🔧 python 3.10 upgrade (#391)

* python 3.10 upgrade

---------

Co-authored-by: Philippe Miron <philippe.miron@dtn.com>

.github/workflows/docs.yml

@@ -15,7 +15,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ["ubuntu-latest"]
-        python-version: ["3.9"]
+        python-version: ["3.10"]
     steps:
     - uses: actions/checkout@v4
     - uses: mamba-org/setup-micromamba@v1

.github/workflows/pypi.yml

@@ -20,7 +20,7 @@ jobs:
       - uses: actions/setup-python@v5
         name: Install Python
         with:
-          python-version: 3.9
+          python-version: 3.10
       - name: Install build dependencies
         run: |
           python -m pip install --upgrade pip
@@ -54,7 +54,7 @@ jobs:
       - uses: actions/setup-python@v5
         name: Install Python
         with:
-          python-version: 3.9
+          python-version: 3.10
       - uses: actions/download-artifact@v4
         with:
           name: releases

clouddrift/adapters/andro.py

@@ -21,7 +21,6 @@
 import tempfile
 import warnings
 from datetime import datetime
-from typing import Union
 
 import numpy as np
 import pandas as pd
@@ -35,7 +34,7 @@
 ANDRO_VERSION = "2022-03-04"
 
 
-def to_xarray(tmp_path: Union[str, None] = None):
+def to_xarray(tmp_path: str | None = None):
     if tmp_path is None:
         tmp_path = ANDRO_TMP_PATH
         os.makedirs(tmp_path, exist_ok=True)

clouddrift/adapters/gdp1h.py

@@ -10,8 +10,8 @@
 import tempfile
 import urllib.request
 import warnings
+from collections.abc import Sequence
 from datetime import datetime, timedelta
-from typing import Optional, Sequence, Union
 
 import numpy as np
 import xarray as xr
@@ -59,8 +59,8 @@
 def download(
     url: str,
     tmp_path: str,
-    drifter_ids: Union[list[int], None] = None,
-    n_random_id: Union[int, None] = None,
+    drifter_ids: list[int] | None = None,
+    n_random_id: int | None = None,
 ):
     """Download individual NetCDF files from the AOML server.
 
@@ -523,10 +523,10 @@ def preprocess(index: int, **kwargs) -> xr.Dataset:
 
 
 def to_raggedarray(
-    drifter_ids: Optional[list[int]] = None,
-    n_random_id: Optional[int] = None,
+    drifter_ids: list[int] | None = None,
+    n_random_id: int | None = None,
     url: str = GDP_DATA_URL,
-    tmp_path: Optional[str] = None,
+    tmp_path: str | None = None,
 ) -> RaggedArray:
     """Download and process individual GDP hourly files and return a RaggedArray
     instance with the data.
@@ -610,11 +610,11 @@ def to_raggedarray(
 
     # set dynamic global attributes
     if ra.attrs_global:
-        ra.attrs_global[
-            "time_coverage_start"
-        ] = f"{datetime(1970,1,1) + timedelta(seconds=int(np.min(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
-        ra.attrs_global[
-            "time_coverage_end"
-        ] = f"{datetime(1970,1,1) + timedelta(seconds=int(np.max(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+        ra.attrs_global["time_coverage_start"] = (
+            f"{datetime(1970,1,1) + timedelta(seconds=int(np.min(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+        )
+        ra.attrs_global["time_coverage_end"] = (
+            f"{datetime(1970,1,1) + timedelta(seconds=int(np.max(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+        )
 
     return ra

clouddrift/adapters/gdp6h.py

@@ -10,7 +10,6 @@
 import tempfile
 import urllib.request
 import warnings
-from typing import Optional, Union
 
 import numpy as np
 import xarray as xr
@@ -39,8 +38,8 @@
 def download(
     url: str,
     tmp_path: str,
-    drifter_ids: Union[list, None] = None,
-    n_random_id: Union[int, None] = None,
+    drifter_ids: list | None = None,
+    n_random_id: int | None = None,
 ):
     """Download individual NetCDF files from the AOML server.
 
@@ -448,8 +447,8 @@ def preprocess(index: int, **kwargs) -> xr.Dataset:
 
 
 def to_raggedarray(
-    drifter_ids: Optional[list[int]] = None,
-    n_random_id: Optional[int] = None,
+    drifter_ids: list[int] | None = None,
+    n_random_id: int | None = None,
     tmp_path: str = GDP_TMP_PATH,
 ) -> RaggedArray:
     """Download and process individual GDP 6-hourly files and return a
@@ -518,11 +517,11 @@ def to_raggedarray(
     )
 
     # update dynamic global attributes
-    ra.attrs_global[
-        "time_coverage_start"
-    ] = f"{datetime.datetime(1970,1,1) + datetime.timedelta(seconds=int(np.min(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
-    ra.attrs_global[
-        "time_coverage_end"
-    ] = f"{datetime.datetime(1970,1,1) + datetime.timedelta(seconds=int(np.max(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+    ra.attrs_global["time_coverage_start"] = (
+        f"{datetime.datetime(1970,1,1) + datetime.timedelta(seconds=int(np.min(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+    )
+    ra.attrs_global["time_coverage_end"] = (
+        f"{datetime.datetime(1970,1,1) + datetime.timedelta(seconds=int(np.max(ra.coords['time']))):%Y-%m-%d:%H:%M:%SZ}"
+    )
 
     return ra

clouddrift/adapters/mosaic.py

@@ -22,7 +22,6 @@
 import xml.etree.ElementTree as ET
 from datetime import datetime
 from io import BytesIO
-from typing import Tuple
 
 import numpy as np
 import pandas as pd
@@ -79,7 +78,7 @@ def get_dataframes() -> tuple[pd.DataFrame, pd.DataFrame]:
     return obs_df, sensors
 
 
-def get_file_urls(xml: bytes) -> Tuple[list[str], list[str]]:
+def get_file_urls(xml: bytes) -> tuple[list[str], list[str]]:
     """Pass the MOSAiC XML string and return the list of filenames and URLs."""
     filenames = [
         tag.text

clouddrift/adapters/subsurface_floats.py

@@ -14,8 +14,8 @@
 import os
 import tempfile
 import warnings
+from collections.abc import Hashable
 from datetime import datetime
-from typing import Hashable, List, Union
 
 import numpy as np
 import pandas as pd
@@ -38,7 +38,7 @@ def download(file: str):
 
 
 def to_xarray(
-    tmp_path: Union[str, None] = None,
+    tmp_path: str | None = None,
 ):
     if tmp_path is None:
         tmp_path = SUBSURFACE_FLOATS_TMP_PATH
@@ -49,7 +49,7 @@ def to_xarray(
     source_data = scipy.io.loadmat(local_file)
 
     # metadata
-    meta_variables: List[Hashable] = [
+    meta_variables: list[Hashable] = [
         "expList",
         "expName",
         "expOrg",

clouddrift/adapters/utils.py

@@ -2,9 +2,9 @@
 import logging
 import os
 import traceback
+from collections.abc import Callable, Sequence
 from datetime import datetime
 from io import BufferedIOBase, StringIO
-from typing import Callable, Sequence, Tuple, Union
 
 import requests
 from requests import Response
@@ -32,10 +32,10 @@
 
 
 def download_with_progress(
-    download_map: Sequence[Tuple[str, Union[BufferedIOBase, str], Union[float, None]]],
-    show_list_progress: Union[bool, None] = None,
+    download_map: Sequence[tuple[str, BufferedIOBase | str, float | None]],
+    show_list_progress: bool | None = None,
     desc: str = "Downloading files",
-    custom_retry_protocol: Union[Callable[[WrappedFn], WrappedFn], None] = None,
+    custom_retry_protocol: Callable[[WrappedFn], WrappedFn] | None = None,
 ):
     if show_list_progress is None:
         show_list_progress = len(download_map) > 20
@@ -45,9 +45,7 @@ def download_with_progress(
         retry_protocol = custom_retry_protocol  # type: ignore
 
     executor = concurrent.futures.ThreadPoolExecutor()
-    futures: dict[
-        concurrent.futures.Future, Tuple[str, Union[BufferedIOBase, str]]
-    ] = dict()
+    futures: dict[concurrent.futures.Future, tuple[str, BufferedIOBase | str]] = dict()
     bar = None
 
     for src, dst, exp_size in download_map:
@@ -93,7 +91,7 @@ def download_with_progress(
 
 def _download_with_progress(
     url: str,
-    output: Union[BufferedIOBase, str],
+    output: BufferedIOBase | str,
     expected_size: float,
     show_progress: bool,
 ):
@@ -121,8 +119,8 @@ def _download_with_progress(
     _logger.debug(f"Downloading from {url} to {output}...")
 
     force_close = False
-    response: Union[Response, None] = None
-    buffer: Union[BufferedIOBase, None] = None
+    response: Response | None = None
+    buffer: BufferedIOBase | None = None
     bar = None
 
     try:

clouddrift/adapters/yomaha.py

@@ -24,7 +24,6 @@
 import warnings
 from datetime import datetime
 from io import BytesIO
-from typing import Union
 
 import numpy as np
 import pandas as pd
@@ -71,7 +70,7 @@ def download(tmp_path: str):
         buffer.close()
 
 
-def to_xarray(tmp_path: Union[str, None] = None):
+def to_xarray(tmp_path: str | None = None):
     if tmp_path is None:
         tmp_path = YOMAHA_TMP_PATH
         os.makedirs(tmp_path, exist_ok=True)

clouddrift/datasets.py

@@ -6,7 +6,7 @@
 """
 
 import os
-from typing import Callable
+from collections.abc import Callable
 
 import xarray as xr
 

clouddrift/kinematics.py

@@ -2,8 +2,6 @@
 Functions for kinematic computations.
 """
 
-from typing import Optional, Tuple, Union
-
 import numpy as np
 import pandas as pd
 import xarray as xr
@@ -23,9 +21,9 @@
 
 
 def kinetic_energy(
-    u: Union[float, list, np.ndarray, xr.DataArray, pd.Series],
-    v: Optional[Union[float, list, np.ndarray, xr.DataArray, pd.Series]] = None,
-) -> Union[float, np.ndarray, xr.DataArray]:
+    u: float | list | np.ndarray | xr.DataArray | pd.Series,
+    v: float | list | np.ndarray | xr.DataArray | pd.Series | None = None,
+) -> float | np.ndarray | xr.DataArray:
     """Compute kinetic energy from zonal and meridional velocities.
 
     Parameters
@@ -65,10 +63,10 @@ def kinetic_energy(
 def inertial_oscillation_from_position(
     longitude: np.ndarray,
     latitude: np.ndarray,
-    relative_bandwidth: Optional[float] = None,
-    wavelet_duration: Optional[float] = None,
-    time_step: Optional[float] = 3600.0,
-    relative_vorticity: Optional[Union[float, np.ndarray]] = 0.0,
+    relative_bandwidth: float | None = None,
+    wavelet_duration: float | None = None,
+    time_step: float | None = 3600.0,
+    relative_vorticity: float | np.ndarray | None = 0.0,
 ) -> np.ndarray:
     """Extract inertial oscillations from consecutive geographical positions.
 
@@ -262,11 +260,11 @@ def inertial_oscillation_from_position(
 
 
 def residual_position_from_displacement(
-    longitude: Union[float, np.ndarray, xr.DataArray],
-    latitude: Union[float, np.ndarray, xr.DataArray],
-    x: Union[float, np.ndarray],
-    y: Union[float, np.ndarray],
-) -> Union[Tuple[float], Tuple[np.ndarray]]:
+    longitude: float | np.ndarray | xr.DataArray,
+    latitude: float | np.ndarray | xr.DataArray,
+    x: float | np.ndarray,
+    y: float | np.ndarray,
+) -> tuple[float] | tuple[np.ndarray]:
     """
     Return residual longitudes and latitudes along a trajectory on the spherical Earth
     after correcting for zonal and meridional displacements x and y in meters.
@@ -326,10 +324,10 @@ def position_from_velocity(
     time: np.ndarray,
     x_origin: float,
     y_origin: float,
-    coord_system: Optional[str] = "spherical",
-    integration_scheme: Optional[str] = "forward",
-    time_axis: Optional[int] = -1,
-) -> Tuple[np.ndarray, np.ndarray]:
+    coord_system: str | None = "spherical",
+    integration_scheme: str | None = "forward",
+    time_axis: int | None = -1,
+) -> tuple[np.ndarray, np.ndarray]:
     """Compute positions from arrays of velocities and time and a pair of origin
     coordinates.
 
@@ -530,10 +528,10 @@ def velocity_from_position(
     x: np.ndarray,
     y: np.ndarray,
     time: np.ndarray,
-    coord_system: Optional[str] = "spherical",
-    difference_scheme: Optional[str] = "forward",
-    time_axis: Optional[int] = -1,
-) -> Tuple[xr.DataArray, xr.DataArray]:
+    coord_system: str | None = "spherical",
+    difference_scheme: str | None = "forward",
+    time_axis: int | None = -1,
+) -> tuple[xr.DataArray, xr.DataArray]:
     """Compute velocity from arrays of positions and time.
 
     x and y can be provided as longitude and latitude in degrees if
@@ -779,9 +777,9 @@ def spin(
     u: np.ndarray,
     v: np.ndarray,
     time: np.ndarray,
-    difference_scheme: Optional[str] = "forward",
-    time_axis: Optional[int] = -1,
-) -> Union[float, np.ndarray]:
+    difference_scheme: str | None = "forward",
+    time_axis: int | None = -1,
+) -> float | np.ndarray:
     """Compute spin continuously from velocities and times.
 
     Spin is traditionally (Sawford, 1999; Veneziani et al., 2005) defined as