rlang-patterns

Tidy evaluation in rlang forwards function arguments using the {{ }} operator, allowing you to pass column names as variables directly into data-masking functions like dplyr verbs for dynamic pipeline execution.

Data masking lets expressions refer to data frame columns as variables. The rlang pronouns .data and .env explicitly resolve column names and environment variables, preventing naming collisions during tidy evaluation.

Use rlang injection operators !! and !!! when you need to programmatically build or splice expressions. These operators enable dynamic code generation by unquoting single values or splicing multiple arguments into a function call.

Manage dynamic dots in rlang by using dedicated helpers to capture and process multiple arguments. This pattern ensures flexible tidy evaluation across data pipelines by cleanly handling variadic arguments passed through your functions.

Custom R functions fail tidy evaluation when arguments are not properly unquoted or forwarded. You must apply rlang patterns like {{ }} for data-masking or explicit .data pronouns to safely resolve variables within your function environment.