> glimpse(as_tibble(mtcars), width = 70L)
Rows: 32
Columns: 11
$ mpg  <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, …
$ cyl  <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8, 8, 8, 8, 8, 4, …
$ disp <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225.0, 360.0, 146.7…
$ hp   <dbl> 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 18…
$ drat <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, …
$ wt   <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.460, 3.570, 3.190…
$ qsec <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20.00…
$ vs   <dbl> 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, …
$ am   <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, …
$ gear <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, …
$ carb <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, …

> glimpse(as_tibble(iris), width = 70L)
Rows: 150
Columns: 5
$ Sepal.Length <dbl> 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4…
$ Sepal.Width  <dbl> 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3…
$ Petal.Length <dbl> 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1…
$ Petal.Width  <dbl> 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0…
$ Species      <fct> setosa, setosa, setosa, setosa, setosa, setosa…

> # No columns
> glimpse(as_tibble(iris[integer()]), width = 70L)
Rows: 150
Columns: 0

> # Non-syntactic names
> df <- tibble(!!!set_names(c(5, 3), c("mean(x)", "var(x)")))
> glimpse(df, width = 28)
Rows: 1
Columns: 2
$ `mean(x)` <dbl> 5
$ `var(x)`  <dbl> 3

> glimpse(as_tibble(df_all), width = 70L)
Rows: 3
Columns: 9
$ a <dbl> 1.0, 2.5, NA
$ b <int> 1, 2, NA
$ c <lgl> TRUE, FALSE, NA
$ d <chr> "a", "b", NA
$ e <fct> a, b, NA
$ f <date> 2015-12-10, 2015-12-11, NA
$ g <dttm> 2015-12-09 10:51:35, 2015-12-09 10:51:36, NA
$ h <list> [1, 2, NA]
$ i <list> [[1, <2, 3>], [<4, 5, 6>], [NA]]

> # options(tibble.width = 50)
> withr::with_options(list(tibble.width = 50), glimpse(as_tibble(df_all)))
Rows: 3
Columns: 9
$ a <dbl> 1.0, 2.5, NA
$ b <int> 1, 2, NA
$ c <lgl> TRUE, FALSE, NA
$ d <chr> "a", "b", NA
$ e <fct> a, b, NA
$ f <date> 2015-12-10, 2015-12-11, NA
$ g <dttm> 2015-12-09 10:51:35, 2015-12-09 10:5…
$ h <list> [1, 2, NA]
$ i <list> [[1, <2, 3>], [<4, 5, 6>], [NA]]

> # options(tibble.width = 35)
> withr::with_options(list(tibble.width = 35), glimpse(as_tibble(df_all)))
Rows: 3
Columns: 9
$ a <dbl> 1.0, 2.5, NA
$ b <int> 1, 2, NA
$ c <lgl> TRUE, FALSE, NA
$ d <chr> "a", "b", NA
$ e <fct> a, b, NA
$ f <date> 2015-12-10, 2015-12-1…
$ g <dttm> 2015-12-09 10:51:35, …
$ h <list> [1, 2, NA]
$ i <list> [[1, <2, 3>], [<4, 5,…

> # non-tibble
> glimpse(5)
 num 5

> iris2 <- as_unknown_rows(iris)
> glimpse(iris2, width = 70L)
Rows: ??
Columns: 5
$ Sepal.Length <dbl> 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4…
$ Sepal.Width  <dbl> 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3…
$ Petal.Length <dbl> 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1…
$ Petal.Width  <dbl> 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0…
$ Species      <fct> setosa, setosa, setosa, setosa, setosa, setosa…

> Species <- unique(iris$Species)
> data <- unname(split(iris, iris$Species))
> nested_iris_df <- tibble(Species, data)
> glimpse(nested_iris_df, width = 70L)
Rows: 3
Columns: 2
$ Species <fct> setosa, versicolor, virginica
$ data    <list> [<data.frame[50 x 5]>, <data.frame[50 x 5]>, <data…

> data <- map(data, as_tibble)
> nested_iris_tbl <- tibble(Species, data)
> glimpse(nested_iris_tbl, width = 70L)
Rows: 3
Columns: 2
$ Species <fct> setosa, versicolor, virginica
$ data    <list> [<tbl_df[50 x 5]>, <tbl_df[50 x 5]>, <tbl_df[50 x …

