Confidentiality-Confidence-Builder

PART ONE: OVERVIEW

This repository will help you practice using {keyring}, and {dotenv}. These are very useful packages when it comes to keeping confidential information off of GitHub.

Step 1.1: Fork this repository so that you have a copy under your own GitHub account

Step 1.2: Clone the new repository that is under your own GitHub account (this will allow you to push your commits)

Step 1.3: Create a .env file using the methods below in PART TWO

Step 1.4: Practice using {keyring} following the steps in PART THREE

Step 1.5: Demo how these tools could be used in a workflow using the R script called dataprep.R (located in the tools/ folder)

PART TWO: USING {dotenv} TO HIDE INTERNAL LINKS

{dotenv} provides a simple solution for teams that need to share access information internally but that information should not be committed to the repository. Learn more here

Step 2.1: Create a .env file. Here you will define visible public names for each sensitive piece of information

• Open a new text file
• Add the following to the first line Visible_Public_Name="hidden information"
• Add a blank line at the end of this file. If not, R will have an issue processing it
• To prepare for today's demo, save the text file as "practice.env" in the root directory
• More dotenv formatting details:
  • Note whitespace is NOT allowed right before or after the equal sign
  • Comments start with #, without any leading whitespace
  • You cannot mix variable definitions and comments in the same line
  • Empty lines (containing whitespace only) are ignored

Step 2.2: Make sure the .env file is not committed to the repository by adding '*.env' to a new line in the .gitignore file in your project folder

Step 2.3: Open a new R script. Install and load the dotenv package.

install.packages("dotenv")
library(dotenv)

Step 2.4: Load hidden sensitive information stored in .env file using dotenv::load_dot_env("practice.env")

Step 2.5: Bring your hidden sensitive information into your global environment using Sys.getenv("Visible_Public_Name")

PART THREE: USING {keyring} TO HIDE PERSONAL USER NAMES AND PASSWORDS

This method is suited for storing personal information that individuals on a team use to access their respective databases

"Each keyring can contain one or many secrets (keys). A key is defined by a service name and a password. Once a key is defined, it persists in the keyring store of the operating system. This means the keys persist beyond the termination of a R session. Specifically, you can define a key once, and then read the key value in completely independent R sessions... Note that all platforms have a default keyring, and key_get(), etc. will use that automatically."

Step 3.1: Open a new R script. Install and load the keyring package.

install.packages("keyring")
library(keyring)

Step 3.2: Store your username with password using key_set_with_value() OR in via Windows Credential Manager

• Set up password information in R using keyring:

keyring::key_set_with_value(service = "test service", 
                   username = "test username",
                   password = "test password")

• Set up a credential in windows:
  • Go to Credential Manager
  • Under the Windows Credentials tab select "Add a generic credential"
  • Enter information and click OK

Step 3.3: Bring your username and password into your code as needed with 'keyring::key_list()' and 'keyring::key_get()'

• keyring::key_list() will show list of the services and usernames you have saved
• keyring::key_list("test service")$username will give you just the username
• keyring::key_get("test service", "test username") will provide the password associated with a given service and username