rcxl
Read xlsx Files with a Native Parser
Reads tabular data from xlsx files with a specialized C parser. Worksheet XML is scanned in a single pass into compact per-column buffers, with no intermediate document model, and the R vectors are built from those. Bundles the 'miniz' and 'libdeflate' decompressors to read the underlying archive.
rcxl
| CRAN checks | Linux | macOS | Windows |
|---|---|---|---|
| results |  |
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Read tabular data from xlsx files with a native C parser.
rcxl scans worksheet XML without building an XML document tree, using intermediate column buffers before constructing R vectors. The miniz
and libdeflate decompressors are bundled, so the package has no R dependencies beyond base R.
Installation
From CRAN:
install.packages("rcxl")
The development version from GitHub:
# install.packages("remotes")
remotes::install_github("vlshields/rcxl")
Usage
read_xlsx() returns a plain data.frame, taking the first row as the header:
library(rcxl)
path <- system.file("extdata", "flights.xlsx", package = "rcxl")
df <- read_xlsx(path)
dim(df)
#> [1] 100 10
Column types are guessed from the cells in the read area; dates come back as
POSIXct in UTC.
xlsx_sheets() lists sheets, and sheet takes a name or an index:
multi <- system.file("extdata", "multisheet.xlsx", package = "rcxl")
xlsx_sheets(multi)
#> [1] "Alpha" "Beta" "Gamma"
read_xlsx(multi, sheet = "Beta")
read_xlsx(multi, sheet = 2)
read_xlsx_all() reads every sheet from a single workbook parse and returns a
named list of data.frames:
sheets <- read_xlsx_all(multi)
names(sheets)
#> [1] "Alpha" "Beta" "Gamma"
Reads can be windowed with an A1 range (column-only and row-only forms work
too), or with skip / n_max:
read_xlsx(path, range = "B3:D10")
read_xlsx(path, range = "B:C")
read_xlsx(path, skip = 5, n_max = 10)
col_names accepts TRUE, FALSE (auto names, header row becomes data), or a
character vector sized to the read area. col_types takes "text",
"numeric", "date", "logical", "guess", "skip", or "list", recycled
if length 1:
read_xlsx(path, col_names = FALSE)
read_xlsx(path, col_types = "text") # everything as character
read_xlsx(path, col_types = c("skip", rep("guess", 9))) # drop the first column
Other arguments: na blanks matching cells, trim_ws trims surrounding
whitespace, and name_repair is one of "unique" (default), "minimal", or
"check_unique". See ?read_xlsx for details.
By default, worksheets with less than 4 MB of uncompressed XML are read
serially and larger ones on several threads. Set the RCXL_THREADS
environment variable to an explicit worker count; it overrides both the
default count and the size threshold.
Performance
Median wall-clock time to read each file, warm cache, measured with the
bench package. The timing runs do not compare outputs. Parity with readxl is
checked separately: tools/parity_big.R requires an exact match, cell for
cell, on the on-time file and the other large workbook, and the test suite
compares the fixtures with a tolerance of 1e-9 on numeric values.
| File | rcxl | rcxl, 1 thread | readxl |
|---|---|---|---|
| BTS on-time reporting, 96 MB | 2.51 s | 3.99 s | 15.9 s |
| numeric fixture, 16 MB | 124 ms | 215 ms | 954 ms |
| mixed fixture, 10 MB | 136 ms | 204 ms | 796 ms |
| shared-strings fixture | 31 ms | 49 ms | 376 ms |
| wide fixture | 24 ms | 45 ms | 186 ms |
rcxl 0.1.1, readxl 1.5.0, R 4.5.0, bench 1.1.4, on an AMD Ryzen 3 7320U
(8 cores) under Linux, 2026-10-15. Medians of 15 iterations (5 for the
on-time file). Across three runs the rcxl medians agreed within 3% and the
readxl medians within 8%, the widest spread being readxl on the on-time file
(15.6 s to 16.7 s). The raw results are in tools/bench_results. The fixtures
come from tools/make_fixtures.R; the on-time file is the public Bureau of
Transportation Statistics on-time reporting table converted to xlsx. The
script is tools/bench_mark.R.
Coming from readxl
rcxl has no guess_max or progress argument. The arguments sheet,
skip, n_max, trim_ws, col_names, and col_types take the same values
as in readxl, and the test suite checks skip, n_max, range, col_names,
and col_types (including forced conversions) against readxl 1.5.0 on the
shipped fixtures. Dates come back as POSIXct in UTC. na and range each differ in one case, and
name_repair offers fewer options (see below).
| readxl | rcxl | |
|---|---|---|
| Return type | tibble | plain data.frame |
| Listing sheets | excel_sheets() |
xlsx_sheets() |
| Reading every sheet | loop over the sheets | read_xlsx_all() |
| Type guessing | first guess_max rows |
every cell in the read area |
| Name repair | .name_repair, any tidyverse option |
name_repair: "unique", "minimal", or "check_unique" |
| Formats | xls and xlsx |
xlsx only |
range entirely past the data |
0-by-0 result | the range's rectangle, as all-NA columns |
na against a numeric cell |
matches the text stored in the file | matches the value, so "-999.0" blanks a cell holding -999 |
Masking
Both packages export read_xlsx(). If both are attached, the one attached
last masks the other:
library(readxl)
library(rcxl)
#> Attaching package: 'rcxl'
#>
#> The following object is masked from 'package:readxl':
#>
#> read_xlsx
To be explicit about which one runs, call it with the namespace:
rcxl::read_xlsx(path)
readxl::read_xlsx(path)
License
MIT. Bundled miniz and libdeflate retain their own copyright and license
terms; see inst/COPYRIGHTS.