Parses the text an R script prints (as captured from source(script, echo = TRUE)) into tidy result tables, one per detected result block. Handles both
one-line test output (t.test, cor.test, ...) and fixed-width text tables
(summary(lm), aov, anova). The result matches the shape of
read_stat_tables(), so it flows into the same STATO typing and ISA-JSON
export.
Arguments
- text
the captured console output: a character vector of lines, or a single string with embedded newlines
- source_label
optional label (e.g. the script name) recorded as the analysis for one-line results
- code_lines
optional character vector of the script's source lines (one element per line), used to recover the source
lineof each result via the echoed statement text.NULL(default) skips line attribution.
Value
a list with one element per detected result block, each a list of
analysis (the test/section label), title, data (a tidy data.frame),
line (1-based source line, or NA when code_lines was not supplied),
line_seq (1-based counter of results sharing that line, or NA), and
call_fn (the recognised statistical function that produced the block,
e.g. "shapiro.test", or "") – the same structure read_stat_tables()
returns, plus these three fields. call_fn lets stato_type_column()
resolve statistic letters that are ambiguous in the printed output alone.
Details
When code_lines is supplied (the script's own text, one element per source
line – what a run's code_text_list[[file]] already is), each result is
additionally tagged with the 1-based source line it came from, recovered by
matching the echoed > /+ statement text against the script. A single
statement that prints several results (e.g. a for loop calling t.test()
each iteration) yields several results sharing one line; these are
distinguished by line_seq (1, 2, 3, ... within that line). Without
code_lines the echo is not parsed and line/line_seq are NA.
Examples
out <- utils::capture.output(t.test(extra ~ group, data = sleep))
res <- read_r_output(out)
res[[1]]$data
#> mean in group 1 mean in group 2
#> 1 0.75 2.33