metaprogramming

To defuse and inject expressions in R, use rlang primitives like `expr()`, `enquo()`, and `enquos()` to capture code, then inject them into data-masked calls using `!!` and `{{` operators. This approach enables programmatic generation and transformation of R code.

Tidy evaluation is an R metaprogramming paradigm where quosures capture both an expression and its environment. Using rlang functions like `quo_get_expr` and `quo_get_env`, developers ensure correct evaluation across packages and data masks.

Yes, you can generate dynamic function calls in R packages by defusing arguments with `enquo()`, modifying the resulting expressions, and injecting them back into data-masked contexts. This allows programmatic code generation for library development.

Yes, rlang defuse and inject patterns require R version 4.3 or higher and rlang version 1.1.3 or higher. These versions provide the necessary front-mended primitives for building and inspecting quosures.

Injected expressions fail when quosures are not properly built or environments are mismatched. Use `quo_get_env` to verify the captured environment and ensure you are using `!!` or `{{` operators correctly within data-masked calls for proper evaluation.

The best way to forward multiple arguments in R metaprogramming is using `enquos()` to defuse them into a list of quosures, then injecting them with the `!!!` operator. This pattern ensures correct environment tracking across data masks.