Merge pull request #274 from dynastyprocess/dev

1.4.1 - patch env issue, scoringhistory, starter_positions

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: ffscrapr
 Title: API Client for Fantasy Football League Platforms
-Version: 1.4.0
+Version: 1.4.1
 Authors@R: 
     c(person(given = "Tan",
              family = "Ho",
@@ -56,6 +56,7 @@ Suggests:
     rmarkdown (>= 2.6),
     testthat (>= 2.1.0),
     withr (>= 2.4.0)
+LazyData: true
 VignetteBuilder:
     knitr
 Encoding: UTF-8

NEWS.md

@@ -1,10 +1,28 @@
+# ffscrapr 1.4.1
+
+The main goal of v1.4.1 is to patch some issues raised by CRAN checks and also correct some bugs in the new experimental `ff_scoringhistory` and `ff_starter_positions` functions released in v1.4.0. 
+
+## New features
+
+- `nflfastr_stat_mapping` is a dataframe that maps nflfastr columns to fantasy scoring rules, and is now exported for end-user usage. It is primarily used inside of `ff_scoringhistory()`.
+
+## Minor changes
+
+- Added `release_questions` to help remind me to maintain test infrastructure
+- `mfl_starter_positions` now correctly calculates offensive starters (first via "iop_starters" if defined and then otherwise by subtracting idp starters) as well as kdst_starters (Resolves #264)
+- Redirected nflfastr download functions to the new nflverse/ repository locations. (Resolves #268)
+- `.ffscrapr_env` relocated from being a child of the base environment to being a child of the empty environment (Resolves #269)
+- `ff_scoringhistory` refactored and adds better support for MFL's fumbles and firstdowns. (Resolves #265)
+
+---
+
 # ffscrapr 1.4.0
 
 The main goal of v1.4.0 is to add preliminary support for connecting ffscrapr to nflfastR weekly data, and to clean up bugs from v1.3.0. Huge thanks goes to [Joe Sydlowski](https://twitter.com/JoeSydlowskiFF) for his contributions on scoring history (and everything else DynastyProcess!)
 
 ## New Features
-- `nflfastr_weekly()` imports weekly offensive statistics from nflfastR's [data repository](https://github.com/guga31bb/nflfastR-data).
-- `nflfastr_rosters()` imports team rosters from nflfastR's [roster repository](https://github.com/mrcaseb/nflfastR-roster).
+- `nflfastr_weekly()` imports weekly offensive statistics from nflfastR's [data repository](https://github.com/nflverse/nflfastR-data).
+- `nflfastr_rosters()` imports team rosters from nflfastR's [roster repository](https://github.com/nflverse/nflfastR-roster).
 - `ff_scoringhistory()` connects your league's scoring settings to the nflfastr data (c/o the functions above), and allows you to reconstruct historical scoring for your league!
 - `ff_starter_positions()` describes the starter rules for each player/position, including min and max starters at each position accounting for flex spots. This should be useful for calculating things like value over replacement!
 

R/0_helpers.R

@@ -150,3 +150,33 @@ set_unescaped_cookies <- function(...) {
 
   httr::config(cookie = cookie)
 }
+
+#' Release questions
+#'
+#' @keywords internal
+#'
+release_bullets <- function(){
+
+  #nocov start
+
+  c(
+    "Tag the current version of ffscrapr-tests as a release version",
+    'Switch all vignettes and tests to use "ffscrapr-tests-v1.x.x" and download "archive/v1.x.x"'
+  )
+
+  #nocov end
+
+}
+
+#' Mappings for nflfastr to fantasy platform scoring
+#'
+#' A small helper dataframe for connecting nflfastr to specific fantasy platform rules.
+#'
+#' @format A data frame with ~85 rows and 3 variables:
+#' \describe{
+#'   \item{nflfastr_event}{the column name of the statistic in the nflfastr_weekly dataset}
+#'   \item{platform}{specific platform that this mapping applies to}
+#'   \item{ff_event}{name of the statistic for that platform}
+#' }
+#'
+"nflfastr_stat_mapping"

R/1_import_nflfastr.R

@@ -26,7 +26,7 @@
 nflfastr_weekly <- function(type = c("offense", "defense", "all")) {
   file_name <- match.arg(type)
 
-  url_query <- "https://github.com/guga31bb/nflfastR-data/raw/master/data/player_stats.rds"
+  url_query <- "https://github.com/nflverse/nflfastR-data/raw/master/data/player_stats.rds"
 
   response <- httr::RETRY("GET", url_query)
 
@@ -66,7 +66,7 @@ nflfastr_weekly <- function(type = c("offense", "defense", "all")) {
 nflfastr_rosters <- function(seasons) {
   checkmate::assert_numeric(seasons, lower = 1999, upper = lubridate::year(Sys.Date()))
 
-  urls <- glue::glue("https://github.com/mrcaseb/nflfastR-roster/raw/master/data/seasons/roster_{seasons}.rds")
+  urls <- glue::glue("https://github.com/nflverse/nflfastR-roster/raw/master/data/seasons/roster_{seasons}.rds")
 
   df_rosters <- purrr::map_df(urls, .nflfastr_roster)
 

R/espn_scoringhistory.R

@@ -20,7 +20,10 @@ ff_scoringhistory.espn_conn <- function(conn, season = 1999:2020, ...) {
 
   # Pull in scoring rules for that league
   league_rules <-
-    ff_scoring(conn)
+    ff_scoring(conn) %>%
+    dplyr::left_join(
+      nflfastr_stat_mapping %>% dplyr::filter(.data$platform == "espn"),
+      by = c("stat_name" = "ff_event"))
 
   # Use custom ffscrapr function to get positions fron nflfastR rosters
   fastr_rosters <-
@@ -41,8 +44,7 @@ ff_scoringhistory.espn_conn <- function(conn, season = 1999:2020, ...) {
         "special_teams_tds"
       )
     ) %>%
-    dplyr::inner_join(stat_mapping, by = c("metric" = "nflfastr_event")) %>%
-    dplyr::inner_join(league_rules, by = c("espn_event" = "stat_name", "position" = "pos")) %>%
+    dplyr::inner_join(league_rules, by = c("metric" = "nflfastr_event", "position" = "pos")) %>%
     dplyr::mutate(points = .data$value * .data$points) %>%
     dplyr::group_by(.data$season, .data$week, .data$player_id, .data$sportradar_id) %>%
     dplyr::mutate(points = round(sum(.data$points, na.rm = TRUE), 2)) %>%

R/flea_scoringhistory.R

@@ -8,10 +8,8 @@
 #'
 #' @examples
 #' \donttest{
-#' #'
-#' conn <- fleaflicker_connect(2020, 312861)
-#' x <- ff_scoringhistory(conn, season = 2020)
-#' x
+#' # conn <- fleaflicker_connect(2020, 312861)
+#' ff_scoringhistory(conn, season = 2020)
 #' }
 #'
 #' @describeIn ff_scoringhistory Fleaflicker: returns scoring history in a flat table, one row per player per week.
@@ -22,7 +20,12 @@ ff_scoringhistory.flea_conn <- function(conn, season = 1999:2020, ...) {
 
   # Pull in scoring rules for that league
   league_rules <-
-    ff_scoring(conn)
+    ff_scoring(conn) %>%
+    dplyr::left_join(
+      nflfastr_stat_mapping %>%
+        dplyr::filter(.data$platform == "fleaflicker") %>%
+        dplyr::mutate(ff_event = as.integer(.data$ff_event)),
+      by = c("event_id" = "ff_event"))
 
   # Use custom ffscrapr function to get positions fron nflfastR rosters
   fastr_rosters <-
@@ -43,8 +46,7 @@ ff_scoringhistory.flea_conn <- function(conn, season = 1999:2020, ...) {
         "special_teams_tds"
       )
     ) %>%
-    dplyr::inner_join(stat_mapping, by = c("metric" = "nflfastr_event")) %>%
-    dplyr::inner_join(league_rules, by = c("fleaflicker_event" = "event_id", "position" = "pos")) %>%
+    dplyr::inner_join(league_rules, by = c("metric" = "nflfastr_event", "position" = "pos")) %>%
     dplyr::mutate(points = .data$value * .data$points) %>%
     dplyr::group_by(.data$season, .data$week, .data$player_id, .data$sportradar_id) %>%
     dplyr::mutate(points = round(sum(.data$points, na.rm = TRUE), 2)) %>%

R/mfl_scoringhistory.R

@@ -29,16 +29,31 @@ ff_scoringhistory.mfl_conn <- function(conn, season = 1999:2020, ...) {
     dplyr::mutate(dplyr::across(
       .cols = c("lower_range", "upper_range"),
       .fns = as.numeric
-    ))
+    )) %>%
+    dplyr::left_join(
+      nflfastr_stat_mapping %>% dplyr::filter(.data$platform == "mfl"),
+      by = c("event" = "ff_event")) %>%
+    dplyr::select(
+      "pos","points","lower_range","upper_range","event", "nflfastr_event", "short_desc"
+    )
 
-  # Use custom ffscrapr function to get positions fron nflfastR rosters
+  # Use custom ffscrapr function to get positions from nflfastR rosters
   fastr_rosters <-
     nflfastr_rosters(season) %>%
     dplyr::mutate(position = dplyr::if_else(.data$position %in% c("HB", "FB"), "RB", .data$position))
 
   # Load stats from nflfastr and map the rules from the internal stat_mapping file
-  nflfastr_weekly() %>%
+  fastr_weekly <- nflfastr_weekly() %>%
     dplyr::inner_join(fastr_rosters, by = c("player_id" = "gsis_id", "season" = "season")) %>%
+    dplyr::select(
+      "season", "player_id", "sportradar_id", "position", "full_name","recent_team","week",
+      "completions", "attempts", "passing_yards", "passing_tds", "interceptions", "sacks",
+      "sack_fumbles_lost", "passing_first_downs", "passing_2pt_conversions", "carries",
+      "rushing_yards", "rushing_tds", "rushing_fumbles_lost", "rushing_first_downs",
+      "rushing_2pt_conversions", "receptions", "targets", "receiving_yards", "receiving_tds",
+      "receiving_fumbles_lost", "receiving_first_downs", "receiving_2pt_conversions",
+      "special_teams_tds", "sack_yards", "rushing_fumbles", "receiving_fumbles", "sack_fumbles"
+    ) %>%
     tidyr::pivot_longer(
       names_to = "metric",
       cols = c(
@@ -47,18 +62,17 @@ ff_scoringhistory.mfl_conn <- function(conn, season = 1999:2020, ...) {
         "rushing_yards", "rushing_tds", "rushing_fumbles_lost", "rushing_first_downs",
         "rushing_2pt_conversions", "receptions", "targets", "receiving_yards", "receiving_tds",
         "receiving_fumbles_lost", "receiving_first_downs", "receiving_2pt_conversions",
-        "special_teams_tds"
+        "special_teams_tds", "sack_yards", "rushing_fumbles", "receiving_fumbles", "sack_fumbles"
       )
     ) %>%
-    dplyr::inner_join(stat_mapping, by = c("metric" = "nflfastr_event")) %>%
-    dplyr::inner_join(league_rules, by = c("mfl_event" = "event", "position" = "pos")) %>%
+    dplyr::inner_join(league_rules, by = c("metric" = "nflfastr_event", "position" = "pos")) %>%
     dplyr::filter(.data$value >= .data$lower_range, .data$value <= .data$upper_range) %>%
     dplyr::mutate(points = .data$value * .data$points) %>%
     dplyr::group_by(.data$season, .data$week, .data$player_id, .data$sportradar_id) %>%
     dplyr::mutate(points = round(sum(.data$points, na.rm = TRUE), 2)) %>%
     dplyr::ungroup() %>%
     dplyr::select("season", "week",
-      "gsis_id" = "player_id", "sportradar_id", "player_name", "pos" = "position",
+      "gsis_id" = "player_id", "sportradar_id", "player_name"="full_name", "pos" = "position",
       "team" = "recent_team", "metric", "value", "points"
     ) %>%
     tidyr::pivot_wider(
@@ -68,4 +82,6 @@ ff_scoringhistory.mfl_conn <- function(conn, season = 1999:2020, ...) {
       values_fill = 0,
       values_fn = max
     )
+
+  return(fastr_weekly)
 }

R/mfl_starterpositions.R

@@ -9,33 +9,43 @@
 #'
 #' @examples
 #' \donttest{
-#' dlfidp_conn <- mfl_connect(2020, league_id = 54040)
+#' dlfidp_conn <- mfl_connect(2020, league_id = 33158)
 #' ff_starter_positions(conn = dlfidp_conn)
 #' }
 #'
 #' @export
 
 ff_starter_positions.mfl_conn <- function(conn, ...) {
+
   starter_positions <- mfl_getendpoint(conn, "league") %>%
     purrr::pluck("content", "league", "starters") %>%
     list() %>%
     tibble::tibble() %>%
-    tidyr::hoist(1, "total_starters" = "count", "defense_starters" = "idp_starters", "position") %>%
+    tidyr::hoist(
+      1,
+      "total_starters" = "count",
+      "defense_starters" = "idp_starters",
+      "offense_starters" = "iop_starters",
+      "position") %>%
     tidyr::unnest_longer("position") %>%
     tidyr::hoist("position", "pos" = "name", "limit") %>%
     tidyr::separate("limit", into = c("min", "max"), sep = "\\-", fill = "right") %>%
     dplyr::mutate_at(c("min", "max", "total_starters"), as.integer) %>%
     dplyr::mutate(
       max = dplyr::coalesce(.data$max, .data$min),
       defense_starters = dplyr::coalesce(as.integer(.data[["defense_starters"]]), 0),
-      offense_starters = as.integer(.data$total_starters) - .data$defense_starters
+      kdst_starters = sum(.data$pos %in% c("DEF","PK","PN","TMPK","TMPN","Coach","ST") * .data$min),
+      offense_starters = dplyr::coalesce(
+        as.integer(.data[["offense_starters"]]),
+        as.integer(.data$total_starters) - .data$defense_starters - .data$kdst_starters)
     ) %>%
     dplyr::select(
       "pos",
       "min",
       "max",
       "offense_starters",
       "defense_starters",
+      "kdst_starters",
       "total_starters"
     )
 

R/sleeper_draftpicks.R

@@ -63,8 +63,9 @@ ff_draftpicks.sleeper_conn <- function(conn, ...) {
     purrr::pluck("content")
 
   draft_rounds <- league_settings %>%
-    purrr::pluck("settings", "draft_rounds") %>%
-    seq_len()
+    purrr::pluck("settings", "draft_rounds")
+
+  draft_rounds <- seq_len(draft_rounds)
 
   # Seems to be that you can only trade three years in advance, hard-coded into the platform
   seasons <- league_settings %>%

R/sleeper_scoringhistory.R

@@ -9,8 +9,8 @@
 #' @examples
 #' \donttest{
 #' #'
-#' conn <- ff_connect(platform = "sleeper", league_id = "522458773317046272", season = 2020)
-#' ff_scoringhistory(conn, season = 2020)
+#' # conn <- ff_connect(platform = "sleeper", league_id = "522458773317046272", season = 2020)
+#' # ff_scoringhistory(conn, season = 2020)
 #' }
 #'
 #' @describeIn ff_scoringhistory Sleeper: returns scoring history in a flat table, one row per player per week.
@@ -21,7 +21,10 @@ ff_scoringhistory.sleeper_conn <- function(conn, season = 1999:2020, ...) {
 
   # Pull in scoring rules for that league
   league_rules <-
-    ff_scoring(conn)
+    ff_scoring(conn) %>%
+    dplyr::left_join(
+      nflfastr_stat_mapping %>% dplyr::filter(.data$platform == "sleeper"),
+      by = c("event" = "ff_event"))
 
   # Use custom ffscrapr function to get positions fron nflfastR rosters
   fastr_rosters <-
@@ -42,8 +45,7 @@ ff_scoringhistory.sleeper_conn <- function(conn, season = 1999:2020, ...) {
         "special_teams_tds"
       )
     ) %>%
-    dplyr::inner_join(stat_mapping, by = c("metric" = "nflfastr_event")) %>%
-    dplyr::inner_join(league_rules, by = c("sleeper_event" = "event", "position" = "pos")) %>%
+    dplyr::inner_join(league_rules, by = c("metric" = "nflfastr_event", "position" = "pos")) %>%
     dplyr::mutate(points = .data$value * .data$points) %>%
     dplyr::group_by(.data$season, .data$week, .data$player_id, .data$sportradar_id) %>%
     dplyr::mutate(points = round(sum(.data$points, na.rm = TRUE), 2)) %>%

R/zzz.R

@@ -1,5 +1,7 @@
 #### On Load ####
 
+.ffscrapr_env <- new.env(parent = emptyenv())
+
 .onLoad <- function(libname, pkgname) {
 
   # nocov start
@@ -89,21 +91,25 @@
 
   # if (memoise_option == "off") packageStartupMessage('Note: ffscrapr.cache is set to "off"')
 
-  env <- rlang::env(
-    user_agent = glue::glue(
-      "ffscrapr/{utils::packageVersion('ffscrapr')} API client package",
-      " https://github.com/dynastyprocess/ffscrapr"
-    ) %>%
-      httr::user_agent(),
-    get = ratelimitr::limit_rate(.retry_get, ratelimitr::rate(60, 60)),
-    get.mfl = ratelimitr::limit_rate(.retry_get, ratelimitr::rate(2, 3)),
-    get.sleeper = ratelimitr::limit_rate(.retry_get, ratelimitr::rate(30, 2)),
-    get.flea = ratelimitr::limit_rate(.retry_get, ratelimitr::rate(30, 2)),
-    get.espn = ratelimitr::limit_rate(.retry_get, ratelimitr::rate(30, 2)),
-    post = ratelimitr::limit_rate(.retry_post, ratelimitr::rate(60, 60))
-  )
-
-  assign(".ffscrapr_env", env, envir = baseenv())
+  user_agent <-  glue::glue("ffscrapr/{utils::packageVersion('ffscrapr')} ",
+                            "API client package ",
+                            "https://github.com/dynastyprocess/ffscrapr") %>%
+    httr::user_agent()
+
+  # get <-  ratelimitr::limit_rate(.retry_get, ratelimitr::rate(60, 60))
+  get.mfl <-  ratelimitr::limit_rate(.retry_get, ratelimitr::rate(2, 3))
+  get.sleeper <-  ratelimitr::limit_rate(.retry_get, ratelimitr::rate(30, 2))
+  get.flea <-  ratelimitr::limit_rate(.retry_get, ratelimitr::rate(30, 2))
+  get.espn <-  ratelimitr::limit_rate(.retry_get, ratelimitr::rate(30, 2))
+  post <-  ratelimitr::limit_rate(.retry_post, ratelimitr::rate(60, 60))
+
+
+  assign("user_agent",user_agent, envir = .ffscrapr_env)
+  assign("get.mfl",get.mfl, envir = .ffscrapr_env)
+  assign("get.sleeper",get.sleeper, envir = .ffscrapr_env)
+  assign("get.flea",get.flea, envir = .ffscrapr_env)
+  assign("get.espn",get.espn, envir = .ffscrapr_env)
+  assign("post",post, envir = .ffscrapr_env)
 
   # nocov end
 }