Mypy fixes

src/meteole/forecast.py

@@ -6,7 +6,6 @@
 import tempfile
 from abc import abstractmethod
 from pathlib import Path
-from typing import Dict, List, Optional
 
 import pandas as pd
 import xarray as xr
@@ -59,7 +58,7 @@ def __init__(
         self.precision = precision
         self._validate_parameters()
 
-        self.folderpath: Optional[Path] = None
+        self.folderpath: Path | None = None
         self.get_capabilities()
 
     def get_capabilities(self) -> pd.DataFrame:
@@ -111,7 +110,7 @@ def _get_available_feature(grid_axis, feature_name):
             features = [int(feature) for feature in features]
         return features
 
-    def get_coverage_description(self, coverage_id: str) -> Dict:
+    def get_coverage_description(self, coverage_id: str) -> dict:
         """This endpoint returns the available axis (times, heights) to properly query coverage
 
         TODO: other informations can be fetched from this endpoint, not yet implemented.
@@ -136,7 +135,7 @@ def get_coverage_description(self, coverage_id: str) -> Dict:
 
     def get_coverages(
         self,
-        coverage_ids: List[str],
+        coverage_ids: list[str],
         lat: tuple = const.FRANCE_METRO_LATITUDES,
         long: tuple = const.FRANCE_METRO_LONGITUDES,
     ) -> pd.DataFrame:
@@ -159,8 +158,8 @@ def get_coverages(
     def _get_coverage_id(
         self,
         indicator: str,
-        run: Optional[str] = None,
-        interval: Optional[str] = None,
+        run: str | None = None,
+        interval: str | None = None,
     ) -> str:
         """
         Get a coverage_id from `capabilities`.
@@ -234,9 +233,9 @@ def get_coverage(
         indicator: str | None = None,
         lat: tuple = const.FRANCE_METRO_LATITUDES,
         long: tuple = const.FRANCE_METRO_LONGITUDES,
-        heights: List[int] | None = None,
-        pressures: List[int] | None = None,
-        forecast_horizons: List[int] | None = None,
+        heights: list[int] | None = None,
+        pressures: list[int] | None = None,
+        forecast_horizons: list[int] | None = None,
         run: str | None = None,
         interval: str | None = None,
         coverage_id: str = "",
@@ -288,8 +287,8 @@ def get_coverage(
         return pd.concat(df_list, axis=0).reset_index(drop=True)
 
     def _raise_if_invalid_or_fetch_default(
-        self, param_name: str, inputs: List[int] | None, availables: List[int]
-    ) -> List[int]:
+        self, param_name: str, inputs: list[int] | None, availables: list[int]
+    ) -> list[int]:
         """
         Checks if the elements in `inputs` are in `availables` and raises a ValueError if not.
         If `inputs` is empty or None, uses the first element from `availables` as the default value.
@@ -345,7 +344,7 @@ def instant_indicators(self) -> str:
         """The list of instant indicators"""
         pass
 
-    def _get_capabilities(self) -> Dict:
+    def _get_capabilities(self) -> dict:
         """The Capabilities of the AROME/ARPEGE service."""
 
         url = f"{self.base_url}/{self.entry_point}/GetCapabilities"

src/meteole/raster.py

@@ -1,6 +1,4 @@
 """Functionnalities to deal with the raster data"""
-from typing import Optional
-
 import cartopy.crs as ccrs
 import matplotlib.pyplot as plt
 import rasterio
@@ -19,7 +17,7 @@ def plot_tiff_file(
     filename,
     data_type: str,
     unit: str,
-    title: Optional[str] = None,
+    title: str | None = None,
 ):
     """
     Plot a tiff file.

src/meteole/vigilance.py

@@ -1,6 +1,5 @@
 import logging
 from io import BytesIO
-from typing import Tuple
 
 import matplotlib.image as mpimg
 import matplotlib.pyplot as plt
@@ -89,7 +88,7 @@ def get_carte_vigilance(self) -> dict:
 
         return req.json()
 
-    def get_phenomenon(self) -> Tuple[pd.DataFrame, pd.DataFrame]:
+    def get_phenomenon(self) -> tuple[pd.DataFrame, pd.DataFrame]:
         """
         get risk prediction by phenomenon and by domain
         Returns: