Merge pull request #329 from ocefpaf/py311

Support Python 3.10 and up

.github/workflows/tests.yml

@@ -10,7 +10,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        python-version: ["3.8", "3.9", "3.10", "3.11"]
+        python-version: ["3.10", "3.11", "3.12"]
         os: [windows-latest, ubuntu-latest, macos-latest]
       fail-fast: false
 

erddapy/core/griddap.py

@@ -1,21 +1,19 @@
 """Griddap handling."""
 
 import functools
-from typing import Dict, List, Optional, Tuple, Union
 
 import pandas as pd
 
 from erddapy.core.url import urlopen
 
-ListLike = Union[List[str], Tuple[str]]
-OptionalStr = Optional[str]
+ListLike = list[str] | tuple[str]
 
 
 @functools.lru_cache(maxsize=128)
 def _griddap_get_constraints(
     dataset_url: str,
     step: int,
-) -> Tuple[Dict, List, List]:
+) -> tuple[dict, list, list]:
     """
     Fetch metadata of griddap dataset and set initial constraints.
 
@@ -64,7 +62,7 @@ def _griddap_get_constraints(
     return constraints_dict, dim_names, variable_names
 
 
-def _griddap_check_constraints(user_constraints: Dict, original_constraints: Dict):
+def _griddap_check_constraints(user_constraints: dict, original_constraints: dict):
     """Check that constraints changed by user match those expected by dataset."""
     if user_constraints.keys() != original_constraints.keys():
         raise ValueError(

erddapy/core/interfaces.py

@@ -5,7 +5,7 @@
 XArray, Iris, etc. objects.
 """
 
-from typing import TYPE_CHECKING, Dict, Optional
+from typing import TYPE_CHECKING
 
 import pandas as pd
 
@@ -19,8 +19,8 @@
 
 def to_pandas(
     url: str,
-    requests_kwargs: Optional[Dict] = None,
-    pandas_kwargs: Optional[Dict] = None,
+    requests_kwargs: dict | None = None,
+    pandas_kwargs: dict | None = None,
 ) -> "pd.DataFrame":
     """
     Convert a URL to Pandas DataFrame.
@@ -39,7 +39,7 @@ def to_pandas(
 def to_ncCF(
     url: str,
     protocol: str = None,
-    requests_kwargs: Optional[Dict] = None,
+    requests_kwargs: dict | None = None,
 ) -> "Dataset":
     """
     Convert a URL to a netCDF4 Dataset.
@@ -58,8 +58,8 @@ def to_ncCF(
 def to_xarray(
     url: str,
     response="opendap",
-    requests_kwargs: Optional[Dict] = None,
-    xarray_kwargs: Optional[Dict] = None,
+    requests_kwargs: dict | None = None,
+    xarray_kwargs: dict | None = None,
 ) -> "xr.Dataset":
     """
     Convert a URL to an xarray dataset.
@@ -83,8 +83,8 @@ def to_xarray(
 
 def to_iris(
     url: str,
-    requests_kwargs: Optional[Dict] = None,
-    iris_kwargs: Optional[Dict] = None,
+    requests_kwargs: dict | None = None,
+    iris_kwargs: dict | None = None,
 ):
     """
     Convert a URL to an iris CubeList.

erddapy/core/netcdf.py

@@ -1,15 +1,16 @@
 """Handles netCDF responses."""
 
 import platform
+from collections.abc import Generator
 from contextlib import contextmanager
 from pathlib import Path
-from typing import BinaryIO, Dict, Generator, Optional
+from typing import BinaryIO
 from urllib.parse import urlparse
 
 from erddapy.core.url import urlopen
 
 
-def _nc_dataset(url, requests_kwargs: Optional[Dict] = None):
+def _nc_dataset(url, requests_kwargs: dict | None = None):
     """Return a netCDF4-python Dataset from memory and fallbacks to disk if that fails."""
     from netCDF4 import Dataset
 

erddapy/core/url.py

@@ -5,15 +5,15 @@
 import io
 from collections import OrderedDict
 from datetime import datetime
-from typing import BinaryIO, Dict, List, Optional, Tuple, Union
+from typing import BinaryIO
 from urllib import parse
 
 import httpx
 import pytz
 from pandas import to_datetime
 
-ListLike = Union[List[str], Tuple[str]]
-OptionalStr = Optional[str]
+ListLike = list[str] | tuple[str]
+OptionalStr = str | None
 
 
 def _sort_url(url):
@@ -39,7 +39,7 @@ def _sort_url(url):
 
 
 @functools.lru_cache(maxsize=128)
-def _urlopen(url: str, auth: Optional[tuple] = None, **kwargs: Dict) -> BinaryIO:
+def _urlopen(url: str, auth: tuple | None = None, **kwargs: dict) -> BinaryIO:
     if "timeout" not in kwargs.keys():
         kwargs["timeout"] = 60
     response = httpx.get(url, follow_redirects=True, auth=auth, **kwargs)
@@ -52,7 +52,7 @@ def _urlopen(url: str, auth: Optional[tuple] = None, **kwargs: Dict) -> BinaryIO
 
 def urlopen(
     url: str,
-    requests_kwargs: Optional[Dict] = None,
+    requests_kwargs: dict | None = None,
 ) -> BinaryIO:
     """Thin wrapper around httpx get content.
 
@@ -68,7 +68,7 @@ def urlopen(
 
 
 @functools.lru_cache(maxsize=128)
-def check_url_response(url: str, **kwargs: Dict) -> str:
+def check_url_response(url: str, **kwargs: dict) -> str:
     """
     Shortcut to `raise_for_status` instead of fetching the whole content.
 
@@ -81,7 +81,7 @@ def check_url_response(url: str, **kwargs: Dict) -> str:
     return url
 
 
-def _distinct(url: str, distinct: Optional[bool] = False) -> str:
+def _distinct(url: str, distinct: bool | None = False) -> str:
     """
     Sort all of the rows in the results table.
 
@@ -114,7 +114,7 @@ def _multi_urlopen(url: str) -> BinaryIO:
     return data
 
 
-def _quote_string_constraints(kwargs: Dict) -> Dict:
+def _quote_string_constraints(kwargs: dict) -> dict:
     """
     Quote constraints of String variables.
 
@@ -126,7 +126,7 @@ def _quote_string_constraints(kwargs: Dict) -> Dict:
     }
 
 
-def _format_constraints_url(kwargs: Dict) -> str:
+def _format_constraints_url(kwargs: dict) -> str:
     """Join the constraint variables with separator '&' to add to the download link."""
     return "".join([f"&{k}{v}" for k, v in kwargs.items()])
 
@@ -138,7 +138,7 @@ def _check_substrings(constraint):
 
 
 def parse_dates(
-    date_time: Union[datetime, str],
+    date_time: datetime | str,
     dayfirst=False,
     yearfirst=False,
 ) -> float:
@@ -170,7 +170,7 @@ def parse_dates(
 def get_search_url(
     server: str,
     response: str = "html",
-    search_for: Optional[str] = None,
+    search_for: str | None = None,
     protocol: str = "tabledap",
     items_per_page: int = 1_000_000,
     page: int = 1,
@@ -362,8 +362,8 @@ def get_download_url(
     server: str,
     dataset_id: OptionalStr = None,
     protocol: OptionalStr = None,
-    variables: Optional[ListLike] = None,
-    dim_names: Optional[ListLike] = None,
+    variables: ListLike | None = None,
+    dim_names: ListLike | None = None,
     response=None,
     constraints=None,
     distinct=False,

erddapy/erddapy.py

@@ -3,7 +3,6 @@
 import functools
 import hashlib
 from pathlib import Path
-from typing import Dict, List, Optional, Tuple, Union
 from urllib.request import urlretrieve
 
 import pandas as pd
@@ -41,8 +40,8 @@
     "ERDDAP",
 ]
 
-ListLike = Union[List[str], Tuple[str]]
-OptionalStr = Optional[str]
+ListLike = list[str] | tuple[str]
+OptionalStr = str | None
 
 
 class ERDDAP:
@@ -127,21 +126,21 @@ def __init__(
         self.response = response
 
         # Initialized only via properties.
-        self.constraints: Optional[Dict] = None
-        self.server_functions: Optional[Dict] = None
+        self.constraints: dict | None = None
+        self.server_functions: dict | None = None
         self.dataset_id: OptionalStr = None
-        self.requests_kwargs: Dict = {}
-        self.auth: Optional[tuple] = None
-        self.variables: Optional[ListLike] = None
-        self.dim_names: Optional[ListLike] = None
+        self.requests_kwargs: dict = {}
+        self.auth: tuple | None = None
+        self.variables: ListLike | None = None
+        self.dim_names: ListLike | None = None
 
         self._get_variables = functools.lru_cache(maxsize=128)(
             self._get_variables_uncached,
         )
         # Caching the last `dataset_id` and `variables` list request for quicker multiple accesses,
         # will be overridden when requesting a new `dataset_id`.
         self._dataset_id: OptionalStr = None
-        self._variables: Dict = {}
+        self._variables: dict = {}
 
     def griddap_initialize(
         self,
@@ -278,8 +277,8 @@ def get_download_url(
         self,
         dataset_id: OptionalStr = None,
         protocol: OptionalStr = None,
-        variables: Optional[ListLike] = None,
-        dim_names: Optional[ListLike] = None,
+        variables: ListLike | None = None,
+        dim_names: ListLike | None = None,
         response=None,
         constraints=None,
         distinct=False,
@@ -345,7 +344,7 @@ def get_download_url(
 
     def to_pandas(
         self,
-        requests_kwargs: Optional[Dict] = None,
+        requests_kwargs: dict | None = None,
         **kw,
     ) -> "pd.DataFrame":
         """Save a data request to a pandas.DataFrame.
@@ -374,7 +373,7 @@ def to_ncCF(self, protocol: str = None, **kw):
 
     def to_xarray(
         self,
-        requests_kwargs: Optional[Dict] = None,
+        requests_kwargs: dict | None = None,
         **kw,
     ):
         """Load the data request into a xarray.Dataset.
@@ -405,7 +404,7 @@ def to_iris(self, **kw):
         url = self.get_download_url(response=response, distinct=distinct)
         return to_iris(url, iris_kwargs=dict(**kw))
 
-    def _get_variables_uncached(self, dataset_id: OptionalStr = None) -> Dict:
+    def _get_variables_uncached(self, dataset_id: OptionalStr = None) -> dict:
         if not dataset_id:
             dataset_id = self.dataset_id
 
@@ -427,7 +426,7 @@ def _get_variables_uncached(self, dataset_id: OptionalStr = None) -> Dict:
             variables.update({variable: attributes})
         return variables
 
-    def get_var_by_attr(self, dataset_id: OptionalStr = None, **kwargs) -> List[str]:
+    def get_var_by_attr(self, dataset_id: OptionalStr = None, **kwargs) -> list[str]:
         """
         Return a variable based on its attributes.
 

erddapy/multiple_server_search.py

@@ -1,7 +1,6 @@
 """Multiple Server Search."""
 
 import multiprocessing
-from typing import Dict
 
 import pandas as pd
 
@@ -19,7 +18,7 @@
 from erddapy.servers.servers import servers
 
 
-def _format_results(dfs: Dict[str, pd.DataFrame]) -> pd.DataFrame:
+def _format_results(dfs: dict[str, pd.DataFrame]) -> pd.DataFrame:
     """Format dictionary of results into a Pandas dataframe."""
     # we return None for bad server, so we need to filter them here
     df_all = pd.concat([list(df.values())[0] for df in dfs if df is not None])
@@ -30,7 +29,7 @@ def fetch_results(
     url: str,
     key: str,
     protocol,
-) -> Dict[str, pd.DataFrame]:
+) -> dict[str, pd.DataFrame]:
     """
     Fetch search results from multiple servers.
 

pyproject.toml

@@ -16,11 +16,9 @@ maintainers = [
     {name = "Callum Rollo", email = "[email protected]"},
     {name = "Filipe Fernandes", email = "[email protected]"},
 ]
-requires-python = ">=3.8"
+requires-python = ">=3.10"
 classifiers = [
   "Programming Language :: Python :: 3 :: Only",
-  "Programming Language :: Python :: 3.8",
-  "Programming Language :: Python :: 3.9",
   "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",
   "Programming Language :: Python :: 3.12",
@@ -56,7 +54,6 @@ select = [
     "T20", # flake8-print
     "UP", # upgrade
 ]
-target-version = "py38"
 line-length = 79
 
 [tool.ruff.per-file-ignores]