date()
[1] "Sun Sep 10 16:20:14 2023"
devtools::load_all()
ℹ Loading readODS
file <- here::here("benchmark/basic_example.ods")
## it was 50.4ms
bench::mark("readODS" = read_ods(file, sheet = 2), check = FALSE, filter_gc = FALSE, iterations = 20) |>
dplyr::transmute(expression, min, median, mean = total_time/n_itr, n_itr)
# A tibble: 1 × 4
expression min median mean
<bch:expr> <bch:tm> <bch:tm> <bch:tm>
1 readODS 7.86ms 9.96ms 15ms
postcodes_file <- here::here("benchmark/civil-service-postcodes-2021.ods")
## it was 13.7s
bench::mark("readODS" = readODS::read_ods(postcodes_file, 2), check = FALSE, filter_gc = FALSE, iterations = 5) |>
dplyr::transmute(expression, min, median, mean = total_time/n_itr, n_itr)
New names:
New names:
New names:
New names:
New names:
New names:
• `` -> `...2`
• `` -> `...3`
• `` -> `...4`
• `` -> `...5`
• `` -> `...6`
• `` -> `...7`
• `` -> `...8`
• `` -> `...9`
• `` -> `...10`
• `` -> `...11`
# A tibble: 1 × 4
expression min median mean
<bch:expr> <bch:tm> <bch:tm> <bch:tm>
1 readODS 433ms 438ms 445ms
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