(ref, number, dummy_events = TRUE)

Arguments

Value

Content of GET request as list

See Also

Other issues: get_issue_comments(), get_issues(), parse_issue_comments(), parse_issue_events(), parse_issues(), post_issue_update(), post_issue(), report_discussion(), report_progress(), viz_waterfall()

Other events: parse_issue_events()

Examples

## Not run: 
myrepo <- create_repo_ref('emilyriederer', 'myrepo')

# single issue workflow
events_res <- get_issue_events(myrepo, number = 1)
events <- parse_issue_events(events_res)

# multi-issue workflow
issue_res <- get_issues(my_repo, state = 'open')
issues <- parse_issues(issues_res)
events <- purrr::map_df(issues$number, ~get_issue_events(myrepo, .x) %>% parse_issue_events())

## End(Not run)

Description

A single issue can be obtained by identification number of number is passed through ...s. In this case, all other query parameters will be ignored.

Usage

get_issues(ref, limit = 1000, ...)

Arguments

Value

Content of GET request as list

See Also

Other issues: get_issue_comments(), get_issue_events(), parse_issue_comments(), parse_issue_events(), parse_issues(), post_issue_update(), post_issue(), report_discussion(), report_progress(), viz_waterfall()

Examples

## Not run: 
myrepo <- create_repo_ref('emilyriederer', 'myrepo')
issues_res <- get_issues(myrepo)
issues <- parse_issues(issues_res)

## End(Not run)

Description

A single milestone can be obtained by identification number of number is passed through ...s. In this case, all other query parameters will be ignored.

Usage

get_milestones(ref, ...)

Arguments

Value

Content of GET request as list

See Also

Other milestones: parse_milestones(), post_milestone()

Examples

## Not run: 
myrepo <- create_repo_ref("emilyriederer", "myrepo")
milestones_res <- get_milestones(myrepo)
milestones <- parse_milestones(milestones_res)

## End(Not run)

Description

Get all labels for a repository

Usage

get_repo_labels(ref)

Arguments

Value

Content of GET request as list

See Also

Other labels: parse_repo_labels()

Examples

## Not run: 
labels_res <- get_repo_labels(my_repo)
labels <- parse_repo_labels(labels_res)

## End(Not run)

Description

The help family of functions lists the optional query parameters available for each of the related get_ functions. When no optional arguments are available, a blank character vector is returned.

Usage

help_get_issues()

help_get_issue_events()

help_get_issue_comments()

help_get_milestones()

help_get_repo_label()

help_post_issue()

help_post_issue_update()

help_post_milestone()

Details

For more details on these parameters, please use the browse_docs() function to navigate to the appropriate part of the GitHub API documentation.

Value

Character string of optional field names

Examples

help_get_issues()
help_get_milestones()

Description

Creaes a new column in your dataframe based on a subset of list-column values following a certain patten. For example, this is useful if you have labels you always apply to a repository with a set structure, e.g. key-value pairs like "priority:high", "priority:medium", and "priority:low" or other structures like "engagement-team", "teaching-team", etc. This function could create a new variable (e.g. "priority", "team") with the values encoded within the labels.

Usage

listcol_extract(data, col_name, regex, new_col_name = NULL, keep_regex = FALSE)

Arguments

Details

This function works only if each observatino contains at most one instance of a given patterns. When multiple labels match the same pattern, one is returned at random.

Value

Dataframe with new column taking values extracted from list column

Examples

## Not run: 
issues <- get_issues(repo)
issues_df <- parse_issues(issues)
listcol_extract(issues_df, "labels_name", "-team$")

## End(Not run)

Description

Some outputs of the get_ and parse_ functions contain list-columns (e.g. the labels column in the issues dataframe). This is an efficient way to represent the provided information, but may make certain information seem slightly inaccessible. This function allows users to filter list columns by the presence of one or more values or a regular expression.

Usage

listcol_filter(data, col_name, matches, is_regex = FALSE)

Arguments

Value

Dataframe containing only rows in which list-column contains element matching provided criteria

Examples

## Not run: 
issues <- get_issues(repo)
issues_df <- parse_issues(issues)

# keep observation containing a label of either "bug" or "feature"
listcol_filter(issues_df, col_name = "labels_name", matches = c("bug", "feature"))

# keep observation containing a label that starts with "region"
listcol_filter(issues_df, col_name = "labels_name", matches = "^region:", is_regex = TRUE)

## End(Not run)

Description

Some outputs of the get_ and parse_ functions contain list-columns (e.g. the labels column in the issues dataframe). This is an efficient way to represent the provided information, but may make certain information seem slightly inaccessible. This function allows users to "pivot" these list columns and instead create a seperate indicator variable to represent the presence or absence of matches within the list column.

Usage

listcol_pivot(
  data,
  col_name,
  regex = ".",
  transform_fx = identity,
  delete_orig = FALSE
)

Arguments

Details

For example, if a repository tags issues with "priority:high", "priority:medium", and "priority:low" along with other labels, this function could be used to create separate "high", "medium", and "low" columns to denote different issue severities. This could be done with listcol_pivot(data, "labels_name", "^priority:", function(x) sub("^priority:", ""))

Value

Dataframe additional logical columns denoting absence / presence of specified list-column elements

Examples

## Not run: 
issues <- get_issues(repo)
issues_df <- parse_issues(issues)
listcol_pivot(issues_df,
  col_name = "labels_name",
  regex = "^priority:",
  transform_fx = function(x) paste0("label_",x),
  delete_orig = TRUE)

## End(Not run)

Description

Parse issue comments from get_issues_comments

Usage

parse_issue_comments(res)

Arguments

Value

Dataframe with one record / issue-comment

See Also

Other issues: get_issue_comments(), get_issue_events(), get_issues(), parse_issue_events(), parse_issues(), post_issue_update(), post_issue(), report_discussion(), report_progress(), viz_waterfall()

Other comments: get_issue_comments(), report_discussion()

Examples

## Not run: 
myrepo <- create_repo_ref('emilyriederer', 'myrepo')
comments_res <- get_issue_comments(myrepo, number = 1)
comments <- parse_issue_comments(comments_res)

## End(Not run)

Description

This function convert list output returned by get into a dataframe. Due to the diverse fields for different types of events, many fields in the dataframe may be NA.

Usage

parse_issue_events(res)

Arguments

Details

Currently, the following event types are unsupported (with regard to processing all of their fields) due to their additional bulk and limited utility with respect to this packages functionality. Please file an issue if you disagree:

• (removed_from/moved_columns_in/added_to)_project: Since this package has limited value with GitHub projects

• converted_note_to_issue: Since issue lineage is not a key concern

• head_ref_(deleted/restored): Since future support for pull requests would likely be handled separately

• merged: Same justification as head_ref

• review_(requested/dismissed/request_removed): Same justification as head_ref

Value

Dataframe with one record / issue-event

See Also

Other issues: get_issue_comments(), get_issue_events(), get_issues(), parse_issue_comments(), parse_issues(), post_issue_update(), post_issue(), report_discussion(), report_progress(), viz_waterfall()

Other events: get_issue_events()

Examples

## Not run: 
myrepo <- create_repo_ref('emilyriederer', 'myrepo')
events_res <- get_issue_events(myrepo, number = 1)
events <- parse_issue_events(events_res)

## End(Not run)

Description

Parse issues overview from get_issues

Usage

parse_issues(res)

Arguments

Value

data.frame with one record / issue

See Also

Other issues: get_issue_comments(), get_issue_events(), get_issues(), parse_issue_comments(), parse_issue_events(), post_issue_update(), post_issue(), report_discussion(), report_progress(), viz_waterfall()

Examples

## Not run: 
myrepo <- create_repo_ref('emilyriederer', 'myrepo')
issues_res <- get_issues(myrepo)
issues <- parse_issues(issues_res)

## End(Not run)

Description

Parse milestones from get_milestones

Usage

parse_milestones(res)

Arguments

Value

Dataframe with one record / milestone

See Also

Other milestones: get_milestones(), post_milestone()

Examples

## Not run: 
myrepo <- create_repo_ref("emilyriederer", "myrepo")
milestones_res <- get_milestones(myrepo)
milestones <- parse_milestones(milestones_res)

## End(Not run)

Description

Parse labels from get_repo_labels

Usage

parse_repo_labels(res)

Arguments

Value

Dataframe with one record / label

See Also

Other labels: get_repo_labels()

Examples

## Not run: 
labels_res <- get_repo_labels(my_repo)
labels <- parse_repo_labels(labels_res)

## End(Not run)

Description

Post issue to GitHub repository

Usage

post_issue(ref, title, ..., distinct = TRUE)

Arguments

Value

Number (identifier) of posted issue

See Also

Other issues: get_issue_comments(), get_issue_events(), get_issues(), parse_issue_comments(), parse_issue_events(), parse_issues(), post_issue_update(), report_discussion(), report_progress(), viz_waterfall()

Examples

## Not run: 
myrepo <- create_repo_ref('emilyriederer', 'myrepo')
post_issue(myrepo,
  title = 'this is the issue title',
  body = 'this is the issue body',
  labels = c('priority:high', 'bug'))

## End(Not run)
## Not run: 
# can be used in conjunction with reprex pkg
# example assumes code for reprex is on clipboard
reprex::reprex(venue = "gh")
post_issue(myrepo,
            title = "something is broken",
            body = paste( clipr::read_clip(), collapse = "\n") )

## End(Not run)

Description

Post updates to existing issue in GitHub repository

Usage

post_issue_update(ref, issue_number, ...)

Arguments

Value

Number (identifier) of updated issue

See Also

Other issues: get_issue_comments(), get_issue_events(), get_issues(), parse_issue_comments(), parse_issue_events(), parse_issues(), post_issue(), report_discussion(), report_progress(), viz_waterfall()

Examples

## Not run: 
myrepo <- create_repo_ref('emilyriederer', 'myrepo')
post_issue_update(myrepo,
  issue_number = 1,
  labels = c('priority:high', 'bug'))

## End(Not run)

Description

Post milestone to GitHub repository

Usage

post_milestone(ref, title, ...)

Arguments

Value

Number (identifier) of posted milestone

See Also

Other milestones: get_milestones(), parse_milestones()

Examples

## Not run: 
myrepo <- create_repo_ref('emilyriederer', 'myrepo')
post_milestone(myrepo,
  title = 'this is the title of the milestone',
  description = 'this is the long and detailed description',
  due_on = '2018-12-31T12:59:59z')

## End(Not run)

Description

Post custom plans (i.e. create milestones and issues) based on yaml read in by read_plan. Please see the "Building Custom Plans" vignette for details.

Usage

post_plan(ref, plan, distinct = TRUE)

Arguments

Value

Dataframe with numbers (identifiers) of posted milestones and issues and issue title

See Also

Other plans and todos: post_todo(), read_plan(), read_todo(), report_plan(), report_todo(), template_yaml()

Examples

## Not run: 
# This example uses example file included in pkg
# You should be able to run example as-is after creating your own repo reference
file_path <- system.file("extdata", "plan.yml", package = "projmgr", mustWork = TRUE)
my_plan <- read_plan(file_path)
post_plan(ref, my_plan)

## End(Not run)

Description

Post custom to-do lists (i.e. issues) based on yaml read in by read_todo. Please see the "Building Custom Plans" vignette for details.

Usage

post_todo(ref, todo, distinct = TRUE)

Arguments

Details

Currently has know bug in that cannot be used to introduce new labels.

Value

Number (identifier) of posted issue

See Also

Other plans and todos: post_plan(), read_plan(), read_todo(), report_plan(), report_todo(), template_yaml()

Examples

## Not run: 
# This example uses example file included in pkg
# You should be able to run example as-is after creating your own repo reference
file_path <- system.file("extdata", "todo.yml", package = "projmgr", mustWork = TRUE)
my_todo <- read_todo(file_path)
post_todo(ref, my_todo)

## End(Not run)

Description

This function reads a carefully constructed YAML file representing a project plan (of milestones and issues). YAML is converted into an R list structure which can then be passed to post_plan() to build infrastructure for your repository.

Usage

read_plan(input)

Arguments

Details

Please see the "Building Custom Plans" vignette for more details.

Value

List containing plan compatible with post_plan() or post_todo()

See Also

Other plans and todos: post_plan(), post_todo(), read_todo(), report_plan(), report_todo(), template_yaml()

Examples

## Not run: 
# This example uses example file included in pkg
# You should be able to run example as-is after creating your own repo reference
file_path <- system.file("extdata", "plan.yml", package = "projmgr", mustWork = TRUE)
my_plan <- read_plan(file_path)
post_plan(ref, my_plan)

## End(Not run)

Description

This function reads a carefully constructed YAML file representing a to-do list (of issues). YAML is converted into an R list structure which can then be passed to post_todo() to build infrastructure for your repository.

Usage

read_todo(input)

Arguments

Details

Please see the "Building Custom Plans" vignette for more details.

Value

List containing plan compatible with post_plan() or post_todo()

See Also

Other plans and todos: post_plan(), post_todo(), read_plan(), report_plan(), report_todo(), template_yaml()

Examples

## Not run: 
# This example uses example file included in pkg
# You should be able to run example as-is after creating your own repo reference
file_path <- system.file("extdata", "todo.yml", package = "projmgr", mustWork = TRUE)
my_todo <- read_todo(file_path)
post_todo(ref, my_todo)

## End(Not run)

Description

Interprets dataframe or tibble of issues by breaking apart milestones and listing each issue title as open or closed, and uses HTML to format results in a highly readable and attractive way. Resulting object returned is a character vector of HTML code with the added class of 'knit_asis' so that when included in an RMarkdown document knitting to HTML, the results will be correctly rendered as HTML.

Usage

report_discussion(comments, issue = NA, link_url = TRUE)

Arguments

Details

HTML output is wrapped in a ⁠<div>⁠ of class 'report_disccusion' for custom CSS styling.

Value

Returns character string of HTML with class attribute to be correctly shown "as-is" in RMarkdown

See Also

Other issues: get_issue_comments(), get_issue_events(), get_issues(), parse_issue_comments(), parse_issue_events(), parse_issues(), post_issue_update(), post_issue(), report_progress(), viz_waterfall()

Other comments: get_issue_comments(), parse_issue_comments()

Examples

## Not run: 
# the following could be run in RMarkdown
repo <- create_repo_ref("emilyriederer", "projmgr")
issue <- get_issues(repo, number = 15)
issue_df <- parse_issues(issue)
comments <- get_issue_comments(repo, number = 15)
comments_df <- parse_issue_comments(comments)
report_discussion(issue_df, comments_df)

## End(Not run)

Description

Interprets list representation of plan, using HTML to format results in a highly readable and attractive way. Resulting object returned is a character vector of HTML code with the added class of 'knit_asis' so that when included in an RMarkdown document knitting to HTML, the results will be correctly rendered as HTML.

Usage

report_plan(plan, show_ratio = TRUE)

Arguments

Details

The resulting HTML unordered list (⁠<ul>⁠) is tagged with class 'report_plan' for custom CSS styling.

Value

Returns character string of HTML with class attribute to be correctly shown "as-is" in RMarkdown

See Also

Other plans and todos: post_plan(), post_todo(), read_plan(), read_todo(), report_todo(), template_yaml()

Examples

## Not run: 
# the following could be run in RMarkdown
plan_path <- system.file("extdata", "plan-ex.yml", package = "projmgr", mustWork = TRUE)
my_plan <- read_plan(plan_path)
report_plan(my_plan)

## End(Not run)

Description

Interprets dataframe or tibble of items (e.g. issues) by breaking apart groups (e.g. milestones), listing each item title as open or closed, and using HTML to format results in a highly readable and attractive way. Resulting object returned is a character vector of HTML code with the added class of 'knit_asis' so that when included in an RMarkdown document knitting to HTML, the results will be correctly rendered as HTML.

Usage

report_progress(
  issues,
  group_var = "milestone_title",
  link_url = TRUE,
  show_ratio = TRUE,
  show_pct = TRUE
)

Arguments

Details

The resulting HTML unordered list (⁠<ul>⁠) is tagged with class 'report_progress' for custom CSS styling.

Items without a related group are put into an "Ungrouped" category. Filter these out before using this function if you wish to only show items that are in a group.

Value

Returns character string of HTML with class attribute to be correctly shown "as-is" in RMarkdown

See Also

Other issues: get_issue_comments(), get_issue_events(), get_issues(), parse_issue_comments(), parse_issue_events(), parse_issues(), post_issue_update(), post_issue(), report_discussion(), viz_waterfall()

Examples

## Not run: 
repo <- create_repo_ref("emilyriederer", "projmgr")
issues <- get_issues(repo, state = 'all')
issues_df <- parse_issues(issues)
report_progress(issues_df)

## End(Not run)

Description

Produces three column task board showing any relevant objects (typically issues or milestones) as "Not Started", "In Progress", or "Done".

Usage

report_taskboard(
  data,
  in_progress_when,
  include_link = FALSE,
  hover = FALSE,
  colors = c("#f0e442", "#56b4e9", "#009e73")
)

Arguments

Details

The following logic is used to determine the status of each issue:

• Done: Items with a state of "closed"

• In Progress: Custom logic via in_progress_when. See ?taskboard_helpers for details.

• Not Started: Default case for items neither In Progress or Closed

Value

Returns character string of HTML/CSS with class attribute to be correctly shown "as-is" in RMarkdown

Examples

## Not run: 
# in RMarkdown
```{r}
issues <- get_issues(myrepo, milestone = 1)
issues_df <- parse_issues(issues)
report_taskboard(issues_df, in_progress_when = is_labeled_with('in-progress'))
````

## End(Not run)

Description

Interprets list representation of to-do list, using HTML to format results in a highly readable and attractive way. Resulting object returned is a character vector of HTML code with the added class of 'knit_asis' so that when included in an RMarkdown document knitting to HTML, the results will be correctly rendered as HTML.

Usage

report_todo(todo, show_ratio = TRUE)

Arguments

Details

The resulting HTML unordered list (⁠<ul>⁠) is tagged with class 'report_todo' for custom CSS styling.

Value

Returns character string of HTML with class attribute to be correctly shown "as-is" in RMarkdown

See Also

Other plans and todos: post_plan(), post_todo(), read_plan(), read_todo(), report_plan(), template_yaml()

Examples

## Not run: 
# the following could be run in RMarkdown
todo_path <- system.file("extdata", "todo-ex.yml", package = "projmgr", mustWork = TRUE)
my_todo <- read_todo(todo_path)
report_todo(my_todo)

## End(Not run)

Description

The viz_taskboard() function creates a three-column layout of entities that are not started, in progress, or done. Objects are classified as done when they have a state of "closed". Object are classified as "To-Do" when they are neither "Closed" or "In Progress". However, what constistutes "In Progress" is user and project dependent. Thus, these functions let users specify what they mean.

Usage

is_labeled()

is_labeled_with(label, any = TRUE)

is_assigned()

is_assigned_to(login, any = TRUE)

is_in_a_milestone()

is_in_milestone(number)

is_created_before(created_date)

is_part_closed()

is_due()

is_due_before(due_date)

has_n_commits(events, n = 1)

Arguments

Details

General options:

• is_created_before: Was created before a user-specified data (as "YYYY-MM-DD" character string)

Issue-specific options:

• is_labeled_with: User-specified label (as character string) exists

• is_assigned: Has been assigned to anyone

• is_assigned_to: Has been assigned to specific user-specified login (as character string)

• is_in_a_milestone: Has been put into any milestone

• is_in_milestone: Has been put into a specific milestone

Milestone-specific options:

• is_part_closed: Has any of its issues closed

• is_due: Has a due date

• is_due_before: Has a due data by or before a user-specified date (as "YYYY-MM-DD" character string)

Value

Function to be passed as in_progress_when argument in viz_taskboard()

Examples

## Not run: 
viz_taskboard(issues, in_progress_when = is_labeled_with('in-progress'))
viz_taskboard(milestones, in_progress_when = is_created_before('2018-12-31'))
viz_taskboard(issues, in_progress_when = is_in_milestone())
report_taskboard(issues, in_progress_when = is_labeled_with('in-progress'))
report_taskboard(milestones, in_progress_when = is_created_before('2018-12-31'))
report_taskboard(issues, in_progress_when = is_in_milestone())

## End(Not run)

Description

Prints YAML templates for either a plan or to-do list to the console as an example for developing your own custom plans and to-do lists. Inspired by similar template_ functions included in the pkgdown package.

Usage

template_yaml(template = c("plan", "todo"))

Arguments

Details

Note that depending on the console, text editor, and settings you are using, the template may or may not preserve the necessary whitespace shown in the output. If you copy-paste the template for modification, ensure that it still adheres to traditional YAML indentation.

Value

Prints template to console

See Also

Other plans and todos: post_plan(), post_todo(), read_plan(), read_todo(), report_plan(), report_todo()

Examples

template_yaml('plan')
template_yaml('todo')

Description

Produces plot with one vertical bar from the specified start variable's value to the end variable's value. Common uses would be to visualize time-to-completion for issues gotten by (get_issues and parse_issues) or milestones. Bars are colored by duration with longer bars as a darker shade of blue, and start/completion is denoted by points at the ends of the bars.

Usage

viz_gantt(data, start = "created_at", end = "closed_at", str_wrap_width = 30)

Arguments

Details

By default, the start date is the issue's created_at date, and the end date is the issue's closed_at date. However, either of these can be altered via the start and end parameters since these dates might not be reflective of the true timeframe (e.g. if issues are posted well in advance of work beginning.)

Unfinished tasks (where the value of the end variable is NA) are colored grey and do not have dots on their bars. Unstarted tasks are dropped because user intent is ambiguous in that case.

Value

ggplot object

See Also

viz_linked

Examples

## Not run: 
issues <- get_issues(myrepo, state = "closed")
issues_df <- parse_issues(issues)
viz_gantt(issues_df)

## End(Not run)

Description

Produces three column task board showing any relevant objects (typically issues or milestones) as "Not Started", "In Progress", or "Done".

Usage

viz_taskboard(data, in_progress_when, str_wrap_width = 30, text_size = 3)

Arguments

Details

The following logic is used to determine the status of each issue:

• Done: Items with a state of "closed"

• In Progress: Custom logic via in_progress_when. See ?taskboard_helpers for details.

• Not Started: Default case for items neither In Progress or Closed

Value

ggplot object

See Also

viz_linked

Examples

## Not run: 
issues <- get_issues(myrepo, milestone = 1)
issues_df <- parse_issues(issues)
viz_taskboard(issues_df, in_progress_when = is_labeled_with('in-progress'))
viz_taskboard(issues_df, in_progress_when = is_in_a_milestone())

## End(Not run)

Description

Creates a four-bar waterfall diagram. Within the specified timeframe, shows initial, newly opened, newly closed, and final open counts. Works with either issues or milestones, as obtained by the get and parse functions.

Usage

viz_waterfall(
  data,
  start_date,
  end_date,
  start = "created_at",
  end = "closed_at"
)

Arguments

Details

The following logic is used to classify issues:

• Initial: ⁠start < start_date and (end > start_date or state == 'open')⁠

• Open: ⁠start >= start_date and start <= end_date⁠

• Closed: ⁠end >= start_date and end <= end_date⁠

• Final: ⁠start < end_date and (end > end_date or state == 'open')⁠

The exact accuracy of the logic depends on filtering that has already been done to the dataset. Think carefully about the population you wish to represent when getting your data.

Value

ggplot object

See Also

Other issues: get_issue_comments(), get_issue_events(), get_issues(), parse_issue_comments(), parse_issue_events(), parse_issues(), post_issue_update(), post_issue(), report_discussion(), report_progress()

Examples

## Not run: 
viz_waterfall(milestones, '2017-01-01', '2017-03-31')

## End(Not run)