Merge pull request #27 from b-rodrigues/fix_issue_7

Fix issue 7

Author: b-rodrigues

.env

@@ -0,0 +1 @@
+AIDER_AUTO_COMMITS=false

.gitignore

@@ -11,4 +11,5 @@ inst/doc
 result
 .envrc
 .direnv
-.aider*
+.aider*
+.env

DESCRIPTION

@@ -34,7 +34,6 @@ Suggests:
     tidyr
 VignetteBuilder: 
     knitr
-Config/fusen/version: 0.5.2
 Encoding: UTF-8
 LazyData: TRUE
 Roxygen: list(markdown = TRUE)

R/.R

@@ -1,5 +1,3 @@
-# WARNING - Generated by {fusen} from dev/flat_chronicle.Rmd: do not edit by hand
-
 #' Decorates a function to output objects of type `chronicle`.
 #' @param .f A function to decorate.
 #' @param .g Optional. A function to apply to the intermediary results for monitoring purposes. Defaults to returning NA.
@@ -24,19 +22,52 @@
 #' @importFrom utils tail
 #' @examples
 #' record(sqrt)(10)
+#' record(sqrt)(x = 10)
 #' @export
 record <- function(.f, .g = (\(x) NA), strict = 2, diff = "none") {
   fstring <- deparse1(substitute(.f))
 
   function(.value, ..., .log_df = data.frame()) {
-    args <- paste0(rlang::enexprs(...), collapse = ",")
+    # Capture the call and arguments
+    other_args_exprs <- rlang::enexprs(...)
+
+    # Determine the main data value and other arguments based on call type
+    if (missing(.value)) {
+      # This is a direct call, not from a pipe.
+      # e.g., r_sqrt(10) or r_select(df, col)
+      if (length(other_args_exprs) == 0) {
+        stop("At least one argument must be provided.", call. = FALSE)
+      }
+      # The first argument in ... is the data
+      data_val <- eval(other_args_exprs[[1]], envir = parent.frame())
+      func_args <- other_args_exprs[-1]
+      log_args_exprs <- other_args_exprs
+    } else {
+      # This is a piped call, either from `|>` or `%>=%` (bind_record)
+      # .value is the data from the pipe.
+      data_val <- .value
+      func_args <- other_args_exprs
+      # For logging, we need to represent the full call.
+      # deparse(substitute(.value)) will give the name of the variable if it came from a pipe.
+      # For bind_record, it might be complex, so we just represent it as the data itself.
+      # A simple deparse is sufficient for most logging cases.
+      log_args_exprs <- c(list(substitute(.value)), other_args_exprs)
+    }
+
+    # For logging, deparse the expressions to get a string representation
+    # For direct calls, this is perfect. For piped calls, it's an approximation.
+    mc <- match.call()
+    mc$.log_df <- NULL
+    mc[[1]] <- NULL
+    args <- paste0(sapply(mc, deparse), collapse = ", ")
 
     start <- Sys.time()
     pure_f <- purely(.f, strict = strict)
-    res_pure <- pure_f(.value, ...)
+    # We pass the evaluated data_val and the unevaluated other args to pure_f
+    res_pure <- do.call(pure_f, c(list(data_val), func_args))
     end <- Sys.time()
 
-    input <- .value
+    input <- data_val
     output <- maybe::from_maybe(res_pure$value, default = maybe::nothing())
     diff_obj <- switch(
       diff,

R/record.R

@@ -17,7 +17,7 @@ knitr::opts_chunk$set(
 
 
 <!-- badges: start -->
-[![R-CMD-check](https://github.com/b-rodrigues/chronicler/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/b-rodrigues/chronicler/actions/workflows/R-CMD-check.yaml)
+[![R-hub v2](https://github.com/b-rodrigues/chronicler/actions/workflows/rhub.yaml/badge.svg)](https://github.com/b-rodrigues/chronicler/actions/workflows/rhub.yaml/)
 [![Codecov test coverage](https://codecov.io/gh/b-rodrigues/chronicler/branch/master/graph/badge.svg)](https://app.codecov.io/gh/b-rodrigues/chronicler?branch=master)
 <!-- badges: end -->
 
@@ -41,12 +41,13 @@ devtools::install_github("b-rodrigues/chronicler")
 
 ## Introduction
 
-`{chronicler}` provides the `record()` function, which allows you to modify functions so that they
-provide enhanced output. This enhanced output consists in a detailed log, and by chaining decorated
-functions, it becomes possible to have a complete trace of the operations that led to the final
-output. These decorated functions work exactly the same as their undecorated counterparts, but some
-care is required for correctly handling them. This introduction will give you a quick overview of
-this package’s functionality.
+`{chronicler}` provides the `record()` function, which allows you to modify
+functions so that they provide enhanced output. This enhanced output consists in
+a detailed log, and by chaining decorated functions, it becomes possible to have
+a complete trace of the operations that led to the final output. These decorated
+functions work exactly the same as their undecorated counterparts, but some care
+is required for correctly handling them. This introduction will give you a quick
+overview of this package’s functionality.
 
 Let's first start with a simple example, by decorating the `sqrt()` function:
 
@@ -113,8 +114,8 @@ b <- 1:10 |>
 
 ```
 
-(`bind_record()` is used to chain multiple decorated functions and will be explained in
-detail in the next section.)
+(`bind_record()` is used to chain multiple decorated functions and will be
+explained in detail in the next section.)
 
 ```{r}
 read_log(b)
@@ -132,9 +133,10 @@ r_exp <- record(exp)
 r_mean <- record(mean)
 ```
 
-you can use the `record_many()` function. `record_many()` takes a list of functions (as strings)
-as an input and puts generated code in your system's clipboard. You can then paste the code
-into your text editor. The gif below illustrates how `record_many()` works:
+you can use the `record_many()` function. `record_many()` takes a list of
+functions (as strings) as an input and puts generated code in your system's
+clipboard. You can then paste the code into your text editor. The gif below
+illustrates how `record_many()` works:
 
 ![`record_many()` in action](https://raw.githubusercontent.com/b-rodrigues/chronicler/master/data-raw/record_many.gif)