fix these fucking tidyverse warnings

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: ffscrapr
 Title: API Client for Fantasy Football League Platforms
-Version: 1.4.8.07
+Version: 1.4.8.09
 Authors@R: 
     c(person(given = "Tan",
              family = "Ho",

NEWS.md

@@ -14,6 +14,8 @@ respect `season` in connection object (v1.4.8.06) (#408, thank you @RandalMorris
 - `ff_rosters()` fleaflicker method now accepts `week` argument (v1.4.8.06)
 - `ff_starters()` fleaflicker method expands to show injury data from box score 
 and keep NA data where a player is not in a slot.  (v1.4.8.07)
+- Silence a whack of tidyverse crap warnings (v1.4.8.09)
+
 
 # ffscrapr 1.4.8
 

R/espn_scoringhistory.R

@@ -24,7 +24,8 @@ ff_scoringhistory.espn_conn <- function(conn, season = 1999:nflreadr::most_recen
     ff_scoring(conn) %>%
     dplyr::left_join(
       ffscrapr::nflfastr_stat_mapping %>% dplyr::filter(.data$platform == "espn"),
-      by = c("stat_name" = "ff_event")
+      by = c("stat_name" = "ff_event"),
+      relationship = "many-to-many"
     )
 
   ros <- .nflfastr_roster(season)
@@ -42,8 +43,16 @@ ff_scoringhistory.espn_conn <- function(conn, season = 1999:nflreadr::most_recen
   }
 
   ros %>%
-    dplyr::inner_join(ps, by = c("gsis_id"="player_id","season")) %>%
-    dplyr::inner_join(league_rules, by = c("metric"="nflfastr_event","pos")) %>%
+    dplyr::inner_join(
+      ps,
+      by = c("gsis_id"="player_id","season"),
+      relationship = "many-to-many"
+    ) %>%
+    dplyr::inner_join(
+      league_rules,
+      by = c("metric"="nflfastr_event","pos"),
+      relationship = "many-to-many"
+    ) %>%
     dplyr::mutate(points = .data$value * .data$points) %>%
     dplyr::group_by(.data$season, .data$week, .data$gsis_id, .data$sportradar_id) %>%
     dplyr::mutate(points = round(sum(.data$points, na.rm = TRUE), 2)) %>%

R/espn_standings.R

@@ -40,12 +40,12 @@ ff_standings.espn_conn <- function(conn, ...) {
 
   records <-
     standings_init %>%
-    dplyr::select(.data$record) %>%
+    dplyr::select("record") %>%
     tidyr::hoist(
       "record",
       "overall"
     ) %>%
-    dplyr::select(-.data$record) %>%
+    dplyr::select(-"record") %>%
     tidyr::hoist(
       "overall",
       "h2h_wins" = "wins",
@@ -55,7 +55,7 @@ ff_standings.espn_conn <- function(conn, ...) {
       "points_for" = "pointsFor",
       "points_against" = "pointsAgainst",
     ) %>%
-    dplyr::select(-.data$overall)
+    dplyr::select(-"overall")
 
   allplay <- ff_schedule(conn) %>%
     .add_allplay()
@@ -65,7 +65,7 @@ ff_standings.espn_conn <- function(conn, ...) {
 
   standings <-
     dplyr::bind_cols(
-      standings_init %>% dplyr::select(-.data$record),
+      standings_init %>% dplyr::select(-"record"),
       records
     ) %>%
     dplyr::left_join(allplay, by = c("franchise_id")) %>%

R/flea_schedule.R

@@ -105,7 +105,12 @@ ff_schedule.flea_conn <- function(conn, week = 1:17, ...) {
       )),
       dplyr::starts_with("is")
     ) %>%
-    dplyr::mutate(dplyr::across(dplyr::contains("_score"), purrr::map_dbl, ~ replace(.x, is.null(.x), NA)))
+    dplyr::mutate(
+      dplyr::across(
+        dplyr::contains("_score"),
+        function(col) purrr::map_dbl(col, ~ replace(.x, is.null(.x), NA))
+        )
+    )
 
   return(schedule)
 }

R/flea_scoringhistory.R

@@ -27,7 +27,8 @@ ff_scoringhistory.flea_conn <- function(conn, season = 1999:nflreadr::most_recen
       ffscrapr::nflfastr_stat_mapping %>%
         dplyr::filter(.data$platform == "fleaflicker") %>%
         dplyr::mutate(ff_event = as.integer(.data$ff_event)),
-      by = c("event_id" = "ff_event")
+      by = c("event_id" = "ff_event"),
+      relationship = "many-to-many"
     )
   ros <- .nflfastr_roster(season)
 
@@ -40,8 +41,14 @@ ff_scoringhistory.flea_conn <- function(conn, season = 1999:nflreadr::most_recen
   }
 
   ros %>%
-    dplyr::inner_join(ps, by = c("gsis_id"="player_id","season")) %>%
-    dplyr::inner_join(league_rules, by = c("metric"="nflfastr_event","pos")) %>%
+    dplyr::inner_join(
+      ps,
+      by = c("gsis_id"="player_id","season"),
+      relationship = "many-to-many") %>%
+    dplyr::inner_join(
+      league_rules,
+      by = c("metric"="nflfastr_event","pos"),
+      relationship = "many-to-many") %>%
     dplyr::mutate(points = .data$value * .data$points) %>%
     dplyr::group_by(.data$season, .data$week, .data$gsis_id, .data$sportradar_id) %>%
     dplyr::mutate(points = round(sum(.data$points, na.rm = TRUE), 2)) %>%

R/flea_standings.R

@@ -19,7 +19,8 @@
 #'
 #' @export
 ff_standings.flea_conn <- function(conn, include_allplay = TRUE, include_potentialpoints = TRUE, ...) {
-  standings <- fleaflicker_getendpoint("FetchLeagueStandings",
+  standings <- fleaflicker_getendpoint(
+    "FetchLeagueStandings",
     league_id = conn$league_id,
     season = conn$season,
     sport = "NFL"
@@ -36,10 +37,15 @@ ff_standings.flea_conn <- function(conn, include_allplay = TRUE, include_potenti
       "points_for" = "pointsFor",
       "points_against" = "pointsAgainst"
     ) %>%
-    dplyr::mutate(dplyr::across(c("points_for", "points_against"), purrr::map_dbl, purrr::pluck, "value")) %>%
+    dplyr::mutate(
+      dplyr::across(
+        c("points_for", "points_against"),
+        function(col) purrr::map_dbl(col, purrr::pluck, "value")
+      )
+    )%>%
     tidyr::hoist("recordOverall", "h2h_wins" = "wins", "h2h_losses" = "losses", "h2h_ties" = "ties") %>%
     dplyr::mutate(
-      dplyr::across(dplyr::starts_with("h2h"), tidyr::replace_na, 0),
+      dplyr::across(dplyr::starts_with("h2h"), ~tidyr::replace_na(.x,0)),
       h2h_winpct = (.data$h2h_wins / (.data$h2h_wins + .data$h2h_losses + .data$h2h_ties)) %>% round(3)
     ) %>%
     dplyr::select(
@@ -74,14 +80,15 @@ ff_standings.flea_conn <- function(conn, include_allplay = TRUE, include_potenti
     dplyr::filter(!is.na(.data$result)) %>%
     dplyr::distinct(.data$week, .data$game_id) %>%
     dplyr::mutate(potentialpoints = purrr::map2(.data$week, .data$game_id, .flea_potentialpointsweek, conn)) %>%
-    tidyr::unnest(.data$potentialpoints) %>%
+    tidyr::unnest("potentialpoints") %>%
     dplyr::group_by(.data$franchise_id) %>%
     dplyr::summarise(potential_points = sum(.data$potential_points)) %>%
     dplyr::ungroup()
 }
 
 .flea_potentialpointsweek <- function(week, game_id, conn) {
-  x <- fleaflicker_getendpoint("FetchLeagueBoxscore",
+  x <- fleaflicker_getendpoint(
+    "FetchLeagueBoxscore",
     sport = "NFL",
     scoring_period = week,
     fantasy_game_id = game_id,