From b2dc63aa7b34a4bb9c9eaccb60f68ea6fb95d189 Mon Sep 17 00:00:00 2001
From: Tan Ho <tan@tanho.ca>
Date: Thu, 27 Jul 2023 23:27:24 -0300
Subject: [PATCH] v1.4.8.04 - update ff_scoring to work with newest dplyr,
 resolves #402

---
 DESCRIPTION                      |  2 +-
 NEWS.md                          |  1 +
 R/mfl_scoring.R                  | 22 ++++++++++++++--------
 tests/testthat/test-ff_scoring.R |  3 +++
 4 files changed, 19 insertions(+), 9 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 4e0c49e8..a75df9ec 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: ffscrapr
 Title: API Client for Fantasy Football League Platforms
-Version: 1.4.8.03
+Version: 1.4.8.04
 Authors@R: 
     c(person(given = "Tan",
              family = "Ho",
diff --git a/NEWS.md b/NEWS.md
index 36c19730..e0db9b2a 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -7,6 +7,7 @@ should be more robust (#397, thank you @logan-888!) (v1.4.8.02)
 - `ff_startpositions.sleeper_conn()` now properly handles leagues with flex
 positions that did not have dedicated posititions (#400, thank you @mcarman8!) 
 (v1.4.8.03)
+- `ff_scoring.mfl_conn()` now works better with new dplyr versions (#402) (v1.4.8.04)
 
 # ffscrapr 1.4.8
 
diff --git a/R/mfl_scoring.R b/R/mfl_scoring.R
index 56c3035f..bd3a5bf6 100644
--- a/R/mfl_scoring.R
+++ b/R/mfl_scoring.R
@@ -25,21 +25,27 @@ ff_scoring.mfl_conn <- function(conn) {
     df <- df %>%
       tibble::tibble() %>%
       tidyr::unnest_wider(1)
+  } else if (!is.null(df$positions)) {
+    df <- df %>%
+      tibble::as_tibble()
   }
 
-  if (!is.null(df$positions)) {
-    df <- df %>% tibble::as_tibble()
+  # convert each nested list of rules to tibble by bind_rows
+  # so that it can be unnested nicely
+  # see ffscrapr#344 for history
+  parse_rule <- function(rule){
+    vec_depth <- purrr::vec_depth(rule)
+    if(vec_depth == 3) rule <- tibble::as_tibble(rule)
+    if(vec_depth == 4) rule <- dplyr::bind_rows(rule)
+    rule %>%
+      dplyr::mutate_all(~unlist(.x) %>% unname())
   }
 
-
   df <- df %>%
     dplyr::mutate(
-      # convert each nested list of rules to tibble by bind_rows
-      # so that it can be unnested nicely
-      # see ffscrapr#344 for history
-      rule = purrr::map(.data$rule, dplyr::bind_rows)
+      rule = purrr::map(.data$rule, parse_rule),
     ) %>%
-    tidyr::unnest("rule") %>%
+    tidyr::unnest_wider("rule") %>%
     tidyr::unnest(c("points", "event", "range")) %>%
     tidyr::separate_rows("positions", sep = "\\|") %>%
     dplyr::left_join(mfl_allrules(conn), by = c("event" = "abbrev")) %>%
diff --git a/tests/testthat/test-ff_scoring.R b/tests/testthat/test-ff_scoring.R
index 076fa787..9baf3e8b 100644
--- a/tests/testthat/test-ff_scoring.R
+++ b/tests/testthat/test-ff_scoring.R
@@ -3,6 +3,8 @@ test_that("ff_scoring returns a tibble", {
 
   dlf <- mfl_connect(2019, 37920)
   dlf_scoring <- ff_scoring(dlf)
+  wade <- mfl_connect(2023, 65804)
+  wade_scoring <- ff_scoring(wade)
 
   jml_conn <- sleeper_connect(league_id = "522458773317046272", season = 2020)
   jml_scoring <- ff_scoring(jml_conn)
@@ -17,6 +19,7 @@ test_that("ff_scoring returns a tibble", {
   expect_tibble(jml_scoring, min.rows = 10)
   expect_tibble(joe_scoring, min.rows = 10)
   expect_tibble(tony_scoring, min.rows = 10)
+  expect_tibble(wade_scoring, min.rows = 10)
 })
 
 test_that("ff_scoring for templates return tibbles", {