diff --git a/R/arith.R b/R/arith.R
index 00fdf71c0..5f1b2b336 100644
--- a/R/arith.R
+++ b/R/arith.R
@@ -19,11 +19,12 @@
 #' # affine:
 #' st_point(c(1,2)) * m + c(2,5)
 #' # world in 0-360 range:
-#' library(maps)
-#' w = st_as_sf(map('world', plot = FALSE, fill = TRUE))
-#' w2 = (st_geometry(w) + c(360,90)) %% c(360) - c(0,90)
-#' w3 = st_wrap_dateline(st_set_crs(w2 - c(180,0), 4326)) + c(180,0)
-#' plot(st_set_crs(w3, 4326), axes = TRUE)
+#' if (require(maps, quietly = TRUE)) {
+#'  w = st_as_sf(map('world', plot = FALSE, fill = TRUE))
+#'  w2 = (st_geometry(w) + c(360,90)) %% c(360) - c(0,90)
+#'  w3 = st_wrap_dateline(st_set_crs(w2 - c(180,0), 4326)) + c(180,0)
+#'  plot(st_set_crs(w3, 4326), axes = TRUE)
+#' }
 #' (mp <- st_point(c(1,2)) + st_point(c(3,4))) # MULTIPOINT (1 2, 3 4)
 #' mp - st_point(c(3,4)) # POINT (1 2)
 #' opar = par(mfrow = c(2,2), mar = c(0, 0, 1, 0))
diff --git a/R/bind.R b/R/bind.R
index ef19874f8..fc3af3a9a 100644
--- a/R/bind.R
+++ b/R/bind.R
@@ -48,13 +48,14 @@ rbind.sf = function(..., deparse.level = 1) {
 #' @details If you need to \code{cbind} e.g. a \code{data.frame} to an \code{sf}, use \link{data.frame} directly and use \link{st_sf} on its result, or use \link[dplyr:bind]{bind_cols}; see examples.
 #' @examples
 #' cbind(a,b,c) # warns
-#' if (require(dplyr))
+#' if (require(dplyr, quietly = TRUE))
 #'   dplyr::bind_cols(a,b)
 #' c = st_sf(a=4, geomc = st_sfc(st_multilinestring(list(matrix(1:4,2)))), crs = crs)
 #' cbind(a,b,c, sf_column_name = "geomc")
 #' df = data.frame(x=3)
 #' st_sf(data.frame(c, df))
-#' dplyr::bind_cols(c, df)
+#' if (require(dplyr, quietly = TRUE))
+#'   dplyr::bind_cols(c, df)
 cbind.sf = function(..., deparse.level = 1, sf_column_name = NULL) {
 	# TODO: handle st_agr?
 	st_sf(data.frame(...), sf_column_name = sf_column_name)
diff --git a/R/crs.R b/R/crs.R
index 9c2bc8c23..9ee8de48d 100644
--- a/R/crs.R
+++ b/R/crs.R
@@ -228,9 +228,7 @@ make_crs = function(x) {
 #' @name st_crs
 #' @examples
 #' sfc = st_sfc(st_point(c(0,0)), st_point(c(1,1)))
-#' library(dplyr)
-#' x = sfc %>% st_set_crs(4326) %>% st_transform(3857)
-#' x
+#' sfc %>% st_set_crs(4326) %>% st_transform(3857)
 #' @export
 st_set_crs = function(x, value) {
 	st_crs(x) = value
diff --git a/R/geom-transformers.R b/R/geom-transformers.R
index a6cab8813..c86cc7b7c 100644
--- a/R/geom-transformers.R
+++ b/R/geom-transformers.R
@@ -574,9 +574,11 @@ st_node.sf = function(x) {
 #' @param ... ignored
 #' @examples
 #' sf = st_sf(a=1, geom=st_sfc(st_linestring(rbind(c(0,0),c(1,1)))), crs = 4326)
-#' seg = st_segmentize(sf, units::set_units(100, km))
-#' seg = st_segmentize(sf, units::set_units(0.01, rad))
-#' nrow(seg$geom[[1]])
+#' if (require(lwgeom, quietly = TRUE)) {
+#'  seg = st_segmentize(sf, units::set_units(100, km))
+#'  seg = st_segmentize(sf, units::set_units(0.01, rad))
+#'  nrow(seg$geom[[1]])
+#' }
 st_segmentize	= function(x, dfMaxLength, ...)
 	UseMethod("st_segmentize")
 
diff --git a/R/graticule.R b/R/graticule.R
index 8988b889f..691034320 100644
--- a/R/graticule.R
+++ b/R/graticule.R
@@ -27,7 +27,7 @@
 #' see example.
 #' @examples
 #' library(sf)
-#' library(maps)
+#' if (require(maps, quietly = TRUE)) {
 #'
 #' usa = st_as_sf(map('usa', plot = FALSE, fill = TRUE))
 #' laea = st_crs("+proj=laea +lat_0=30 +lon_0=-95") # Lambert equal area
@@ -59,6 +59,7 @@
 #'			srt = g$angle_end[i] - 90, pos = 3, cex = .7)
 #' }))
 #' plot(usa, graticule = st_crs(4326), axes = TRUE, lon = seq(-60,-130,by=-10))
+#' }
 st_graticule = function(x = c(-180,-90,180,90), crs = st_crs(x),
 	datum = st_crs(4326), ..., lon = NULL, lat = NULL, ndiscr = 100,
 	margin = 0.001)
diff --git a/R/jitter.R b/R/jitter.R
index 3be3a84f0..a49fec85d 100644
--- a/R/jitter.R
+++ b/R/jitter.R
@@ -5,7 +5,7 @@
 #' @param factor numeric; fractional amount of jittering to be applied
 #' @details jitters coordinates with an amount such that \code{runif(1, -amount, amount)} is added to the coordinates. x- and y-coordinates are jittered independently but all coordinates of a single geometry are jittered with the same amount, meaning that the geometry shape does not change. For longlat data, a latitude correction is made such that jittering in East and North directions are identical in distance in the center of the bounding box of \code{x}.
 #' @examples
-#' nc = read_sf(system.file("gpkg/nc.gpkg", package="sf"))
+#' nc = st_read(system.file("gpkg/nc.gpkg", package="sf"))
 #' pts = st_centroid(st_geometry(nc))
 #' plot(pts)
 #' plot(st_jitter(pts, .05), add = TRUE, col = 'red')
diff --git a/R/join.R b/R/join.R
index effcfe573..d42161720 100644
--- a/R/join.R
+++ b/R/join.R
@@ -105,8 +105,9 @@ st_join = function(x, y, join, ...) UseMethod("st_join")
 #' st_join(a, b, left = FALSE)
 #' # two ways to aggregate y's attribute values outcome over x's geometries:
 #' st_join(a, b) %>% aggregate(list(.$a.x), mean)
-#' library(dplyr)
-#' st_join(a, b) %>% group_by(a.x) %>% summarise(mean(a.y))
+#' if (require(dplyr, quietly = TRUE)) {
+#'  st_join(a, b) %>% group_by(a.x) %>% summarise(mean(a.y))
+#' }
 #' # example of largest = TRUE:
 #' nc <- st_transform(st_read(system.file("shape/nc.shp", package="sf")), 2264)                
 #' gr = st_sf(
diff --git a/R/make_grid.R b/R/make_grid.R
index 7ce0daa96..35ff34cec 100644
--- a/R/make_grid.R
+++ b/R/make_grid.R
@@ -20,7 +20,7 @@
 #' # non-default offset:
 #' plot(st_make_grid(sfc, cellsize = .1, square = FALSE, offset = c(0, .05 / (sqrt(3)/2))))
 #' plot(sfc, add = TRUE)
-#' nc = read_sf(system.file("shape/nc.shp", package="sf"))
+#' nc = st_read(system.file("shape/nc.shp", package="sf"))
 #' g = st_make_grid(nc)
 #' plot(g)
 #' plot(st_geometry(nc), add = TRUE)
diff --git a/R/nearest.R b/R/nearest.R
index ec665cbbe..3a8728687 100644
--- a/R/nearest.R
+++ b/R/nearest.R
@@ -23,7 +23,7 @@
 #' plot(st_sfc(b2, b3), add = TRUE, col = NA, border = 'blue')
 #' plot(ls, add = TRUE, col = 'red')
 #' 
-#' nc = read_sf(system.file("gpkg/nc.gpkg", package="sf"))
+#' nc = st_read(system.file("gpkg/nc.gpkg", package="sf"))
 #' plot(st_geometry(nc))
 #' ls = st_nearest_points(nc[1,], nc)
 #' plot(ls, col = 'red', add = TRUE)
diff --git a/R/read.R b/R/read.R
index 06e09c624..4ea027f6a 100644
--- a/R/read.R
+++ b/R/read.R
@@ -121,7 +121,7 @@ set_utf8 = function(x) {
 #' # spatial filter, as wkt:
 #' wkt = st_as_text(st_geometry(nc[1,]))
 #' # filter by (bbox overlaps of) first feature geometry:
-#' read_sf(system.file("gpkg/nc.gpkg", package="sf"), wkt_filter = wkt)
+#' st_read(system.file("gpkg/nc.gpkg", package="sf"), wkt_filter = wkt)
 #' @export
 st_read = function(dsn, layer, ...) UseMethod("st_read")
 
@@ -246,7 +246,7 @@ st_read.character = function(dsn, layer, ..., query = NA, options = NULL, quiet
 #' # read geojson from string:
 #' geojson_txt <- paste("{\"type\":\"MultiPoint\",\"coordinates\":",
 #'    "[[3.2,4],[3,4.6],[3.8,4.4],[3.5,3.8],[3.4,3.6],[3.9,4.5]]}")
-#' x = read_sf(geojson_txt)
+#' x = st_read(geojson_txt)
 #' x
 read_sf <- function(..., quiet = TRUE, stringsAsFactors = FALSE, as_tibble = TRUE) {
 	st_read(..., quiet = quiet, stringsAsFactors = stringsAsFactors, as_tibble = as_tibble)
@@ -369,12 +369,13 @@ abbreviate_shapefile_names = function(x) {
 #' nc = st_read(system.file("shape/nc.shp", package="sf"))
 #' st_write(nc, paste0(tempdir(), "/", "nc.shp"))
 #' st_write(nc, paste0(tempdir(), "/", "nc.shp"), delete_layer = TRUE) # overwrites
-#' data(meuse, package = "sp") # loads data.frame from sp
-#' meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992)
-#' # writes X and Y as columns:
-#' st_write(meuse_sf, paste0(tempdir(), "/", "meuse.csv"), layer_options = "GEOMETRY=AS_XY")
-#' st_write(meuse_sf, paste0(tempdir(), "/", "meuse.csv"), layer_options = "GEOMETRY=AS_WKT",
-#'   delete_dsn=TRUE) # overwrites
+#' if (require(sp, quietly = TRUE)) {
+#'  data(meuse, package = "sp") # loads data.frame from sp
+#'  meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992)
+#'  # writes X and Y as columns:
+#'  st_write(meuse_sf, paste0(tempdir(), "/", "meuse.csv"), layer_options = "GEOMETRY=AS_XY")
+#'  st_write(meuse_sf, paste0(tempdir(), "/", "meuse.csv"), layer_options = "GEOMETRY=AS_WKT",
+#'    delete_dsn=TRUE) # overwrites
 #' \dontrun{
 #'  library(sp)
 #'  example(meuse, ask = FALSE, echo = FALSE)
@@ -383,6 +384,7 @@ abbreviate_shapefile_names = function(x) {
 #'  demo(nc, ask = FALSE)
 #'  try(st_write(nc, "PG:dbname=postgis", "sids", layer_options = "OVERWRITE=true"))
 #' }
+#' }
 #' @export
 st_write = function(obj, dsn, layer, ...) UseMethod("st_write")
 
diff --git a/R/sample.R b/R/sample.R
index 4f2434d0e..6e911dec2 100644
--- a/R/sample.R
+++ b/R/sample.R
@@ -46,6 +46,7 @@ st_sample = function(x, size, ...) UseMethod("st_sample")
 #' plot(x, axes = TRUE, graticule = TRUE)
 #' if (sf_extSoftVersion()["proj.4"] >= "4.9.0")
 #'   plot(p <- st_sample(x, 1000), add = TRUE)
+#' if (require(lwgeom, quietly = TRUE)) { # for st_segmentize()
 #' x2 = st_transform(st_segmentize(x, 1e4), st_crs("+proj=ortho +lat_0=30 +lon_0=45"))
 #' g = st_transform(st_graticule(), st_crs("+proj=ortho +lat_0=30 +lon_0=45"))
 #' plot(x2, graticule = g)
@@ -53,6 +54,7 @@ st_sample = function(x, size, ...) UseMethod("st_sample")
 #'   p2 = st_transform(p, st_crs("+proj=ortho +lat_0=30 +lon_0=45"))
 #'   plot(p2, add = TRUE)
 #' }
+#' }
 #' x = st_sfc(st_polygon(list(rbind(c(0,0),c(90,0),c(90,10),c(0,90),c(0,0))))) # NOT long/lat:
 #' plot(x)
 #' p_exact = st_sample(x, 1000, exact = TRUE)
diff --git a/R/sf.R b/R/sf.R
index 66f59844e..593f2951e 100644
--- a/R/sf.R
+++ b/R/sf.R
@@ -29,10 +29,12 @@ st_as_sf = function(x, ...) UseMethod("st_as_sf")
 #' df = st_as_sf(d, wkt = "geom")
 #' d$geom2 = st_sfc(pt1, pt2)
 #' st_as_sf(d) # should warn
-#' data(meuse, package = "sp")
-#' meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992, agr = "constant")
-#' meuse_sf[1:3,]
-#' summary(meuse_sf)
+#' if (require(sp, quietly = TRUE)) {
+#'  data(meuse, package = "sp")
+#'  meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992, agr = "constant")
+#'  meuse_sf[1:3,]
+#'  summary(meuse_sf)
+#' }
 #' @export
 st_as_sf.data.frame = function(x, ..., agr = NA_agr_, coords, wkt,
 		dim = "XYZ", remove = TRUE, na.fail = TRUE, sf_column_name = NULL) {
diff --git a/R/sp.R b/R/sp.R
index f58766479..5551361dc 100644
--- a/R/sp.R
+++ b/R/sp.R
@@ -23,7 +23,7 @@
 
 #' @name st_as_sf
 #' @examples
-#' library(sp)
+#' if (require(sp, quietly = TRUE)) {
 #' x = rbind(c(-1,-1), c(1,-1), c(1,1), c(-1,1), c(-1,-1))
 #' x1 = 0.1 * x + 0.1
 #' x2 = 0.1 * x + 0.4
@@ -52,6 +52,7 @@
 #' pol.grd = as(meuse.grid, "SpatialPolygonsDataFrame")
 #' # summary(st_as_sf(pol.grd))
 #' # summary(st_as_sf(as(pol.grd, "SpatialLinesDataFrame")))
+#' }
 #' @export
 st_as_sf.Spatial = function(x, ...) {
 	if ("data" %in% slotNames(x))
@@ -238,6 +239,7 @@ setAs("XY", "Spatial", function(from) as(st_sfc(from), "Spatial"))
 #' @export
 #' @examples
 #' nc <- st_read(system.file("shape/nc.shp", package="sf"))
+#' if (require(sp, quietly = TRUE)) {
 #' # convert to SpatialPolygonsDataFrame
 #' spdf <- as_Spatial(nc)
 #' # identical to
@@ -246,6 +248,7 @@ setAs("XY", "Spatial", function(from) as(st_sfc(from), "Spatial"))
 #' as(st_geometry(nc), "Spatial")
 #' # back to sf
 #' as(spdf, "sf")
+#' }
 as_Spatial = function(from, cast = TRUE, IDs = paste0("ID", seq_along(from))) {
 	if (inherits(from, "sf")) {
 		geom = st_geometry(from)
diff --git a/R/tidyverse.R b/R/tidyverse.R
index 60f634512..fd3d96df8 100644
--- a/R/tidyverse.R
+++ b/R/tidyverse.R
@@ -38,9 +38,10 @@ group_split.sf <- function(.tbl, ..., .keep = TRUE) {
 #' @param ... other arguments
 #' @name tidyverse
 #' @examples
-#' library(dplyr)
-#' nc = st_read(system.file("shape/nc.shp", package="sf"))
-#' nc %>% filter(AREA > .1) %>% plot()
+#' if (require(dplyr, quietly = TRUE)) {
+#'  nc = read_sf(system.file("shape/nc.shp", package="sf"))
+#'  nc %>% filter(AREA > .1) %>% plot()
+#' }
 filter.sf <- function(.data, ..., .dots) {
 	agr = st_agr(.data)
 	class(.data) <- setdiff(class(.data), "sf")
@@ -50,9 +51,11 @@ filter.sf <- function(.data, ..., .dots) {
 #' @name tidyverse
 #' @examples
 #' # plot 10 smallest counties in grey:
-#' st_geometry(nc) %>% plot()
-#' nc %>% select(AREA) %>% arrange(AREA) %>% slice(1:10) %>% plot(add = TRUE, col = 'grey')
-#' title("the ten counties with smallest area")
+#' if (require(dplyr, quietly = TRUE)) {
+#'  st_geometry(nc) %>% plot()
+#'  nc %>% select(AREA) %>% arrange(AREA) %>% slice(1:10) %>% plot(add = TRUE, col = 'grey')
+#'  title("the ten counties with smallest area")
+#' }
 arrange.sf <- function(.data, ..., .dots) {
 	sf_column_name = attr(.data, "sf_column")
 	class(.data) = setdiff(class(.data), "sf")
@@ -62,8 +65,10 @@ arrange.sf <- function(.data, ..., .dots) {
 #' @name tidyverse
 #' @param add see corresponding function in dplyr
 #' @examples
-#' nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
-#' nc %>% group_by(area_cl) %>% class()
+#' if (require(dplyr, quietly = TRUE)) {
+#'  nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
+#'  nc %>% group_by(area_cl) %>% class()
+#' }
 group_by.sf <- function(.data, ..., add = FALSE) {
 	sf_column_name = attr(.data, "sf_column")
 	class(.data) <- setdiff(class(.data), "sf")
@@ -102,7 +107,9 @@ rowwise.sf <- function(x, ...) {
 
 #' @name tidyverse
 #' @examples
-#' nc2 <- nc %>% mutate(area10 = AREA/10)
+#' if (require(dplyr, quietly = TRUE)) {
+#'  nc2 <- nc %>% mutate(area10 = AREA/10)
+#' }
 mutate.sf <- function(.data, ..., .dots) {
 	#st_as_sf(NextMethod(), sf_column_name = attr(.data, "sf_column"))
 	agr = st_agr(.data)
@@ -113,8 +120,10 @@ mutate.sf <- function(.data, ..., .dots) {
 
 #' @name tidyverse
 #' @examples
-#' nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
-#' nc %>% transmute(AREA = AREA/10) %>% class()
+#' if (require(dplyr, quietly = TRUE)) {
+#'  nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
+#'  nc %>% transmute(AREA = AREA/10) %>% class()
+#' }
 transmute.sf <- function(.data, ..., .dots) {
 	sf_column_name = attr(.data, "sf_column")
 	agr = st_agr(.data)
@@ -125,10 +134,12 @@ transmute.sf <- function(.data, ..., .dots) {
 
 #' @name tidyverse
 #' @examples
-#' nc %>% select(SID74, SID79) %>% names()
-#' nc %>% select(SID74, SID79, geometry) %>% names()
-#' nc %>% select(SID74, SID79) %>% class()
-#' nc %>% select(SID74, SID79, geometry) %>% class()
+#' if (require(dplyr, quietly = TRUE)) {
+#'  nc %>% select(SID74, SID79) %>% names()
+#'  nc %>% select(SID74, SID79, geometry) %>% names()
+#'  nc %>% select(SID74, SID79) %>% class()
+#'  nc %>% select(SID74, SID79, geometry) %>% class()
+#' }
 #' @details \code{select} keeps the geometry regardless whether it is selected or not; to deselect it, first pipe through \code{as.data.frame} to let dplyr's own \code{select} drop it.
 select.sf <- function(.data, ...) {
 
@@ -168,7 +179,9 @@ select.sf <- function(.data, ...) {
 
 #' @name tidyverse
 #' @examples
-#' nc2 <- nc %>% rename(area = AREA)
+#' if (require(dplyr, quietly = TRUE)) {
+#'  nc2 <- nc %>% rename(area = AREA)
+#' }
 rename.sf <- function(.data, ...) {
 
 	if (!requireNamespace("tidyselect", quietly = TRUE))
@@ -212,7 +225,9 @@ rename.sf <- function(.data, ...) {
 
 #' @name tidyverse
 #' @examples
-#' nc %>% slice(1:2)
+#' if (require(dplyr, quietly = TRUE)) {
+#'  nc %>% slice(1:2)
+#' }
 slice.sf <- function(.data, ..., .dots) {
 	class(.data) <- setdiff(class(.data), "sf")
 	sf_column <- attr(.data, "sf_column")
@@ -229,11 +244,13 @@ slice.sf <- function(.data, ..., .dots) {
 #'
 #' In case \code{do_union} is \code{FALSE}, \code{summarise} will simply combine geometries using \link{c.sfg}. When polygons sharing a boundary are combined, this leads to geometries that are invalid; see for instance \url{https://github.com/r-spatial/sf/issues/681}.
 #' @examples
-#' nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
-#' nc.g <- nc %>% group_by(area_cl)
-#' nc.g %>% summarise(mean(AREA))
-#' nc.g %>% summarise(mean(AREA)) %>% plot(col = grey(3:6 / 7))
-#' nc %>% as.data.frame %>% summarise(mean(AREA))
+#' if (require(dplyr, quietly = TRUE)) {
+#'  nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
+#'  nc.g <- nc %>% group_by(area_cl)
+#'  nc.g %>% summarise(mean(AREA))
+#'  nc.g %>% summarise(mean(AREA)) %>% plot(col = grey(3:6 / 7))
+#'  nc %>% as.data.frame %>% summarise(mean(AREA))
+#' }
 summarise.sf <- function(.data, ..., .dots, do_union = TRUE, is_coverage = FALSE) {
 	sf_column = attr(.data, "sf_column")
 	precision = st_precision(.data)
@@ -276,7 +293,9 @@ summarise.sf <- function(.data, ..., .dots, do_union = TRUE, is_coverage = FALSE
 #' @name tidyverse
 #' @param .keep_all see corresponding function in dplyr
 #' @examples
-#' nc[c(1:100, 1:10), ] %>% distinct() %>% nrow()
+#' if (require(dplyr, quietly = TRUE)) {
+#'  nc[c(1:100, 1:10), ] %>% distinct() %>% nrow()
+#' }
 #' @details \code{distinct} gives distinct records for which all attributes and geometries are distinct; \link{st_equals} is used to find out which geometries are distinct.
 distinct.sf <- function(.data, ..., .keep_all = FALSE) {
 	sf_column = attr(.data, "sf_column")
@@ -310,8 +329,9 @@ distinct.sf <- function(.data, ..., .keep_all = FALSE) {
 #' @param na.rm see original function docs
 #' @param factor_key see original function docs
 #' @examples
-#' library(tidyr)
-#' nc %>% select(SID74, SID79) %>% gather("VAR", "SID", -geometry) %>% summary()
+#' if (require(tidyr, quietly = TRUE) && require(dplyr, quietly = TRUE)) {
+#'  nc %>% select(SID74, SID79) %>% gather("VAR", "SID", -geometry) %>% summary()
+#' }
 gather.sf <- function(data, key, value, ..., na.rm = FALSE, convert = FALSE, factor_key = FALSE) {
 
 	if (! requireNamespace("rlang", quietly = TRUE))
@@ -415,11 +435,12 @@ pivot_wider.sf = function(data,
 #' @param fill see original function docs
 #' @param drop see original function docs
 #' @examples
-#' library(tidyr)
-#' nc$row = 1:100 # needed for spread to work
-#' nc %>% select(SID74, SID79, geometry, row) %>%
+#' if (require(tidyr, quietly = TRUE) && require(dplyr, quietly = TRUE)) {
+#'  nc$row = 1:100 # needed for spread to work
+#'  nc %>% select(SID74, SID79, geometry, row) %>%
 #'		gather("VAR", "SID", -geometry, -row) %>%
 #'		spread(VAR, SID) %>% head()
+#' }
 spread.sf <- function(data, key, value, fill = NA, convert = FALSE, drop = TRUE,
 	        sep = NULL) {
 
@@ -450,12 +471,14 @@ sample_frac.sf <- function(tbl, size = 1, replace = FALSE, weight = NULL, .env =
 
 #' @name tidyverse
 #' @examples
-#' storms.sf = st_as_sf(storms, coords = c("long", "lat"), crs = 4326)
-#' x <- storms.sf %>% group_by(name, year) %>% nest
-#' trs = lapply(x$data, function(tr) st_cast(st_combine(tr), "LINESTRING")[[1]]) %>%
+#' if (require(tidyr, quietly = TRUE) && require(dplyr, quietly = TRUE)) {
+#'  storms.sf = st_as_sf(storms, coords = c("long", "lat"), crs = 4326)
+#'  x <- storms.sf %>% group_by(name, year) %>% nest
+#'  trs = lapply(x$data, function(tr) st_cast(st_combine(tr), "LINESTRING")[[1]]) %>%
 #'     st_sfc(crs = 4326)
-#' trs.sf = st_sf(x[,1:2], trs)
-#' plot(trs.sf["year"], axes = TRUE)
+#'  trs.sf = st_sf(x[,1:2], trs)
+#'  plot(trs.sf["year"], axes = TRUE)
+#' }
 #' @details \code{nest} assumes that a simple feature geometry list-column was among the columns that were nested.
 nest.sf = function (.data, ...) {
 
diff --git a/R/transform.R b/R/transform.R
index 1943bc95c..0216dfbf6 100644
--- a/R/transform.R
+++ b/R/transform.R
@@ -167,12 +167,13 @@ st_wrap_dateline = function(x, options, quiet) UseMethod("st_wrap_dateline")
 #' @export
 #' @examples
 #' st_wrap_dateline(st_sfc(st_linestring(rbind(c(-179,0),c(179,0))), crs = 4326))
-#' library(maps)
-#' wrld <- st_as_sf(maps::map("world", fill = TRUE, plot = FALSE))
-#' wrld_wrap <- st_wrap_dateline(wrld, options = c("WRAPDATELINE=YES", "DATELINEOFFSET=180"),
+#' if (require(maps, quietly = TRUE)) {
+#'  wrld <- st_as_sf(maps::map("world", fill = TRUE, plot = FALSE))
+#'  wrld_wrap <- st_wrap_dateline(wrld, options = c("WRAPDATELINE=YES", "DATELINEOFFSET=180"),
 #'    quiet = TRUE)
-#' wrld_moll <- st_transform(wrld_wrap, "+proj=moll")
-#' plot(st_geometry(wrld_moll), col = "transparent")
+#'  wrld_moll <- st_transform(wrld_wrap, "+proj=moll")
+#'  plot(st_geometry(wrld_moll), col = "transparent")
+#' }
 #' @details For a discussion of using \code{options}, see \url{https://github.com/r-spatial/sf/issues/280} and \url{https://github.com/r-spatial/sf/issues/541}
 st_wrap_dateline.sfc = function(x, options = "WRAPDATELINE=YES", quiet = TRUE) {
 	if (is.na(st_crs(x)))
diff --git a/R/valid.R b/R/valid.R
index d6bbad312..bf16d6030 100644
--- a/R/valid.R
+++ b/R/valid.R
@@ -80,7 +80,7 @@ st_make_valid.sfc = function(x, ..., oriented = FALSE, s2_options = s2::s2_optio
 			s2_options = s2::s2_options(snap = s2::s2_snap_precision(st_precision(x)))
 		s2 = s2::s2_rebuild(s2, s2_options)
 		st_as_sfc(s2, crs = crs)
-	} else if (compareVersion(CPL_geos_version(), "3.8.0") > -1) {
+	} else if (compareVersion(CPL_geos_version(), "3.8.0") == -1) {
 		if (!requireNamespace("lwgeom", quietly = TRUE))
 			stop("package lwgeom required, please install it first") # nocov
 		st_sfc(lwgeom::lwgeom_make_valid(x), crs = crs)
diff --git a/man/Ops.Rd b/man/Ops.Rd
index a31eada10..593959ff1 100644
--- a/man/Ops.Rd
+++ b/man/Ops.Rd
@@ -34,11 +34,12 @@ diag(m) = c(1, 3)
 # affine:
 st_point(c(1,2)) * m + c(2,5)
 # world in 0-360 range:
-library(maps)
-w = st_as_sf(map('world', plot = FALSE, fill = TRUE))
-w2 = (st_geometry(w) + c(360,90)) \%\% c(360) - c(0,90)
-w3 = st_wrap_dateline(st_set_crs(w2 - c(180,0), 4326)) + c(180,0)
-plot(st_set_crs(w3, 4326), axes = TRUE)
+if (require(maps, quietly = TRUE)) {
+ w = st_as_sf(map('world', plot = FALSE, fill = TRUE))
+ w2 = (st_geometry(w) + c(360,90)) \%\% c(360) - c(0,90)
+ w3 = st_wrap_dateline(st_set_crs(w2 - c(180,0), 4326)) + c(180,0)
+ plot(st_set_crs(w3, 4326), axes = TRUE)
+}
 (mp <- st_point(c(1,2)) + st_point(c(3,4))) # MULTIPOINT (1 2, 3 4)
 mp - st_point(c(3,4)) # POINT (1 2)
 opar = par(mfrow = c(2,2), mar = c(0, 0, 1, 0))
diff --git a/man/bind.Rd b/man/bind.Rd
index 4ca08cc3e..1a8df263a 100644
--- a/man/bind.Rd
+++ b/man/bind.Rd
@@ -45,11 +45,12 @@ rbind(a,b)
 rbind(a,b)
 rbind(b,c)
 cbind(a,b,c) # warns
-if (require(dplyr))
+if (require(dplyr, quietly = TRUE))
   dplyr::bind_cols(a,b)
 c = st_sf(a=4, geomc = st_sfc(st_multilinestring(list(matrix(1:4,2)))), crs = crs)
 cbind(a,b,c, sf_column_name = "geomc")
 df = data.frame(x=3)
 st_sf(data.frame(c, df))
-dplyr::bind_cols(c, df)
+if (require(dplyr, quietly = TRUE))
+  dplyr::bind_cols(c, df)
 }
diff --git a/man/coerce-methods.Rd b/man/coerce-methods.Rd
index aaea72517..bde8efde4 100644
--- a/man/coerce-methods.Rd
+++ b/man/coerce-methods.Rd
@@ -38,6 +38,7 @@ For converting simple features (i.e., \code{sf} objects) to their \code{Spatial}
 }
 \examples{
 nc <- st_read(system.file("shape/nc.shp", package="sf"))
+if (require(sp, quietly = TRUE)) {
 # convert to SpatialPolygonsDataFrame
 spdf <- as_Spatial(nc)
 # identical to
@@ -47,3 +48,4 @@ as(st_geometry(nc), "Spatial")
 # back to sf
 as(spdf, "sf")
 }
+}
diff --git a/man/geos_unary.Rd b/man/geos_unary.Rd
index e82d2729b..73819565d 100644
--- a/man/geos_unary.Rd
+++ b/man/geos_unary.Rd
@@ -244,7 +244,9 @@ if (compareVersion(sf_extSoftVersion()[["GEOS"]], "3.7.0") > -1) {
 st_polygonize(st_node(l))
 st_node(st_multilinestring(list(rbind(c(0,0), c(1,1), c(0,1), c(1,0), c(0,0)))))
 sf = st_sf(a=1, geom=st_sfc(st_linestring(rbind(c(0,0),c(1,1)))), crs = 4326)
-seg = st_segmentize(sf, units::set_units(100, km))
-seg = st_segmentize(sf, units::set_units(0.01, rad))
-nrow(seg$geom[[1]])
+if (require(lwgeom, quietly = TRUE)) {
+ seg = st_segmentize(sf, units::set_units(100, km))
+ seg = st_segmentize(sf, units::set_units(0.01, rad))
+ nrow(seg$geom[[1]])
+}
 }
diff --git a/man/st_as_sf.Rd b/man/st_as_sf.Rd
index 06b0cf26e..7dbe4e908 100644
--- a/man/st_as_sf.Rd
+++ b/man/st_as_sf.Rd
@@ -86,11 +86,13 @@ d$geom = c("POINT(0 0)", "POINT(0 1)")
 df = st_as_sf(d, wkt = "geom")
 d$geom2 = st_sfc(pt1, pt2)
 st_as_sf(d) # should warn
-data(meuse, package = "sp")
-meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992, agr = "constant")
-meuse_sf[1:3,]
-summary(meuse_sf)
-library(sp)
+if (require(sp, quietly = TRUE)) {
+ data(meuse, package = "sp")
+ meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992, agr = "constant")
+ meuse_sf[1:3,]
+ summary(meuse_sf)
+}
+if (require(sp, quietly = TRUE)) {
 x = rbind(c(-1,-1), c(1,-1), c(1,1), c(-1,1), c(-1,-1))
 x1 = 0.1 * x + 0.1
 x2 = 0.1 * x + 0.4
@@ -119,6 +121,7 @@ summary(st_as_sf(as(meuse.riv, "SpatialLines")))
 pol.grd = as(meuse.grid, "SpatialPolygonsDataFrame")
 # summary(st_as_sf(pol.grd))
 # summary(st_as_sf(as(pol.grd, "SpatialLinesDataFrame")))
+}
 if (require(spatstat.geom)) {
   g = st_as_sf(gorillas)
   # select only the points:
diff --git a/man/st_crs.Rd b/man/st_crs.Rd
index f40c88bc2..c80e17efb 100644
--- a/man/st_crs.Rd
+++ b/man/st_crs.Rd
@@ -133,9 +133,7 @@ sfc = st_sfc(st_point(c(0,0)), st_point(c(1,1)))
 st_crs(sfc) = 4326
 sfc
 sfc = st_sfc(st_point(c(0,0)), st_point(c(1,1)))
-library(dplyr)
-x = sfc \%>\% st_set_crs(4326) \%>\% st_transform(3857)
-x
+sfc \%>\% st_set_crs(4326) \%>\% st_transform(3857)
 st_crs("EPSG:3857")$input
 st_crs(3857)$proj4string
 st_crs(3857)$b     # numeric
diff --git a/man/st_graticule.Rd b/man/st_graticule.Rd
index 2cc37eafe..88bf353ca 100644
--- a/man/st_graticule.Rd
+++ b/man/st_graticule.Rd
@@ -55,7 +55,7 @@ Compute graticules and their parameters
 
 \examples{
 library(sf)
-library(maps)
+if (require(maps, quietly = TRUE)) {
 
 usa = st_as_sf(map('usa', plot = FALSE, fill = TRUE))
 laea = st_crs("+proj=laea +lat_0=30 +lon_0=-95") # Lambert equal area
@@ -88,3 +88,4 @@ if (g$type[i] == "E" && g$y_end[i] - max(g$y_end) > -1000)
 }))
 plot(usa, graticule = st_crs(4326), axes = TRUE, lon = seq(-60,-130,by=-10))
 }
+}
diff --git a/man/st_jitter.Rd b/man/st_jitter.Rd
index bb72dc9cc..31f5206f1 100644
--- a/man/st_jitter.Rd
+++ b/man/st_jitter.Rd
@@ -20,7 +20,7 @@ jitter geometries
 jitters coordinates with an amount such that \code{runif(1, -amount, amount)} is added to the coordinates. x- and y-coordinates are jittered independently but all coordinates of a single geometry are jittered with the same amount, meaning that the geometry shape does not change. For longlat data, a latitude correction is made such that jittering in East and North directions are identical in distance in the center of the bounding box of \code{x}.
 }
 \examples{
-nc = read_sf(system.file("gpkg/nc.gpkg", package="sf"))
+nc = st_read(system.file("gpkg/nc.gpkg", package="sf"))
 pts = st_centroid(st_geometry(nc))
 plot(pts)
 plot(st_jitter(pts, .05), add = TRUE, col = 'red')
diff --git a/man/st_join.Rd b/man/st_join.Rd
index fe1ec2e1c..5cecf908e 100644
--- a/man/st_join.Rd
+++ b/man/st_join.Rd
@@ -78,8 +78,9 @@ st_join(a, b)
 st_join(a, b, left = FALSE)
 # two ways to aggregate y's attribute values outcome over x's geometries:
 st_join(a, b) \%>\% aggregate(list(.$a.x), mean)
-library(dplyr)
-st_join(a, b) \%>\% group_by(a.x) \%>\% summarise(mean(a.y))
+if (require(dplyr, quietly = TRUE)) {
+ st_join(a, b) \%>\% group_by(a.x) \%>\% summarise(mean(a.y))
+}
 # example of largest = TRUE:
 nc <- st_transform(st_read(system.file("shape/nc.shp", package="sf")), 2264)                
 gr = st_sf(
diff --git a/man/st_make_grid.Rd b/man/st_make_grid.Rd
index 1aefb0362..d4e15882b 100644
--- a/man/st_make_grid.Rd
+++ b/man/st_make_grid.Rd
@@ -48,7 +48,7 @@ plot(sfc, add = TRUE)
 # non-default offset:
 plot(st_make_grid(sfc, cellsize = .1, square = FALSE, offset = c(0, .05 / (sqrt(3)/2))))
 plot(sfc, add = TRUE)
-nc = read_sf(system.file("shape/nc.shp", package="sf"))
+nc = st_read(system.file("shape/nc.shp", package="sf"))
 g = st_make_grid(nc)
 plot(g)
 plot(st_geometry(nc), add = TRUE)
diff --git a/man/st_nearest_points.Rd b/man/st_nearest_points.Rd
index 7a2bc643d..75926c847 100644
--- a/man/st_nearest_points.Rd
+++ b/man/st_nearest_points.Rd
@@ -48,7 +48,7 @@ plot(b1, xlim = c(-.2,1.2), ylim = c(-.2,1.2), col = NA, border = 'green')
 plot(st_sfc(b2, b3), add = TRUE, col = NA, border = 'blue')
 plot(ls, add = TRUE, col = 'red')
 
-nc = read_sf(system.file("gpkg/nc.gpkg", package="sf"))
+nc = st_read(system.file("gpkg/nc.gpkg", package="sf"))
 plot(st_geometry(nc))
 ls = st_nearest_points(nc[1,], nc)
 plot(ls, col = 'red', add = TRUE)
diff --git a/man/st_read.Rd b/man/st_read.Rd
index 7ecc50c63..0109b73d0 100644
--- a/man/st_read.Rd
+++ b/man/st_read.Rd
@@ -199,11 +199,11 @@ nc_gpkg_sql = st_read(system.file("gpkg/nc.gpkg", package = "sf"),
 # spatial filter, as wkt:
 wkt = st_as_text(st_geometry(nc[1,]))
 # filter by (bbox overlaps of) first feature geometry:
-read_sf(system.file("gpkg/nc.gpkg", package="sf"), wkt_filter = wkt)
+st_read(system.file("gpkg/nc.gpkg", package="sf"), wkt_filter = wkt)
 # read geojson from string:
 geojson_txt <- paste("{\"type\":\"MultiPoint\",\"coordinates\":",
    "[[3.2,4],[3,4.6],[3.8,4.4],[3.5,3.8],[3.4,3.6],[3.9,4.5]]}")
-x = read_sf(geojson_txt)
+x = st_read(geojson_txt)
 x
 \dontrun{
 library(RPostgreSQL)
diff --git a/man/st_sample.Rd b/man/st_sample.Rd
index 08dc00274..03879c6d0 100644
--- a/man/st_sample.Rd
+++ b/man/st_sample.Rd
@@ -80,6 +80,7 @@ x = st_sfc(st_polygon(list(rbind(c(0,0),c(90,0),c(90,90),c(0,90),c(0,0)))), crs
 plot(x, axes = TRUE, graticule = TRUE)
 if (sf_extSoftVersion()["proj.4"] >= "4.9.0")
   plot(p <- st_sample(x, 1000), add = TRUE)
+if (require(lwgeom, quietly = TRUE)) { # for st_segmentize()
 x2 = st_transform(st_segmentize(x, 1e4), st_crs("+proj=ortho +lat_0=30 +lon_0=45"))
 g = st_transform(st_graticule(), st_crs("+proj=ortho +lat_0=30 +lon_0=45"))
 plot(x2, graticule = g)
@@ -87,6 +88,7 @@ if (sf_extSoftVersion()["proj.4"] >= "4.9.0") {
   p2 = st_transform(p, st_crs("+proj=ortho +lat_0=30 +lon_0=45"))
   plot(p2, add = TRUE)
 }
+}
 x = st_sfc(st_polygon(list(rbind(c(0,0),c(90,0),c(90,10),c(0,90),c(0,0))))) # NOT long/lat:
 plot(x)
 p_exact = st_sample(x, 1000, exact = TRUE)
diff --git a/man/st_transform.Rd b/man/st_transform.Rd
index 84a6db023..6e3c0a0fa 100644
--- a/man/st_transform.Rd
+++ b/man/st_transform.Rd
@@ -121,12 +121,13 @@ library(units)
 set_units(st_area(st_transform(nc[1,], 2264)), m^2)
 st_transform(structure(p1, proj4string = "+init=epsg:4326"), "+init=epsg:3857")
 st_wrap_dateline(st_sfc(st_linestring(rbind(c(-179,0),c(179,0))), crs = 4326))
-library(maps)
-wrld <- st_as_sf(maps::map("world", fill = TRUE, plot = FALSE))
-wrld_wrap <- st_wrap_dateline(wrld, options = c("WRAPDATELINE=YES", "DATELINEOFFSET=180"),
+if (require(maps, quietly = TRUE)) {
+ wrld <- st_as_sf(maps::map("world", fill = TRUE, plot = FALSE))
+ wrld_wrap <- st_wrap_dateline(wrld, options = c("WRAPDATELINE=YES", "DATELINEOFFSET=180"),
    quiet = TRUE)
-wrld_moll <- st_transform(wrld_wrap, "+proj=moll")
-plot(st_geometry(wrld_moll), col = "transparent")
+ wrld_moll <- st_transform(wrld_wrap, "+proj=moll")
+ plot(st_geometry(wrld_moll), col = "transparent")
+}
 sf_proj_info("datum")
 }
 \seealso{
diff --git a/man/st_write.Rd b/man/st_write.Rd
index 7108c8cc3..6e0b30d3f 100644
--- a/man/st_write.Rd
+++ b/man/st_write.Rd
@@ -118,12 +118,13 @@ omitted; it returns TRUE on success, FALSE on failure, invisibly.
 nc = st_read(system.file("shape/nc.shp", package="sf"))
 st_write(nc, paste0(tempdir(), "/", "nc.shp"))
 st_write(nc, paste0(tempdir(), "/", "nc.shp"), delete_layer = TRUE) # overwrites
-data(meuse, package = "sp") # loads data.frame from sp
-meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992)
-# writes X and Y as columns:
-st_write(meuse_sf, paste0(tempdir(), "/", "meuse.csv"), layer_options = "GEOMETRY=AS_XY")
-st_write(meuse_sf, paste0(tempdir(), "/", "meuse.csv"), layer_options = "GEOMETRY=AS_WKT",
-  delete_dsn=TRUE) # overwrites
+if (require(sp, quietly = TRUE)) {
+ data(meuse, package = "sp") # loads data.frame from sp
+ meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992)
+ # writes X and Y as columns:
+ st_write(meuse_sf, paste0(tempdir(), "/", "meuse.csv"), layer_options = "GEOMETRY=AS_XY")
+ st_write(meuse_sf, paste0(tempdir(), "/", "meuse.csv"), layer_options = "GEOMETRY=AS_WKT",
+   delete_dsn=TRUE) # overwrites
 \dontrun{
  library(sp)
  example(meuse, ask = FALSE, echo = FALSE)
@@ -133,6 +134,7 @@ st_write(meuse_sf, paste0(tempdir(), "/", "meuse.csv"), layer_options = "GEOMETR
  try(st_write(nc, "PG:dbname=postgis", "sids", layer_options = "OVERWRITE=true"))
 }
 }
+}
 \seealso{
 \link{st_drivers}, \link{dbWriteTable}
 }
diff --git a/man/tidyverse.Rd b/man/tidyverse.Rd
index 8118137f3..d3ed2c8a3 100644
--- a/man/tidyverse.Rd
+++ b/man/tidyverse.Rd
@@ -296,41 +296,64 @@ In case \code{do_union} is \code{FALSE}, \code{summarise} will simply combine ge
 \code{nest} assumes that a simple feature geometry list-column was among the columns that were nested.
 }
 \examples{
-library(dplyr)
-nc = st_read(system.file("shape/nc.shp", package="sf"))
-nc \%>\% filter(AREA > .1) \%>\% plot()
+if (require(dplyr, quietly = TRUE)) {
+ nc = read_sf(system.file("shape/nc.shp", package="sf"))
+ nc \%>\% filter(AREA > .1) \%>\% plot()
+}
 # plot 10 smallest counties in grey:
-st_geometry(nc) \%>\% plot()
-nc \%>\% select(AREA) \%>\% arrange(AREA) \%>\% slice(1:10) \%>\% plot(add = TRUE, col = 'grey')
-title("the ten counties with smallest area")
-nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
-nc \%>\% group_by(area_cl) \%>\% class()
-nc2 <- nc \%>\% mutate(area10 = AREA/10)
-nc \%>\% transmute(AREA = AREA/10, geometry = geometry) \%>\% class()
-nc \%>\% transmute(AREA = AREA/10) \%>\% class()
-nc \%>\% select(SID74, SID79) \%>\% names()
-nc \%>\% select(SID74, SID79, geometry) \%>\% names()
-nc \%>\% select(SID74, SID79) \%>\% class()
-nc \%>\% select(SID74, SID79, geometry) \%>\% class()
-nc2 <- nc \%>\% rename(area = AREA)
-nc \%>\% slice(1:2)
-nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
-nc.g <- nc \%>\% group_by(area_cl)
-nc.g \%>\% summarise(mean(AREA))
-nc.g \%>\% summarise(mean(AREA)) \%>\% plot(col = grey(3:6 / 7))
-nc \%>\% as.data.frame \%>\% summarise(mean(AREA))
-nc[c(1:100, 1:10), ] \%>\% distinct() \%>\% nrow()
-library(tidyr)
-nc \%>\% select(SID74, SID79) \%>\% gather("VAR", "SID", -geometry) \%>\% summary()
-library(tidyr)
-nc$row = 1:100 # needed for spread to work
-nc \%>\% select(SID74, SID79, geometry, row) \%>\%
+if (require(dplyr, quietly = TRUE)) {
+ st_geometry(nc) \%>\% plot()
+ nc \%>\% select(AREA) \%>\% arrange(AREA) \%>\% slice(1:10) \%>\% plot(add = TRUE, col = 'grey')
+ title("the ten counties with smallest area")
+}
+if (require(dplyr, quietly = TRUE)) {
+ nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
+ nc \%>\% group_by(area_cl) \%>\% class()
+}
+if (require(dplyr, quietly = TRUE)) {
+ nc2 <- nc \%>\% mutate(area10 = AREA/10)
+}
+if (require(dplyr, quietly = TRUE)) {
+ nc \%>\% transmute(AREA = AREA/10, geometry = geometry) \%>\% class()
+ nc \%>\% transmute(AREA = AREA/10) \%>\% class()
+}
+if (require(dplyr, quietly = TRUE)) {
+ nc \%>\% select(SID74, SID79) \%>\% names()
+ nc \%>\% select(SID74, SID79, geometry) \%>\% names()
+ nc \%>\% select(SID74, SID79) \%>\% class()
+ nc \%>\% select(SID74, SID79, geometry) \%>\% class()
+}
+if (require(dplyr, quietly = TRUE)) {
+ nc2 <- nc \%>\% rename(area = AREA)
+}
+if (require(dplyr, quietly = TRUE)) {
+ nc \%>\% slice(1:2)
+}
+if (require(dplyr, quietly = TRUE)) {
+ nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
+ nc.g <- nc \%>\% group_by(area_cl)
+ nc.g \%>\% summarise(mean(AREA))
+ nc.g \%>\% summarise(mean(AREA)) \%>\% plot(col = grey(3:6 / 7))
+ nc \%>\% as.data.frame \%>\% summarise(mean(AREA))
+}
+if (require(dplyr, quietly = TRUE)) {
+ nc[c(1:100, 1:10), ] \%>\% distinct() \%>\% nrow()
+}
+if (require(tidyr, quietly = TRUE) && require(dplyr, quietly = TRUE)) {
+ nc \%>\% select(SID74, SID79) \%>\% gather("VAR", "SID", -geometry) \%>\% summary()
+}
+if (require(tidyr, quietly = TRUE) && require(dplyr, quietly = TRUE)) {
+ nc$row = 1:100 # needed for spread to work
+ nc \%>\% select(SID74, SID79, geometry, row) \%>\%
 	gather("VAR", "SID", -geometry, -row) \%>\%
 	spread(VAR, SID) \%>\% head()
-storms.sf = st_as_sf(storms, coords = c("long", "lat"), crs = 4326)
-x <- storms.sf \%>\% group_by(name, year) \%>\% nest
-trs = lapply(x$data, function(tr) st_cast(st_combine(tr), "LINESTRING")[[1]]) \%>\%
+}
+if (require(tidyr, quietly = TRUE) && require(dplyr, quietly = TRUE)) {
+ storms.sf = st_as_sf(storms, coords = c("long", "lat"), crs = 4326)
+ x <- storms.sf \%>\% group_by(name, year) \%>\% nest
+ trs = lapply(x$data, function(tr) st_cast(st_combine(tr), "LINESTRING")[[1]]) \%>\%
     st_sfc(crs = 4326)
-trs.sf = st_sf(x[,1:2], trs)
-plot(trs.sf["year"], axes = TRUE)
+ trs.sf = st_sf(x[,1:2], trs)
+ plot(trs.sf["year"], axes = TRUE)
+}
 }
diff --git a/tests/aggregate.Rout.save b/tests/aggregate.Rout.save
index 436e8fac8..aec1b1a3b 100644
--- a/tests/aggregate.Rout.save
+++ b/tests/aggregate.Rout.save
@@ -1,6 +1,6 @@
 
-R version 4.1.2 (2021-11-01) -- "Bird Hippie"
-Copyright (C) 2021 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -16,7 +16,7 @@ Type 'demo()' for some demos, 'help()' for on-line help, or
 Type 'q()' to quit R.
 
 > library(sf)
-Linking to GEOS 3.10.1, GDAL 3.4.0, PROJ 8.2.0; sf_use_s2() is TRUE
+Linking to GEOS 3.10.2, GDAL 3.4.3, PROJ 8.2.0; sf_use_s2() is TRUE
 > # aggregate
 > pl1 = st_polygon(list(rbind(c(0,0),c(1,0),c(1,1),c(0,0))))
 > pl2 = st_polygon(list(rbind(c(0,0),c(1,1),c(0,1),c(0,0))))
@@ -40,39 +40,38 @@ CRS:           NA
   Group.1   a                       geometry
 1       1 1.5 POLYGON ((1 0, 0 0, 0 1, 1 ...
 > # expect_warning(st_cast(a, "POINT"))
-> demo(meuse_sf, echo = FALSE, ask = FALSE)
-> a = aggregate(meuse_sf, list(meuse_sf$soil), mean)
-There were 12 warnings (use warnings() to see them)
-> attributes(a)$agr
+> if (require(sp, quietly = TRUE)) {
++  demo(meuse_sf, echo = FALSE, ask = FALSE)
++  a = aggregate(meuse_sf, list(meuse_sf$soil), mean)
++  print(attributes(a)$agr)
++  a = aggregate(meuse_sf, list(soil = meuse_sf$soil), mean)
++  print(attributes(a)$agr)
++  a = aggregate(meuse_sf, list(meuse_sf$soil, meuse_sf$ffreq), mean)
++  print(attributes(a)$agr)
++  a = aggregate(meuse_sf, list(soil = meuse_sf$soil, ff = meuse_sf$ffreq), mean)
++  print(attributes(a)$agr)
++ }
   Group.1   cadmium    copper      lead      zinc      elev      dist        om 
  identity aggregate aggregate aggregate aggregate aggregate aggregate aggregate 
     ffreq      soil      lime   landuse    dist.m 
 aggregate aggregate aggregate aggregate aggregate 
 Levels: constant aggregate identity
-> a = aggregate(meuse_sf, list(soil = meuse_sf$soil), mean)
-There were 12 warnings (use warnings() to see them)
-> attributes(a)$agr
      soil   cadmium    copper      lead      zinc      elev      dist        om 
  identity aggregate aggregate aggregate aggregate aggregate aggregate aggregate 
     ffreq    soil.1      lime   landuse    dist.m 
 aggregate aggregate aggregate aggregate aggregate 
 Levels: constant aggregate identity
-> a = aggregate(meuse_sf, list(meuse_sf$soil, meuse_sf$ffreq), mean)
-There were 32 warnings (use warnings() to see them)
-> attributes(a)$agr
   Group.1   Group.2   cadmium    copper      lead      zinc      elev      dist 
  identity  identity aggregate aggregate aggregate aggregate aggregate aggregate 
        om     ffreq      soil      lime   landuse    dist.m 
 aggregate aggregate aggregate aggregate aggregate aggregate 
 Levels: constant aggregate identity
-> a = aggregate(meuse_sf, list(soil = meuse_sf$soil, ff = meuse_sf$ffreq), mean)
-There were 32 warnings (use warnings() to see them)
-> attributes(a)$agr
      soil        ff   cadmium    copper      lead      zinc      elev      dist 
  identity  identity aggregate aggregate aggregate aggregate aggregate aggregate 
        om     ffreq    soil.1      lime   landuse    dist.m 
 aggregate aggregate aggregate aggregate aggregate aggregate 
 Levels: constant aggregate identity
+There were 50 or more warnings (use warnings() to see the first 50)
 > 
 > # aggregate by sf/sfc
 > a = st_polygon(list(rbind(c(0,0), c(1,0), c(1,1), c(0,1), c(0,0)))) * 2
@@ -110,4 +109,4 @@ CRS:           NA
 > 
 > proc.time()
    user  system elapsed 
-  0.638   0.067   0.698 
+  1.177   0.056   1.225 
diff --git a/tests/crs.Rout.save b/tests/crs.Rout.save
index 152857dd1..8ab980f4b 100644
--- a/tests/crs.Rout.save
+++ b/tests/crs.Rout.save
@@ -1,6 +1,6 @@
 
-R version 4.1.2 (2021-11-01) -- "Bird Hippie"
-Copyright (C) 2021 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -82,8 +82,17 @@ POINT (111319.5 111325.1)
 + }
 [1] "datum files installed"
 > 
-> x0 = sp::CRS("+init=epsg:4326")
-> cat(sp::wkt(x0), "\n")
+> if (require(sp, quietly = TRUE)) {
++  x0 = sp::CRS("+init=epsg:4326")
++  cat(sp::wkt(x0), "\n")
++  x = st_crs(x0)
++  print(x)
++ 
++  y0 = st_crs(4326)
++  y0
++  y = as(y0, "CRS")
++  cat(sp::wkt(y), "\n")
++ }
 GEOGCRS["WGS 84",
     ENSEMBLE["World Geodetic System 1984 ensemble",
         MEMBER["World Geodetic System 1984 (Transit)",
@@ -121,8 +130,6 @@ GEOGCRS["WGS 84",
         SCOPE["unknown"],
         AREA["World."],
         BBOX[-90,-180,90,180]]] 
-> x = st_crs(x0)
-> x
 Coordinate Reference System:
   User input: WGS 84 
   wkt:
@@ -163,40 +170,6 @@ GEOGCRS["WGS 84",
         SCOPE["unknown"],
         AREA["World."],
         BBOX[-90,-180,90,180]]]
-> 
-> y0 = st_crs(4326)
-> y0
-Coordinate Reference System:
-  User input: EPSG:4326 
-  wkt:
-GEOGCRS["WGS 84",
-    ENSEMBLE["World Geodetic System 1984 ensemble",
-        MEMBER["World Geodetic System 1984 (Transit)"],
-        MEMBER["World Geodetic System 1984 (G730)"],
-        MEMBER["World Geodetic System 1984 (G873)"],
-        MEMBER["World Geodetic System 1984 (G1150)"],
-        MEMBER["World Geodetic System 1984 (G1674)"],
-        MEMBER["World Geodetic System 1984 (G1762)"],
-        MEMBER["World Geodetic System 1984 (G2139)"],
-        ELLIPSOID["WGS 84",6378137,298.257223563,
-            LENGTHUNIT["metre",1]],
-        ENSEMBLEACCURACY[2.0]],
-    PRIMEM["Greenwich",0,
-        ANGLEUNIT["degree",0.0174532925199433]],
-    CS[ellipsoidal,2],
-        AXIS["geodetic latitude (Lat)",north,
-            ORDER[1],
-            ANGLEUNIT["degree",0.0174532925199433]],
-        AXIS["geodetic longitude (Lon)",east,
-            ORDER[2],
-            ANGLEUNIT["degree",0.0174532925199433]],
-    USAGE[
-        SCOPE["Horizontal component of 3D system."],
-        AREA["World."],
-        BBOX[-90,-180,90,180]],
-    ID["EPSG",4326]]
-> y = as(y0, "CRS")
-> cat(sp::wkt(y), "\n")
 GEOGCRS["WGS 84",
     ENSEMBLE["World Geodetic System 1984 ensemble",
         MEMBER["World Geodetic System 1984 (Transit)"],
@@ -240,4 +213,4 @@ GEOGCRS["WGS 84",
 > 
 > proc.time()
    user  system elapsed 
-  0.874   0.060   0.927 
+  1.297   0.072   1.380 
diff --git a/tests/dist.Rout.save b/tests/dist.Rout.save
index 2ec87dd1b..ebced7abc 100644
--- a/tests/dist.Rout.save
+++ b/tests/dist.Rout.save
@@ -1,6 +1,6 @@
 
-R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
-Copyright (C) 2021 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -16,7 +16,6 @@ Type 'demo()' for some demos, 'help()' for on-line help, or
 Type 'q()' to quit R.
 
 > suppressPackageStartupMessages(library(sf))
-> library(sp)
 > suppressPackageStartupMessages(library(units))
 > 
 > x = st_sfc(
@@ -36,23 +35,25 @@ Type 'q()' to quit R.
 + crs = 4326
 + )
 > 
-> d.sf = st_distance(x, y)
-> d.sp = spDists(as(x, "Spatial"), as(y, "Spatial"))
-> units(d.sp) = as_units("km")
-> round(d.sf - d.sp, 7)
+> if (require(sp, quietly = TRUE)) {
++  d.sf = st_distance(x, y)
++  d.sp = spDists(as(x, "Spatial"), as(y, "Spatial"))
++  units(d.sp) = as_units("km")
++  print(round(d.sf - d.sp, 7))
++ 
++ #summary(unclass(d.sf) - d.sp)
++ 
++  st_crs(x) = st_crs(y) = NA
++  d.sf = st_distance(x, y)
++  d.sp = spDists(as(x, "Spatial"), as(y, "Spatial"))
++  print(round(d.sf - d.sp, 7))
++ }
 Units: [m]
          [,1]      [,2]      [,3]      [,4]      [,5]
 [1,] 6107.765 -124.3896 -248.7792 -373.1688 -497.5585
 [2,] 6065.138    0.0000 -124.3896 -248.7792 -373.1688
 [3,] 5940.569 -124.3896    0.0000 -124.3896 -248.7792
 [4,] 5743.252 -248.7792 -124.3896    0.0000 -124.3896
-> 
-> #summary(unclass(d.sf) - d.sp)
-> 
-> st_crs(x) = st_crs(y) = NA
-> d.sf = st_distance(x, y)
-> d.sp = spDists(as(x, "Spatial"), as(y, "Spatial"))
-> round(d.sf - d.sp, 7)
      [,1] [,2] [,3] [,4] [,5]
 [1,]    0    0    0    0    0
 [2,]    0    0    0    0    0
@@ -80,7 +81,7 @@ Units: [m]
 > st_length(z)
 1451026 [m]
 > st_length(z) - sum(d[1,2], d[2,3], d[3,4], d[4,5])
-2.328306e-10 [m]
+0 [m]
 > 
 > # st_line_sample:
 > ls = st_sfc(st_linestring(rbind(c(0,0),c(0,1))),
@@ -108,4 +109,4 @@ Error in st_line_sample(ls, density = 1/1000) :
 > 
 > proc.time()
    user  system elapsed 
-  1.856   0.097   2.456 
+  1.343   0.096   1.431 
diff --git a/tests/dplyr.R b/tests/dplyr.R
index 1c326611a..50e6886a1 100644
--- a/tests/dplyr.R
+++ b/tests/dplyr.R
@@ -1,111 +1,112 @@
 suppressPackageStartupMessages(library(sf))
 
-library(dplyr)
-options(dplyr.summarise.inform=FALSE)
-read_sf(system.file("shape/nc.shp", package="sf"), quiet = TRUE) %>%
+if (require(dplyr, quietly = TRUE)) {
+ options(dplyr.summarise.inform=FALSE)
+ read_sf(system.file("shape/nc.shp", package="sf"), quiet = TRUE) %>%
 	st_transform(3857) -> nc
-nc %>% filter(AREA > .1) %>% plot()
+ nc %>% filter(AREA > .1) %>% plot()
 
 # plot 10 smallest counties in grey:
-nc %>% 
-  select(BIR74, geometry) %>% 
-  plot()
+ nc %>% 
+   select(BIR74, geometry) %>% 
+   plot()
 
-nc %>% 
+ nc %>% 
   select(AREA, geometry) %>% 
   arrange(AREA) %>% 
   slice(1:10) %>% 
   plot(add = TRUE, col = 'grey', main ="")
 
 # select: check both when geometry is part of the selection, and when not:
-nc %>% select(SID74, SID79) %>% names()
-nc %>% select(SID74, SID79, geometry) %>% names()
-nc %>% select(SID74, SID79) %>% class()
-nc %>% select(SID74, SID79, geometry) %>% class()
+ nc %>% select(SID74, SID79) %>% names()
+ nc %>% select(SID74, SID79, geometry) %>% names()
+ nc %>% select(SID74, SID79) %>% class()
+ nc %>% select(SID74, SID79, geometry) %>% class()
 
 # group_by:
-nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
-nc %>% group_by(area_cl) %>% class()
+ nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
+ nc %>% group_by(area_cl) %>% class()
 
 # mutate:
-nc2 <- nc %>% mutate(area10 = AREA/10)
+ nc2 <- nc %>% mutate(area10 = AREA/10)
 
 # transmute:
-nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
-nc %>% transmute(AREA = AREA/10) %>% class()
+ nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
+ nc %>% transmute(AREA = AREA/10) %>% class()
 
 # rename:
-nc2 <- nc %>% rename(area = AREA)
+ nc2 <- nc %>% rename(area = AREA)
 
 # distinct:
-nc[c(1:100,1:10),] %>% distinct() %>% nrow()
+ nc[c(1:100,1:10),] %>% distinct() %>% nrow()
 
 # summarize:
-nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
-nc.g <- nc %>% group_by(area_cl)
-nc.g %>% summarise(mean(AREA))
-nc.g %>% summarize(mean(AREA)) %>% plot(col = 3:6/7)
+ nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
+ nc.g <- nc %>% group_by(area_cl)
+ nc.g %>% summarise(mean(AREA))
+ nc.g %>% summarize(mean(AREA)) %>% plot(col = 3:6/7)
 
-library(tidyr)
+ library(tidyr)
 
 # time-wide to long table, using tidyr::gather
 # stack the two SID columns for the July 1, 1974 - June 30, 1978 and July 1, 1979 - June 30, 1984 periods
 # (see https://cran.r-project.org/web/packages/spdep/vignettes/sids.pdf)
-nc %>% select(SID74, SID79, geometry) %>% gather("VAR", "SID", -geometry) %>% summary()
+ nc %>% select(SID74, SID79, geometry) %>% gather("VAR", "SID", -geometry) %>% summary()
 
 # spread:
-nc$row = 1:100
-nc.g <- nc %>% select(SID74, SID79, row) %>% gather("VAR", "SID", -row, -geometry)
-nc.g %>% tail()
-nc.g %>% spread(VAR, SID) %>% head()
-nc %>% select(SID74, SID79, geometry, row) %>% gather("VAR", "SID", -geometry, -row) %>% spread(VAR, SID) %>% head()
+ nc$row = 1:100
+ nc.g <- nc %>% select(SID74, SID79, row) %>% gather("VAR", "SID", -row, -geometry)
+ nc.g %>% tail()
+ nc.g %>% spread(VAR, SID) %>% head()
+ nc %>% select(SID74, SID79, geometry, row) %>% gather("VAR", "SID", -geometry, -row) %>% spread(VAR, SID) %>% head()
 
 # test st_set_crs in pipe:
-sfc = st_sfc(st_point(c(0,0)), st_point(c(1,1)))
-x <- sfc %>% st_set_crs(4326) %>% st_transform(3857)
-x
+ sfc = st_sfc(st_point(c(0,0)), st_point(c(1,1)))
+ x <- sfc %>% st_set_crs(4326) %>% st_transform(3857)
+ x
 
 read_sf(system.file("shape/nc.shp", package="sf"), quiet = TRUE) %>%
 	st_transform(3857) -> nc
-nc.merc <- st_transform(nc, 32119) # NC State Plane
-suppressPackageStartupMessages(library(units))
-install_unit("person")
-person = as_units("person")
-nc.merc <- nc.merc %>% mutate(area = st_area(nc.merc), dens = BIR74 * person / area)
+ nc.merc <- st_transform(nc, 32119) # NC State Plane
+ suppressPackageStartupMessages(library(units))
+ install_unit("person")
+ person = as_units("person")
+ nc.merc <- nc.merc %>% mutate(area = st_area(nc.merc), dens = BIR74 * person / area)
 
 # summary(nc.merc$dens) # requires units 0.4-2
-nc.merc$area_cl <- cut(nc$AREA, c(0, .1, .12, .15, .25))
-nc.grp <- nc.merc %>% group_by(area_cl)
+ nc.merc$area_cl <- cut(nc$AREA, c(0, .1, .12, .15, .25))
+ nc.grp <- nc.merc %>% group_by(area_cl)
 
-out <- nc.grp %>% summarise(A = sum(area), pop = sum(dens * area), 
+ out <- nc.grp %>% summarise(A = sum(area), pop = sum(dens * area), 
 	new_dens = sum(dens * area)/sum(area)) 
 
 # mean densities depend on grouping:
-nc.merc %>% summarize(mean(dens))
-out %>% summarise(mean(new_dens))
+ nc.merc %>% summarize(mean(dens))
+ out %>% summarise(mean(new_dens))
 
 # total densities don't:
-nc.merc %>% summarise(sum(area * dens))
-out %>% summarise(sum(A * new_dens))
+ nc.merc %>% summarise(sum(area * dens))
+ out %>% summarise(sum(A * new_dens))
 
-conn = system.file("gpkg/nc.gpkg", package = "sf")
+ conn = system.file("gpkg/nc.gpkg", package = "sf")
 
-library(DBI)
-library(RSQLite)
-con = dbConnect(SQLite(), dbname = system.file("gpkg/nc.gpkg", package = "sf"))
-dbReadTable(con, "nc.gpkg") %>% filter(AREA > 0.2) %>% collect %>% st_sf
+if (require(DBI, quietly = TRUE) && require(RSQLite, quietly = TRUE)) {
+ con = dbConnect(SQLite(), dbname = system.file("gpkg/nc.gpkg", package = "sf"))
+ dbReadTable(con, "nc.gpkg") %>% filter(AREA > 0.2) %>% collect %>% st_sf
 
 # nest:
-storms.sf = st_as_sf(storms, coords = c("long", "lat"), crs = 4326)
-x <- storms.sf %>% group_by(name, year) %>% nest
+ storms.sf = st_as_sf(storms, coords = c("long", "lat"), crs = 4326)
+ x <- storms.sf %>% group_by(name, year) %>% nest
 
-nrow(distinct(nc[c(1,1,1,2,2,3:100),]))
+ nrow(distinct(nc[c(1,1,1,2,2,3:100),]))
 
 # set.seed(1331)
-nc$gp <- sample(10, 100, replace=TRUE)
+ nc$gp <- sample(10, 100, replace=TRUE)
 # Get centroid of each group of polygons; https://github.com/r-spatial/sf/issues/969
-nc_gp_cent <- nc %>%
+ nc_gp_cent <- nc %>%
                 group_by(gp) %>%
                 group_map(st_area)
 
-nc %>% st_filter(nc[1,]) %>% nrow
+ nc %>% st_filter(nc[1,]) %>% nrow
+} # DBI & SQLITE
+} # dplyr
diff --git a/tests/dplyr.Rout.save b/tests/dplyr.Rout.save
index e2d546e0f..921ae8117 100644
--- a/tests/dplyr.Rout.save
+++ b/tests/dplyr.Rout.save
@@ -1,6 +1,6 @@
 
-R version 4.1.2 (2021-11-01) -- "Bird Hippie"
-Copyright (C) 2021 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -17,7 +17,116 @@ Type 'q()' to quit R.
 
 > suppressPackageStartupMessages(library(sf))
 > 
-> library(dplyr)
+> if (require(dplyr, quietly = TRUE)) {
++  options(dplyr.summarise.inform=FALSE)
++  read_sf(system.file("shape/nc.shp", package="sf"), quiet = TRUE) %>%
++ 	st_transform(3857) -> nc
++  nc %>% filter(AREA > .1) %>% plot()
++ 
++ # plot 10 smallest counties in grey:
++  nc %>% 
++    select(BIR74, geometry) %>% 
++    plot()
++ 
++  nc %>% 
++   select(AREA, geometry) %>% 
++   arrange(AREA) %>% 
++   slice(1:10) %>% 
++   plot(add = TRUE, col = 'grey', main ="")
++ 
++ # select: check both when geometry is part of the selection, and when not:
++  nc %>% select(SID74, SID79) %>% names()
++  nc %>% select(SID74, SID79, geometry) %>% names()
++  nc %>% select(SID74, SID79) %>% class()
++  nc %>% select(SID74, SID79, geometry) %>% class()
++ 
++ # group_by:
++  nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
++  nc %>% group_by(area_cl) %>% class()
++ 
++ # mutate:
++  nc2 <- nc %>% mutate(area10 = AREA/10)
++ 
++ # transmute:
++  nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
++  nc %>% transmute(AREA = AREA/10) %>% class()
++ 
++ # rename:
++  nc2 <- nc %>% rename(area = AREA)
++ 
++ # distinct:
++  nc[c(1:100,1:10),] %>% distinct() %>% nrow()
++ 
++ # summarize:
++  nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
++  nc.g <- nc %>% group_by(area_cl)
++  nc.g %>% summarise(mean(AREA))
++  nc.g %>% summarize(mean(AREA)) %>% plot(col = 3:6/7)
++ 
++  library(tidyr)
++ 
++ # time-wide to long table, using tidyr::gather
++ # stack the two SID columns for the July 1, 1974 - June 30, 1978 and July 1, 1979 - June 30, 1984 periods
++ # (see https://cran.r-project.org/web/packages/spdep/vignettes/sids.pdf)
++  nc %>% select(SID74, SID79, geometry) %>% gather("VAR", "SID", -geometry) %>% summary()
++ 
++ # spread:
++  nc$row = 1:100
++  nc.g <- nc %>% select(SID74, SID79, row) %>% gather("VAR", "SID", -row, -geometry)
++  nc.g %>% tail()
++  nc.g %>% spread(VAR, SID) %>% head()
++  nc %>% select(SID74, SID79, geometry, row) %>% gather("VAR", "SID", -geometry, -row) %>% spread(VAR, SID) %>% head()
++ 
++ # test st_set_crs in pipe:
++  sfc = st_sfc(st_point(c(0,0)), st_point(c(1,1)))
++  x <- sfc %>% st_set_crs(4326) %>% st_transform(3857)
++  x
++ 
++ read_sf(system.file("shape/nc.shp", package="sf"), quiet = TRUE) %>%
++ 	st_transform(3857) -> nc
++  nc.merc <- st_transform(nc, 32119) # NC State Plane
++  suppressPackageStartupMessages(library(units))
++  install_unit("person")
++  person = as_units("person")
++  nc.merc <- nc.merc %>% mutate(area = st_area(nc.merc), dens = BIR74 * person / area)
++ 
++ # summary(nc.merc$dens) # requires units 0.4-2
++  nc.merc$area_cl <- cut(nc$AREA, c(0, .1, .12, .15, .25))
++  nc.grp <- nc.merc %>% group_by(area_cl)
++ 
++  out <- nc.grp %>% summarise(A = sum(area), pop = sum(dens * area), 
++ 	new_dens = sum(dens * area)/sum(area)) 
++ 
++ # mean densities depend on grouping:
++  nc.merc %>% summarize(mean(dens))
++  out %>% summarise(mean(new_dens))
++ 
++ # total densities don't:
++  nc.merc %>% summarise(sum(area * dens))
++  out %>% summarise(sum(A * new_dens))
++ 
++  conn = system.file("gpkg/nc.gpkg", package = "sf")
++ 
++ if (require(DBI, quietly = TRUE) && require(RSQLite, quietly = TRUE)) {
++  con = dbConnect(SQLite(), dbname = system.file("gpkg/nc.gpkg", package = "sf"))
++  dbReadTable(con, "nc.gpkg") %>% filter(AREA > 0.2) %>% collect %>% st_sf
++ 
++ # nest:
++  storms.sf = st_as_sf(storms, coords = c("long", "lat"), crs = 4326)
++  x <- storms.sf %>% group_by(name, year) %>% nest
++ 
++  nrow(distinct(nc[c(1,1,1,2,2,3:100),]))
++ 
++ # set.seed(1331)
++  nc$gp <- sample(10, 100, replace=TRUE)
++ # Get centroid of each group of polygons; https://github.com/r-spatial/sf/issues/969
++  nc_gp_cent <- nc %>%
++                 group_by(gp) %>%
++                 group_map(st_area)
++ 
++  nc %>% st_filter(nc[1,]) %>% nrow
++ } # DBI & SQLITE
++ } # dplyr
 
 Attaching package: 'dplyr'
 
@@ -29,259 +138,10 @@ The following objects are masked from 'package:base':
 
     intersect, setdiff, setequal, union
 
-> options(dplyr.summarise.inform=FALSE)
-> read_sf(system.file("shape/nc.shp", package="sf"), quiet = TRUE) %>%
-+ 	st_transform(3857) -> nc
-> nc %>% filter(AREA > .1) %>% plot()
+[1] 4
 Warning message:
 plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all 
 > 
-> # plot 10 smallest counties in grey:
-> nc %>% 
-+   select(BIR74, geometry) %>% 
-+   plot()
-> 
-> nc %>% 
-+   select(AREA, geometry) %>% 
-+   arrange(AREA) %>% 
-+   slice(1:10) %>% 
-+   plot(add = TRUE, col = 'grey', main ="")
-> 
-> # select: check both when geometry is part of the selection, and when not:
-> nc %>% select(SID74, SID79) %>% names()
-[1] "SID74"    "SID79"    "geometry"
-> nc %>% select(SID74, SID79, geometry) %>% names()
-[1] "SID74"    "SID79"    "geometry"
-> nc %>% select(SID74, SID79) %>% class()
-[1] "sf"         "tbl_df"     "tbl"        "data.frame"
-> nc %>% select(SID74, SID79, geometry) %>% class()
-[1] "sf"         "tbl_df"     "tbl"        "data.frame"
-> 
-> # group_by:
-> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
-> nc %>% group_by(area_cl) %>% class()
-[1] "sf"         "grouped_df" "tbl_df"     "tbl"        "data.frame"
-> 
-> # mutate:
-> nc2 <- nc %>% mutate(area10 = AREA/10)
-> 
-> # transmute:
-> nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
-[1] "sf"         "tbl_df"     "tbl"        "data.frame"
-> nc %>% transmute(AREA = AREA/10) %>% class()
-[1] "sf"         "tbl_df"     "tbl"        "data.frame"
-> 
-> # rename:
-> nc2 <- nc %>% rename(area = AREA)
-> 
-> # distinct:
-> nc[c(1:100,1:10),] %>% distinct() %>% nrow()
-[1] 100
-> 
-> # summarize:
-> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
-> nc.g <- nc %>% group_by(area_cl)
-> nc.g %>% summarise(mean(AREA))
-Simple feature collection with 4 features and 2 fields
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: -9386880 ymin: 4012991 xmax: -8399788 ymax: 4382079
-Projected CRS: WGS 84 / Pseudo-Mercator
-# A tibble: 4 × 3
-  area_cl     `mean(AREA)`                                              geometry
-  <fct>              <dbl>                                    <MULTIPOLYGON [m]>
-1 (0,0.1]           0.0760 (((-8863447 4143479, -8857175 4151339, -8858837 4156…
-2 (0.1,0.12]        0.112  (((-9362143 4197312, -9355589 4200996, -9354263 4203…
-3 (0.12,0.15]       0.134  (((-9302071 4171499, -9311146 4181234, -9311292 4183…
-4 (0.15,0.25]       0.190  (((-8830723 4133018, -8832558 4137955, -8832096 4141…
-> nc.g %>% summarize(mean(AREA)) %>% plot(col = 3:6/7)
-> 
-> library(tidyr)
-> 
-> # time-wide to long table, using tidyr::gather
-> # stack the two SID columns for the July 1, 1974 - June 30, 1978 and July 1, 1979 - June 30, 1984 periods
-> # (see https://cran.r-project.org/web/packages/spdep/vignettes/sids.pdf)
-> nc %>% select(SID74, SID79, geometry) %>% gather("VAR", "SID", -geometry) %>% summary()
-          geometry       VAR                 SID        
- MULTIPOLYGON :200   Length:200         Min.   : 0.000  
- epsg:3857    :  0   Class :character   1st Qu.: 2.000  
- +proj=merc...:  0   Mode  :character   Median : 5.000  
-                                        Mean   : 7.515  
-                                        3rd Qu.: 9.000  
-                                        Max.   :57.000  
-> 
-> # spread:
-> nc$row = 1:100
-> nc.g <- nc %>% select(SID74, SID79, row) %>% gather("VAR", "SID", -row, -geometry)
-> nc.g %>% tail()
-Simple feature collection with 6 features and 3 fields
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: -8802506 ymin: 4012991 xmax: -8492268 ymax: 4166167
-Projected CRS: WGS 84 / Pseudo-Mercator
-# A tibble: 6 × 4
-    row                                                     geometry VAR     SID
-  <int>                                           <MULTIPOLYGON [m]> <chr> <dbl>
-1    95 (((-8588146 4131923, -8589850 4133303, -8589356 4135198, -8… SID79     4
-2    96 (((-8711999 4081959, -8719511 4077863, -8731642 4078864, -8… SID79     5
-3    97 (((-8685774 4073056, -8697387 4077823, -8700120 4077570, -8… SID79     3
-4    98 (((-8755885 4021935, -8802506 4069795, -8798771 4071779, -8… SID79    17
-5    99 (((-8678517 4054264, -8679088 4061405, -8680136 4061550, -8… SID79     9
-6   100 (((-8755885 4021935, -8753548 4025868, -8753052 4030195, -8… SID79     6
-> nc.g %>% spread(VAR, SID) %>% head()
-Simple feature collection with 6 features and 3 fields
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: -9099356 ymin: 4310668 xmax: -8434988 ymax: 4382079
-Projected CRS: WGS 84 / Pseudo-Mercator
-# A tibble: 6 × 4
-    row                                                     geometry SID74 SID79
-  <int>                                           <MULTIPOLYGON [m]> <dbl> <dbl>
-1     1 (((-9069486 4332934, -9077066 4338201, -9079419 4338351, -9…     1     0
-2     2 (((-9043562 4351030, -9043652 4352973, -9046117 4356516, -9…     0     3
-3     3 (((-8956335 4334068, -8958566 4335747, -8965300 4336025, -8…     5     6
-4     4 (((-8461241 4344709, -8462173 4347214, -8463902 4346972, -8…     1     2
-5     5 (((-8595797 4333852, -8597683 4330212, -8604808 4329788, -8…     9     3
-6     6 (((-8543185 4332878, -8569416 4332369, -8570981 4333107, -8…     7     5
-> nc %>% select(SID74, SID79, geometry, row) %>% gather("VAR", "SID", -geometry, -row) %>% spread(VAR, SID) %>% head()
-Simple feature collection with 6 features and 3 fields
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: -9099356 ymin: 4310668 xmax: -8434988 ymax: 4382079
-Projected CRS: WGS 84 / Pseudo-Mercator
-# A tibble: 6 × 4
-                                                      geometry   row SID74 SID79
-                                            <MULTIPOLYGON [m]> <int> <dbl> <dbl>
-1 (((-9069486 4332934, -9077066 4338201, -9079419 4338351, -9…     1     1     0
-2 (((-9043562 4351030, -9043652 4352973, -9046117 4356516, -9…     2     0     3
-3 (((-8956335 4334068, -8958566 4335747, -8965300 4336025, -8…     3     5     6
-4 (((-8461241 4344709, -8462173 4347214, -8463902 4346972, -8…     4     1     2
-5 (((-8595797 4333852, -8597683 4330212, -8604808 4329788, -8…     5     9     3
-6 (((-8543185 4332878, -8569416 4332369, -8570981 4333107, -8…     6     7     5
-> 
-> # test st_set_crs in pipe:
-> sfc = st_sfc(st_point(c(0,0)), st_point(c(1,1)))
-> x <- sfc %>% st_set_crs(4326) %>% st_transform(3857)
-> x
-Geometry set for 2 features 
-Geometry type: POINT
-Dimension:     XY
-Bounding box:  xmin: 0 ymin: 0 xmax: 111319.5 ymax: 111325.1
-Projected CRS: WGS 84 / Pseudo-Mercator
-POINT (0 0)
-POINT (111319.5 111325.1)
-> 
-> read_sf(system.file("shape/nc.shp", package="sf"), quiet = TRUE) %>%
-+ 	st_transform(3857) -> nc
-> nc.merc <- st_transform(nc, 32119) # NC State Plane
-> suppressPackageStartupMessages(library(units))
-> install_unit("person")
-> person = as_units("person")
-> nc.merc <- nc.merc %>% mutate(area = st_area(nc.merc), dens = BIR74 * person / area)
-> 
-> # summary(nc.merc$dens) # requires units 0.4-2
-> nc.merc$area_cl <- cut(nc$AREA, c(0, .1, .12, .15, .25))
-> nc.grp <- nc.merc %>% group_by(area_cl)
-> 
-> out <- nc.grp %>% summarise(A = sum(area), pop = sum(dens * area), 
-+ 	new_dens = sum(dens * area)/sum(area)) 
-> 
-> # mean densities depend on grouping:
-> nc.merc %>% summarize(mean(dens))
-Simple feature collection with 1 feature and 1 field
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: 123829 ymin: 14744.69 xmax: 930521.8 ymax: 318259.9
-Projected CRS: NAD83 / North Carolina
-# A tibble: 1 × 2
-  `mean(dens)`                                                          geometry
-  [person/m^2]                                                <MULTIPOLYGON [m]>
-1   0.00000259 (((138426 177699.3, 145548.6 177837.2, 151051.2 180557.6, 152246…
-> out %>% summarise(mean(new_dens))
-Simple feature collection with 1 feature and 1 field
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: 123829 ymin: 14744.69 xmax: 930521.8 ymax: 318259.9
-Projected CRS: NAD83 / North Carolina
-# A tibble: 1 × 2
-  `mean(new_dens)`                                                      geometry
-      [person/m^2]                                            <MULTIPOLYGON [m]>
-1       0.00000259 (((154399.2 148898.9, 142569.6 149407.8, 123829 150481.4, 12…
-> 
-> # total densities don't:
-> nc.merc %>% summarise(sum(area * dens))
-Simple feature collection with 1 feature and 1 field
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: 123829 ymin: 14744.69 xmax: 930521.8 ymax: 318259.9
-Projected CRS: NAD83 / North Carolina
-# A tibble: 1 × 2
-  `sum(area * dens)`                                                    geometry
-            [person]                                          <MULTIPOLYGON [m]>
-1             329962 (((138426 177699.3, 145548.6 177837.2, 151051.2 180557.6, …
-> out %>% summarise(sum(A * new_dens))
-Simple feature collection with 1 feature and 1 field
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: 123829 ymin: 14744.69 xmax: 930521.8 ymax: 318259.9
-Projected CRS: NAD83 / North Carolina
-# A tibble: 1 × 2
-  `sum(A * new_dens)`                                                   geometry
-             [person]                                         <MULTIPOLYGON [m]>
-1              329962 (((154399.2 148898.9, 142569.6 149407.8, 123829 150481.4,…
-> 
-> conn = system.file("gpkg/nc.gpkg", package = "sf")
-> 
-> library(DBI)
-> library(RSQLite)
-> con = dbConnect(SQLite(), dbname = system.file("gpkg/nc.gpkg", package = "sf"))
-> dbReadTable(con, "nc.gpkg") %>% filter(AREA > 0.2) %>% collect %>% st_sf
-Simple feature collection with 11 features and 15 fields
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: -80.06441 ymin: 33.88199 xmax: -76.49254 ymax: 36.06665
-CRS:           NA
-First 10 features:
-   fid  AREA PERIMETER CNTY_ CNTY_ID     NAME  FIPS FIPSNO CRESS_ID BIR74 SID74
-1   37 0.219     2.130  1938    1938     Wake 37183  37183       92 14484    16
-2   47 0.201     1.805  1968    1968 Randolph 37151  37151       76  4456     7
-3   54 0.207     1.851  1989    1989 Johnston 37101  37101       51  3999     6
-4   57 0.203     3.197  2004    2004 Beaufort 37013  37013        7  2692     7
-5   79 0.241     2.214  2083    2083  Sampson 37163  37163       82  3025     4
-6   88 0.204     1.871  2100    2100   Duplin 37061  37061       31  2483     4
-7   94 0.240     2.004  2150    2150  Robeson 37155  37155       78  7889    31
-8   96 0.225     2.107  2162    2162   Bladen 37017  37017        9  1782     8
-9   97 0.214     2.152  2185    2185   Pender 37141  37141       71  1228     4
-10  98 0.240     2.365  2232    2232 Columbus 37047  37047       24  3350    15
-   NWBIR74 BIR79 SID79 NWBIR79                           geom
-1     4397 20857    31    6221 MULTIPOLYGON (((-78.92107 3...
-2      384  5711    12     483 MULTIPOLYGON (((-79.76499 3...
-3     1165  4780    13    1349 MULTIPOLYGON (((-78.53874 3...
-4     1131  2909     4    1163 MULTIPOLYGON (((-77.10377 3...
-5     1396  3447     4    1524 MULTIPOLYGON (((-78.11377 3...
-6     1061  2777     7    1227 MULTIPOLYGON (((-77.68983 3...
-7     5904  9087    26    6899 MULTIPOLYGON (((-78.86451 3...
-8      818  2052     5    1023 MULTIPOLYGON (((-78.2615 34...
-9      580  1602     3     763 MULTIPOLYGON (((-78.02592 3...
-10    1431  4144    17    1832 MULTIPOLYGON (((-78.65572 3...
-> 
-> # nest:
-> storms.sf = st_as_sf(storms, coords = c("long", "lat"), crs = 4326)
-> x <- storms.sf %>% group_by(name, year) %>% nest
-> 
-> nrow(distinct(nc[c(1,1,1,2,2,3:100),]))
-[1] 100
-> 
-> # set.seed(1331)
-> nc$gp <- sample(10, 100, replace=TRUE)
-> # Get centroid of each group of polygons; https://github.com/r-spatial/sf/issues/969
-> nc_gp_cent <- nc %>%
-+                 group_by(gp) %>%
-+                 group_map(st_area)
-> 
-> nc %>% st_filter(nc[1,]) %>% nrow
-[1] 4
-> 
 > proc.time()
    user  system elapsed 
-  2.796   0.072   2.862 
+  3.146   0.104   3.289 
diff --git a/tests/graticule.R b/tests/graticule.R
index 58a072d80..efc23df77 100644
--- a/tests/graticule.R
+++ b/tests/graticule.R
@@ -1,4 +1,4 @@
-library(maps)
+if (require(maps, quietly = TRUE)) {
 m = map('usa', plot = FALSE, fill = TRUE)
 suppressPackageStartupMessages(library(sf))
 m0 <- st_as_sfc(m)
@@ -44,11 +44,11 @@ plot(nc[1], graticule = st_crs(nc), axes = TRUE)
 
 g = st_graticule()
 
-library(ggplot2)
-if (utils::packageVersion("ggplot2") > "2.2.1") {
+if (require(ggplot2, quietly = TRUE) && utils::packageVersion("ggplot2") > "2.2.1") {
   ggplot() + geom_sf(data = st_set_crs(nc, NA_crs_)) # NA_crs_ for crs
 }
 
 library(maps) #421
 (wrld2 = st_as_sf(map('world2', plot=FALSE, fill=TRUE )))
 try(plot(wrld2, graticule = TRUE))
+}
diff --git a/tests/graticule.Rout.save b/tests/graticule.Rout.save
index 7fadbbd32..a111bd083 100644
--- a/tests/graticule.Rout.save
+++ b/tests/graticule.Rout.save
@@ -1,6 +1,6 @@
 
-R version 4.0.4 (2021-02-15) -- "Lost Library Book"
-Copyright (C) 2021 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -15,26 +15,26 @@ Type 'demo()' for some demos, 'help()' for on-line help, or
 'help.start()' for an HTML browser interface to help.
 Type 'q()' to quit R.
 
-> library(maps)
-> m = map('usa', plot = FALSE, fill = TRUE)
-> suppressPackageStartupMessages(library(sf))
-> m0 <- st_as_sfc(m)
-> m <- st_as_sf(m)
-> 
-> laea = st_crs("+proj=laea +lat_0=30 +lon_0=-95") # Lambert equal area
-> m <- st_transform(st_as_sf(m), laea)
-> 
-> bb = st_bbox(m)
-> bbox = st_linestring(rbind(c( bb[1],bb[2]),c( bb[3],bb[2]),c( bb[3],bb[4]),c( bb[1],bb[4]),c( bb[1],bb[2])))
-> 
-> g = st_graticule(m)
-> plot(m, xlim = 1.2 * c(-2450853.4, 2186391.9))
-> plot(g[1], add = TRUE, col = 'grey')
-> plot(bbox, add = TRUE)
-> points(g$x_start, g$y_start, col = 'red')
-> points(g$x_end, g$y_end, col = 'blue')
-> 
-> invisible(lapply(seq_len(nrow(g)), function(i) {
+> if (require(maps, quietly = TRUE)) {
++ m = map('usa', plot = FALSE, fill = TRUE)
++ suppressPackageStartupMessages(library(sf))
++ m0 <- st_as_sfc(m)
++ m <- st_as_sf(m)
++ 
++ laea = st_crs("+proj=laea +lat_0=30 +lon_0=-95") # Lambert equal area
++ m <- st_transform(st_as_sf(m), laea)
++ 
++ bb = st_bbox(m)
++ bbox = st_linestring(rbind(c( bb[1],bb[2]),c( bb[3],bb[2]),c( bb[3],bb[4]),c( bb[1],bb[4]),c( bb[1],bb[2])))
++ 
++ g = st_graticule(m)
++ plot(m, xlim = 1.2 * c(-2450853.4, 2186391.9))
++ plot(g[1], add = TRUE, col = 'grey')
++ plot(bbox, add = TRUE)
++ points(g$x_start, g$y_start, col = 'red')
++ points(g$x_end, g$y_end, col = 'blue')
++ 
++ invisible(lapply(seq_len(nrow(g)), function(i) {
 + 	if (g$type[i] == "N" && g$x_start[i] - min(g$x_start) < 1000)
 + 		text(g[i,"x_start"], g[i,"y_start"], labels = parse(text = g[i,"degree_label"]), 
 + 			srt = g$angle_start[i], pos = 2, cex = .7)
@@ -48,45 +48,28 @@ Type 'q()' to quit R.
 + 		text(g[i,"x_end"], g[i,"y_end"], labels = parse(text = g[i,"degree_label"]), 
 + 			srt = g$angle_end[i] - 90, pos = 3, cex = .7)
 + }))
-> 
-> plot(m, graticule = st_crs(4326))
-> nc = st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)
-> # options(warn=2)
-> g = st_graticule(nc, datum = st_crs(nc))
-> #g = st_graticule(nc)
-> 
-> plot(nc[1], graticule = st_crs(nc))
-> 
-> plot(nc[1], graticule = st_crs(nc), axes = TRUE)
-> 
-> g = st_graticule()
-> 
-> library(ggplot2)
-> if (utils::packageVersion("ggplot2") > "2.2.1") {
++ 
++ plot(m, graticule = st_crs(4326))
++ nc = st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)
++ # options(warn=2)
++ g = st_graticule(nc, datum = st_crs(nc))
++ #g = st_graticule(nc)
++ 
++ plot(nc[1], graticule = st_crs(nc))
++ 
++ plot(nc[1], graticule = st_crs(nc), axes = TRUE)
++ 
++ g = st_graticule()
++ 
++ if (require(ggplot2, quietly = TRUE) && utils::packageVersion("ggplot2") > "2.2.1") {
 +   ggplot() + geom_sf(data = st_set_crs(nc, NA_crs_)) # NA_crs_ for crs
 + }
-> 
-> library(maps) #421
-> (wrld2 = st_as_sf(map('world2', plot=FALSE, fill=TRUE )))
-Simple feature collection with 253 features and 1 field
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: 0 ymin: -89.99001 xmax: 360 ymax: 83.59961
-Geodetic CRS:  WGS 84
-First 10 features:
-                     ID                           geom
-1                 Aruba MULTIPOLYGON (((290.1009 12...
-2           Afghanistan MULTIPOLYGON (((74.89131 37...
-3                Angola MULTIPOLYGON (((23.9665 -10...
-4              Anguilla MULTIPOLYGON (((296.9988 18...
-5               Albania MULTIPOLYGON (((20.06396 42...
-6               Finland MULTIPOLYGON (((20.61133 60...
-7               Andorra MULTIPOLYGON (((1.706055 42...
-8  United Arab Emirates MULTIPOLYGON (((53.92783 24...
-9             Argentina MULTIPOLYGON (((295.4508 -5...
-10              Armenia MULTIPOLYGON (((45.55235 40...
-> try(plot(wrld2, graticule = TRUE))
++ 
++ library(maps) #421
++ (wrld2 = st_as_sf(map('world2', plot=FALSE, fill=TRUE )))
++ try(plot(wrld2, graticule = TRUE))
++ }
 > 
 > proc.time()
    user  system elapsed 
-  3.120   0.258   3.505 
+  1.960   0.175   2.135 
diff --git a/tests/grid.R b/tests/grid.R
index 4147d19bc..889397245 100644
--- a/tests/grid.R
+++ b/tests/grid.R
@@ -15,12 +15,14 @@ pushViewport(st_viewport(nc))
 invisible(lapply(st_geometry(nc), function(x) grid.draw(st_as_grob(x, gp = gpar(fill = 'red')))))
 
 # POINTS:
-data(meuse, package = "sp")
-meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992, agr = "constant")
-grid.newpage()
-pushViewport(st_viewport(meuse_sf))
-invisible(lapply(st_geometry(meuse_sf), 
+if (require(sp, quietly = TRUE)) {
+ data(meuse, package = "sp")
+ meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992, agr = "constant")
+ grid.newpage()
+ pushViewport(st_viewport(meuse_sf))
+ invisible(lapply(st_geometry(meuse_sf), 
 	function(x) grid.draw(st_as_grob(x, gp = gpar(fill = 'red')))))
+}
 
 # MULTIPOINTS
 mp = st_multipoint(cbind(runif(100), runif(100)))
@@ -40,6 +42,7 @@ grid.newpage()
 pushViewport(st_viewport(ls))
 grid.draw(st_as_grob(ls, gp = gpar(fill = 'red')))
 
+if (require(sp, quietly = TRUE)) {
 # POINTS, right aspect in Long/Lat:
 meuse_ll = st_transform(meuse_sf, 4326)
 grid.newpage()
@@ -53,6 +56,7 @@ grid.newpage()
 pushViewport(st_viewport(meuse_ll))
 invisible(lapply(st_geometry(meuse_ll), 
 	function(x) grid.draw(st_as_grob(x, gp = gpar(fill = 'red')))))
+}
 
 gc = st_geometrycollection(list(st_point(0:1), st_linestring(matrix(1:4,2))))
 grb = st_as_grob(gc)
diff --git a/tests/grid.Rout.save b/tests/grid.Rout.save
index bd0fb69b5..8e737eb88 100644
--- a/tests/grid.Rout.save
+++ b/tests/grid.Rout.save
@@ -1,6 +1,6 @@
 
-R version 3.5.2 (2018-12-20) -- "Eggshell Igloo"
-Copyright (C) 2018 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -32,12 +32,14 @@ Type 'q()' to quit R.
 > invisible(lapply(st_geometry(nc), function(x) grid.draw(st_as_grob(x, gp = gpar(fill = 'red')))))
 > 
 > # POINTS:
-> data(meuse, package = "sp")
-> meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992, agr = "constant")
-> grid.newpage()
-> pushViewport(st_viewport(meuse_sf))
-> invisible(lapply(st_geometry(meuse_sf), 
+> if (require(sp, quietly = TRUE)) {
++  data(meuse, package = "sp")
++  meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992, agr = "constant")
++  grid.newpage()
++  pushViewport(st_viewport(meuse_sf))
++  invisible(lapply(st_geometry(meuse_sf), 
 + 	function(x) grid.draw(st_as_grob(x, gp = gpar(fill = 'red')))))
++ }
 > 
 > # MULTIPOINTS
 > mp = st_multipoint(cbind(runif(100), runif(100)))
@@ -57,23 +59,25 @@ Type 'q()' to quit R.
 > pushViewport(st_viewport(ls))
 > grid.draw(st_as_grob(ls, gp = gpar(fill = 'red')))
 > 
-> # POINTS, right aspect in Long/Lat:
-> meuse_ll = st_transform(meuse_sf, 4326)
-> grid.newpage()
-> pushViewport(st_viewport(meuse_ll))
-> invisible(lapply(st_geometry(meuse_ll), 
+> if (require(sp, quietly = TRUE)) {
++ # POINTS, right aspect in Long/Lat:
++ meuse_ll = st_transform(meuse_sf, 4326)
++ grid.newpage()
++ pushViewport(st_viewport(meuse_ll))
++ invisible(lapply(st_geometry(meuse_ll), 
 + 	function(x) grid.draw(st_as_grob(x, gp = gpar(fill = 'red')))))
-> 
-> # WRONG aspect:
-> st_crs(meuse_ll) = NA
-> grid.newpage()
-> pushViewport(st_viewport(meuse_ll))
-> invisible(lapply(st_geometry(meuse_ll), 
++ 
++ # WRONG aspect:
++ st_crs(meuse_ll) = NA
++ grid.newpage()
++ pushViewport(st_viewport(meuse_ll))
++ invisible(lapply(st_geometry(meuse_ll), 
 + 	function(x) grid.draw(st_as_grob(x, gp = gpar(fill = 'red')))))
++ }
 > 
 > gc = st_geometrycollection(list(st_point(0:1), st_linestring(matrix(1:4,2))))
 > grb = st_as_grob(gc)
 > 
 > proc.time()
    user  system elapsed 
-  0.620   0.035   0.647 
+  1.496   0.059   1.566 
diff --git a/tests/maps.R b/tests/maps.R
index 5f1b788f7..0bd4d8831 100644
--- a/tests/maps.R
+++ b/tests/maps.R
@@ -1,11 +1,12 @@
-suppressPackageStartupMessages(library(maps))
 suppressPackageStartupMessages(library(sf))
 
-m = map(xlim = c(4,9), ylim = c(48,55), fill = TRUE, plot = FALSE)
-st_as_sf(m)
-m = map(xlim = c(4,9), ylim = c(48,55), plot = FALSE)
-st_as_sf(m, fill = FALSE)
-st_as_sf(map(), fill = FALSE)
-st_as_sf(map(fill = TRUE))
-st_as_sf(map(), fill = FALSE, group = FALSE)
-st_as_sf(map(fill = TRUE), group = FALSE)
+if (require(maps, quietly = TRUE)) {
+ m = map(xlim = c(4,9), ylim = c(48,55), fill = TRUE, plot = FALSE)
+ st_as_sf(m)
+ m = map(xlim = c(4,9), ylim = c(48,55), plot = FALSE)
+ st_as_sf(m, fill = FALSE)
+ st_as_sf(map(), fill = FALSE)
+ st_as_sf(map(fill = TRUE))
+ st_as_sf(map(), fill = FALSE, group = FALSE)
+ st_as_sf(map(fill = TRUE), group = FALSE)
+}
diff --git a/tests/maps.Rout.save b/tests/maps.Rout.save
index 5f6a26714..ac515901d 100644
--- a/tests/maps.Rout.save
+++ b/tests/maps.Rout.save
@@ -1,6 +1,6 @@
 
-R version 4.0.4 (2021-02-15) -- "Lost Library Book"
-Copyright (C) 2021 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -15,92 +15,18 @@ Type 'demo()' for some demos, 'help()' for on-line help, or
 'help.start()' for an HTML browser interface to help.
 Type 'q()' to quit R.
 
-> suppressPackageStartupMessages(library(maps))
 > suppressPackageStartupMessages(library(sf))
 > 
-> m = map(xlim = c(4,9), ylim = c(48,55), fill = TRUE, plot = FALSE)
-> st_as_sf(m)
-Simple feature collection with 6 features and 1 field
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: -4.7625 ymin: 42.34048 xmax: 15.0166 ymax: 57.73692
-Geodetic CRS:  WGS 84
-           ID                           geom
-1     Belgium MULTIPOLYGON (((5.993945 50...
-2     Germany MULTIPOLYGON (((8.587891 54...
-3     Denmark MULTIPOLYGON (((9.739746 54...
-4      France MULTIPOLYGON (((5.789746 49...
-5  Luxembourg MULTIPOLYGON (((6.116504 50...
-6 Netherlands MULTIPOLYGON (((4.226171 51...
-> m = map(xlim = c(4,9), ylim = c(48,55), plot = FALSE)
-> st_as_sf(m, fill = FALSE)
-Simple feature collection with 6 features and 1 field
-Geometry type: MULTILINESTRING
-Dimension:     XY
-Bounding box:  xmin: 2.524902 ymin: 47.59272 xmax: 10.92617 ymax: 57.73692
-Geodetic CRS:  WGS 84
-           ID                           geom
-1     Belgium MULTILINESTRING ((5.993945 ...
-2     Germany MULTILINESTRING ((6.116504 ...
-3     Denmark MULTILINESTRING ((4.226171 ...
-4      France MULTILINESTRING ((8.587891 ...
-5  Luxembourg MULTILINESTRING ((7.615625 ...
-6 Netherlands MULTILINESTRING ((6.344336 ...
-> st_as_sf(map(), fill = FALSE)
-Simple feature collection with 253 features and 1 field
-Geometry type: MULTILINESTRING
-Dimension:     XY
-Bounding box:  xmin: -180 ymin: -84.51308 xmax: 189.4905 ymax: 83.57725
-Geodetic CRS:  WGS 84
-First 10 features:
-                     ID                           geom
-1                 Aruba MULTILINESTRING ((-69.89912...
-2           Afghanistan MULTILINESTRING ((74.89131 ...
-3                Angola MULTILINESTRING ((74.5414 3...
-4              Anguilla MULTILINESTRING ((61.26201 ...
-5               Albania MULTILINESTRING ((66.52226 ...
-6               Finland MULTILINESTRING ((67.75899 ...
-7               Andorra MULTILINESTRING ((11.74307 ...
-8  United Arab Emirates MULTILINESTRING ((13.06816 ...
-9             Argentina MULTILINESTRING ((20.56621 ...
-10              Armenia MULTILINESTRING ((20.61133 ...
-> st_as_sf(map(fill = TRUE))
-Simple feature collection with 253 features and 1 field
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: -180 ymin: -85.19218 xmax: 190.2708 ymax: 83.59961
-Geodetic CRS:  WGS 84
-First 10 features:
-                     ID                           geom
-1                 Aruba MULTIPOLYGON (((-69.89912 1...
-2           Afghanistan MULTIPOLYGON (((74.89131 37...
-3                Angola MULTIPOLYGON (((23.9665 -10...
-4              Anguilla MULTIPOLYGON (((-63.00122 1...
-5               Albania MULTIPOLYGON (((20.06396 42...
-6               Finland MULTIPOLYGON (((20.61133 60...
-7               Andorra MULTIPOLYGON (((1.706055 42...
-8  United Arab Emirates MULTIPOLYGON (((53.92783 24...
-9             Argentina MULTIPOLYGON (((-64.54916 -...
-10              Armenia MULTIPOLYGON (((45.55235 40...
-> st_as_sf(map(), fill = FALSE, group = FALSE)
-Simple feature collection with 1627 features and 1 field
-Geometry type: MULTILINESTRING
-Dimension:     XY
-Bounding box:  xmin: -180 ymin: -84.51308 xmax: 189.4905 ymax: 83.57725
-Geodetic CRS:  WGS 84
-First 10 features:
-                                  ID                           geom
-1                              Aruba MULTILINESTRING ((-69.89912...
-2                        Afghanistan MULTILINESTRING ((74.89131 ...
-3                             Angola MULTILINESTRING ((74.5414 3...
-4                     Angola:Cabinda MULTILINESTRING ((60.84336 ...
-5                           Anguilla MULTILINESTRING ((61.26201 ...
-6                            Albania MULTILINESTRING ((66.52226 ...
-7        Finland:Aland Islands:Foglo MULTILINESTRING ((67.75899 ...
-8       Finland:Aland Islands:Eckero MULTILINESTRING ((23.9665 -...
-9  Finland:Aland Islands:Fasta Aland MULTILINESTRING ((23.38066 ...
-10                           Andorra MULTILINESTRING ((11.74307 ...
-> st_as_sf(map(fill = TRUE), group = FALSE)
+> if (require(maps, quietly = TRUE)) {
++  m = map(xlim = c(4,9), ylim = c(48,55), fill = TRUE, plot = FALSE)
++  st_as_sf(m)
++  m = map(xlim = c(4,9), ylim = c(48,55), plot = FALSE)
++  st_as_sf(m, fill = FALSE)
++  st_as_sf(map(), fill = FALSE)
++  st_as_sf(map(fill = TRUE))
++  st_as_sf(map(), fill = FALSE, group = FALSE)
++  st_as_sf(map(fill = TRUE), group = FALSE)
++ }
 Simple feature collection with 1627 features and 1 field
 Geometry type: MULTIPOLYGON
 Dimension:     XY
@@ -121,4 +47,4 @@ First 10 features:
 > 
 > proc.time()
    user  system elapsed 
-  3.026   0.138   3.334 
+  1.891   0.063   1.947 
diff --git a/tests/plot.R b/tests/plot.R
index efcd19a5c..d815f1e20 100644
--- a/tests/plot.R
+++ b/tests/plot.R
@@ -1,6 +1,7 @@
 suppressPackageStartupMessages(library(sf))
 options(rgdal_show_exportToProj4_warnings = "none")
-library(dplyr)
+
+if (require(dplyr, quietly = TRUE)) {
 
 # plot linestrings:
 l1 = st_linestring(matrix(runif(6)-0.5,,2))
@@ -114,3 +115,4 @@ plot(nc["e"], logz = TRUE)
 # shared key:
 plot(nc[c("SID74", "SID79")], key.pos = -1)
 plot(nc[c("BIR74", "BIR79")], key.pos = 1, logz=TRUE)
+}
diff --git a/tests/plot.Rout.save b/tests/plot.Rout.save
index 5f43ab414..9491bf548 100644
--- a/tests/plot.Rout.save
+++ b/tests/plot.Rout.save
@@ -1,6 +1,6 @@
 
-R version 4.1.0 (2021-05-18) -- "Camp Pontanezen"
-Copyright (C) 2021 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -17,7 +17,122 @@ Type 'q()' to quit R.
 
 > suppressPackageStartupMessages(library(sf))
 > options(rgdal_show_exportToProj4_warnings = "none")
-> library(dplyr)
+> 
+> if (require(dplyr, quietly = TRUE)) {
++ 
++ # plot linestrings:
++ l1 = st_linestring(matrix(runif(6)-0.5,,2))
++ l2 = st_linestring(matrix(runif(6)-0.5,,2))
++ l3 = st_linestring(matrix(runif(6)-0.5,,2))
++ s = st_sf(a=2:4, b=st_sfc(l1,l2,l3))
++ plot(s, col = s$a, axes = FALSE)
++ plot(s, col = s$a)
++ attr(s$b, "proj4string") = sp::CRS("+proj=longlat +ellps=WGS84 +no_defs")@projargs
++ plot(s, col = s$a, axes = TRUE)
++ plot(s, col = s$a, lty = s$a, lwd = s$a, pch = s$a, type = 'b')
++ l4 = st_linestring(matrix(runif(6),,2))
++ plot(st_sf(a=1,b=st_sfc(l4)), add = TRUE)
++ # plot multilinestrings:
++ ml1 = st_multilinestring(list(l1, l2))
++ ml2 = st_multilinestring(list(l3, l4))
++ ml = st_sf(a = 2:3, b = st_sfc(ml1, ml2))
++ plot(ml, col = ml$a, lty = ml$a, lwd = ml$a, pch = ml$a, type = 'b')
++ # plot points:
++ p1 = st_point(c(1,2))
++ p2 = st_point(c(3,3))
++ p3 = st_point(c(3,0))
++ p = st_sf(a=2:4, b=st_sfc(p1,p2,p3))
++ plot(p, col = s$a, axes = TRUE)
++ plot(p, col = s$a)
++ plot(p, col = p$a, pch = p$a, cex = p$a, bg = s$a, lwd = 2, lty = 2, type = 'b')
++ p4 = st_point(c(2,2))
++ plot(st_sf(a=1, st_sfc(p4)), add = TRUE)
++ # multipoints:
++ mp1 = st_multipoint(matrix(1:4,2))
++ mp2 = st_multipoint(matrix(5:8,2))
++ mp = st_sf(a = 2:3, b = st_sfc(mp1, mp2))
++ plot(mp)
++ plot(mp, col = mp$a, pch = mp$a, cex = mp$a, bg = mp$a, lwd = mp$a, lty = mp$a, type = 'b')
++ # polygon:
++ outer = matrix(c(0,0,10,0,10,10,0,10,0,0),ncol=2, byrow=TRUE)
++ hole1 = matrix(c(1,1,1,2,2,2,2,1,1,1),ncol=2, byrow=TRUE)
++ hole2 = matrix(c(5,5,5,6,6,6,6,5,5,5),ncol=2, byrow=TRUE)
++ pl1 = st_polygon(list(outer, hole1, hole2))
++ pl2 = st_polygon(list(outer+10, hole1+10, hole2+10))
++ po = st_sf(a = 2:3, st_sfc(pl1,pl2))
++ plot(po, col = po$a, border = rev(po$a), lwd=3)
++ # multipolygon
++ r10 = matrix(rep(c(0,10),each=5),5)
++ pl1 = list(outer, hole1, hole2)
++ pl2 = list(outer+10, hole1+10, hole2+10)
++ pl3 = list(outer+r10, hole1+r10, hole2+r10)
++ mpo1 = st_multipolygon(list(pl1,pl2))
++ mpo2 = st_multipolygon(list(pl3))
++ mpo = st_sf(a=2:3, b=st_sfc(mpo1,mpo2))
++ plot(mpo, col = mpo$a, border = rev(mpo$a), lwd = 2)
++ # geometrycollection:
++ gc1 = st_geometrycollection(list(mpo1, st_point(c(21,21)), l1 * 2 + 21))
++ gc2 = st_geometrycollection(list(mpo2, l2 - 2, l3 - 2, st_point(c(-1,-1))))
++ gc = st_sf(a=2:3, b = st_sfc(gc1,gc2))
++ plot(gc, cex = gc$a, col = gc$a, border = rev(gc$a) + 2, lwd = 2)
++ 
++ plot(gc1)
++ 
++ plot(st_sfc(mp1, mpo1))
++ 
++ # color ramp
++ nc = st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)
++ plot(nc)
++ plot(nc, axes = TRUE)
++ plot(nc, col="lightgrey") 
++ plot(st_centroid(nc), add = TRUE, col = 1)
++ nc %>% 
++   select(geometry) %>% 
++   plot()
++ 
++ nc$f = cut(nc[[1]], 5)
++ plot(nc["f"], key.pos = 1)
++ plot(nc[1],   key.pos = 1)
++ 
++ # test background map plotting:
++ load("bgmap.rda")
++ merc = st_crs(3857)
++ WGS84 = st_crs(4326)
++ nc = st_transform(nc, WGS84)
++ ## ggmap:
++ #library(ggmap)
++ #bgMap = get_map(unname(st_bbox(nc)), source = "google", zoom = 8) 
++ plot(st_transform(nc[1], merc), bgMap = bgMap)
++ 
++ # RgoogleMaps:
++ #library(RgoogleMaps)
++ #center = c(mean(st_bbox(nc)[c(2,4)]), mean(st_bbox(nc)[c(1,3)]))
++ #g = GetMap(center=center, zoom=6) # google
++ par(mar = c(0,0,1,0))
++ plot(st_transform(nc, merc), bgMap = g)
++ 
++ m = st_make_grid()
++ st_crs(m) = NA_crs_
++ m = st_segmentize(m, 2)
++ st_crs(m) = 4326
++ plot(m, axes = TRUE)
++ g = st_transform(m, st_crs("+proj=ortho +lat_0=30 +lon_0=45"), check = TRUE)
++ plot(g, axes = TRUE)
++ 
++ nc[[1]] = NA
++ nc[[10]] = 1
++ plot(nc, pal = rainbow, nbreaks = 3)
++ plot(nc, pal = rainbow, breaks = "jenks", nbreaks = 3)
++ plot(nc, pal = rainbow, breaks = (0:10)/3)
++ 
++ # logz:
++ nc$e = 10^(nc$SID74)
++ plot(nc["e"], logz = TRUE)
++ 
++ # shared key:
++ plot(nc[c("SID74", "SID79")], key.pos = -1)
++ plot(nc[c("BIR74", "BIR79")], key.pos = 1, logz=TRUE)
++ }
 
 Attaching package: 'dplyr'
 
@@ -29,143 +144,8 @@ The following objects are masked from 'package:base':
 
     intersect, setdiff, setequal, union
 
-> 
-> # plot linestrings:
-> l1 = st_linestring(matrix(runif(6)-0.5,,2))
-> l2 = st_linestring(matrix(runif(6)-0.5,,2))
-> l3 = st_linestring(matrix(runif(6)-0.5,,2))
-> s = st_sf(a=2:4, b=st_sfc(l1,l2,l3))
-> plot(s, col = s$a, axes = FALSE)
-> plot(s, col = s$a)
-> attr(s$b, "proj4string") = sp::CRS("+proj=longlat +ellps=WGS84 +no_defs")@projargs
-> plot(s, col = s$a, axes = TRUE)
-> plot(s, col = s$a, lty = s$a, lwd = s$a, pch = s$a, type = 'b')
-> l4 = st_linestring(matrix(runif(6),,2))
-> plot(st_sf(a=1,b=st_sfc(l4)), add = TRUE)
-> # plot multilinestrings:
-> ml1 = st_multilinestring(list(l1, l2))
-> ml2 = st_multilinestring(list(l3, l4))
-> ml = st_sf(a = 2:3, b = st_sfc(ml1, ml2))
-> plot(ml, col = ml$a, lty = ml$a, lwd = ml$a, pch = ml$a, type = 'b')
-> # plot points:
-> p1 = st_point(c(1,2))
-> p2 = st_point(c(3,3))
-> p3 = st_point(c(3,0))
-> p = st_sf(a=2:4, b=st_sfc(p1,p2,p3))
-> plot(p, col = s$a, axes = TRUE)
-> plot(p, col = s$a)
-> plot(p, col = p$a, pch = p$a, cex = p$a, bg = s$a, lwd = 2, lty = 2, type = 'b')
-> p4 = st_point(c(2,2))
-> plot(st_sf(a=1, st_sfc(p4)), add = TRUE)
-> # multipoints:
-> mp1 = st_multipoint(matrix(1:4,2))
-> mp2 = st_multipoint(matrix(5:8,2))
-> mp = st_sf(a = 2:3, b = st_sfc(mp1, mp2))
-> plot(mp)
-> plot(mp, col = mp$a, pch = mp$a, cex = mp$a, bg = mp$a, lwd = mp$a, lty = mp$a, type = 'b')
-> # polygon:
-> outer = matrix(c(0,0,10,0,10,10,0,10,0,0),ncol=2, byrow=TRUE)
-> hole1 = matrix(c(1,1,1,2,2,2,2,1,1,1),ncol=2, byrow=TRUE)
-> hole2 = matrix(c(5,5,5,6,6,6,6,5,5,5),ncol=2, byrow=TRUE)
-> pl1 = st_polygon(list(outer, hole1, hole2))
-> pl2 = st_polygon(list(outer+10, hole1+10, hole2+10))
-> po = st_sf(a = 2:3, st_sfc(pl1,pl2))
-> plot(po, col = po$a, border = rev(po$a), lwd=3)
-> # multipolygon
-> r10 = matrix(rep(c(0,10),each=5),5)
-> pl1 = list(outer, hole1, hole2)
-> pl2 = list(outer+10, hole1+10, hole2+10)
-> pl3 = list(outer+r10, hole1+r10, hole2+r10)
-> mpo1 = st_multipolygon(list(pl1,pl2))
-> mpo2 = st_multipolygon(list(pl3))
-> mpo = st_sf(a=2:3, b=st_sfc(mpo1,mpo2))
-> plot(mpo, col = mpo$a, border = rev(mpo$a), lwd = 2)
-> # geometrycollection:
-> gc1 = st_geometrycollection(list(mpo1, st_point(c(21,21)), l1 * 2 + 21))
-> gc2 = st_geometrycollection(list(mpo2, l2 - 2, l3 - 2, st_point(c(-1,-1))))
-> gc = st_sf(a=2:3, b = st_sfc(gc1,gc2))
-> plot(gc, cex = gc$a, col = gc$a, border = rev(gc$a) + 2, lwd = 2)
-> 
-> plot(gc1)
-> 
-> plot(st_sfc(mp1, mpo1))
-> 
-> # color ramp
-> nc = st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)
-> plot(nc)
-Warning message:
-plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all 
-> plot(nc, axes = TRUE)
-Warning message:
-plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all 
-> plot(nc, col="lightgrey") 
-Warning message:
-plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all 
-> plot(st_centroid(nc), add = TRUE, col = 1)
-Warning messages:
-1: In st_centroid.sf(nc) :
-  st_centroid assumes attributes are constant over geometries of x
-2: In plot.sf(st_centroid(nc), add = TRUE, col = 1) :
-  ignoring all but the first attribute
-> nc %>% 
-+   select(geometry) %>% 
-+   plot()
-> 
-> nc$f = cut(nc[[1]], 5)
-> plot(nc["f"], key.pos = 1)
-> plot(nc[1],   key.pos = 1)
-> 
-> # test background map plotting:
-> load("bgmap.rda")
-> merc = st_crs(3857)
-> WGS84 = st_crs(4326)
-> nc = st_transform(nc, WGS84)
-> ## ggmap:
-> #library(ggmap)
-> #bgMap = get_map(unname(st_bbox(nc)), source = "google", zoom = 8) 
-> plot(st_transform(nc[1], merc), bgMap = bgMap)
-> 
-> # RgoogleMaps:
-> #library(RgoogleMaps)
-> #center = c(mean(st_bbox(nc)[c(2,4)]), mean(st_bbox(nc)[c(1,3)]))
-> #g = GetMap(center=center, zoom=6) # google
-> par(mar = c(0,0,1,0))
-> plot(st_transform(nc, merc), bgMap = g)
-Warning message:
-plotting the first 10 out of 15 attributes; use max.plot = 15 to plot all 
-> 
-> m = st_make_grid()
-> st_crs(m) = NA_crs_
-> m = st_segmentize(m, 2)
-> st_crs(m) = 4326
-> plot(m, axes = TRUE)
-> g = st_transform(m, st_crs("+proj=ortho +lat_0=30 +lon_0=45"), check = TRUE)
-> plot(g, axes = TRUE)
-> 
-> nc[[1]] = NA
-> nc[[10]] = 1
-> plot(nc, pal = rainbow, nbreaks = 3)
-Warning messages:
-1: plotting the first 10 out of 15 attributes; use max.plot = 15 to plot all 
-2: In min(x) : no non-missing arguments to min; returning Inf
-3: In max(x) : no non-missing arguments to max; returning -Inf
-> plot(nc, pal = rainbow, breaks = "jenks", nbreaks = 3)
-Warning messages:
-1: plotting the first 10 out of 15 attributes; use max.plot = 15 to plot all 
-2: In min(x) : no non-missing arguments to min; returning Inf
-3: In max(x) : no non-missing arguments to max; returning -Inf
-> plot(nc, pal = rainbow, breaks = (0:10)/3)
-Warning message:
-plotting the first 10 out of 15 attributes; use max.plot = 15 to plot all 
-> 
-> # logz:
-> nc$e = 10^(nc$SID74)
-> plot(nc["e"], logz = TRUE)
-> 
-> # shared key:
-> plot(nc[c("SID74", "SID79")], key.pos = -1)
-> plot(nc[c("BIR74", "BIR79")], key.pos = 1, logz=TRUE)
+There were 13 warnings (use warnings() to see them)
 > 
 > proc.time()
    user  system elapsed 
-  5.220   0.169   5.379 
+  5.863   0.119   6.022 
diff --git a/tests/roundtrip.R b/tests/roundtrip.R
index 0e0ef8aad..b504160cf 100644
--- a/tests/roundtrip.R
+++ b/tests/roundtrip.R
@@ -12,20 +12,22 @@ pol3 = list(outer + 24)
 mp = list(pol1,pol2,pol3)
 mp1 = st_multipolygon(mp)
 sf = st_sf(a=1, st_sfc(mp1))
-a = as(sf, "Spatial")
-class(a)
-b = st_as_sf(a)
-a2 = as(a, "SpatialPolygonsDataFrame")
-all.equal(a, a2) # round-trip
+if (require(sp, quietly = TRUE)) {
+ a = as(sf, "Spatial")
+ print(class(a))
+ b = st_as_sf(a)
+ a2 = as(a, "SpatialPolygonsDataFrame")
+ print(all.equal(a, a2)) # round-trip
 
-b1 = as(a, "sf")
-all.equal(b, b1)
-b = st_as_sfc(a)
-b1 = as(a, "sfc")
-all.equal(b, b1)
+ b1 = as(a, "sf")
+ print(all.equal(b, b1))
+ b = st_as_sfc(a)
+ b1 = as(a, "sfc")
+ print(all.equal(b, b1))
+}
 
 # SpatialMultiPoints
-library(sp)
+if (require(sp, quietly = TRUE)) {
 suppressWarnings(RNGversion("3.5.3"))
 set.seed(1331)
 # example(SpatialMultiPoints, ask = FALSE, echo = FALSE) # loads mpdf
@@ -57,3 +59,4 @@ all.equal(nc, st_as_sf(as(nc, "Spatial")))
 st_crs(nc) == st_crs(st_as_sf(as(nc, "Spatial")))
 
 detach("package:sp")
+}
diff --git a/tests/roundtrip.Rout.save b/tests/roundtrip.Rout.save
index fc447722c..20183e053 100644
--- a/tests/roundtrip.Rout.save
+++ b/tests/roundtrip.Rout.save
@@ -1,6 +1,6 @@
 
-R version 4.1.2 (2021-11-01) -- "Bird Hippie"
-Copyright (C) 2021 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -29,62 +29,61 @@ Type 'q()' to quit R.
 > mp = list(pol1,pol2,pol3)
 > mp1 = st_multipolygon(mp)
 > sf = st_sf(a=1, st_sfc(mp1))
-> a = as(sf, "Spatial")
-> class(a)
+> if (require(sp, quietly = TRUE)) {
++  a = as(sf, "Spatial")
++  print(class(a))
++  b = st_as_sf(a)
++  a2 = as(a, "SpatialPolygonsDataFrame")
++  print(all.equal(a, a2)) # round-trip
++ 
++  b1 = as(a, "sf")
++  print(all.equal(b, b1))
++  b = st_as_sfc(a)
++  b1 = as(a, "sfc")
++  print(all.equal(b, b1))
++ }
 [1] "SpatialPolygonsDataFrame"
 attr(,"package")
 [1] "sp"
-> b = st_as_sf(a)
-> a2 = as(a, "SpatialPolygonsDataFrame")
-> all.equal(a, a2) # round-trip
 [1] TRUE
-> 
-> b1 = as(a, "sf")
-> all.equal(b, b1)
 [1] TRUE
-> b = st_as_sfc(a)
-> b1 = as(a, "sfc")
-> all.equal(b, b1)
 [1] TRUE
 > 
 > # SpatialMultiPoints
-> library(sp)
-> suppressWarnings(RNGversion("3.5.3"))
-> set.seed(1331)
-> # example(SpatialMultiPoints, ask = FALSE, echo = FALSE) # loads mpdf
-> cl1 = cbind(rnorm(3, 10), rnorm(3, 10))
-> cl2 = cbind(rnorm(5, 10), rnorm(5,  0))
-> cl3 = cbind(rnorm(7,  0), rnorm(7, 10))
-> mpdf = SpatialMultiPointsDataFrame(list(cl1, cl2, cl3), data.frame(a = 1:3))
-> m = st_as_sf(mpdf)
-> all.equal(as(m, "Spatial"), mpdf) # TRUE
-[1] TRUE
-> 
-> demo(meuse, ask = FALSE, echo = FALSE)
-> #meuse = spTransform(meuse, CRS("+proj=longlat +ellps=WGS84 +no_defs"))
-> pol.grd = as(meuse.grid, "SpatialPolygonsDataFrame")
-> #meuse.grd = spTransform(meuse.grid, CRS("+proj=longlat +ellps=WGS84 +no_defs"))
-> #pol.grd = spTransform(pol.grd, CRS("+proj=longlat +ellps=WGS84 +no_defs"))
-> #meuse.area = spTransform(meuse.area, CRS("+proj=longlat +ellps=WGS84 +no_defs"))
-> #meuse.riv = spTransform(meuse.riv, CRS("+proj=longlat +ellps=WGS84 +no_defs"))
-> #summary(st_as_sf(meuse))
-> #summary(st_as_sf(meuse.grd))
-> #x <- st_as_sf(meuse.grid) # don't print: CRS variations.
-> #summary(st_as_sf(meuse.area))
-> #summary(st_as_sf(meuse.riv))
-> #summary(st_as_sf(as(meuse.riv, "SpatialLines")))
-> #summary(st_as_sf(pol.grd))
-> #summary(st_as_sf(as(pol.grd, "SpatialLinesDataFrame")))
-> 
-> nc = st_read(system.file("gpkg/nc.gpkg", package="sf"), "nc.gpkg", quiet = TRUE)
-> all.equal(nc, st_as_sf(as(nc, "Spatial")))
-[1] "Names: 1 string mismatch"                                  
-[2] "Attributes: < Component \"sf_column\": 1 string mismatch >"
-> st_crs(nc) == st_crs(st_as_sf(as(nc, "Spatial")))
-[1] TRUE
-> 
-> detach("package:sp")
+> if (require(sp, quietly = TRUE)) {
++ suppressWarnings(RNGversion("3.5.3"))
++ set.seed(1331)
++ # example(SpatialMultiPoints, ask = FALSE, echo = FALSE) # loads mpdf
++ cl1 = cbind(rnorm(3, 10), rnorm(3, 10))
++ cl2 = cbind(rnorm(5, 10), rnorm(5,  0))
++ cl3 = cbind(rnorm(7,  0), rnorm(7, 10))
++ mpdf = SpatialMultiPointsDataFrame(list(cl1, cl2, cl3), data.frame(a = 1:3))
++ m = st_as_sf(mpdf)
++ all.equal(as(m, "Spatial"), mpdf) # TRUE
++ 
++ demo(meuse, ask = FALSE, echo = FALSE)
++ #meuse = spTransform(meuse, CRS("+proj=longlat +ellps=WGS84 +no_defs"))
++ pol.grd = as(meuse.grid, "SpatialPolygonsDataFrame")
++ #meuse.grd = spTransform(meuse.grid, CRS("+proj=longlat +ellps=WGS84 +no_defs"))
++ #pol.grd = spTransform(pol.grd, CRS("+proj=longlat +ellps=WGS84 +no_defs"))
++ #meuse.area = spTransform(meuse.area, CRS("+proj=longlat +ellps=WGS84 +no_defs"))
++ #meuse.riv = spTransform(meuse.riv, CRS("+proj=longlat +ellps=WGS84 +no_defs"))
++ #summary(st_as_sf(meuse))
++ #summary(st_as_sf(meuse.grd))
++ #x <- st_as_sf(meuse.grid) # don't print: CRS variations.
++ #summary(st_as_sf(meuse.area))
++ #summary(st_as_sf(meuse.riv))
++ #summary(st_as_sf(as(meuse.riv, "SpatialLines")))
++ #summary(st_as_sf(pol.grd))
++ #summary(st_as_sf(as(pol.grd, "SpatialLinesDataFrame")))
++ 
++ nc = st_read(system.file("gpkg/nc.gpkg", package="sf"), "nc.gpkg", quiet = TRUE)
++ all.equal(nc, st_as_sf(as(nc, "Spatial")))
++ st_crs(nc) == st_crs(st_as_sf(as(nc, "Spatial")))
++ 
++ detach("package:sp")
++ }
 > 
 > proc.time()
    user  system elapsed 
-  1.850   0.044   1.894 
+  1.735   0.065   1.789 
diff --git a/tests/s2.Rout.save b/tests/s2.Rout.save
index d5c83a09d..1c6ba7416 100644
--- a/tests/s2.Rout.save
+++ b/tests/s2.Rout.save
@@ -1,6 +1,6 @@
 
-R version 4.1.2 (2021-11-01) -- "Bird Hippie"
-Copyright (C) 2021 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -16,7 +16,7 @@ Type 'demo()' for some demos, 'help()' for on-line help, or
 Type 'q()' to quit R.
 
 > library(sf)
-Linking to GEOS 3.10.1, GDAL 3.4.0, PROJ 8.2.0; sf_use_s2() is TRUE
+Linking to GEOS 3.10.2, GDAL 3.4.3, PROJ 8.2.0; sf_use_s2() is TRUE
 > d = data.frame(z = 1:100, x = runif(100), y = runif(100))
 > n0 = st_as_sf(d, coords = c("x", "y"), crs = 4326)
 > n1 = st_transform(n0, 3857)
@@ -66,4 +66,4 @@ Linking to GEOS 3.10.1, GDAL 3.4.0, PROJ 8.2.0; sf_use_s2() is TRUE
 > 
 > proc.time()
    user  system elapsed 
-  1.239   0.044   1.275 
+  1.829   0.063   1.885 
diff --git a/tests/sfc.R b/tests/sfc.R
index ae9d58008..b2b907e79 100644
--- a/tests/sfc.R
+++ b/tests/sfc.R
@@ -1,5 +1,4 @@
 suppressPackageStartupMessages(library(sf))
-library(testthat)
 
 p = st_point(c(1/3,1/6))
 st_sfc(p, precision = 1000)
@@ -34,7 +33,9 @@ attr(d1, "sf_col") = "geom"
 st_geometry(d1) = d$geom
 
 d$geometry = d$geom # second geometry list-column
-expect_warning(st_geometry(d) <- d$geom)
+if (require(testthat, quietly = TRUE)) {
+ expect_warning(st_geometry(d) <- d$geom)
+}
 d
 
 x = st_sfc(list(st_point(0:1), st_point(0:1)), crs = 4326)
@@ -62,7 +63,6 @@ st_cast(x, "POINT")
 sf = st_sf(a = 3:2, geom = x)
 st_cast(sf, "POINT")
 
-suppressPackageStartupMessages( library(dplyr) )
 
 x %>% st_cast("POINT")
 
@@ -126,7 +126,6 @@ format(st_bbox(nc))
 st_agr("constant")
 st_agr()
 x <- st_sf(a = 1:2, b = 3:4, geom = x, agr = c("constant", "aggregate"))
-suppressPackageStartupMessages(library(dplyr))
 y <- x %>% st_set_agr("constant")
 y
 
@@ -155,6 +154,7 @@ b = data.frame(x = c("a", "b", "c"), b = c(2,5,6))
 merge(a, b)
 merge(a, b, all = TRUE)
 
+if (require(dplyr, quietly = TRUE)) {
 # joins:
 inner_join(a, b)
 left_join(a, b)
@@ -163,6 +163,7 @@ full_join(a, b)
 semi_join(a, b)
 anti_join(a, b)
 left_join(a, data.frame(b, geometry = 1), by = "b")
+}
 
 # st_joins:
 a = st_sf(a = 1:3,
@@ -221,8 +222,10 @@ lengths(p_sample_exact)
 #plot(p_sample[[1]], add = TRUE)
 #plot(p_sample_exact[[1]], add = TRUE)
 
-#class(st_bind_cols(nc, as.data.frame(nc)[1:3]))
-class(dplyr::bind_cols(nc, as.data.frame(nc)[1:3]))
+if (require(dplyr, quietly = TRUE)) {
+ #class(st_bind_cols(nc, as.data.frame(nc)[1:3]))
+ print(class(dplyr::bind_cols(nc, as.data.frame(nc)[1:3])))
+}
 class(rbind(nc, nc))
 class(cbind(nc, nc))
 
@@ -238,13 +241,13 @@ plot(st_jitter(st_geometry(nc), factor = .01), add = TRUE, col = '#ff8888')
 st_jitter(st_sfc(st_point(0:1)), amount = .1)
 
 # st_bbox:
-library(sp)
+if (require(sp, quietly = TRUE) && require(raster, quietly = TRUE)) {
 demo(meuse, ask = FALSE, echo = FALSE)
 suppressWarnings(st_bbox(meuse))
 crs = suppressWarnings(st_crs(meuse))
-library(raster)
 suppressWarnings(st_bbox(raster(meuse.grid)))
 st_bbox(extent(raster()))
+}
 
 # st_to_s2
 if (FALSE) { # stops working with GDAL 2.3.0 / PROJ 5.0.1:
diff --git a/tests/sfc.Rout.save b/tests/sfc.Rout.save
index ca4f557aa..7cb16e5bf 100644
--- a/tests/sfc.Rout.save
+++ b/tests/sfc.Rout.save
@@ -1,6 +1,6 @@
 
-R version 4.1.2 (2021-11-01) -- "Bird Hippie"
-Copyright (C) 2021 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -16,7 +16,6 @@ Type 'demo()' for some demos, 'help()' for on-line help, or
 Type 'q()' to quit R.
 
 > suppressPackageStartupMessages(library(sf))
-> library(testthat)
 > 
 > p = st_point(c(1/3,1/6))
 > st_sfc(p, precision = 1000)
@@ -154,7 +153,9 @@ CRS:           NA
 > st_geometry(d1) = d$geom
 > 
 > d$geometry = d$geom # second geometry list-column
-> expect_warning(st_geometry(d) <- d$geom)
+> if (require(testthat, quietly = TRUE)) {
++  expect_warning(st_geometry(d) <- d$geom)
++ }
 > d
 Simple feature collection with 2 features and 1 field
 Active geometry column: geom
@@ -232,7 +233,6 @@ CRS:           NA
 Warning message:
 In st_cast.MULTIPOINT(X[[i]], ...) : point from first coordinate only
 > 
-> suppressPackageStartupMessages( library(dplyr) )
 > 
 > x %>% st_cast("POINT")
 Geometry set for 2 features 
@@ -347,7 +347,7 @@ use `st_zm(...)` to coerce to XY dimensions
 > 
 > sf_extSoftVersion()[1:3]
     GEOS     GDAL   proj.4 
-"3.10.1"  "3.4.0"  "8.2.0" 
+"3.10.2"  "3.4.3"  "8.2.0" 
 > 
 > # Ops.sfc:
 > ls = st_sfc(st_linestring(rbind(c(0,0),c(0,1))))
@@ -448,7 +448,6 @@ Levels: constant aggregate identity
 [1] <NA>
 Levels: constant aggregate identity
 > x <- st_sf(a = 1:2, b = 3:4, geom = x, agr = c("constant", "aggregate"))
-> suppressPackageStartupMessages(library(dplyr))
 > y <- x %>% st_set_agr("constant")
 > y
 Simple feature collection with 2 features and 2 fields
@@ -550,71 +549,37 @@ CRS:           NA
 3 6  2    c              POINT (1 1)
 4 7  3 <NA>              POINT (2 2)
 > 
-> # joins:
-> inner_join(a, b)
+> if (require(dplyr, quietly = TRUE)) {
++ # joins:
++ inner_join(a, b)
++ left_join(a, b)
++ right_join(a, b)
++ full_join(a, b)
++ semi_join(a, b)
++ anti_join(a, b)
++ left_join(a, data.frame(b, geometry = 1), by = "b")
++ }
+
+Attaching package: 'dplyr'
+
+The following object is masked from 'package:testthat':
+
+    matches
+
+The following objects are masked from 'package:stats':
+
+    filter, lag
+
+The following objects are masked from 'package:base':
+
+    intersect, setdiff, setequal, union
+
 Joining, by = "b"
-Simple feature collection with 2 features and 3 fields
-Geometry type: POINT
-Dimension:     XY
-Bounding box:  xmin: 0 ymin: 0 xmax: 1 ymax: 1
-CRS:           NA
-  a b x    geometry
-1 1 5 b POINT (0 0)
-2 2 6 c POINT (1 1)
-> left_join(a, b)
 Joining, by = "b"
-Simple feature collection with 3 features and 3 fields
-Geometry type: POINT
-Dimension:     XY
-Bounding box:  xmin: 0 ymin: 0 xmax: 2 ymax: 2
-CRS:           NA
-  a b    x    geometry
-1 1 5    b POINT (0 0)
-2 2 6    c POINT (1 1)
-3 3 7 <NA> POINT (2 2)
-> right_join(a, b)
 Joining, by = "b"
-Simple feature collection with 3 features and 3 fields (with 1 geometry empty)
-Geometry type: POINT
-Dimension:     XY
-Bounding box:  xmin: 0 ymin: 0 xmax: 1 ymax: 1
-CRS:           NA
-   a b x    geometry
-1  1 5 b POINT (0 0)
-2  2 6 c POINT (1 1)
-3 NA 2 a POINT EMPTY
-> full_join(a, b)
 Joining, by = "b"
-Simple feature collection with 4 features and 3 fields (with 1 geometry empty)
-Geometry type: POINT
-Dimension:     XY
-Bounding box:  xmin: 0 ymin: 0 xmax: 2 ymax: 2
-CRS:           NA
-   a b    x    geometry
-1  1 5    b POINT (0 0)
-2  2 6    c POINT (1 1)
-3  3 7 <NA> POINT (2 2)
-4 NA 2    a POINT EMPTY
-> semi_join(a, b)
 Joining, by = "b"
-Simple feature collection with 2 features and 2 fields
-Geometry type: POINT
-Dimension:     XY
-Bounding box:  xmin: 0 ymin: 0 xmax: 1 ymax: 1
-CRS:           NA
-  a b    geometry
-1 1 5 POINT (0 0)
-2 2 6 POINT (1 1)
-> anti_join(a, b)
 Joining, by = "b"
-Simple feature collection with 1 feature and 2 fields
-Geometry type: POINT
-Dimension:     XY
-Bounding box:  xmin: 2 ymin: 2 xmax: 2 ymax: 2
-CRS:           NA
-  a b    geometry
-1 3 7 POINT (2 2)
-> left_join(a, data.frame(b, geometry = 1), by = "b")
 Simple feature collection with 3 features and 4 fields
 Geometry type: POINT
 Dimension:     XY
@@ -809,15 +774,17 @@ MULTIPOINT EMPTY
 > #plot(p_sample[[1]], add = TRUE)
 > #plot(p_sample_exact[[1]], add = TRUE)
 > 
-> #class(st_bind_cols(nc, as.data.frame(nc)[1:3]))
-> class(dplyr::bind_cols(nc, as.data.frame(nc)[1:3]))
+> if (require(dplyr, quietly = TRUE)) {
++  #class(st_bind_cols(nc, as.data.frame(nc)[1:3]))
++  print(class(dplyr::bind_cols(nc, as.data.frame(nc)[1:3])))
++ }
 New names:
-* AREA -> AREA...1
-* PERIMETER -> PERIMETER...2
-* CNTY_ -> CNTY_...3
-* AREA -> AREA...16
-* PERIMETER -> PERIMETER...17
-* ...
+• `AREA` -> `AREA...1`
+• `PERIMETER` -> `PERIMETER...2`
+• `CNTY_` -> `CNTY_...3`
+• `AREA` -> `AREA...16`
+• `PERIMETER` -> `PERIMETER...17`
+• `CNTY_` -> `CNTY_...18`
 [1] "sf"         "data.frame"
 > class(rbind(nc, nc))
 [1] "sf"         "data.frame"
@@ -852,13 +819,13 @@ CRS:           NA
 POINT (-0.0500922 0.992953)
 > 
 > # st_bbox:
-> library(sp)
-> demo(meuse, ask = FALSE, echo = FALSE)
-> suppressWarnings(st_bbox(meuse))
-  xmin   ymin   xmax   ymax 
-178605 329714 181390 333611 
-> crs = suppressWarnings(st_crs(meuse))
-> library(raster)
+> if (require(sp, quietly = TRUE) && require(raster, quietly = TRUE)) {
++ demo(meuse, ask = FALSE, echo = FALSE)
++ suppressWarnings(st_bbox(meuse))
++ crs = suppressWarnings(st_crs(meuse))
++ suppressWarnings(st_bbox(raster(meuse.grid)))
++ st_bbox(extent(raster()))
++ }
 
 Attaching package: 'raster'
 
@@ -866,12 +833,12 @@ The following object is masked from 'package:dplyr':
 
     select
 
-> suppressWarnings(st_bbox(raster(meuse.grid)))
-  xmin   ymin   xmax   ymax 
-178440 329600 181560 333760 
-> st_bbox(extent(raster()))
 xmin ymin xmax ymax 
 -180  -90  180   90 
+Warning messages:
+1: no function found corresponding to methods exports from 'raster' for: 'area' 
+2: In showSRID(uprojargs, format = "PROJ", multiline = "NO", prefer_proj = prefer_proj) :
+  Discarded datum Amersfoort in Proj4 definition
 > 
 > # st_to_s2
 > if (FALSE) { # stops working with GDAL 2.3.0 / PROJ 5.0.1:
@@ -1123,4 +1090,4 @@ CRS:           NA
 > 
 > proc.time()
    user  system elapsed 
-  8.386   0.119   8.498 
+ 10.773   0.216  10.985 
diff --git a/tests/spatstat.R b/tests/spatstat.R
index 273530c10..8b17aa4e4 100644
--- a/tests/spatstat.R
+++ b/tests/spatstat.R
@@ -1,5 +1,5 @@
-suppressPackageStartupMessages(library(spatstat.random))
 suppressPackageStartupMessages(library(sf))
+if (require(spatstat.random, quietly = TRUE)) {
 
 data(chicago)
 st_as_sf(chicago)
@@ -107,3 +107,4 @@ as.psp(sf, marks = 5:1)
 (x = st_as_sf(as.psp(sf)))
 (y = st_as_sfc(as.psp(sf)))
 all.equal(st_geometry(x), y)
+}
diff --git a/tests/spatstat.Rout.save b/tests/spatstat.Rout.save
index c82e07252..2859786c4 100644
--- a/tests/spatstat.Rout.save
+++ b/tests/spatstat.Rout.save
@@ -1,6 +1,6 @@
 
-R version 4.1.2 (2021-11-01) -- "Bird Hippie"
-Copyright (C) 2021 The R Foundation for Statistical Computing
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
+Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
@@ -15,77 +15,118 @@ Type 'demo()' for some demos, 'help()' for on-line help, or
 'help.start()' for an HTML browser interface to help.
 Type 'q()' to quit R.
 
-> suppressPackageStartupMessages(library(spatstat.random))
 > suppressPackageStartupMessages(library(sf))
-> 
-> data(chicago)
-> st_as_sf(chicago)
-Simple feature collection with 620 features and 4 fields
-Geometry type: GEOMETRY
-Dimension:     XY
-Bounding box:  xmin: 0.3893523 ymin: 153.1034 xmax: 1281.986 ymax: 1276.56
-CRS:           NA
-First 10 features:
-     label seg tp marks                           geom
-1   window  NA NA  <NA> POLYGON ((0.3893523 153.103...
-2  segment  NA NA  <NA> LINESTRING (0.3894739 1253....
-3  segment  NA NA  <NA> LINESTRING (109.683 1251.77...
-4  segment  NA NA  <NA> LINESTRING (109.683 1251.77...
-5  segment  NA NA  <NA> LINESTRING (198.1486 1276.5...
-6  segment  NA NA  <NA> LINESTRING (197.9988 1251.1...
-7  segment  NA NA  <NA> LINESTRING (290.4787 1276.5...
-8  segment  NA NA  <NA> LINESTRING (288.9907 1250.5...
-9  segment  NA NA  <NA> LINESTRING (380.1326 1276.5...
-10 segment  NA NA  <NA> LINESTRING (379.9827 1249.8...
-> # ppp:
-> g = gorillas
-> st_as_sf(g)
-Simple feature collection with 648 features and 4 fields
-Geometry type: GEOMETRY
-Dimension:     XY
-Bounding box:  xmin: 580457.9 ymin: 674172.8 xmax: 585934 ymax: 678739.2
-CRS:           NA
-First 10 features:
-   group season       date  label                           geom
-NA  <NA>   <NA>       <NA> window POLYGON ((584712 674237.1, ...
-1  major    dry 2006-01-06  point      POINT (582518.4 676886.2)
-2  major    dry 2006-01-10  point        POINT (581823 677422.7)
-3  major    dry 2006-01-15  point        POINT (582131 676937.9)
-4  major    dry 2006-01-24  point        POINT (582111.9 677420)
-5  minor    dry 2006-01-27  point      POINT (582585.1 677509.7)
-6  major    dry 2006-01-28  point      POINT (582302.3 677521.6)
-7  major    dry 2006-02-01  point      POINT (583167.2 676730.5)
-8  major    dry 2006-02-03  point      POINT (583584.5 677207.1)
-9  major    dry 2006-02-13  point      POINT (583117.8 676850.3)
-> marks(g) = NULL
-> st_as_sf(g)
-Simple feature collection with 648 features and 1 field
-Geometry type: GEOMETRY
-Dimension:     XY
-Bounding box:  xmin: 580457.9 ymin: 674172.8 xmax: 585934 ymax: 678739.2
-CRS:           NA
-First 10 features:
-    label                           geom
-1  window POLYGON ((584712 674237.1, ...
-2   point      POINT (582518.4 676886.2)
-3   point        POINT (581823 677422.7)
-4   point        POINT (582131 676937.9)
-5   point        POINT (582111.9 677420)
-6   point      POINT (582585.1 677509.7)
-7   point      POINT (582302.3 677521.6)
-8   point      POINT (583167.2 676730.5)
-9   point      POINT (583584.5 677207.1)
-10  point      POINT (583117.8 676850.3)
-> 
-> # multipolygon: https://github.com/r-spatial/sf/issues/1161
-> window = read_sf(system.file("shape/nc.shp", package = "sf")) %>%
+> if (require(spatstat.random, quietly = TRUE)) {
++ 
++ data(chicago)
++ st_as_sf(chicago)
++ # ppp:
++ g = gorillas
++ st_as_sf(g)
++ marks(g) = NULL
++ st_as_sf(g)
++ 
++ # multipolygon: https://github.com/r-spatial/sf/issues/1161
++ window = read_sf(system.file("shape/nc.shp", package = "sf")) %>%
 +   st_transform(32119)
-> 
-> win = spatstat.geom::as.owin(window)
-> 
-> set.seed(1331)
-> pp2a = runifpoint(n = 50, win = win)
-> print(st_as_sf(pp2a))
++ 
++ win = spatstat.geom::as.owin(window)
++ 
++ set.seed(1331)
++ pp2a = runifpoint(n = 50, win = win)
++ print(st_as_sf(pp2a))
++ 
++ # st_sample going the spatstat way
++ x <- sf::st_sfc(sf::st_polygon(list(rbind(c(0, 0), c(10, 0), c(10, 10), c(0, 0)))))
++ try(pts <- st_sample(x, type = "thomas"))
++ try(pts <- st_sample(x, kappa = 1, mu = 10, type = "Thomas"))
++ # points expected
++ set.seed(1331)
++ pts <- st_sample(x, kappa = 1, mu = 10, scale = 0.1, type = "Thomas")
++ #plot(x)
++ #plot(pts, add = TRUE)
++ pts
++ 
++ # see https://github.com/r-spatial/sf/issues/1233
++ # png("/tmp/spa%03d.png")
++ 
++ p1 = st_point(0:1)
++ p2 = st_point(1:2)
++ p3 = st_point(c(-1,2))
++ p = st_sfc(p1, p2, p3)
++ as.ppp(p)
++ try(as.ppp(st_set_crs(p, 4326)))
++ 
++ sf = st_sf(geom = p)
++ try(as.ppp(sf))
++ sf = st_sf(a = 1:3, geom = p)
++ as.ppp(sf)
++ sf = st_sf(a = 1:3, b=3:1, geom = p)
++ as.ppp(sf) # warns
++ 
++ w = st_as_sfc(st_bbox(st_sfc(p1, p2)))
++ sf = st_sf(a = 1:3, geom = p)
++ (p0 = rbind(st_sf(a = 0, geom = w), sf))
++ try(as.ppp(p0)) # errors: one point outside window
++ 
++ w = st_as_sfc(st_bbox(p))
++ sf = st_sf(a = 1:3, geom = p)
++ (p0 = rbind(st_sf(a = 0, geom = w), sf))
++ as.ppp(p0)
++ 
++ # as.owin.sf, as.owin.sfc_*
++ nc = st_read(system.file("gpkg/nc.gpkg", package="sf"), check_ring_dir = TRUE, quiet = TRUE)
++ try(as.owin(nc)) # should be projected
++ nc = st_transform(nc, 32119)
++ plot(as.owin(nc), col = 'grey')
++ plot(as.owin(st_geometry(nc)), col = 'grey')
++ 
++ sq = rbind(c(-1,-1), c(1, -1), c(1,1), c(-1,1), c(-1,-1))
++ pol = st_polygon(list(0.5 * sq, sq[5:1,] * 0.45)) # w hole
++ plot(as.owin(pol), col = 'grey')
++ plot(as.owin(st_sfc(pol)), col = 'grey')
++ mpol = st_multipolygon(list(
++ 	list(sq, sq[5:1,] * 0.9),
++ 	list(sq * 2, sq[5:1,] * 1.8)))
++ plot(as.owin(mpol), col = 'grey')
++ plot(as.owin(st_sfc(mpol)), col = 'grey')
++ plot(as.owin(st_sfc(pol, mpol)), col = 'grey')
++ plot(as.owin(st_sf(a=1:2, st_sfc(pol, mpol))), col = 'grey')
++ (o = as.owin(st_sf(a=1:2, st_sfc(pol, mpol))))
++ st_as_sfc(o)
++ 
++ plot(st_as_sfc(o), col = 'blue', main = 'st_as_sfc(o)')
++ plot(st_as_sf(o), col = 'blue', main = 'st_as_sf(o)')
++ 
++ data(japanesepines)
++ st_as_sf(japanesepines) # warns about multiplier
++ jp = rescale(japanesepines)
++ st_as_sf(jp) # No warning
++ 
++ data(nztrees)
++ qNZ <- quadratcount(nztrees, nx=4, ny=3)
++ ts = as.tess(qNZ)
++ plot(st_as_sfc(ts))
++ 
++ ls = st_linestring(rbind(c(0,0), c(1,1), c(2,0)))
++ plot(as.psp(ls))
++ mls = st_multilinestring(list(rbind(c(0,0), c(1,1), c(2,0)), rbind(c(3,3), c(4,2))))
++ plot(as.psp(mls))
++ 
++ plot(as.psp(st_sfc(ls)))
++ plot(as.psp(st_sfc(mls)))
++ plot(as.psp(st_sfc(ls, mls)))
++ 
++ sf = st_sf(st_cast(st_sfc(ls, mls), "MULTILINESTRING"), marks = 1:2, foo = 2:1)
++ as.psp(sf) # picks marks itself
++ as.psp(sf, marks = 5:1)
++ 
++ (x = st_as_sf(as.psp(sf)))
++ (y = st_as_sfc(as.psp(sf)))
++ all.equal(st_geometry(x), y)
++ }
+spatstat.geom 2.4-0
+spatstat.random 2.2-0
 Simple feature collection with 51 features and 1 field
 Geometry type: GEOMETRY
 Dimension:     XY
@@ -103,238 +144,26 @@ First 10 features:
 8   point        POINT (843281.2 287246)
 9   point        POINT (648479.4 235471)
 10  point      POINT (852595.8 267252.6)
-> 
-> # st_sample going the spatstat way
-> x <- sf::st_sfc(sf::st_polygon(list(rbind(c(0, 0), c(10, 0), c(10, 10), c(0, 0)))))
-> try(pts <- st_sample(x, type = "thomas"))
 Error in st_poly_sample(x, size = size, ..., type = type, by_polygon = by_polygon) : 
   rthomas is not an exported function from spatstat.random.
-> try(pts <- st_sample(x, kappa = 1, mu = 10, type = "Thomas"))
 Error in st_poly_sample(x, size = size, ..., type = type, by_polygon = by_polygon) : 
   The spatstat function rThomas did not return a valid result. Consult the help file.
 Error message from spatstat:
 Error : 'scale' should be a single number
 
-> # points expected
-> set.seed(1331)
-> pts <- st_sample(x, kappa = 1, mu = 10, scale = 0.1, type = "Thomas")
-> #plot(x)
-> #plot(pts, add = TRUE)
-> pts
-Simple feature collection with 597 features and 1 field
-Geometry type: POINT
-Dimension:     XY
-Bounding box:  xmin: 1.213108 ymin: 0.02200954 xmax: 9.994943 ymax: 8.82534
-CRS:           NA
-First 10 features:
-   label                      geom
-2  point POINT (9.076646 8.661168)
-3  point POINT (9.347089 8.800523)
-4  point  POINT (9.207624 8.82534)
-5  point POINT (9.403886 8.666932)
-6  point  POINT (9.437082 8.63911)
-7  point POINT (9.254756 8.573871)
-8  point  POINT (9.29172 8.678031)
-9  point POINT (9.735812 1.621866)
-10 point POINT (9.853825 1.616409)
-11 point POINT (9.665138 1.593111)
-> 
-> # see https://github.com/r-spatial/sf/issues/1233
-> # png("/tmp/spa%03d.png")
-> 
-> p1 = st_point(0:1)
-> p2 = st_point(1:2)
-> p3 = st_point(c(-1,2))
-> p = st_sfc(p1, p2, p3)
-> as.ppp(p)
-Planar point pattern: 3 points
-window: rectangle = [-1, 1] x [1, 2] units
-> try(as.ppp(st_set_crs(p, 4326)))
 Error : Only projected coordinates may be converted to spatstat class objects
-> 
-> sf = st_sf(geom = p)
-> try(as.ppp(sf))
-Planar point pattern: 3 points
-window: rectangle = [-1, 1] x [1, 2] units
-> sf = st_sf(a = 1:3, geom = p)
-> as.ppp(sf)
-Marked planar point pattern: 3 points
-marks are numeric, of storage type  'integer'
-window: rectangle = [-1, 1] x [1, 2] units
-> sf = st_sf(a = 1:3, b=3:1, geom = p)
-> as.ppp(sf) # warns
-Marked planar point pattern: 3 points
-marks are numeric, of storage type  'integer'
-window: rectangle = [-1, 1] x [1, 2] units
-Warning message:
-In as.ppp.sf(sf) : only first attribute column is used for marks
-> 
-> w = st_as_sfc(st_bbox(st_sfc(p1, p2)))
-> sf = st_sf(a = 1:3, geom = p)
-> (p0 = rbind(st_sf(a = 0, geom = w), sf))
-Simple feature collection with 4 features and 1 field
-Geometry type: GEOMETRY
-Dimension:     XY
-Bounding box:  xmin: -1 ymin: 1 xmax: 1 ymax: 2
-CRS:           NA
-  a                           geom
-1 0 POLYGON ((0 1, 1 1, 1 2, 0 ...
-2 1                    POINT (0 1)
-3 2                    POINT (1 2)
-4 3                   POINT (-1 2)
-> try(as.ppp(p0)) # errors: one point outside window
 Error in `marks<-.ppp`(`*tmp*`, value = value) : 
   number of rows of data frame != number of points
-In addition: Warning message:
-1 point was rejected as lying outside the specified window 
-> 
-> w = st_as_sfc(st_bbox(p))
-> sf = st_sf(a = 1:3, geom = p)
-> (p0 = rbind(st_sf(a = 0, geom = w), sf))
-Simple feature collection with 4 features and 1 field
-Geometry type: GEOMETRY
-Dimension:     XY
-Bounding box:  xmin: -1 ymin: 1 xmax: 1 ymax: 2
-CRS:           NA
-  a                           geom
-1 0 POLYGON ((-1 1, 1 1, 1 2, -...
-2 1                    POINT (0 1)
-3 2                    POINT (1 2)
-4 3                   POINT (-1 2)
-> as.ppp(p0)
-Marked planar point pattern: 3 points
-marks are numeric, of storage type  'double'
-window: polygonal boundary
-enclosing rectangle: [-1, 1] x [1, 2] units
-> 
-> # as.owin.sf, as.owin.sfc_*
-> nc = st_read(system.file("gpkg/nc.gpkg", package="sf"), check_ring_dir = TRUE, quiet = TRUE)
-> try(as.owin(nc)) # should be projected
+In addition: Warning messages:
+1: In as.ppp.sf(sf) : only first attribute column is used for marks
+2: 1 point was rejected as lying outside the specified window 
 Error in as.owin.sfc_MULTIPOLYGON(st_cast(W, "MULTIPOLYGON"), ...) : 
   Only projected coordinates may be converted to spatstat class objects
-> nc = st_transform(nc, 32119)
-> plot(as.owin(nc), col = 'grey')
-> plot(as.owin(st_geometry(nc)), col = 'grey')
-> 
-> sq = rbind(c(-1,-1), c(1, -1), c(1,1), c(-1,1), c(-1,-1))
-> pol = st_polygon(list(0.5 * sq, sq[5:1,] * 0.45)) # w hole
-> plot(as.owin(pol), col = 'grey')
-> plot(as.owin(st_sfc(pol)), col = 'grey')
-> mpol = st_multipolygon(list(
-+ 	list(sq, sq[5:1,] * 0.9),
-+ 	list(sq * 2, sq[5:1,] * 1.8)))
-> plot(as.owin(mpol), col = 'grey')
-> plot(as.owin(st_sfc(mpol)), col = 'grey')
-> plot(as.owin(st_sfc(pol, mpol)), col = 'grey')
-> plot(as.owin(st_sf(a=1:2, st_sfc(pol, mpol))), col = 'grey')
-> (o = as.owin(st_sf(a=1:2, st_sfc(pol, mpol))))
-window: polygonal boundary
-enclosing rectangle: [-2, 2] x [-2, 2] units
-> st_as_sfc(o)
-Geometry set for 1 feature 
-Geometry type: MULTIPOLYGON
-Dimension:     XY
-Bounding box:  xmin: -2 ymin: -2 xmax: 2 ymax: 2
-CRS:           NA
-MULTIPOLYGON (((2 2, -2 2, -2 -2, 2 -2, 2 2), (...
-> 
-> plot(st_as_sfc(o), col = 'blue', main = 'st_as_sfc(o)')
-> plot(st_as_sf(o), col = 'blue', main = 'st_as_sf(o)')
-> 
-> data(japanesepines)
-> st_as_sf(japanesepines) # warns about multiplier
-Simple feature collection with 66 features and 1 field
-Geometry type: GEOMETRY
-Dimension:     XY
-Bounding box:  xmin: 0 ymin: 0 xmax: 1 ymax: 1
-CRS:           NA
-First 10 features:
-    label                           geom
-1  window POLYGON ((0 0, 1 0, 1 1, 0 ...
-2   point              POINT (0.09 0.09)
-3   point              POINT (0.29 0.02)
-4   point              POINT (0.38 0.03)
-5   point              POINT (0.39 0.18)
-6   point              POINT (0.48 0.03)
-7   point              POINT (0.59 0.02)
-8   point              POINT (0.65 0.16)
-9   point              POINT (0.67 0.13)
-10  point              POINT (0.73 0.13)
+[1] TRUE
 Warning message:
 In st_as_sfc.owin(spatstat.geom::as.owin(x)) :
   The spatstat object has an measurement unit multiplier != 1. Consider rescaling before converting.
-> jp = rescale(japanesepines)
-> st_as_sf(jp) # No warning
-Simple feature collection with 66 features and 1 field
-Geometry type: GEOMETRY
-Dimension:     XY
-Bounding box:  xmin: 0 ymin: 0 xmax: 5.7 ymax: 5.7
-CRS:           NA
-First 10 features:
-    label                           geom
-1  window POLYGON ((0 0, 5.7 0, 5.7 5...
-2   point            POINT (0.513 0.513)
-3   point            POINT (1.653 0.114)
-4   point            POINT (2.166 0.171)
-5   point            POINT (2.223 1.026)
-6   point            POINT (2.736 0.171)
-7   point            POINT (3.363 0.114)
-8   point            POINT (3.705 0.912)
-9   point            POINT (3.819 0.741)
-10  point            POINT (4.161 0.741)
-> 
-> data(nztrees)
-> qNZ <- quadratcount(nztrees, nx=4, ny=3)
-> ts = as.tess(qNZ)
-> plot(st_as_sfc(ts))
-> 
-> ls = st_linestring(rbind(c(0,0), c(1,1), c(2,0)))
-> plot(as.psp(ls))
-> mls = st_multilinestring(list(rbind(c(0,0), c(1,1), c(2,0)), rbind(c(3,3), c(4,2))))
-> plot(as.psp(mls))
-> 
-> plot(as.psp(st_sfc(ls)))
-> plot(as.psp(st_sfc(mls)))
-> plot(as.psp(st_sfc(ls, mls)))
-> 
-> sf = st_sf(st_cast(st_sfc(ls, mls), "MULTILINESTRING"), marks = 1:2, foo = 2:1)
-> as.psp(sf) # picks marks itself
-marked planar line segment pattern: 5 line segments
-Mark variables:  marks, foo
-window: rectangle = [0, 4] x [0, 3] units
-> as.psp(sf, marks = 5:1)
-marked planar line segment pattern: 5 line segments
-marks are numeric, of type 'integer'
-window: rectangle = [0, 4] x [0, 3] units
-> 
-> (x = st_as_sf(as.psp(sf)))
-Simple feature collection with 6 features and 3 fields
-Geometry type: GEOMETRY
-Dimension:     XY
-Bounding box:  xmin: 0 ymin: 0 xmax: 4 ymax: 3
-CRS:           NA
-    marks foo   label                           geom
-NA     NA  NA  window POLYGON ((0 0, 4 0, 4 3, 0 ...
-1       1   2 segment          LINESTRING (0 0, 1 1)
-1.1     1   2 segment          LINESTRING (1 1, 2 0)
-2       2   1 segment          LINESTRING (0 0, 1 1)
-2.1     2   1 segment          LINESTRING (1 1, 2 0)
-2.2     2   1 segment          LINESTRING (3 3, 4 2)
-> (y = st_as_sfc(as.psp(sf)))
-Geometry set for 6 features 
-Geometry type: GEOMETRY
-Dimension:     XY
-Bounding box:  xmin: 0 ymin: 0 xmax: 4 ymax: 3
-CRS:           NA
-First 5 geometries:
-POLYGON ((0 0, 4 0, 4 3, 0 3, 0 0))
-LINESTRING (0 0, 1 1)
-LINESTRING (1 1, 2 0)
-LINESTRING (0 0, 1 1)
-LINESTRING (1 1, 2 0)
-> all.equal(st_geometry(x), y)
-[1] TRUE
 > 
 > proc.time()
    user  system elapsed 
-  2.019   0.071   2.083 
+  2.801   0.108   2.903 
diff --git a/tests/stars.R b/tests/stars.R
index 2ec9e7237..0895b0635 100644
--- a/tests/stars.R
+++ b/tests/stars.R
@@ -8,7 +8,7 @@ try(gdal_metadata(tif, "wrongDomain"))
 gdal_metadata(tif, c("IMAGE_STRUCTURE"))
 try(length(gdal_metadata(tif, c("DERIVED_SUBDATASETS")))) # fails on Fedora 26
 
-if (require(stars)) {
+if (require(stars, quietly = TRUE)) {
   tif = system.file("tif/geomatrix.tif", package = "sf")
   r = read_stars(tif)
   d = (st_dimensions(r))
diff --git a/tests/stars.Rout.save b/tests/stars.Rout.save
index 0a71f1a2d..8a89b98d3 100644
--- a/tests/stars.Rout.save
+++ b/tests/stars.Rout.save
@@ -1,5 +1,5 @@
 
-R version 4.1.3 (2022-03-10) -- "One Push-Up"
+R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
 Copyright (C) 2022 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu (64-bit)
 
@@ -35,7 +35,7 @@ attr(,"class")
 > try(length(gdal_metadata(tif, c("DERIVED_SUBDATASETS")))) # fails on Fedora 26
 [1] 2
 > 
-> if (require(stars)) {
+> if (require(stars, quietly = TRUE)) {
 +   tif = system.file("tif/geomatrix.tif", package = "sf")
 +   r = read_stars(tif)
 +   d = (st_dimensions(r))
@@ -91,8 +91,6 @@ attr(,"class")
 +     }
 +   }
 + }
-Loading required package: stars
-Loading required package: abind
 [1] TRUE
 [1] TRUE
 Geometry set for 20 features 
@@ -246,6 +244,9 @@ First 10 features:
 
 
 
+Warning message:
+In read_stars(lc, RAT = "Land Cover Class") :
+  categorical data values starting at 0 are shifted with one to start at 1
 > 
 > r = gdal_read(tif)
 > gt = c(0,1,0,0,0,1)
@@ -263,4 +264,4 @@ First 10 features:
 > 
 > proc.time()
    user  system elapsed 
-  1.954   0.081   2.036 
+  2.229   0.122   2.345 
diff --git a/tests/testthat.R b/tests/testthat.R
index f29a5c9f6..246bdc8bc 100644
--- a/tests/testthat.R
+++ b/tests/testthat.R
@@ -1,4 +1,4 @@
-library(testthat)
-suppressPackageStartupMessages(library(sf))
-
-test_check("sf")
+if (require(testthat, quietly = TRUE)) {
+ suppressPackageStartupMessages(library(sf))
+ test_check("sf")
+}
diff --git a/tests/testthat/test_crs.R b/tests/testthat/test_crs.R
index abab96b4c..39e8ac332 100644
--- a/tests/testthat/test_crs.R
+++ b/tests/testthat/test_crs.R
@@ -89,6 +89,7 @@ test_that("old-style crs are repaired", {
 })
 
 test_that("sp-style CRS objects are accepted", {
+  skip_if_not_installed("sp")
   library(sp)
   x = CRS("+proj=longlat")
   x_crs = st_crs("+proj=longlat")
@@ -105,6 +106,7 @@ test_that("print.crs works", {
 })
 
 test_that("crs.Raster works", {
+  skip_if_not_installed("raster")
   library(raster)
   r = raster()
   x = st_crs(r)
diff --git a/tests/testthat/test_sf.R b/tests/testthat/test_sf.R
index 04b925da4..897794741 100644
--- a/tests/testthat/test_sf.R
+++ b/tests/testthat/test_sf.R
@@ -20,6 +20,7 @@ test_that("we can subset sf objects", {
 })
 
 test_that("we can create points sf from data.frame", {
+  skip_if_not_installed("sp")
   data(meuse, package = "sp") # load data.frame from sp
   meuse_sf = st_as_sf(meuse, coords = c("x", "y"), crs = 28992)
   meuse_sf[1:5,]
@@ -63,6 +64,7 @@ test_that("rbind/cbind work", {
 })
 
 test_that("st_as_sf bulk points work", {
+  skip_if_not_installed("sp")
   data(meuse, package = "sp") # load data.frame from sp
   x <- meuse
   meuse_sf = st_as_sf(x, coords = c("x", "y"), crs = 28992)
@@ -82,6 +84,7 @@ test_that("st_as_sf bulk points work", {
 })
 
 test_that("transform work", {
+  skip_if_not_installed("sp")
   data(meuse, package = "sp")
   x  = st_as_sf(meuse, coords = c("x", "y"), crs = 28992)
   x2 = transform(x, elev2 = elev^2, lead_zinc = lead/zinc)
diff --git a/tests/testthat/test_sp.R b/tests/testthat/test_sp.R
index 22412fe62..e77bbcd43 100644
--- a/tests/testthat/test_sp.R
+++ b/tests/testthat/test_sp.R
@@ -1,6 +1,7 @@
 context("sf: sp conversion tests")
 
 test_that("we can convert points & lines to and from sp objects", {
+  skip_if_not_installed("sp")
   pt1 = st_point(1:2)
   pt2 = st_point(3:4)
   s1 = st_sf(a = c("x", "y"), geom = st_sfc(pt1, pt2))
@@ -24,6 +25,7 @@ test_that("we can convert points & lines to and from sp objects", {
 })
 
 test_that("as() can convert GEOMETRY to Spatial (#131)", {
+  skip_if_not_installed("sp")
   single <- list(rbind(c(0,0), c(1,0), c(1, 1), c(0,1), c(0,0))) %>% st_polygon()
   multi <- list(single + 2, single + 4) %>% st_multipolygon()
 
@@ -52,6 +54,7 @@ test_that("as() can convert GEOMETRY to Spatial (#131)", {
 })
 
 test_that("as_Spatial can convert sf (#519)", {
+    skip_if_not_installed("sp")
 	h <- st_read(system.file("shape/nc.shp", package = "sf"), quiet = TRUE)
 
 	u <- as(h, "Spatial")
@@ -65,18 +68,21 @@ test_that("as_Spatial can convert sf (#519)", {
 })
 
 test_that("Can convert `XY` objects to sp", {
+    skip_if_not_installed("sp")
 	expect_is(as(st_point(1:2), "Spatial"), "SpatialPoints")
 	expect_error(as(st_point(1:3), "Spatial"))
 	expect_error(as(st_point(1:4), "Spatial"))
 })
 
 test_that("Can't convert `M` dimension to sp", {
+    skip_if_not_installed("sp")
 	skip_if_not(sf_extSoftVersion()[["GDAL"]] >= "2.1.0")
 	x <- read_sf(system.file("shape/storms_xyzm_feature.shp", package = "sf"), quiet = TRUE)
 	expect_error(as_Spatial(x), "not supported by sp")
 })
 
 test_that("conversion to sp breaks on empty geometries", {
+  skip_if_not_installed("sp")
   mysfc <- st_sfc(list(
     st_polygon(list(matrix(c(1,3,2,1,0,0,1,0), 4, 2))),
     st_polygon()  # empty polygon
diff --git a/tests/testthat/test_tidy.R b/tests/testthat/test_tidy.R
index 49da9b623..4f9c7a832 100644
--- a/tests/testthat/test_tidy.R
+++ b/tests/testthat/test_tidy.R
@@ -1,14 +1,16 @@
 context("sf: dplyr syntax")
 
-suppressMessages(library(dplyr))
+suppressMessages(require(dplyr, quietly = TRUE))
 nc <- st_read(system.file("shape/nc.shp", package="sf"), quiet = TRUE)
 
 test_that("select works", {
+  skip_if_not_installed("dplyr")
   expect_true(nc %>% select_("AREA", attr(., "sf_column"))  %>% inherits("sf"))
   expect_true(nc %>% select(AREA) %>% inherits("sf"))
 })
 
 test_that("filter to sfc works", {
+  skip_if_not_installed("dplyr")
   tbl = tibble(a = c("A", "B", "C"),
               geometry = st_sfc(st_point(c(1, 1)),
                                 st_point(),
@@ -20,14 +22,16 @@ test_that("filter to sfc works", {
                    d[1:2, ])
 })
 
-suppressMessages(library(tidyr))
+suppressMessages(require(tidyr, quietly = TRUE))
 test_that("separate and unite work", {
+  skip_if_not_installed("dplyr")
   expect_true(nc %>% separate(CNTY_ID, c("a", "b"), sep = 2) %>% inherits("sf"))
   expect_true(nc %>% separate(CNTY_ID, c("a", "b"), sep = 2) %>%
 	unite(CNTY_ID_NEW, c("a", "b"), sep = "") %>% inherits("sf"))
 })
 
 test_that("separate_rows work", {
+  skip_if_not_installed("dplyr")
   d <- st_as_sf(data.frame(
     x = seq_len(3),
     y = c("a", "d,e,f", "g,h"),
@@ -50,6 +54,7 @@ test_that("separate_rows work", {
 })
 
 test_that("group/ungroup works", {
+ skip_if_not_installed("dplyr")
  tbl = tibble(a = c(1,1,2,2), g = st_sfc(st_point(0:1), st_point(1:2), st_point(2:3), st_point(3:4)))
  d = st_sf(tbl)
  e <- d %>% group_by(a) %>% ungroup
@@ -57,6 +62,7 @@ test_that("group/ungroup works", {
 })
 
 test_that("sample_n etc work", {
+	skip_if_not_installed("dplyr")
 	tbl = tibble(a = c(1,1,2,2), g = st_sfc(st_point(0:1), st_point(1:2), st_point(2:3), st_point(3:4)))
 	d = st_sf(tbl)
 
@@ -72,6 +78,7 @@ test_that("sample_n etc work", {
 })
 
 test_that("nest() works", {
+	skip_if_not_installed("dplyr")
 	tbl = tibble(a = c(1,1,2,2), g = st_sfc(st_point(0:1), st_point(1:2), st_point(2:3), st_point(3:4)))
 	d = st_sf(tbl)
 	out = d %>% group_by(a) %>% nest()
@@ -99,6 +106,7 @@ test_that("st_intersection of tbl returns tbl", {
 })
 
 test_that("unnest works", {
+  skip_if_not_installed("dplyr")
   skip_if_not_installed("tidyr")
   skip_if_not(utils::packageVersion("tidyr") > "0.7.2")
   nc = read_sf(system.file("shape/nc.shp", package = "sf")) %>%
@@ -207,6 +215,7 @@ test_that("bind_cols() returns type of first input", {
 })
 
 test_that("can rename geometry column with `select()`", {
+	skip_if_not_installed("dplyr")
 	sf = st_sf(
 		x = 1,
 		geo = st_sfc(st_point(1:2)),
@@ -221,6 +230,7 @@ test_that("can rename geometry column with `select()`", {
 })
 
 test_that("can rename geometry column with `rename()` (#1431)", {
+	skip_if_not_installed("dplyr")
 	geo_pt = st_sfc(st_point())
 	geo_ln = st_sfc(st_linestring())
 	sf = st_sf(x = 1, geo2 = geo_pt, geo1 = geo_ln, sf_column_name = "geo1")
@@ -245,6 +255,7 @@ test_that("can rename geometry column with `rename()` (#1431)", {
 })
 
 test_that("`select()` and `transmute()` observe back-stickiness of geometry column (#1425)", {
+	skip_if_not_installed("dplyr")
 	sf = read_sf(system.file("shape/nc.shp", package = "sf"))
 	exp = sf[, c("NAME", "FIPS")]
 	expect_identical(dplyr::select(sf, NAME, FIPS), exp)
diff --git a/tests/testthat/test_wkb.R b/tests/testthat/test_wkb.R
index 8e35e72d7..d94d07fa7 100644
--- a/tests/testthat/test_wkb.R
+++ b/tests/testthat/test_wkb.R
@@ -51,6 +51,7 @@ test_that("Reading of truncated buffers results in a proper error", {
 })
 
 test_that("st_as_sfc() honors crs argument", {
+  skip_if_not_installed("blob")
   raw = st_as_binary(st_point(c(26e5, 12e5)))
 
   list = list(raw)
diff --git a/tests/testthat/test_write.R b/tests/testthat/test_write.R
index fc0bf8a5e..240250125 100644
--- a/tests/testthat/test_write.R
+++ b/tests/testthat/test_write.R
@@ -1,11 +1,14 @@
 context("sf: write")
 
+if (require(sp, quietly = TRUE)) {
 data(meuse, package = "sp")
 meuse <- st_as_sf(meuse, coords = c("x", "y"), crs = 28992)
 drvs <- st_drivers()$name[sapply(st_drivers()$name,
 	function(x) is_driver_can(x, operation = "write"))] %>% as.character()
+}
 
 test_that("sf can write to all writable formats", {
+	skip_if_not_installed("sp")
 	# write to all formats available
 	tf <- tempfile()
 	excluded_drivers = c("gps", # requires options
@@ -20,6 +23,7 @@ test_that("sf can write to all writable formats", {
 })
 
 test_that("sf can write to netcdf", {
+	skip_if_not_installed("sp")
 	skip_on_os("windows")
 	tf <- tempfile()
 	if ("netCDF" %in% drvs) {
@@ -28,6 +32,7 @@ test_that("sf can write to netcdf", {
 })
 
 test_that("sf can write units (#264)", {
+	skip_if_not_installed("sp")
     tf <- tempfile(fileext = ".gpkg")
     meuse[["length"]] <- meuse[["cadmium"]]
     units(meuse$length) <- units::as_units("km")
@@ -90,6 +95,7 @@ test_that("delete and update work (#304)", {
 })
 
 test_that("layer is deleted when fails to create features (#549)", {
+	skip_if_not_installed("sp")
 	skip_on_os("mac")
 	shp <- tempfile(fileext = ".shp")
 	x <- st_sf(a = 1:2, geom = st_sfc(st_point(0:1), st_multipoint(matrix(1:4,2,2))))