Test full process with datasets

background_task.py

@@ -108,19 +108,11 @@ class Matchmaking:
             data_dict["model"].append(model.name)
             data_dict["elo"].append(model.elo)
             data_dict["games_played"].append(model.games_played)
-
         df = pd.DataFrame(data_dict)
-        fileobj = open('env_elos/elo.csv', 'w')
-        df.to_csv(fileobj, index=False)
-        api.upload_file(
-            fileobj,
-            "env_elos/elo.csv",
-            "CarlCochet/BotFights",
-            "Update elos",
-        )
-        df_matches = pd.DataFrame(self.matches)
-        date = datetime.now()
-        df_matches.to_csv(f"match_history/{date.strftime('%Y-%m-%d_%H-%M-%S_%f')}.csv", index=False)
+        df.to_csv(os.path.join(DATASET_REPO_URL, "resolve", "main", ELO_FILE))
+        # df_matches = pd.DataFrame(self.matches)
+        # date = datetime.now()
+        # df_matches.to_csv(f"match_history/{date.strftime('%Y-%m-%d_%H-%M-%S_%f')}.csv", index=False)
 
 
 def match(model1, model2) -> float:
@@ -148,7 +140,7 @@ def get_models_list() -> list:
     """
     models = []
     models_names = []
-    data = pd.read_csv("env_elos/elo.csv")
+    data = pd.read_csv(os.path.join(DATASET_REPO_URL, "resolve", "main", ELO_FILE))
     # models_on_hub = api.list_models(filter=["reinforcement-learning", env, "stable-baselines3"])
     models_on_hub = []
     for i, row in data.iterrows():