Explain rlang metaprogramming patterns for data-masking and expression injection in R.
npx skills add https://github.com/jhelvy/dotfiles --skill rlang-patterns-jhelvy
Please help me install this Agent Skill. Skill: rlang-patterns Source: https://github.com/jhelvy/dotfiles/tree/main/claude/skills/rlang-patterns Command: npx skills add https://github.com/jhelvy/dotfiles --skill rlang-patterns-jhelvy
This Skill helps R programmers understand and implement advanced metaprogramming techniques using the rlang package, enabling them to write more robust, flexible, and powerful functions, especially those involving tidy evaluation and data-masking.
{{}}, .data, and .env for seamless column referencing in functions.!! and !!! for programmatically injecting expressions and arguments.... dynamically with name injection and splicing.Use the rlang-patterns skill to learn how to forward function arguments using the embracing {{}} operator.
High-intent search queries and answers about installing and using this skill.
Tidy evaluation allows you to pass column names by using the embracing operator {{ }} inside your R function to forward arguments seamlessly. This enables robust data-masking for user-defined expressions in tidyverse-compatible pipelines.
Expression injection with !! injects a single expression or object, while !!! splices a list of arguments into a function call. These rlang operators allow you to programmatically build and modify R code structures dynamically.
Dynamic dots are handled using rlang to capture, inject names, and splice arguments passed through .... This allows flexible argument forwarding and dynamic expansion of inputs within complex data analysis pipelines.
Use .data and .env pronouns when your data-masking function risks variable name collisions. They explicitly disambiguate whether an expression should be evaluated from the data frame or the surrounding environment.
You need rlang metaprogramming patterns when developing R packages that accept user-defined column names or expressions. These patterns ensure your functions interact safely and effectively with the tidyverse framework.
This failure occurs because data-masking functions expect expressions or symbols, not strings. You must use rlang metaprogramming patterns like the embracing operator {{ }} or convert strings to symbols for proper evaluation.
CodingKaiserApply modern tidyverse and rlang patterns to R development tasks.
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ab604Teach rlang metaprogramming patterns for tidy evaluation in R code.
laurenoconnelllabExplains how to use @, !!, and related tools for R metaprogramming and tidy evaluation.