The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

REDCapSync

Several R packages exist for using the REDCap Application Program Interface (API) such as, redcapAPI, REDCapR, and tidyREDCap. However, REDCapSync is the first “get-everything” REDCap R package that converts REDCap projects into a standardized, API-efficient, and project-agnostic R6 object.

What is REDCapSync?

REDCapSync unleashes the full power of the REDCap API even for the basic R user. When a sync is performed, REDCapSync uses a cache of previous saves, a user-defined directory, and the REDCap log to only update data that changed since the last API call. Project objects can be used for the best that R has to offer via statistics, visualization, functions, shiny apps, and more!

The aims of REDCapSync are to…

Encapsulate the REDCap API into one standardized object to streamline use.
Automate common tasks such as cleaning, deidentification and merges.
Automate distribution of user-defined Excel datasets to local/cloud storage for one or many REDCap projects.
Convert labelled REDCap data from R or Excel for upload using REDCap API.
Power the companion shiny app RosyREDCap

By leveraging the combined strengths of R and REDCap, users can maintain strong data pipelines that include statistics, visuals, and even shiny applications!

Installation

The stable release version can be installed from CRAN.

install.packages("REDCapSync")

Development Version

You can install the development version from GitHub with the pak. Windows users may need to install RTools version 4.5 to use pak.

# install.packages("pak")
pak::pak("thecodingdocs/REDCapSync")

Alternatively, you can install the development version from GitHub with the remotes package.

# install.packages("remotes")
remotes::install_github("thecodingdocs/REDCapSync")

If you have any issues, try downloading the most recent version of R at RStudio and update all packages in RStudio. See thecodingdocs.com/r/getting-started.

Getting Started!

Getting started is as simple as 1.) setting your token, 2.) setting up a project, and 3.) running project$sync(). See Getting Started page for the basics!

# 1.) setting your token -------------------------------------------------------
Sys.setenv(REDCAPSYNC_FIRST_PROJECT = "YoUrNevErShaReToken")    # put in console
# or WAY BETTER put this in your .Renviron file...
# REDCAPSYNC_FIRST_PROJECT = 'YoUrNevErShaReToken
# Then save file, restart R session (`.rs.restartR()`) and library(REDCapSync)

# 2.) setting up a project -----------------------------------------------------
project <- setup_project(
  project_name = "FIRST_PROJECT",                       
  redcap_uri = "https://redcap.fake.edu/api/",             # same as REDCapR
  dir_path = getwd(),                            # choose appropriate folder
  sync_frequency = "daily",                          # only checks max daily 
  get_entire_log = TRUE                       # for small or medium projects
)

# install.packages("keyring") 
project$test_token()                    # will launch keyring if token fails

# 3.) running project$sync() ---------------------------------------------------
project$sync() 

project$generate_dataset("custom", envir = globalenv())

For an in-depth demonstration of both REDCapSync and RosyREDCap, see RMed26-Demo.

Framework

Minimum Requirements

R (and RStudio) installed on your computer or server.
Access to at least one REDCap project (real or test) with API Token privileges according to user rights.
Ideally, you should have User Permissions to logging in order to use the package efficiently
Appropriate permission to export and analyze data for projects for which you have a token.
Basic R knowledge such as installing a package and running code.
Thoughtful attention to how and where data you create is used and stored.

Contributing

If you wish to contribute to this software, use github issues and pull requests.

Style Guidelines

Functions

Exported function names: snake_case
- Examples: setup_project, load_project, sync
Internal function names: snake_case
- Examples: get_project_token, get_redcap_data
- Exceptions: .onLoad (R standard)
  - redcapAPI functions (dromedaryCase)
  - utils functions: write.csv, object.size, browseURL
Function parameters: snake_case
- examples: project_name, dir_path, redcap_uri, sync_frequency
Function variables: snake_case

Constants/Data

Internal constants: SCREAMING_SNAKE_CASE
- Examples: FAKE_TOKEN, BLANK_PROJECT_COLS, SYNC_FREQUENCY
Internal datasets: SCREAMING_SNAKE_CASE
- Examples: TEST_CLASSIC, TEST_REPEATING, TEST_CANCER
Environment variable names: SCREAMING_SNAKE_CASE
- Examples: REDCAPSYNC_TEST_CLASSIC

R6 Class

R6ClassGenerator and R6 Classes: PascalCase with capitalized “REDCap” acronym
- Example: REDCapSyncProject
R6 public_methods: snake_case
R6 active_bindings: snake_case
- Exception: .internal for custom functions

Package Use

project_name: SCREAMING_SNAKE_CASE (numbers allowed if not first)
REDCapSyncProject object environment name can be “project” or user-defined
Package options: snake.case
- Examples: redcapsync.config.show.api.messages

Disclaimers

With great power comes great responsibility! The REDCap API has the with ability to read and write sensitive data. The API token holder is ultimately responsible for their activity and security.
Always confirm that you have the appropriate permission to use and store data.
REDCap is maintained by Vanderbilt University and is not responsible for testing, developing, or maintaining this software.
This package is still in development and is subject to changes, especially pre-CRAN submission.