use native pipe

Author: boshek

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: tidyhydat
 Title: Extract and Tidy Canadian 'Hydrometric' Data
-Version: 0.6.1
+Version: 0.6.1.9000
 Authors@R: c(person("Sam", "Albers", email = "sam.albers@gmail.com", role = c("aut", "cre"),
     comment = c(ORCID = "0000-0002-9270-7884")),
     person("David", "Hutchinson", email = "david.hutchinson@canada.ca", role = "ctb"),
@@ -45,4 +45,4 @@ VignetteBuilder: knitr
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
 LazyData: true
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.2

NAMESPACE

@@ -4,7 +4,6 @@ S3method(plot,hy)
 S3method(plot,realtime)
 S3method(print,hy)
 S3method(print,realtime)
-export("%>%")
 export(download_hydat)
 export(enexpr)
 export(enquo)
@@ -59,7 +58,6 @@ export(search_stn_name)
 export(search_stn_number)
 export(sym)
 export(syms)
-importFrom(dplyr,"%>%")
 importFrom(rlang,":=")
 importFrom(rlang,.data)
 importFrom(rlang,UQ)

NEWS.md

@@ -1,4 +1,4 @@
-# tidyhydat 0.6.2
+# tidyhydat 0.6.1.9000
 - bump minimum R version to 4.0.0
 - dropped httr in favour of httr2
 - fix bug where `download_hydat()` fails if `tempdir()` is on a different device than `hydat_path` (@mpdavison, #192)

R/download.R

@@ -184,9 +184,9 @@ hy_check <- function(hydat_path = NULL) {
 
 
   invisible(lapply(have_tbls, function(x) {
-    tbl_rows <- dplyr::tbl(con, x) %>%
-      utils::head(1) %>%
-      dplyr::collect() %>%
+    tbl_rows <- dplyr::tbl(con, x) |>
+      utils::head(1) |>
+      dplyr::collect() |>
       nrow()
 
     if (tbl_rows == 0) {

R/hy.R

@@ -361,7 +361,7 @@ hy_agency_list <- function(hydat_path = NULL) {
     on.exit(hy_src_disconnect(hydat_con), add = TRUE)
   }
 
-  agency_list <- dplyr::tbl(hydat_con, "AGENCY_LIST") %>%
+  agency_list <- dplyr::tbl(hydat_con, "AGENCY_LIST") |>
     dplyr::collect()
 
   as.hy(agency_list)
@@ -389,7 +389,7 @@ hy_reg_office_list <- function(hydat_path = NULL) {
     on.exit(hy_src_disconnect(hydat_con), add = TRUE)
   }
 
-  regional_office_list <- dplyr::tbl(hydat_con, "REGIONAL_OFFICE_LIST") %>%
+  regional_office_list <- dplyr::tbl(hydat_con, "REGIONAL_OFFICE_LIST") |>
     dplyr::collect()
 
   as.hy(regional_office_list)
@@ -418,7 +418,7 @@ hy_datum_list <- function(hydat_path = NULL) {
     on.exit(hy_src_disconnect(hydat_con), add = TRUE)
   }
 
-  datum_list <- dplyr::tbl(hydat_con, "DATUM_LIST") %>%
+  datum_list <- dplyr::tbl(hydat_con, "DATUM_LIST") |>
     dplyr::collect()
 
   as.hy(datum_list)
@@ -448,8 +448,8 @@ hy_version <- function(hydat_path = NULL) {
     on.exit(hy_src_disconnect(hydat_con), add = TRUE)
   }
 
-  version <- dplyr::tbl(hydat_con, "VERSION") %>%
-    dplyr::collect() %>%
+  version <- dplyr::tbl(hydat_con, "VERSION") |>
+    dplyr::collect() |>
     dplyr::mutate(Date = lubridate::ymd_hms(Date))
 
   version

R/hy_annual_instant_peaks.R

@@ -54,8 +54,8 @@ hy_annual_instant_peaks <- function(station_number = NULL,
   sym_STATION_NUMBER <- sym("STATION_NUMBER")
 
   ## Data manipulations
-  aip <- dplyr::tbl(hydat_con, "ANNUAL_INSTANT_PEAKS") %>%
-    dplyr::filter(!!sym_STATION_NUMBER %in% stns) %>%
+  aip <- dplyr::tbl(hydat_con, "ANNUAL_INSTANT_PEAKS") |>
+    dplyr::filter(!!sym_STATION_NUMBER %in% stns) |>
     dplyr::collect()
 
   ## Add in english data type

R/hy_annual_stats.R

@@ -75,7 +75,7 @@ hy_annual_stats <- function(station_number = NULL,
     annual_statistics <- dplyr::filter(annual_statistics, !!sym_YEAR >= start_year & !!sym_YEAR <= end_year)
   }
 
-  annual_statistics <- dplyr::filter(annual_statistics, !!sym_STATION_NUMBER %in% stns) %>%
+  annual_statistics <- dplyr::filter(annual_statistics, !!sym_STATION_NUMBER %in% stns) |>
     dplyr::collect()
 
   ## TODO: Figure out how to do this in fewer steps
@@ -106,10 +106,10 @@ hy_annual_stats <- function(station_number = NULL,
   colnames(as_max) <- gsub("MAX_", "", names(as_max))
 
   ## bind into 1 dataframe and by year and join in the symbol
-  annual_statistics <- as_mean %>%
-    dplyr::bind_rows(as_min) %>%
-    dplyr::bind_rows(as_max) %>%
-    dplyr::arrange(YEAR) %>%
+  annual_statistics <- as_mean |>
+    dplyr::bind_rows(as_min) |>
+    dplyr::bind_rows(as_max) |>
+    dplyr::arrange(YEAR) |>
     dplyr::left_join(tidyhydat::hy_data_symbols, by = c("SYMBOL" = "SYMBOL_ID"))
 
   ## Format date of occurence; SuppressWarnings are justified because NA's are valid for MEAN Sum_stat

R/hy_db.R

@@ -28,8 +28,8 @@
 #'
 #' # one you're sure the results are what you want
 #' # get a data.frame using collect()
-#' tbl(src, "STATIONS") %>%
-#'   filter(PROV_TERR_STATE_LOC == "BC") %>%
+#' tbl(src, "STATIONS") |>
+#'   filter(PROV_TERR_STATE_LOC == "BC") |>
 #'   collect()
 #'
 #' # close the connection to the database

R/hy_stations.R

@@ -82,10 +82,10 @@ hy_stations <- function(station_number = NULL,
   sym_STATION_NUMBER <- sym("STATION_NUMBER")
 
   ## Create the dataframe to return
-  df <- dplyr::tbl(hydat_con, "STATIONS") %>%
-    dplyr::filter(!!sym_STATION_NUMBER %in% stns) %>%
-    dplyr::collect() %>%
-    dplyr::mutate(REGIONAL_OFFICE_ID = as.numeric(REGIONAL_OFFICE_ID)) %>%
+  df <- dplyr::tbl(hydat_con, "STATIONS") |>
+    dplyr::filter(!!sym_STATION_NUMBER %in% stns) |>
+    dplyr::collect() |>
+    dplyr::mutate(REGIONAL_OFFICE_ID = as.numeric(REGIONAL_OFFICE_ID)) |>
     dplyr::mutate(
       HYD_STATUS = dplyr::case_when(
         HYD_STATUS == "D" ~ "DISCONTINUED",

R/realtime.R

@@ -148,7 +148,7 @@ realtime_stations <- function(prov_terr_state_loc = NULL) {
 #' @examples
 #' \dontrun{
 #'
-#' realtime_dd(c("08MF005", "02LA004")) %>%
+#' realtime_dd(c("08MF005", "02LA004")) |>
 #'   realtime_add_local_datetime()
 #' }
 #'
@@ -188,7 +188,7 @@ realtime_add_local_datetime <- function(.data, set_tz = NULL) {
 #'
 #' @examples
 #' \dontrun{
-#' realtime_dd("08MF005") %>% realtime_daily_mean()
+#' realtime_dd("08MF005") |> realtime_daily_mean()
 #' }
 #'
 #' @export