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To reap all the advantages of the riskassessment application, an organization needs to generate and store results frequently derived from the app, including but not limited to:

  1. Uploading new packages, & storing their metric info and riskmetric score
  2. Publishing reviewer comments
  3. Submitting package decisions
  4. Storing organization-wide metric weights and score-based thresholds for decision automation
  5. Credential management for authorized users
  6. Etc

To accomplish this, the app uses configuration settings to create and populate several storage solutions locally, in the app’s root directory:

  • A SQLite database named credentials.sqlite (by default) for credential management
  • A json file named loggit.json (by default), recording rudimentary logs of actions performed in the app
  • A SQLite database named database.sqlite (by default) for storing all pkg info, metric info, and comments/ decisions

Note that this article won’t cover the credentials database since that’s that’s been covered (at length) in the “Credential Manager” guide. As you might expect, some deployment environments come with limitations that are not amicable to storage method defined above! Spoiler alert - shinyapps.io is one of them. This article will provide more details about these crucial storage objects and share a run down of the following deployment options with helpful tips:

  • shinyapps.io

  • RStudio Connect

  • Shiny Server

  • ShinyProxy

Note! In the future, we’ll consider adding utilities that would allow users to connect to an external, or remote storage method (like a database).


Installing vs Forking

Before we discuss deployment methods, we should note that the riskassessment application is developed using renv as a form of source control. This helps maintain stability in the code base. While you can install riskassessment from Github, it is strongly recommended to use a fork of the riskassessment repository for deployment. This will serve a handful or purposes for your organization:

  1. You can utilize renv in your deployment to help ensure you share the same environment as the app developers, ensuring consistent behavior.
  2. You will have easier access to the configuration file allowing for a more streamlined deployment if you have several projects.


The db-config.yml file

Starting with {riskassessment} v1.0.0, a configuration file can be found at inst/db-config.yml which is used to initialize the application for deployment. This configuration contains elements vital to app initialization and will only grow as development continues. Many of the elements in the file are also editable from within the application itself (provided your user role has the privileges to do so). Currently, db-config.yml contains the following major elements:

  • assessment_db: A string designating the file path of the assessment SQLite database (will be created upon initialization). It has a default value of database.sqlite.
  • credential_db: A string designating the file path of the credentials SQLite database (will be created upon initialization). It has a default value of credentials.sqlite.
  • loggit_json: A string designating the file path of the logging JSON file (will be created upon initialization). It has a default value of loggit.json.
  • credentials: A list defining user roles and privileges to assigned to those roles in the credentials database.
  • decisions: A list defining decision categories, automated decision rules (optional), and custom decision category colors (also optional).
  • metric_weights: A list containing the riskmetric weights to use upon initialization. These weights are used to increase and decrease the priority of any one metric.

Below is a look at the current default configuration if you were to fork the riskassessment code today:


default:
  assessment_db: database.sqlite
  loggit_json: loggit.json
  credential_db: credentials.sqlite
  credentials:
    roles:
      - admin
      - lead
      - reviewer
    privileges:
      admin: [admin, weight_adjust, auto_decision_adjust, final_decision, revert_decision, add_package, delete_package]
      lead: [weight_adjust, auto_decision_adjust, final_decision, revert_decision, add_package, delete_package]
      reviewer: add_package
  decisions:
    categories:
      - Low Risk
      - Medium Risk
      - High Risk
  metric_weights:
    covr_coverage: 0


Configuring the assessment database

When the riskassessment::run_app() function is ran, the code base will check if an assessment sqlite file exists by the name you give it (default is database.sqlite) and if it doesn’t, several tables will be initiated to create this database just before the app launches. Note that the user has the authority to name the database file to whatever they like using the inst/db-config.yml file. There, you can include a file path preceding the file name if you wish to move the location of the database away from the root directory. For example, the following code would create a database called “database.sqlite” in the dev/ folder:

default:
  assessment_db: ./dev/database.sqlite

At the time this vignette was authored, the database will initialize the following tables with all NULL values:

  • comments: stores user comments, including user names associated with each comment entry, comment type, and timestamp
  • community_usage_metrics: stores CRAN package downloads per month
  • metric: stores metric info, including the riskmetric name, label, short description, type, and weight
  • package_metrics: stores all package-specific rismetric metrics
  • package: Contains all package information, like name, version, maintainer, etc. It also contains a the riskmetric score, the weighted score, decision, and timestamp.

Note: if any changes/ updates occur in these tables with a new release of riskassessment, you may need to delete the database file before re-running the app. Any such changes should be announced as ‘breaking changes’ in the app. If so, remember to save a copy of your current database file in another directory for backup purposes.


Database log file config

As mentioned previously, the loggit.json file is initiated to track general actions performed in the application, especially those that would reflect a change in the assessment db (database.sqlite file). At the time this vignette was authored, here’s a summary of actions logged:

  • App start up
  • User log-ins
  • Enabling/ Disabling or changing automated decision rules
  • Decisions initiated by users or the decision automation rules, including
  • When pkgs are added or removed from the database, or when there are issues with this process, like when there is an absence of data to that support certain metrics
  • Re-weighting pkg metrics
  • Any database issues or conflicts that may arise

Each loggit “transaction” recorded contains a lot of info, but most notably, it will contain a time stamp, record type (“info”, “warn”, or “error”), and a message. For database transactions, the message will usually include the query that was executed. All log entries are always printed out in the R console for your convenience. For example:

riskassessment::run_app()
> [1] "Log file set to loggit.json"
> Listening on http://127.0.0.1:4097
> {"timestamp": "2023-03-20T11:46:23-0400", "log_lvl": "INFO", "log_msg": "User admin signed on as admin"}
> {"timestamp": "2023-03-20T11:46:33-0400", "log_lvl": "INFO", "log_msg": "The following decision rules were implemented by admin (admin): Medium = (0.33__COMMA__ 0.66]; Low = (0__COMMA__ 0.33]; High = (0.66__COMMA__ 1]."}

Feel free to use this information as you see fit! Similar to the assessment_db parameter in inst/db-config, you can name the file whatever you like, and save it in an any directory you’d like. Below, we save it in the dev/ folder and name it “loggit.json”:

default:
  assessment_db: ./dev/database.sqlite
  assessment_db: ./dev/loggit.json


Credentials configuration

Similar to the assessment database, when the riskassessment::run_app() function executes, the code base will check if an credentials sqlite file exists by the name you give it (default is credentials.sqlite) and if it doesn’t, riskassessment will initiate this new database before the app launches. Note that the user has the authority to name the database sqlite file whatever they desire using inst/db-config.yml. There, you can include a file path preceding the file name if you wish to move the location of the database away from the root directory. For example, the following code would create a database called “credentials.sqlite” in the dev/ folder:

default:
  assessment_db: ./dev/database.sqlite
  assessment_db: ./dev/loggit.json
  credential_db: ./dev/credentials.sqlite

Right after the credentials_db element is used, the credentials element (with two sub-elements: roles and privileges) must be populated. As a guide, below is a snippet of the default values for these elements, but we encourage you to design the configuration that works for you (or your organization).

credentials:
  roles:
    - admin
    - lead
    - reviewer
  privileges:
    admin: [admin, weight_adjust, auto_decision_adjust, final_decision, revert_decision, add_package, delete_package]
    lead: [weight_adjust, auto_decision_adjust, final_decision, revert_decision, add_package, delete_package]
    reviewer: add_package

Note the “User Roles and Privileges” guide is entirely dedicated to this config. For full details, please visit & read that article!


Decisions configuration

The decisions element contains up to three sub-elements: categories (mandatory), rules, and colors. Here is a snipped from one of the example configurations:

decisions:
  categories:
    - Insignificant Risk
    - Minor Risk
    - Moderate Risk
    - Major Risk
    - Severe Risk
  rules:
    Insignificant Risk:
      - 0
      - .1
    Severe Risk:
      - .7
      - 1
  colors:
    Moderate Risk: !expr grDevices::rgb(52, 235, 229, maxColorValue = 255)

Notice that you can set as many decision categories as you wish, but you must specify at least two! If you want to set up automatic decision rules before deploying the app, you can do so using the rules element. Just list the category name and underneath it, a mutually exclusive range of values so that when a package is uploaded, if it’s risk score falls between those values, it will automatically get labelled with the appropriate decision. Categories not addressed under the rules banner will not receive automated decisions. However, users with this privilege can change this configuration in the app at a later time.

Similarly for colors, you can detail specific colors be assigned to certain categories. If you don’t care what color is used for each category, then a color-blind friendly color palette is used to fill in the rest.


Metric weights configuration

The metric_weights element contains the named list of weights. If a weight is not supplied, it will default to 1. The current list of weights that can be included are the following: has_vignettes, has_news, news_current, has_bug_reports_url, has_website, has_maintainer, has_source_control, export_help, bugs_status, license, covr_coverage, downloads_1yr. As seen above, the default configuration sets the weight for covr_coverage to 0. If you want to ignore a certain metric because it has little value to our organization, you could give it a value of zero.

When metrics are not explicitly given here, the app uses the default weight of 1 for each, unless of course there already exists a assessment database previously initialized where those metric weights were manually changed. If you wanted to toggle all current metrics, there is no harm in stating each metric and weight, so you could set up the config file to look like this, for example:

metric_weights:
  has_vignettes: 2
  has_news: 0.5
  news_current: 2
  has_bug_reports_url: 1
  has_website: 1
  has_maintainer: 1
  has_source_control: 1
  export_help: 2
  bugs_status: 5
  license: 1
  downloads_1yr.: 3
  covr_coverage: 0

riskmetric will use these weights to score your package according to our org’s needs!


Deployment options


shinyapps.io

Beware: shinyapps.io does not offer persistent storage of riskassessment’s SQLite database or logs. Thus, it is not likely a viable deployment option for your organization or group. For example, our demo application (hosted on shinyapps.io) contains a pre-prepared database of packages that can’t be permanently altered. It CAN be altered within a session, but any changes will not persist outside the session.


Posit Connect & Shiny Server


On a server, if you want to save files on disk, you’ll need to set write permissions accordingly on the folder you want to save the database, logs, and auto-decision json file.

On Posit Connect, you need to use an absolute path to specify the directory where to save the files. You can find more information here: Persistent Storage on Posit Connect.


Beyond that, it’s important to note that we strongly encourage those deploying the app to take advantage of the renv.lock file used to maintain package version dependencies. For more information on how to use renv.lock and our general dev philosophy as it pertains to package management, please read the “Using renv article. Highly related, we encourage the use of git-backed deployment when possible. So, immediately after you update/sync your package dependencies using renv, you may want to run rsconnect::writeManifest() before deploying from a dedicated branch. For more information on git-backed deployment & manifest files, please read the Posit article on git-backed content.


ShinyProxy

With ShinyProxy, you can use a Docker volume to write files outside of the application container. In application.yml, you use can something like this in the specs describing the application:

container-volumes: [ “/var/log/shinylogs:/root/logs” ]

/var/log/shinylogs is a directory on the server where you deploy your applications with ShinyProxy. /root/logs is a directory inside your Docker image.