merging

Author: erikvansebille

.github/workflows/ci.yml

@@ -18,21 +18,16 @@ defaults:
 
 jobs:
   unit-test:
-    name: "py${{ matrix.python-version }} | ${{ matrix.os }} | unit tests (${{ matrix.test-subfolder }})"
+    name: "py${{ matrix.python-version }} | ${{ matrix.os }} | unit tests"
     runs-on: ${{ matrix.os }}-latest
     strategy:
       fail-fast: false
       matrix:
         os: [ubuntu] #, mac, windows] # TODO v4: Re-enable windows and mac
-        test-subfolder: ["/"]
         python-version: ["3.12"]
         include:
           - os: ubuntu
             python-version: "3.11"
-            test-subfolder: "/"
-          - os: ubuntu
-            python-version: "3.12"
-            test-subfolder: "/v4"
     steps:
       - name: Checkout
         uses: actions/checkout@v4
@@ -43,7 +38,7 @@ jobs:
           python-version: ${{ matrix.python-version }}
       - name: Unit test
         run: |
-          coverage run -m pytest -v -s --html=${{ matrix.os }}_${{ matrix.python-version }}_unit_test_report.html --self-contained-html tests${{ matrix.test-subfolder }}
+          coverage run -m pytest -v -s --html=${{ matrix.os }}_${{ matrix.python-version }}_unit_test_report.html --self-contained-html
           coverage xml
       - name: Codecov
         uses: codecov/codecov-action@v5.3.1
@@ -58,6 +53,8 @@ jobs:
           name: Unittest report ${{ matrix.os }}-${{ matrix.python-version }}
           path: ${{ matrix.os }}_${{ matrix.python-version }}_unit_test_report.html
   integration-test:
+    # TODO v4: Re-enable the workflow once development has stabilized and we want to run integration tests again
+    if: false
     name: "py${{ matrix.python-version }} | ${{ matrix.os }} | integration tests"
     runs-on: ${{ matrix.os }}-latest
     strategy:
@@ -111,6 +108,8 @@ jobs:
           pattern: "* report *"
   typechecking:
     name: mypy
+    # TODO v4: Enable typechecking again
+    if: false
     runs-on: ubuntu-latest
     steps:
       - name: Checkout

parcels/_core/utils/time.py

@@ -6,10 +6,10 @@
 import cftime
 import numpy as np
 
-T = TypeVar("T", datetime, cftime.datetime)
-
 if TYPE_CHECKING:
-    from parcels._typing import DatetimeLike
+    from parcels._typing import TimeLike
+
+T = TypeVar("T", bound="TimeLike")
 
 
 class TimeInterval:
@@ -92,7 +92,7 @@ def is_compatible(
 
 
 def get_datetime_type_calendar(
-    example_datetime: DatetimeLike,
+    example_datetime: TimeLike,
 ) -> tuple[type, str | None]:
     """Get the type and calendar of a datetime object.
 

parcels/_core/utils/unstructured.py

@@ -1,12 +1,10 @@
-from collections.abc import Hashable
-
 DIM_TO_VERTICAL_LOCATION_MAP = {
     "nz1": "center",
     "nz": "face",
 }
 
 
-def get_vertical_location_from_dims(dims: tuple[Hashable, ...]):
+def get_vertical_location_from_dims(dims: tuple[str, ...]):
     """
     Determine the vertical location of the field based on the uxarray.UxDataArray object variables.
 

parcels/_datasets/__init__.py

@@ -3,7 +3,7 @@
 
 This subpackage uses xarray to generate *idealised* structured and unstructured hydrodynamical datasets that are compatible with Parcels. The goals are three-fold:
 
-1. To provide users with documentation for the types of datasets they can expect Parcels to work with.
+1. To provide users with documentation for the types of datasets they can expect Parcels to work with. When reporting bugs, users can use these datasets to reproduce the bug they're experiencing (allowing developers to quickly troubleshoot the problem).
 2. To supply our tutorials with hydrodynamical datasets.
 3. To offer developers datasets for use in test cases.
 
@@ -36,8 +36,10 @@
 
 This subpackage is broken down into structured and unstructured parts. Each of these have common submodules:
 
-* ``circulation_model`` -> hardcoded datasets with the intention of mimicking datasets from a certain (ocean) circulation model
+* ``circulation_model`` -> hardcoded datasets with the intention of mimicking dataset structure from a certain (ocean) circulation model. If you'd like to see Parcel support a new model, please open an issue in our issue tracker.
+    * exposes a dict ``datasets`` mapping dataset names to xarray datasets
 * ``generic`` -> hardcoded datasets that are generic, and not tied to a certain (ocean) circulation model. Instead these focus on the fundamental properties of the dataset
+    * exposes a dict ``datasets`` mapping dataset names to xarray datasets
 * ``generated`` -> functions to generate datasets with varying properties
 * ``utils`` -> any utility functions necessary related to either generating or validating datasets