validate_param

Centralized parameter validation to reduce code duplication

internal

Provides a framework and toolkit to guide R dashboard developers in
implementing the Behavioral Insight Design (BID) framework. The package offers
functions for documenting each of the five stages (Interpret, Notice,
Anticipate, Structure, and Validate), along with a comprehensive concept
dictionary. Works with both 'shiny' applications and 'Quarto' dashboards.

Jeremy Winget

bidux

Behavioral Insight Design: A Toolkit for Integrating Behavioral
Science in UI/UX Design

validate_param function

<dl><dt>value</dt>
<dd>The value to validate</dd>
<dt>arg_name</dt>
<dd>The argument name for error messages</dd>
<dt>type</dt>
<dd>Expected type: "character", "logical", "numeric"</dd>
<dt>min_length</dt>
<dd>Minimum length for vectors</dd>
<dt>max_length</dt>
<dd>Maximum length for vectors</dd>
<dt>allow_na</dt>
<dd>Whether NA values are allowed</dd>
<dt>choices</dt>
<dd>Valid choices for character parameters</dd></dl>

Arguments

Common validation utility for bidux functions (DRY principle) — validate_param

<dl>

<dt>value</dt>
<dd>The value to validate</dd>


<dt>arg_name</dt>
<dd>The argument name for error messages</dd>


<dt>type</dt>
<dd>Expected type: "character", "logical", "numeric"</dd>


<dt>min_length</dt>
<dd>Minimum length for vectors</dd>


<dt>max_length</dt>
<dd>Maximum length for vectors</dd>


<dt>allow_na</dt>
<dd>Whether NA values are allowed</dd>


<dt>choices</dt>
<dd>Valid choices for character parameters</dd>

</dl>

validate_param: Common validation utility for bidux functions (DRY principle)

Description

Usage

Arguments