Package 'connectViz'

Title: Visualize Your 'RStudio Connect' Server Usage Data
Description: A collection of helper functions and 'htmlwidgets' to help admins or user better understand how 'RStudio Connect' is used in their organization. The package provides plug and play visualizations that can be customized depending on needs.
Authors: David Granjon [aut, cre], Christophe Regouby [ctb]
Maintainer: David Granjon <[email protected]>
License: MIT + file LICENSE
Version: 0.0.0.9146
Built: 2026-05-24 07:14:48 UTC
Source: https://github.com/RinteRface/connectviz

Help Index

Generic calendar chart generator

Description

Generic calendar chart generator

Usage

create_app_daily_session_chart(
  calendar_data,
  title = "Cumulated daily usage",
  subtitle = "time units: minutes",
  start_date = NULL,
  end_date = NULL,
  callback = NULL
)

Arguments

calendar_data

Calendar chart data.
title

Chart title.
subtitle

Chart subtitle.
start_date

Default to minimum calendar_data date. Could also be an input value with Shiny.
end_date

Default to maximum calendar_data date. Could also be an input value with Shiny.
callback

JS function to pass to onRender. This is useful to access the widget API on the R side at render time and add events on the fly.

Value

An echarts4r line chart

Daily app usage chart

Description

Leverages echarts4r. See https://echarts4r.john-coene.com/articles/chart_types.html#calendar-1. .

Usage

create_app_daily_usage_chart(app_usage, ...)

Arguments

app_usage

Returned by get_app_daily_usage.
...

Pass down any param to create_calendar_chart.

Value

A calendar chart displaying daily app usage.

Process app data for ranking table

Description

See create_app_ranking_table.

Usage

create_app_ranking(content, users, apps, start_date = NULL, end_date = NULL)

Arguments

content

Get from get_content. Can be reactive.
users

Get from get_users. Can be reactive.
apps

Get from get_usage_shiny. Can be reactive.
start_date

Default to minimum calendar_data date. Could also be an input value with Shiny.
end_date

Default to maximum calendar_data date. Could also be an input value with Shiny.

Value

A list containing: ⁠[[1]]⁠ merged data between app usage and users data. ⁠[[2]]⁠: data to be digested by create_app_ranking_table.

Create app ranking table

Description

Leverages the toastui htmlwidget. See https://dreamrs.github.io/toastui/articles/extras/grid.html.

Usage

create_app_ranking_table(ranking, pagination = 10, height = NULL)

Arguments

ranking

Ranked data from create_app_ranking.
pagination

Control number of lines to display per page. If NULL, all data are displayed.
height

Table height. CSS units.

Value

An htmlwidget table containing app ranking, owner sorted by usage.

Create Shiny apps consumer ranking

Description

Sort consumers by number of views.

Usage

create_apps_consumer_ranking(apps, users)

Arguments

apps

Get from get_usage_shiny. Can be reactive or not.
users

Get from get_users. Can be reactive or not.

Value

A 3 columns tibble with apps consumer sorted by number of view. The role columns allows further analysis.

Create apps consumer ranking bar chart

Description

Create apps consumer ranking bar chart

Usage

create_apps_consumer_ranking_chart(ranking, threshold)

Arguments

ranking

Data obtained from create_apps_consumer_ranking.
threshold

Minimum number of app threshold. You'll need a numericInput wrapped by reactive.

Value

A bar chart with consumer sorted by descending number of total views.

Generic calendar chart generator

Description

Generic calendar chart generator

Usage

create_calendar_chart(
  calendar_data,
  title,
  subtitle = NULL,
  start_date = NULL,
  end_date = NULL,
  callback = NULL
)

Arguments

calendar_data

Calendar chart data.
title

Chart title.
subtitle

Chart subtitle.
start_date

Default to minimum calendar_data date. Could also be an input value with Shiny.
end_date

Default to maximum calendar_data date. Could also be an input value with Shiny.
callback

JS function to pass to onRender. This is useful to access the widget API on the R side at render time and add events on the fly.

Value

An echarts4r calendar chart

Create cumulated app duration/user

Description

Bar chart

Usage

create_cumulated_duration_per_user(
  apps_usage,
  start_date = NULL,
  end_date = NULL,
  selected_app
)

Arguments

apps_usage

First element returned by create_app_ranking. Can be reactive.
start_date

Default to minimum calendar_data date. Could also be an input value with Shiny.
end_date

Default to maximum calendar_data date. Could also be an input value with Shiny.
selected_app

Selected app name (string). You'll need a selectInput for instance wrapped by reactive.

Value

An echarts4r barchart.

Create cumulated app hits/user

Description

Bar chart

Usage

create_cumulated_hits_per_user(
  apps_usage,
  start_date = NULL,
  end_date = NULL,
  selected_app
)

Arguments

apps_usage

First element returned by create_app_ranking. Can be reactive.
start_date

Default to minimum calendar_data date. Could also be an input value with Shiny.
end_date

Default to maximum calendar_data date. Could also be an input value with Shiny.
selected_app

Selected app name (string). You'll need a selectInput for instance wrapped by reactive.

Value

An echarts4r barchart.

Create developer project network overview

Description

Leverages visNetwork.

Usage

create_dev_project_overview(client, apps_usage, selected_dev)

Arguments

client

RSC client. See create_rsc_client.
apps_usage

First element returned by create_app_ranking. Can be reactive.
selected_dev

Developer to select. You'll need a selectInput wrapped by reactive.

Value

A visNetwork htmlwidget with developer projects.

Create a developer ranking

Description

Rank developers by number of published apps

Usage

create_dev_ranking(users, content)

Arguments

users

Get from get_users.
content

Get from get_content.

Value

A tibble with developer ranked by decreasing number of apps.

Create developers ranking bar chart

Description

Devs are ranked by number of developed apps. See create_dev_ranking.

Usage

create_dev_ranking_chart(ranking, threshold)

Arguments

ranking

Obtained after calling create_dev_ranking. Can be reactive.
threshold

Minimum number of app threshold. You'll need a numericInput wrapped by reactive.

Value

An echarts4r bar chart.

Create standard pie chart

Description

Pie chart with percentage data

Usage

create_pie_chart(data, x_axis)

Arguments

data

Get from sort_users_by_role.
x_axis

x variable.

Value

A pie chart.

Create a connection to RStudio Connect server

Description

Leverages connectapi toolkit. Expect to have Sys.getenv("CONNECT_SERVER") and Sys.getenv("CONNECT_API_KEY") properly setup.

Usage

create_rsc_client()

Daily app consumption for selected user

Description

Daily app consumption for selected user

Usage

create_user_daily_consumption_chart(usage)

Arguments

usage

Get from get_user_daily_consumption.

Value

An echarts4r calendar chart

Generate htmlWidgets table

Description

Leverage toastui API.

Usage

generate_table(logs, sparkline = FALSE, pagination = 10, height = NULL)

Arguments

logs

Obtained with get_rsc_apps_usage.
sparkline

Whether to draw a sparkline.
pagination

Control number of lines to display per page. If NULL, all data are displayed.
height

Table height. CSS units.

Value

An htmlwidget table.

Daily app usage

Description

Used by create_app_daily_usage_chart .

Usage

get_app_daily_usage(apps_usage, selected_app)

Arguments

apps_usage

Second element returned by create_app_ranking. Can also be reactive.
selected_app

Selected app name (string). You'll need a selectInput for instance. wrapped by reactive.

Value

Calendar data for daily app usage.

Get most used app

Description

Get most used app

Usage

get_max_rsc_apps_usage(logs)

Arguments

logs

Obtained after calling get_rsc_apps_usage.

Value

A numeric value.

Extract app usage dates

Description

Extract app usage dates

Usage

get_rsc_app_dates(app, logs)

Arguments

app

app_name to filter.
logs

Given by RSC database.

Value

A tibble containing dates of usage for the given app as well as the correponding session duration.

Get RSC apps usage

Description

Called on apps_usage data

Usage

get_rsc_apps_usage(logs)

Arguments

logs

Given by RSC database.

Value

A 3 columns tibble with app name, usage and date of usage (nested tibble).

Get app count for each developer

Description

Get app count for each developer

Usage

get_rsc_developer_apps_count(developer, logs)

Arguments

developer

Developer unique id.
logs

All data logs.

Value

A number with all apps

Get app list for each developer + usage

Description

Get app list for each developer + usage

Usage

get_rsc_developer_apps_list(developer, logs)

Arguments

developer

Unique user id. Typically app_developer_id key.
logs

RSC logs.

Value

Tibble containing app name + count

Get daily shiny app usage for a given user

Description

Get daily shiny app usage for a given user

Usage

get_user_daily_consumption(content, users, apps, selected_user)

Arguments

content

Get from get_content. Can be reactive.
users

Get from get_users. Can be reactive.
apps

Get from get_usage_shiny. Can be reactive.
selected_user

User to select. You'll need a selectInput wrapped by reactive.

Value

A list. ⁠[[1]]⁠ contains the row events filtered for the given user. ⁠[[2]]⁠ is 2 columns tibble containing daily app consumption for given user (grouped by dates).

Merge RStudio Connect data together

Description

See create_app_ranking.

Usage

merge_rsc_data(content, users, apps)

Arguments

content

Get from get_content. Can be reactive.
users

Get from get_users. Can be reactive.
apps

Get from get_usage_shiny. Can be reactive.

Value

A list of 3 tibbles. ⁠[[1]]⁠: light RSC content data (less columns); ⁠[[2]]⁠: light RSC users data (less columns); ⁠[[3]]⁠: merged apps_usage data.

Process RSC content

Description

Select relevant information for RSC content data. See merge_rsc_data.

Usage

process_rsc_content(content)

Arguments

content

Get from get_content.

Value

A 3 columns tibble with content guid, app_name and owner guid. Owner guid is the same returned in process_rsc_user.

Process RSC user

Description

Select relevant information for RSC users data. See merge_rsc_data.

Usage

process_rsc_user(users)

Arguments

users

Get from get_users.

Value

A 2 columns tibble with user guid and username.

Sort RStudio Connect content by access type

Description

Sort RStudio Connect content by access type

Usage

sort_content_by_access(content, start_date = NULL, end_date = NULL)

Arguments

content

Get from get_content.
start_date

Date filter.
end_date

Date filter.

Value

A tibble with content grouped by access type.

Sort RStudio Connect content by app mode

Description

Sort RStudio Connect content by app mode

Usage

sort_content_by_appmode(content, start_date = NULL, end_date = NULL)

Arguments

content

Get from get_content.
start_date

Date filter.
end_date

Date filter.

Value

A tibble with content grouped by app mode.

Sort RStudio Connect content by python version

Description

Sort RStudio Connect content by python version

Usage

sort_content_by_pyversion(content)

Arguments

content

Get from get_content.

Value

A tibble with content grouped by python version.

Sort RStudio Connect content by R version

Description

Sort RStudio Connect content by R version

Usage

sort_content_by_rversion(content, start_date = NULL, end_date = NULL)

Arguments

content

Get from get_content.
start_date

Date filter.
end_date

Date filter.

Value

A tibble with content grouped by R version.

Sort RStudio Connect users by role

Description

Users are grouped by user_role to check the server role repartition. Using start_date and end_date allows to filter data given a specific time range.

Usage

sort_users_by_role(users, start_date = NULL, end_date = NULL)

Arguments

users

Get from get_users.
start_date

Date filter.
end_date

Date filter.

Value

A tibble with user grouped by role.