This vignette is partly outdated since nested structure was implemented completely. In particular, the serialization is now done differently.
library("dplyr")
library("purrr")
pkgload::load_all()This vignette builds on the vignette “Data Structures” and discusses how to go forward with the nested structure of the parse data. In order to compute the white space information in a nested data structure, we use a visitor approach to separate the algorithm (computing white space information and later apply transformations) from the object (nested data structure). The function create_filler() (name depreciated, now called initialize_attributes()) can then be used to compute current white space information on every level of nesting within the nested parse data if applied in combination with the visitor. In the sequel, a parse table at one level of nesting will be denoted with the term nest, which always represents a complete expression. Our visiting functions pre_visit() and post_visit() take an object to operate on and a list of functions. Concretely, the object is the nested parse table. Each function is applied at each level of nesting nesting before the next level of nesting is entered. You can find out more about the visitor on the help file for visit (note that this function is not exported by styler). pre_visit
## function(pd_nested, funs) {
## if (is.null(pd_nested)) return()
## pd_transformed <- visit_one(pd_nested, funs)
##
## pd_transformed$child <- map(pd_transformed$child, pre_visit, funs = funs)
## pd_transformed
## }
## <environment: namespace:styler>
visit_one
## function(pd_flat, funs) {
## reduce(funs, function(x, fun) fun(x),
## .init = pd_flat)
## }
## <environment: namespace:styler>This comes with two advantages.
We go through the whole structure only as many times as we call the visitor (instead of every *_nested() function going through it once, which is more efficient in terms of speed.
We go through the whole structure only as many times as we call the visitor (instead of every *_nested() function going through it once), which is more efficient in terms of speed.
create_filler() was adapted to also initialize indention and lag_newlines.
create_filler
## function(pd_flat) {
##
## pd_flat$line3 <- lead(pd_flat$line1, default = tail(pd_flat$line2, 1))
## pd_flat$col3 <- lead(pd_flat$col1, default = tail(pd_flat$col2, 1) + 1L)
## pd_flat$newlines <- pd_flat$line3 - pd_flat$line2
## pd_flat$lag_newlines <- lag(pd_flat$newlines, default = 0L)
## pd_flat$col2_nl <- if_else(pd_flat$newlines > 0L, 0L, pd_flat$col2)
## pd_flat$spaces <- pd_flat$col3 - pd_flat$col2_nl - 1L
## pd_flat$multi_line <- ifelse(pd_flat$terminal, FALSE, NA)
## pd_flat$indention_ref_id <- NA
## ret <- pd_flat[, !(names(pd_flat) %in% c("line3", "col3", "col2_nl"))]
##
##
## if (!("indent" %in% names(ret))) {
## ret$indent <- 0
## }
##
## if (any(ret$spaces < 0L)) {
## stop("Invalid parse data")
## }
##
## ret
## }
## <environment: namespace:styler>
code <- "a <- function(x) { if(x > 1) { 1+1 } else {x} }"
pd_nested <- compute_parse_data_nested(code)
pd_nested_enhanced <- pre_visit(pd_nested, c(create_filler))
pd_nested_enhanced
## # A tibble: 1 x 20
## line1 col1 line2 col2 id parent token terminal text short
## <int> <int> <int> <int> <int> <int> <chr> <lgl> <chr> <chr>
## 1 1 1 1 47 49 0 expr FALSE
## # ... with 10 more variables: token_before <chr>, token_after <chr>,
## # internal <lgl>, child <list>, newlines <int>, lag_newlines <int>,
## # spaces <int>, multi_line <lgl>, indention_ref_id <lgl>, indent <dbl>As a next step, we need to find a way to serialize the nested tibble, or in other words, to transform it to its character vector representation. As a starting point, consider the function serialize that was introduced in the vignette “Data Structures”.
serialize <- function(x) {
out <- Map(
function(terminal, text, child) {
if (terminal)
text
else
serialize(child)
},
x$terminal, x$text, x$child
)
out
}
serialize(pd_nested) %>% unlist
## [1] "a" "<-" "function" "(" "x" ")"
## [7] "{" "if" "(" "x" ">" "1"
## [13] ")" "{" "1" "+" "1" "}"
## [19] "else" "{" "x" "}" "}"serialize can be combined with serialize_parse_data_flat. The latter pastes together the column “text” of a flat parse table by taking into account space and line break information, splits the string by line break and returns it.
serialize_parse_data_flat
## function(pd_flat) {
## pd_flat %>%
## summarize_(
## text_ws = ~paste0(
## text, newlines_and_spaces(newlines, spaces),
## collapse = "")) %>%
## .[["text_ws"]] %>%
## strsplit("\n", fixed = TRUE) %>%
## .[[1L]]
## }
## <environment: namespace:styler>However, things get a bit more complicated, mainly because line break and white space information is not only contained in the terminal tibbles of the nested parse data, but even before, as the following example shows.
pd_nested_enhanced$child[[1]]
## # A tibble: 3 x 20
## line1 col1 line2 col2 id parent token terminal text short
## <int> <int> <int> <int> <int> <int> <chr> <lgl> <chr> <chr>
## 1 1 1 1 1 3 49 expr FALSE
## 2 1 3 1 4 2 49 LEFT_ASSIGN TRUE <- <-
## 3 1 6 1 47 48 49 expr FALSE
## # ... with 10 more variables: token_before <chr>, token_after <chr>,
## # internal <lgl>, child <list>, newlines <int>, lag_newlines <int>,
## # spaces <int>, multi_line <lgl>, indention_ref_id <lgl>, indent <dbl>
pd_nested_enhanced$child[[1]]$child[[1]]
## # A tibble: 1 x 20
## line1 col1 line2 col2 id parent token terminal text short
## <int> <int> <int> <int> <int> <int> <chr> <lgl> <chr> <chr>
## 1 1 1 1 1 1 3 SYMBOL TRUE a a
## # ... with 10 more variables: token_before <chr>, token_after <chr>,
## # child <list>, internal <lgl>, newlines <int>, lag_newlines <int>,
## # spaces <int>, multi_line <lgl>, indention_ref_id <lgl>, indent <dbl>After “a” in code, there is a space, but this information is not contained in the tibble where we find the terminal “a”. In general, we must add newlines and spaces values after we computed character vector representation of the expression. In our example: we know that there is a space after the non-terminal “a” by looking at pd_nested_enhanced$child[[1]]. Therefore, we need to add this space to the very last terminal within pd_nested_enhanced$child[[1]] before we collapse everything together.
serialize_parse_data_nested_helper
## function(pd_nested, pass_indent) {
## out <- pmap(list(pd_nested$terminal, pd_nested$text, pd_nested$child,
## pd_nested$spaces, pd_nested$lag_newlines, pd_nested$indent),
## function(terminal, text, child, spaces, lag_newlines, indent) {
## total_indent <- pass_indent + indent
## preceding_linebreak <- if_else(lag_newlines > 0, 1, 0)
## if (terminal) {
## c(add_newlines(lag_newlines),
## add_spaces(total_indent * preceding_linebreak),
## text,
## add_spaces(spaces))
## } else {
## c(add_newlines(lag_newlines),
## add_spaces(total_indent * preceding_linebreak),
## serialize_parse_data_nested_helper(child, total_indent),
## add_spaces(spaces))
## }
## }
## )
## out
## }
## <environment: namespace:styler>
serialize_parse_data_nested
## function(pd_nested) {
## out <- c(add_newlines(start_on_line(pd_nested) - 1),
## serialize_parse_data_nested_helper(pd_nested, pass_indent = 0)) %>%
## unlist() %>%
## paste0(collapse = "") %>%
## strsplit("\n", fixed = TRUE) %>%
## .[[1L]] %>%
## trimws(which = "right")
## out
## }
## <environment: namespace:styler>Before we are done, we need to add information regarding indention to the parse table. We can add indention after every line break that comes after a round bracket with indent_round(). And then serialize it.
pre_visit(pd_nested,
c(create_filler,
purrr::partial(indent_round, indent_by = 2)))
## # A tibble: 1 x 20
## line1 col1 line2 col2 id parent token terminal text short
## <int> <int> <int> <int> <int> <int> <chr> <lgl> <chr> <chr>
## 1 1 1 1 47 49 0 expr FALSE
## # ... with 10 more variables: token_before <chr>, token_after <chr>,
## # internal <lgl>, child <list>, newlines <int>, lag_newlines <int>,
## # spaces <int>, multi_line <lgl>, indention_ref_id <lgl>, indent <dbl>We can see how indention works with a more complicated example
indented <- c(
"call(",
" 1,",
" call2(",
" 2, 3,",
" call3(1, 2, 22),",
" 5",
" ),",
" 144",
")"
)
not_indented <- trimws(indented)
back_and_forth <- not_indented %>%
compute_parse_data_nested() %>%
pre_visit(c(create_filler,
purrr::partial(indent_round, indent_by = 2))) %>%
serialize_parse_data_nested()
identical(indented, back_and_forth)
## [1] TRUE