Export Canvas groups to a Zoom breakout participant list.

canvas_groups_to_zoom.R

# PREPARATIONS:
#
# * Have Teacher status in your Canvas course.
# * Get an API token for your Canvas account as described here:
#   https://community.canvaslms.com/t5/Admin-Guide/How-do-I-manage-API-access-tokens-as-an-admin/ta-p/89
#   You only need to do this once. If you generate a new token, the old one becomes invalid.
#   Keep your API token secret. It works like a password.
# * Find your course's ID number in Canvas. For example, course 1234 is at
#   https://nmbu.instructure.com/courses/1234
# * Install revision 7496d66 of rcanvas
#   (I experience bugs in authentication in later revisions as of 2021-02-23)
#   remotes::install_github(repo = "daranzolin/rcanvas", ref = "7496d66")

library(rcanvas)
library(tidyverse)

# ADJUSTMENTS FOR YOUR COURSE:

course_id <- 1234  # Replace with your course id
Sys.setenv(CANVAS_DOMAIN="https://nmbu.instructure.com")  # Change if you're not at NMBU
# Insert your API token below. Keep it private; it works as a password!
Sys.setenv(CANVAS_API_TOKEN="10453~1k...")


# User Groups:
ug <- get_course_user_groups(course_id) %>% 
  as_tibble %>% 
  filter(sortable_name != "Student, Test")

# Users:
u <- do_query(c("courses", course_id, "users"), 
              args = list(enrollment_type = "student")) %>% 
  as_tibble

# Add columns from u to ug into data frame:
d <- ug %>% full_join(u %>% select(id, name, login_id, email), by = "id")

# Export to Zoom:
d %>% 
  select(group_name, email) %>% 
  write_csv(paste0(course_id, "_zoom.csv"))

# EXCEL WILL MESS UP INTERNATIONAL CHARACTERS (ÆØÅ etc)
# if you open a CSV file directly.
# Instead, create an empty Excel workbook and choose
# Data > From Text/CSV (button near upper left) > Choose your file > 
# Choose File origin: "65001 Unicode (UTF-8)"
# (it's listed alphabetically under U)
# and click Load.


# OTHER STUFF YOU MIGHT WANT TO DO:

# Canvas Gradebook sorts in the order determined by the display language.
# If we want to match e.g. Norwegian, we can:
# stringi::stri_sort(u$sortable_name, locale = "nb_NO")

# Students not in a group:
# d %>% filter(is.na(group_name))

# Students in multiple groups:
# d %>% count(sortable_name, sort = TRUE, name = "grupper") %>% filter(grupper > 1)


# You can extract pieces of information from group names
# using regular expressions, see https://regex101.com
# Here's an example from STAT100, which has e.g.
# "Fysisk kollokvie 1", "Digital kollokvie 5", "Individuelt løp 23"
#
# extract(ug,
#         group_name,
#         into = c("gruppe", "nummer"),
#         # https://regex101.com/r/Zi0n52/1
#         regex = "(.*?) ([0-9]+)",
#         remove = FALSE)