Lint some code plus improve performance with base R and vctrs + reduce pipe

[olivroy]

Summary

This PR updates some code and has 2 goals

Performance

Partially inspired by https://www.tidyverse.org/blog/2023/04/performant-packages/

• Use more vctrs and base R instead of dplyr when possible
• use fixed = TRUE
• Simplify some dplyr code
• a tibble is not always necessary. and can be replaced with vctrs::data_frame() for complex cases or data.frame()

linting / code consistency

• Reduce magrittr pipe in codebase
• Use magrittr pipe in test-fmt_percent.R
• linting suggested by lintr
• space and quotes

Checklist

• I understand and agree to the Code of Conduct.
• I have listed any major changes in the NEWS.
• I have added testthat unit tests to tests/testthat for any new functionality.

• Follows-up on add performance monitoring tests and initial improvements #968 + Improve performance of render_html() #1470

#performance

Other possibilities, see if we can reduce as_tibble() calls

Profiling

Before:

This PR

Seems to be a significant memory usage gain!

with the following example:

The overall impact may not be that big, but still base R has some interesting improvements

bench::mark(
  mtcars |> dplyr::filter(vs > 5) |> dplyr::pull(cyl),
  mtcars[mtcars$vs > 5, "cyl", drop = TRUE]
)
#> # A tibble: 2 × 6
#>   expression                            min  median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>                        <bch:t> <bch:t>     <dbl> <bch:byt>    <dbl>
#> 1 "dplyr::pull(dplyr::filter(mtcar…  1.08ms  1.43ms      556.    4.05MB     8.46
#> 2 "mtcars[mtcars$vs > 5, \"cyl\", …  16.7µs  19.5µs    36483.      184B     7.30

bench::mark(
  mtcars |> dplyr::arrange(cyl),
  mtcars[order(mtcars$cyl), ]
)
#> # A tibble: 2 × 6
#>   expression                       min   median `itr/sec` mem_alloc `gc/sec`
#>   <bch:expr>                  <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl>
#> 1 dplyr::arrange(mtcars, cyl)    1.6ms   1.93ms      468.    4.24MB     6.36
#> 2 mtcars[order(mtcars$cyl), ]  107.8µs  122.7µs     6326.    3.86KB    12.6

I used this example

library(dplyr)
library(gt) # or load_all()
best_gas_mileage_city <- 
  gtcars |> 
  arrange(desc(mpg_c)) |>
  slice(1) |>
  mutate(car = paste(mfr, model)) |>
  pull(car)

# Use dplyr functions to get the car with the highest horsepower
# this will be used to target the correct cell for a footnote
highest_horsepower <- 
  gtcars |> 
  arrange(desc(hp)) |>
  slice(1) |>
  mutate(car = paste(mfr, model)) |>
  pull(car)

# Define our preferred order for `ctry_origin`
order_countries <- c("Germany", "Italy", "United States", "Japan")

# Create a display table with `gtcars`, using all of the previous
# statements piped together + additional `tab_footnote()` stmts
tab <-
  gtcars |>
  arrange(
    factor(ctry_origin, levels = order_countries),
    mfr, desc(msrp)
  ) |>
  mutate(car = paste(mfr, model)) |>
  select(-mfr, -model) |>
  group_by(ctry_origin) |>
  gt(rowname_col = "car") |>
  cols_hide(columns = c(drivetrain, bdy_style)) |>
  cols_move(
    columns = c(trsmn, mpg_c, mpg_h),
    after = trim
  ) |>
  tab_spanner(
    label = "Performance",
    columns = c(mpg_c, mpg_h, hp, hp_rpm, trq, trq_rpm)
  ) |>
  cols_merge(
    columns = c(mpg_c, mpg_h),
    pattern = "<<{1}c<br>{2}h>>"
  ) |>
  cols_merge(
    columns = c(hp, hp_rpm),
    pattern = "{1}<br>@{2}rpm"
  ) |>
  cols_merge(
    columns = c(trq, trq_rpm),
    pattern = "{1}<br>@{2}rpm"
  ) |>
  cols_label(
    mpg_c = "MPG",
    hp = "HP",
    trq = "Torque",
    year = "Year",
    trim = "Trim",
    trsmn = "Transmission",
    msrp = "MSRP"
  ) |>
  fmt_currency(columns = msrp, decimals = 0) |>
  cols_align(
    align = "center",
    columns = c(mpg_c, hp, trq)
  ) |>
  tab_style(
    style = cell_text(size = px(12)),
    locations = cells_body(
      columns = c(trim, trsmn, mpg_c, hp, trq)
    )
  ) |>
  text_transform(
    locations = cells_body(columns = trsmn),
    fn = function(x) {
      
      speed <- substr(x, 1, 1)
      
      type <-
        dplyr::case_when(
          substr(x, 2, 3) == "am" ~ "Automatic/Manual",
          substr(x, 2, 2) == "m" ~ "Manual",
          substr(x, 2, 2) == "a" ~ "Automatic",
          substr(x, 2, 3) == "dd" ~ "Direct Drive"
        )
      
      paste(speed, " Speed<br><em>", type, "</em>")
    }
  ) |>
  tab_header(
    title = md("The Cars of **gtcars**"),
    subtitle = "These are some fine automobiles"
  ) |>
  tab_source_note(
    source_note = md(
      "Source: Various pages within the Edmonds website."
    )
  ) |>
  tab_footnote(
    footnote = md("Best gas mileage (city) of all the **gtcars**."),
    locations = cells_body(
      columns = mpg_c,
      rows = best_gas_mileage_city
    )
  ) |>
  tab_footnote(
    footnote = md("The highest horsepower of all the **gtcars**."),
    locations = cells_body(
      columns = hp,
      rows = highest_horsepower
    )
  ) |>
  tab_footnote(
    footnote = "All prices in U.S. dollars (USD).",
    locations = cells_column_labels(columns = msrp)
  ) 
tab %>% gt:::render_as_html()

[rich-iannone]

All of this is so great. I somewhat regret using so much dplyr in the codebase (though I guess it was faster for development) but going down the road of slowly replacing this with base R will make everything so much faster. Thanks for your dedication here!

[rich-iannone]

LGTM!