README

Overview

This is a basic R package for interfacing with the Intellidemia Concourse API.

Installation

bRush is not available on CRAN and can be installed directly from GitHub using the devtools package (which is available on CRAN).

devtools::install_github("erikpal/concourse_client")

Setup and use of API Token

To use this package, get the API token from the admin panel.

Place the token in a file called .Renviron as such:

CONCOURSE_KEY = ABcD123efG45hIJ78KLMno9PQrstuVwXyZ10

This method follows the best practice for developing API packages as documented here: https://cran.r-project.org/web/packages/httr/vignettes/api-packages.html

Alternatively, you may place the token in a text file called token.txt to be loaded from the working directory at the time needed.

You may store multiple keys for multiple servers, and override the default name of “CONCOURSE_KEY” by passing this arugument when making requests:

env_var_name = "NameOfApiKey"

Setup and use of server urls

The loadURL function will load urls provided in .Renviron file as well. By default, the variables CONCOURSE_SANDBOX, CONCOURSE_URL use “sandbox” or “production” as shortcuts for you development and production environments. CONCOURSE_SANDBOX is the default for all functions. Any variable name can be specified, and you may also pass an actual url instead of using environment variables (e.g, server = “https://univ.campusconcourse.com/”).

Example Usage

Example #1 - Make a custom table of syllabus items in a department (BIOL) templates

library(dplyr)
library(purrr)
library(tidyr)
library(magrittr)
library(concourseClient)

getCourseIDs(template = "templates", department_id = "BIOL") %>%  ## Call to get course IDs
  pull(external_id) %>%                                           ## Pull the IDs column
  map_df(~getCourseInfo(.x,                                       ## Call each syllabus
                        verbose = TRUE) %>%                       ## Use verbose mode
           .[["syllabus"]] %>%                                    ## Pull the syllabus list
           .[["children"]] %$%                                    ## Pull the children list
           tibble(external_id = .x,                               ## Make a data frame, add the ID
                  items = map(., ~.x$pretty_name)                 ## Unlist the pretty name
                  )
         ) %>% 
  unnest(items) %>%                                               ## Unnest the lsit of pretty names
  mutate(exists = TRUE) %>%                                       ## Make a variable to spread
  complete(items, nesting(external_id), 
           fill = list(exists = FALSE)) %>%                       ## Complete the data set with FALSE
  pivot_wider(names_from = items,                                 ## Spread the pretty names
              values_from = exists)                               ## Fill with exists

Example #2 - Create a report of syllabus activity for current classes by department

library(dplyr)
library(purrr)
library(concourseClient)

getCourseIDs(timeframe = "current", department_id = "PYCH") %>%   ## Call to get course IDs
  pull(external_id) %>%                                           ## Pull the IDs column
  map_df(~getSyllabusAccess(.x,                                   ## Call each syllabus
                            verbose = TRUE) %>%                   ## Use verbose mode
           .[["registrants"]] %>%                                 ## Pull the registrants list
           do.call(rbind, .) %>%                                  ## Convert the list to a matrix
           as.data.frame() %>%                                    ## Convert the matix to a df
           mutate(course_id = .x)                                 ## Add a course id column
  )

erikpal / concourse_client