Prepare for release (#784)

* Update version and changelog

* update hooks

* fix date in changelog

.pre-commit-config.yaml

@@ -13,18 +13,18 @@ repos:
       - id: debug-statements
 
   - repo: https://github.com/psf/black
-    rev: 23.11.0
+    rev: 23.12.1
     hooks:
       - id: black
         language_version: python3
 
   - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: "v0.1.5"
+    rev: "v0.1.11"
     hooks:
       - id: ruff
 
   - repo: https://github.com/nbQA-dev/nbQA
-    rev: 1.7.0
+    rev: 1.7.1
     hooks:
       - id: nbqa-black
       - id: nbqa-ruff

CHANGELOG.md

@@ -1,3 +1,8 @@
+## [Version 1.5.3] - 2024-01-10
+
+- Fix `numpy<2` in anticipation of numpy 2.0 release.
+
+
 ## [Version 1.5.2] - 2023-11-07
 
 - `RayExecutor` can now forward remote kwargs to ray jobs.

eolearn/__init__.py

@@ -1,6 +1,6 @@
 """Main module of the `eolearn` package."""
 
-__version__ = "1.5.2"
+__version__ = "1.5.3"
 
 import importlib.util
 import warnings

eolearn/core/eodata.py

@@ -445,9 +445,9 @@ def __repr__(self) -> str:
             content = self[feature_type]
 
             content = {k: content._get_unloaded(k) for k in content}  # noqa: SLF001
-            inner_content_repr = "\n    ".join([
-                f"{label}: {self._repr_value(value)}" for label, value in sorted(content.items())
-            ])
+            inner_content_repr = "\n    ".join(
+                [f"{label}: {self._repr_value(value)}" for label, value in sorted(content.items())]
+            )
             content_str = "{\n    " + inner_content_repr + "\n  }"
 
             feature_repr_list.append(f"{feature_type.value}={content_str}")

examples/water-monitor/WaterMonitorWorkflow.ipynb

@@ -356,9 +356,9 @@
     "        # we're only interested in the water within the dam borders\n",
     "        water_masks = water_masks[..., np.newaxis] * eopatch.mask_timeless[\"NOMINAL_WATER\"]\n",
     "\n",
-    "        water_levels = np.asarray([\n",
-    "            np.count_nonzero(mask) / np.count_nonzero(eopatch.mask_timeless[\"NOMINAL_WATER\"]) for mask in water_masks\n",
-    "        ])\n",
+    "        water_levels = np.asarray(\n",
+    "            [np.count_nonzero(mask) / np.count_nonzero(eopatch.mask_timeless[\"NOMINAL_WATER\"]) for mask in water_masks]\n",
+    "        )\n",
     "\n",
     "        eopatch[FeatureType.MASK, \"WATER_MASK\"] = water_masks\n",
     "        eopatch[FeatureType.SCALAR, \"WATER_LEVEL\"] = water_levels[..., np.newaxis]\n",
@@ -646,7 +646,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.4"
+   "version": "3.8.10"
   },
   "vscode": {
    "interpreter": {

tests/core/test_utils/test_common.py

@@ -98,9 +98,9 @@ class ApplyToAxesTestCase:
         function=partial(np.flip, axis=0),
         data=np.arange(2 * 3 * 4).reshape((2, 3, 4)),
         spatial_axes=(1, 2),
-        expected=np.array([
-            [[8, 9, 10, 11], [4, 5, 6, 7], [0, 1, 2, 3]], [[20, 21, 22, 23], [16, 17, 18, 19], [12, 13, 14, 15]]
-        ]),
+        expected=np.array(
+            [[[8, 9, 10, 11], [4, 5, 6, 7], [0, 1, 2, 3]], [[20, 21, 22, 23], [16, 17, 18, 19], [12, 13, 14, 15]]]
+        ),
     ),
     ApplyToAxesTestCase(
         function=lambda x: x + 1,