Develop

airsenal/framework/data_fetcher.py

@@ -377,7 +377,9 @@ def get_num_free_transfers(self, fpl_team_id=None):
         Requires login
         """
         squad_data = self.get_current_squad_data(fpl_team_id)
-        return squad_data["transfers"]["limit"]
+        return max(
+            0, squad_data["transfers"]["limit"] - squad_data["transfers"]["made"]
+        )
 
     def get_current_bank(self, fpl_team_id=None):
         """

airsenal/framework/optimization_utils.py

@@ -436,7 +436,7 @@ def next_week_transfers(
     """Given a previous strategy and some optimisation constraints, determine the valid
     options for the number of transfers (or chip played) in the following gameweek.
 
-    strat is a tuple (free_transfers, hit_so_far, strat_dict)
+    strat is a tuple (free_transfers, total_points_hits, strat_dict)
     strat_dict must have key chips_played, which is a dict indexed by gameweek with
     possible values None, "wildcard", "free_hit", "bench_boost" or triple_captain"
 
@@ -446,7 +446,9 @@ def next_week_transfers(
     max_free_transfers - maximum number of free transfers saved in the game rules
     (2 before 2024/25, 5 from 2024/25 season)
 
-    Returns (new_transfers, new_ft_available, new_points_hits) tuples.
+    Returns (new_transfers, new_ft_available, total_points_hits, hit_this_gw) tuples.
+        - total_points_hits is the total points hit so far including this gw
+        - hit_this_gw is the points hit incurred this gameweek
     """
     # check that the 'chips' dict we are given makes sense:
     if chips is None:
@@ -524,17 +526,20 @@ def next_week_transfers(
         if allow_triple_captain:
             new_transfers += [f"T{nt}" for nt in ft_choices]
 
-    new_points_hits = [
-        hit_so_far + calc_points_hit(nt, ft_available) for nt in new_transfers
-    ]
+    hit_this_gw = [calc_points_hit(nt, ft_available) for nt in new_transfers]
+    total_points_hits = [hit_so_far + hit for hit in hit_this_gw]
     new_ft_available = [
         calc_free_transfers(nt, ft_available, max_free_transfers)
         for nt in new_transfers
     ]
 
     # return list of (num_transfers, free_transfers, hit_so_far) tuples for each new
     # strategy
-    return list(zip(new_transfers, new_ft_available, new_points_hits, strict=False))
+    return list(
+        zip(
+            new_transfers, new_ft_available, total_points_hits, hit_this_gw, strict=True
+        )
+    )
 
 
 def count_expected_outputs(
@@ -590,7 +595,7 @@ def count_expected_outputs(
                 max_free_transfers=max_free_transfers,
             )
 
-            for n_transfers, new_free_transfers, new_hit in possibilities:
+            for n_transfers, new_free_transfers, new_hit, _ in possibilities:
                 # make a copy of the strategy up to this point, then add on this gw
                 new_dict = deepcopy(s[2])
 

airsenal/scripts/fill_transfersuggestion_table.py

@@ -37,7 +37,6 @@
 from airsenal.framework.optimization_transfers import make_best_transfers
 from airsenal.framework.optimization_utils import (
     MAX_FREE_TRANSFERS,
-    calc_points_hit,
     check_tag_valid,
     count_expected_outputs,
     fill_suggestion_table,
@@ -131,7 +130,15 @@ def optimize(
         else:
             profiler = None
 
-        num_transfers, free_transfers, hit_so_far, squad, strat_dict, sid = status
+        (
+            num_transfers,
+            free_transfers,
+            hit_so_far,
+            hit_this_gw,
+            squad,
+            strat_dict,
+            sid,
+        ) = status
         # num_transfers will be 0, 1, 2, OR 'W' or 'F', OR 'T0', T1', 'T2',
         # OR 'B0', 'B1', or 'B2' (the latter six represent triple captain or
         # bench boost along with 0, 1, or 2 transfers).
@@ -203,18 +210,16 @@ def optimize(
                 (updater, increment, pid) if updater is not None else None,
             )
 
-            points_hit = calc_points_hit(num_transfers, free_transfers)
             discount_factor = get_discount_factor(root_gw, gw)
-            points -= points_hit * discount_factor
+            points -= hit_this_gw * discount_factor
             strat_dict["total_score"] += points
             strat_dict["points_per_gw"][gw] = points
             strat_dict["free_transfers"][gw] = free_transfers
             strat_dict["num_transfers"][gw] = num_transfers
-            strat_dict["points_hit"][gw] = points_hit
+            strat_dict["points_hit"][gw] = hit_this_gw
             strat_dict["discount_factor"][gw] = discount_factor
             strat_dict["players_in"][gw] = transfers["in"]
             strat_dict["players_out"][gw] = transfers["out"]
-
             depth += 1
 
         if depth >= len(gameweek_range):
@@ -240,16 +245,15 @@ def optimize(
                 chips=chips_gw_dict[gw + 1],
                 max_free_transfers=max_free_transfers,
             )
-
             for strat in strategies:
-                # strat: (num_transfers, free_transfers, hit_so_far)
-                num_transfers, free_transfers, hit_so_far = strat
+                num_transfers, free_transfers, hit_so_far, hit_this_gw = strat
 
                 queue.put(
                     (
                         num_transfers,
                         free_transfers,
                         hit_so_far,
+                        hit_this_gw,
                         new_squad,
                         strat_dict,
                         sid,
@@ -319,7 +323,8 @@ def print_strat(strat: dict) -> None:
     print(" ===============================================")
     for gw in gameweeks_as_int:
         print(f"\n =========== Gameweek {gw} ================\n")
-        print(f"Chips played:  {strat['chips_played'][str(gw)]}\n")
+        print(f"Chips played: {strat['chips_played'][str(gw)]}")
+        print(f"Points Hits: {strat['points_hit'][str(gw)]}\n")
         print("Players in:\t\t\tPlayers out:")
         print("-----------\t\t\t------------")
         for i in range(len(strat["players_in"][str(gw)])):
@@ -382,15 +387,20 @@ def discord_payload(strat: dict, lineup: list[str]) -> dict:
 
 
 def print_team_for_next_gw(
-    strat: dict, season: str = CURRENT_SEASON, fpl_team_id: int | None = None
+    strat: dict,
+    season: str = CURRENT_SEASON,
+    fpl_team_id: int | None = None,
+    use_api: bool = False,
 ) -> Squad:
     """
     Display the team (inc. subs and captain) for the next gameweek
     """
     gameweeks_as_str = strat["points_per_gw"].keys()
     gameweeks_as_int = sorted([int(gw) for gw in gameweeks_as_str])
     next_gw = gameweeks_as_int[0]
-    t = get_starting_squad(next_gw=next_gw, season=season, fpl_team_id=fpl_team_id)
+    t = get_starting_squad(
+        next_gw=next_gw, season=season, fpl_team_id=fpl_team_id, use_api=use_api
+    )
     for pidout in strat["players_out"][str(next_gw)]:
         t.remove_player(pidout)
     for pidin in strat["players_in"][str(next_gw)]:
@@ -488,6 +498,7 @@ def run_optimization(
             apifetcher=fetcher,
             is_replay=is_replay,
         )
+    print(f"Starting with {num_free_transfers} free transfers")
 
     # create the output directory for temporary json files
     # giving the points prediction for each strategy
@@ -591,7 +602,7 @@ def update_progress(increment=1, index=None):
         processor.start()
         procs.append(processor)
     # add starting node to the queue
-    squeue.put((0, num_free_transfers, 0, starting_squad, {}, "starting"))
+    squeue.put((0, num_free_transfers, 0, 0, starting_squad, {}, "starting"))
 
     for i, p in enumerate(procs):
         progress_bars[i].close()
@@ -620,7 +631,7 @@ def update_progress(increment=1, index=None):
     print(f"Best score: {best_strategy['total_score']}")
     print_strat(best_strategy)
     best_squad = print_team_for_next_gw(
-        best_strategy, season=season, fpl_team_id=fpl_team_id
+        best_strategy, season=season, fpl_team_id=fpl_team_id, use_api=use_api
     )
 
     # If a valid discord webhook URL has been stored