improved python version compatibility

src/enfobench/__version__.py

@@ -1 +1 @@
-__version__ = "0.0.10"
+__version__ = "0.0.11"

src/enfobench/evaluation/_cross_validate.py

@@ -1,6 +1,4 @@
-from __future__ import annotations
-
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Union, List, Optional
 
 import pandas as pd
 from tqdm import tqdm
@@ -44,13 +42,13 @@ def generate_cutoff_dates(
 
 
 def cross_validate(
-    model: Model | ForecastClient,
+    model: Union[Model, ForecastClient],
     start: pd.Timestamp,
     horizon: pd.Timedelta,
     step: pd.Timedelta,
     y: pd.Series,
-    level: list[int] | None = None,
-    freq: str | None = None,
+    level: Optional[List[int]] = None,
+    freq: Optional[str] = None,
 ) -> pd.DataFrame:
     """Cross-validate a model.
 

src/enfobench/evaluation/_evaluate.py

@@ -1,4 +1,4 @@
-from typing import Callable
+from typing import Callable, Dict
 
 import pandas as pd
 
@@ -24,8 +24,8 @@ def evaluate_metric_on_forecast(forecast: pd.DataFrame, metric: Callable) -> flo
 
 
 def evaluate_metrics_on_forecast(
-    forecast: pd.DataFrame, metrics: dict[str, Callable]
-) -> dict[str, float]:
+    forecast: pd.DataFrame, metrics: Dict[str, Callable]
+) -> Dict[str, float]:
     """Evaluate multiple metrics on a single forecast.
 
     Parameters:
@@ -71,7 +71,7 @@ def evaluate_metric_on_forecasts(forecasts: pd.DataFrame, metric: Callable) -> p
 
 
 def evaluate_metrics_on_forecasts(
-    forecasts: pd.DataFrame, metrics: dict[str, Callable]
+    forecasts: pd.DataFrame, metrics: Dict[str, Callable]
 ) -> pd.DataFrame:
     """Evaluate multiple metrics on a set of forecasts made at different cutoff points.
 

src/enfobench/evaluation/client.py

@@ -1,6 +1,5 @@
-from __future__ import annotations
-
 import io
+from typing import Dict, Union, Optional, List
 
 import pandas as pd
 import requests
@@ -39,9 +38,9 @@ def predict(
         horizon: int,
         y: pd.Series,
         # X: pd.DataFrame,
-        level: list[int] | None = None,
+        level: Optional[List[int]] = None,
     ) -> pd.DataFrame:
-        params: dict[str, int | list[int]] = {
+        params: Dict[str, Union[int, List[int]]] = {
             "horizon": horizon,
         }
         if level is not None:

src/enfobench/evaluation/protocols.py

@@ -1,7 +1,5 @@
-from __future__ import annotations
-
 from enum import Enum
-from typing import Any, Protocol
+from typing import Any, Protocol, Optional, List
 
 import pandas as pd
 from pydantic import BaseModel
@@ -32,8 +30,8 @@ def predict(
         self,
         h: int,
         y: pd.Series,
-        X: pd.DataFrame | None = None,
-        level: list[int] | None = None,
+        X: Optional[pd.DataFrame] = None,
+        level: Optional[List[int]] = None,
         **kwargs,
     ) -> pd.DataFrame:
         ...

src/enfobench/evaluation/server.py

@@ -1,7 +1,5 @@
-from __future__ import annotations
-
 import io
-from typing import Annotated, List
+from typing import Annotated, List, Optional
 
 import pandas as pd
 import pkg_resources
@@ -33,7 +31,7 @@ async def predict(
         horizon: int,
         y: Annotated[bytes, File()],
         # X: Annotated[bytes, File()],
-        level: List[int] | None = Query(None),
+        level: Optional[List[int]] = Query(None),
     ):
         y_df = pd.read_parquet(io.BytesIO(y))
         # X_df = pd.read_parquet(io.BytesIO(X))