Change file structure

app.py

@@ -11,11 +11,13 @@ from apscheduler.schedulers.background import BackgroundScheduler
 
 
 DATASET_REPO_URL = "https://huggingface.co/datasets/CarlCochet/BotFightData"
-ELO_FILENAME = "elo.csv"
-ELO_DIR = "soccer_elo"
-ELO_FILE = os.path.join(ELO_DIR, ELO_FILENAME)
+ELO_FILENAME = "soccer_elo.csv"
 HF_TOKEN = os.environ.get("HF_TOKEN")
 
+repo = Repository(
+    clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
+)
+
 block = gr.Blocks()
 matchmaking = Matchmaking()
 api = HfApi()
@@ -24,10 +26,6 @@ scheduler = BackgroundScheduler()
 scheduler.add_job(func=init_matchmaking, trigger="interval", seconds=15000)
 scheduler.start()
 
-repo = Repository(
-    local_dir=ELO_DIR, clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
-)
-
 
 def update_elos():
     matchmaking.read_history()
@@ -36,7 +34,7 @@ def update_elos():
 
 
 def get_elo_data() -> pd.DataFrame:
-    data = pd.read_csv(os.path.join(DATASET_REPO_URL, "resolve", "main", ELO_FILE))
+    data = pd.read_csv(os.path.join(DATASET_REPO_URL, "resolve", "main", ELO_FILENAME))
     return data
 
 

background_task.py

@@ -6,13 +6,11 @@ from huggingface_hub import HfApi, Repository
 
 
 DATASET_REPO_URL = "https://huggingface.co/datasets/CarlCochet/BotFightData"
-ELO_FILENAME = "elo.csv"
-ELO_DIR = "soccer_elo"
-ELO_FILE = os.path.join(ELO_DIR, ELO_FILENAME)
+ELO_FILENAME = "soccer_elo.csv"
 HF_TOKEN = os.environ.get("HF_TOKEN")
 
 repo = Repository(
-    local_dir=ELO_DIR, clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
+    clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
 )
 
 
@@ -114,7 +112,7 @@ class Matchmaking:
             data_dict["games_played"].append(model.games_played)
         df = pd.DataFrame(data_dict)
         print(df.head())
-        df.to_csv(ELO_FILE)
+        df.to_csv(ELO_FILENAME)
         repo.push_to_hub(commit_message="Update ELO")
         # df_matches = pd.DataFrame(self.matches)
         # date = datetime.now()
@@ -146,7 +144,7 @@ def get_models_list() -> list:
     """
     models = []
     models_names = []
-    data = pd.read_csv(os.path.join(DATASET_REPO_URL, "resolve", "main", ELO_FILE))
+    data = pd.read_csv(os.path.join(DATASET_REPO_URL, "resolve", "main", ELO_FILENAME))
     # models_on_hub = api.list_models(filter=["reinforcement-learning", env, "stable-baselines3"])
     models_on_hub = []
     for i, row in data.iterrows():