Fix imports as a result of removing the Hero class.

database/database.py

@@ -1,14 +1,8 @@
-import datetime
 import threading
-
 from mysql.connector import pooling
-
 import leaderboards
-from heroes import Hero
-
 lock = threading.Lock()
 
-
 class DatabaseAccess:
     def __init__(
         self, user: str, password: str, host: str, port: str | int, database: str
@@ -117,17 +111,11 @@ def add_leaderboard_entry(
                 (
                     leaderboard_entry.region.name,
                     leaderboard_entry.role.name,
-                    leaderboard_entry.games,
+                    0, # games played, legacy
                     # can be string or Hero object. If it's a Hero object, get the name.
-                    leaderboard_entry.heroes[0].name
-                    if isinstance(leaderboard_entry.heroes[0], Hero)
-                    else leaderboard_entry.heroes[0],
-                    leaderboard_entry.heroes[1].name
-                    if isinstance(leaderboard_entry.heroes[1], Hero)
-                    else leaderboard_entry.heroes[1],
-                    leaderboard_entry.heroes[2].name
-                    if isinstance(leaderboard_entry.heroes[2], Hero)
-                    else leaderboard_entry.heroes[2],
+                    leaderboard_entry.heroes[0],
+                    leaderboard_entry.heroes[1],
+                    leaderboard_entry.heroes[2],
                 ),
             )
             connection.commit()
@@ -170,7 +158,6 @@ def get_all_records(self, seasonNumber: str) -> list[leaderboards.LeaderboardEnt
                     ],
                     role=leaderboards.Role[line[2]],
                     region=leaderboards.Region[line[1]],
-                    games=line[3],
                 )
             )
         return results

heroes/hero_comparison.py

@@ -142,7 +142,7 @@ def predict_hero_name(self, image: Image, model_directory: Path) -> str:
         NNModel = importlib.import_module(f"models.{model_directory.name}.model").NNModel
         transformer = importlib.import_module(f"models.{model_directory.name}.model").transformer
 
-        st_dict = torch.load("./model_save.pth")
+        st_dict = torch.load(model_directory / "model.pth")
         model = NNModel(num_classes=40)
         model.to(device)
         model.load_state_dict(st_dict)

statistic/__init__.py

@@ -2,21 +2,13 @@
 
 import database
 import leaderboards
-from heroes import Hero, Heroes
+from heroes import Heroes
 
 
 def convert_dict_to_hero_count_array(data: dict) -> list[dict]:
     return [{"hero": i[0], "count": i[1]} for i in data.items()]
 
 
-def extract_games_played(i: leaderboards.LeaderboardEntry):
-    return i.games
-
-
-def filter_games_results(i: leaderboards.LeaderboardEntry) -> bool:
-    return 25 <= i.games <= 725
-
-
 def get_occurrences(
     *,
     data: list[leaderboards.LeaderboardEntry],
@@ -96,7 +88,7 @@ def get_occurrences_most_played(
         if entry.role not in acceptedRoles:
             continue
 
-        mostPlayedHero: Hero | str = entry.heroes[mostPlayedSlot]
+        mostPlayedHero: str = entry.heroes[mostPlayedSlot]
         if isinstance(mostPlayedHero, str):
             if mostPlayedHero in results:
                 results[mostPlayedHero] += 1
@@ -115,26 +107,6 @@ def get_occurrences_most_played(
     )
 
 
-def get_avg_games_played_by_region(
-    *, data: list[leaderboards.LeaderboardEntry], region: leaderboards.Region
-) -> list[dict]:
-    results: dict[str, float] = {}
-
-    for entry in filter(filter_games_results, data):
-        if entry.region != region:
-            continue
-        if entry.role.name in results:
-            results[entry.role.name] += entry.games / 500
-            continue
-        results[entry.role.name] = entry.games / 500
-
-    return sorted(
-        convert_dict_to_hero_count_array(results),
-        key=lambda x: x["count"],
-        reverse=True,
-    )
-
-
 def convert_count_dict_to_array(data: list[dict]) -> list[int | float]:
     return [entry["count"] for entry in data]
 
@@ -151,21 +123,6 @@ def get_stdev(data: list[dict]) -> float:
     return statistics.stdev(convert_count_dict_to_array(data))
 
 
-def get_games_played_max(data: list[leaderboards.LeaderboardEntry]) -> int:
-    # return max(map(extract_games_played, filter(filter_games_results, data)))
-    return 0
-
-
-def get_games_played_min(data: list[leaderboards.LeaderboardEntry]) -> int:
-    # return min(map(extract_games_played, filter(filter_games_results, data)))
-    return 0
-
-
-def get_games_played_total(data: list[leaderboards.LeaderboardEntry]) -> int:
-    # return sum(map(extract_games_played, filter(filter_games_results, data)))
-    return 0
-
-
 def get_number_of_ohp(data: list[leaderboards.LeaderboardEntry]) -> int:
     return len([i for i in data if i.heroes[1] == "Blank" or i.heroes[1] == "Blank2"])