Drop magrittr

Fixes #522

DESCRIPTION

@@ -35,7 +35,6 @@ Imports:
     httr (>= 1.3.0),
     jsonlite (>= 0.9.22),
     lifecycle (>= 1.0.0),
-    magrittr (>= 1.5),
     progress,
     rappdirs,
     tibble (>= 1.3.4),

NAMESPACE

@@ -16,7 +16,6 @@ S3method(print,screen_name)
 S3method(print,user_id)
 S3method(round_time,Date)
 S3method(round_time,POSIXt)
-export("%>%")
 export(as_screenname)
 export(as_userid)
 export(bearer_token)
@@ -97,4 +96,3 @@ export(users_data)
 export(users_with_tweets)
 export(write_as_csv)
 import(rlang)
-importFrom(magrittr,"%>%")

NEWS.md

@@ -1,5 +1,8 @@
 # rtweet ...
 
+- rtweet no longer re-exports the pipe; if you want to continue using it, you'll
+  need to `library(magrittr)` or `library(dplyr)` (#522).
+
 - `stream_tweets()` has been overhauled to only write valid data. This obsoletes
   all previous strategy to cleen up bad data after the fact (#350, #356).
 

R/post-list.R

@@ -34,10 +34,9 @@
 #' cnn_users <- search_users("CNN", n = 200)
 #'
 #' ## filter and select more users to add to list
-#' more_users <- cnn_users %>%
-#'   subset(verified & !tolower(screen_name) %in% tolower(users)) %>%
-#'   .$screen_name %>%
-#'   grep("cnn", ., ignore.case = TRUE, value = TRUE)
+#' more_users <- cnn_users$screen_name[cnn_users$verified]
+#' more_users <- setdiff(more_users, users)
+#' more_users <- more_users[grepl("cnn", more_users, ignore.case = TRUE)]
 #'
 #' ## add more users to list- note: can only add up to 100 at a time
 #' post_list(users = more_users, slug = "cnn-accounts")
@@ -47,9 +46,7 @@
 #'   rtweet:::api_screen_name()))
 #'
 #' ## select users on list without "cnn" in their name field
-#' drop_users <- cnn_users %>%
-#'   subset(screen_name %in% more_users & !grepl("cnn", name, ignore.case = TRUE)) %>%
-#'   .$screen_name
+#' drop_users <- cnn_users$screen_name[!grepl("cnn", cnn_users$screen_name, ignore.case = TRUE)]
 #'
 #' ## drop these users from the cnn list
 #' post_list(users = drop_users, slug = "cnn-accounts",

R/ts_plot.R

@@ -19,17 +19,14 @@
 #' @examples
 #'
 #' \dontrun{
-#'
 #' ## search for tweets containing "rstats"
 #' rt <- search_tweets("rstats", n = 10000)
 #'
 #' ## plot frequency in 1 min intervals
 #' ts_plot(rt, "mins")
 #'
 #' ## plot multiple time series--retweets vs non-retweets
-#' rt %>%
-#'   dplyr::group_by(is_retweet) %>%
-#'   ts_plot("hours")
+#' ts_plot(dplyr::group_by(tmls, is_retweet), "hours")
 #'
 #' ## compare account activity for some important US political figures
 #' tmls <- get_timeline(
@@ -44,9 +41,7 @@
 #' ts_plot(dplyr::group_by(tmls, screen_name), "weeks")
 #'
 #' ## group by screen name and is_retweet
-#' tmls %>%
-#'   dplyr::group_by(tmls, screen_name, is_retweet) %>%
-#'   ts_plot("months")
+#' ts_plot(dplyr::group_by(tmls, screen_name, is_retweet), "months")
 #'
 #' }
 #' @family ts_data
@@ -110,10 +105,7 @@ ts_plot_ <- function(data, by = "days", trim = 0L, tz ="UTC", ...) {
 #' ts_data(sens, "weeks")
 #'
 #' ## group by screen name and then use weekly intervals
-#' sens %>%
-#'   dplyr::group_by(screen_name) %>%
-#'   ts_plot("weeks")
-#'
+#' ts_plot(dplyr::group_by(sens, screen_name), "weeks")
 #' }
 #'
 #' @export

R/tweet_threading.R

@@ -15,7 +15,7 @@
 #' @examples 
 #' \dontrun{
 #' tw <- lookup_statuses('1084143184664510470')
-#' tw_thread <- tw%>%tweet_threading()
+#' tw_thread <- tweet_threading(tw)
 #' tw_thread
 #' }
 #' @seealso 
@@ -36,7 +36,7 @@ tweet_threading <- function(tw, traverse = c('backwards','forwards'), n = 10, ve
   for(i in traverse){
     cat('\n')
     .f <- get(sprintf('tweet_threading_%s',i),envir = asNamespace('rtweet'))
-    tw <- tw%>%.f(n,verbose)
+    tw <- .f(tw, n,verbose)
   }
 
   tw