metaprogramming-rlang

Pass column names as function arguments in dplyr by using the rlang embrace operator `{{ }}` to implement tidy evaluation, safely forwarding the variable for data-masking operations.

Tidy evaluation is an R programming framework enabling data masking, allowing expressions to be evaluated within a data frame's scope so you can reference column names directly without quoting strings.

Use rlang injection operators `!!` and `!!!` inside R functions to unquote and splice expressions dynamically, allowing you to build complex data-masking APIs programmatically before evaluation.

You can build custom R package APIs relying on tidyverse data masking by implementing rlang metaprogramming patterns, utilizing pronouns and embracing to ensure robust dynamic argument handling.

Custom R functions fail forwarding arguments to dplyr verbs when tidy evaluation is not implemented, requiring the rlang embrace operator `{{ }}` to correctly resolve the data-masking environment.

The best way to handle dynamic arguments in tidyverse functions is using rlang metaprogramming, which provides injection operators and pronouns to safely manage data-masking and expression evaluation.