Ruff: enable ruff-specific rules

docs/conf.py

@@ -19,7 +19,7 @@
 # documentation root, use os.path.abspath to make it absolute, like shown here.
 sys.path.insert(0, os.path.abspath('..'))
 
-import torchgeo  # noqa: E402
+import torchgeo
 
 # -- Project information -----------------------------------------------------
 

docs/tutorials/custom_raster_dataset.ipynb

@@ -369,8 +369,8 @@
     "    date_format = '%Y%m%dT%H%M%S'\n",
     "    is_image = True\n",
     "    separate_files = True\n",
-    "    all_bands = ['B02', 'B03', 'B04', 'B08']\n",
-    "    rgb_bands = ['B04', 'B03', 'B02']"
+    "    all_bands = ('B02', 'B03', 'B04', 'B08')\n",
+    "    rgb_bands = ('B04', 'B03', 'B02')"
    ]
   },
   {
@@ -432,8 +432,8 @@
     "    date_format = '%Y%m%dT%H%M%S'\n",
     "    is_image = True\n",
     "    separate_files = True\n",
-    "    all_bands = ['B02', 'B03', 'B04', 'B08']\n",
-    "    rgb_bands = ['B04', 'B03', 'B02']\n",
+    "    all_bands = ('B02', 'B03', 'B04', 'B08')\n",
+    "    rgb_bands = ('B04', 'B03', 'B02')\n",
     "\n",
     "    def plot(self, sample):\n",
     "        # Find the correct band index order\n",

experiments/ssl4eo/download_ssl4eo.py

@@ -125,7 +125,7 @@ def filter_collection(
 
     if filtered.size().getInfo() == 0:
         raise ee.EEException(
-            f'ImageCollection.filter: No suitable images found in ({coords[1]:.4f}, {coords[0]:.4f}) between {period[0]} and {period[1]}.'  # noqa: E501
+            f'ImageCollection.filter: No suitable images found in ({coords[1]:.4f}, {coords[0]:.4f}) between {period[0]} and {period[1]}.'
         )
     return filtered
 

experiments/ssl4eo/sample_ssl4eo.py

@@ -47,7 +47,7 @@
 def get_world_cities(
     download_root: str = 'world_cities', size: int = 10000
 ) -> pd.DataFrame:
-    url = 'https://simplemaps.com/static/data/world-cities/basic/simplemaps_worldcities_basicv1.71.zip'  # noqa: E501
+    url = 'https://simplemaps.com/static/data/world-cities/basic/simplemaps_worldcities_basicv1.71.zip'
     filename = 'worldcities.csv'
     download_and_extract_archive(url, download_root)
     cols = ['city', 'lat', 'lng', 'population']

pyproject.toml

@@ -268,7 +268,7 @@ quote-style = "single"
 skip-magic-trailing-comma = true
 
 [tool.ruff.lint]
-extend-select = ["ANN", "D", "I", "NPY201", "UP"]
+extend-select = ["ANN", "D", "I", "NPY201", "RUF", "UP"]
 ignore = ["ANN101", "ANN102", "ANN401"]
 
 [tool.ruff.lint.per-file-ignores]

tests/data/dfc2022/data.py

@@ -19,36 +19,36 @@
 
 train_set = [
     {
-        'image': 'labeled_train/Nantes_Saint-Nazaire/BDORTHO/44-2013-0295-6713-LA93-0M50-E080.tif',  # noqa: E501
-        'dem': 'labeled_train/Nantes_Saint-Nazaire/RGEALTI/44-2013-0295-6713-LA93-0M50-E080_RGEALTI.tif',  # noqa: E501
-        'target': 'labeled_train/Nantes_Saint-Nazaire/UrbanAtlas/44-2013-0295-6713-LA93-0M50-E080_UA2012.tif',  # noqa: E501
+        'image': 'labeled_train/Nantes_Saint-Nazaire/BDORTHO/44-2013-0295-6713-LA93-0M50-E080.tif',
+        'dem': 'labeled_train/Nantes_Saint-Nazaire/RGEALTI/44-2013-0295-6713-LA93-0M50-E080_RGEALTI.tif',
+        'target': 'labeled_train/Nantes_Saint-Nazaire/UrbanAtlas/44-2013-0295-6713-LA93-0M50-E080_UA2012.tif',
     },
     {
-        'image': 'labeled_train/Nice/BDORTHO/06-2014-1007-6318-LA93-0M50-E080.tif',  # noqa: E501
-        'dem': 'labeled_train/Nice/RGEALTI/06-2014-1007-6318-LA93-0M50-E080_RGEALTI.tif',  # noqa: E501
-        'target': 'labeled_train/Nice/UrbanAtlas/06-2014-1007-6318-LA93-0M50-E080_UA2012.tif',  # noqa: E501
+        'image': 'labeled_train/Nice/BDORTHO/06-2014-1007-6318-LA93-0M50-E080.tif',
+        'dem': 'labeled_train/Nice/RGEALTI/06-2014-1007-6318-LA93-0M50-E080_RGEALTI.tif',
+        'target': 'labeled_train/Nice/UrbanAtlas/06-2014-1007-6318-LA93-0M50-E080_UA2012.tif',
     },
 ]
 
 unlabeled_set = [
     {
-        'image': 'unlabeled_train/Calais_Dunkerque/BDORTHO/59-2012-0650-7077-LA93-0M50-E080.tif',  # noqa: E501
-        'dem': 'unlabeled_train/Calais_Dunkerque/RGEALTI/59-2012-0650-7077-LA93-0M50-E080_RGEALTI.tif',  # noqa: E501
+        'image': 'unlabeled_train/Calais_Dunkerque/BDORTHO/59-2012-0650-7077-LA93-0M50-E080.tif',
+        'dem': 'unlabeled_train/Calais_Dunkerque/RGEALTI/59-2012-0650-7077-LA93-0M50-E080_RGEALTI.tif',
     },
     {
-        'image': 'unlabeled_train/LeMans/BDORTHO/72-2013-0469-6789-LA93-0M50-E080.tif',  # noqa: E501
-        'dem': 'unlabeled_train/LeMans/RGEALTI/72-2013-0469-6789-LA93-0M50-E080_RGEALTI.tif',  # noqa: E501
+        'image': 'unlabeled_train/LeMans/BDORTHO/72-2013-0469-6789-LA93-0M50-E080.tif',
+        'dem': 'unlabeled_train/LeMans/RGEALTI/72-2013-0469-6789-LA93-0M50-E080_RGEALTI.tif',
     },
 ]
 
 val_set = [
     {
-        'image': 'val/Marseille_Martigues/BDORTHO/13-2014-0900-6268-LA93-0M50-E080.tif',  # noqa: E501
-        'dem': 'val/Marseille_Martigues/RGEALTI/13-2014-0900-6268-LA93-0M50-E080_RGEALTI.tif',  # noqa: E501
+        'image': 'val/Marseille_Martigues/BDORTHO/13-2014-0900-6268-LA93-0M50-E080.tif',
+        'dem': 'val/Marseille_Martigues/RGEALTI/13-2014-0900-6268-LA93-0M50-E080_RGEALTI.tif',
     },
     {
-        'image': 'val/Clermont-Ferrand/BDORTHO/63-2013-0711-6530-LA93-0M50-E080.tif',  # noqa: E501
-        'dem': 'val/Clermont-Ferrand/RGEALTI/63-2013-0711-6530-LA93-0M50-E080_RGEALTI.tif',  # noqa: E501
+        'image': 'val/Clermont-Ferrand/BDORTHO/63-2013-0711-6530-LA93-0M50-E080.tif',
+        'dem': 'val/Clermont-Ferrand/RGEALTI/63-2013-0711-6530-LA93-0M50-E080_RGEALTI.tif',
     },
 ]
 

tests/data/seasonet/data.py

@@ -112,7 +112,7 @@
     # Compute checksums
     with open(archive, 'rb') as f:
         md5 = hashlib.md5(f.read()).hexdigest()
-        print(f'{season}: {repr(md5)}')
+        print(f'{season}: {md5!r}')
 
 # Write meta.csv
 with open('meta.csv', 'w') as f:
@@ -121,7 +121,7 @@
 # Compute checksums
 with open('meta.csv', 'rb') as f:
     md5 = hashlib.md5(f.read()).hexdigest()
-    print(f'meta.csv: {repr(md5)}')
+    print(f'meta.csv: {md5!r}')
 
 os.makedirs('splits', exist_ok=True)
 
@@ -138,4 +138,4 @@
 # Compute checksums
 with open('splits.zip', 'rb') as f:
     md5 = hashlib.md5(f.read()).hexdigest()
-    print(f'splits: {repr(md5)}')
+    print(f'splits: {md5!r}')

tests/datasets/test_eurocrops.py

@@ -83,5 +83,5 @@ def test_invalid_query(self, dataset: EuroCrops) -> None:
             dataset[query]
 
     def test_integrity_error(self, dataset: EuroCrops) -> None:
-        dataset.zenodo_files = [('AA.zip', 'invalid')]
+        dataset.zenodo_files = (('AA.zip', 'invalid'),)
         assert not dataset._check_integrity()

tests/datasets/test_geo.py

@@ -72,7 +72,7 @@ class CustomVectorDataset(VectorDataset):
 
 
 class CustomSentinelDataset(Sentinel2):
-    all_bands: list[str] = []
+    all_bands: tuple[str, ...] = ()
     separate_files = False
 
 
@@ -356,7 +356,7 @@ def test_no_data(self, tmp_path: Path) -> None:
 
     def test_no_all_bands(self) -> None:
         root = os.path.join('tests', 'data', 'sentinel2')
-        bands = ['B04', 'B03', 'B02']
+        bands = ('B04', 'B03', 'B02')
         transforms = nn.Identity()
         cache = True
         msg = (

tests/trainers/test_byol.py

@@ -73,7 +73,7 @@ def test_trainer(
             '1',
         ]
 
-        main(['fit'] + args)
+        main(['fit', *args])
 
     @pytest.fixture
     def weights(self) -> WeightsEnum:

tests/trainers/test_classification.py

@@ -103,13 +103,13 @@ def test_trainer(
             '1',
         ]
 
-        main(['fit'] + args)
+        main(['fit', *args])
         try:
-            main(['test'] + args)
+            main(['test', *args])
         except MisconfigurationException:
             pass
         try:
-            main(['predict'] + args)
+            main(['predict', *args])
         except MisconfigurationException:
             pass
 
@@ -259,13 +259,13 @@ def test_trainer(
             '1',
         ]
 
-        main(['fit'] + args)
+        main(['fit', *args])
         try:
-            main(['test'] + args)
+            main(['test', *args])
         except MisconfigurationException:
             pass
         try:
-            main(['predict'] + args)
+            main(['predict', *args])
         except MisconfigurationException:
             pass
 

tests/trainers/test_detection.py

@@ -97,13 +97,13 @@ def test_trainer(
             '1',
         ]
 
-        main(['fit'] + args)
+        main(['fit', *args])
         try:
-            main(['test'] + args)
+            main(['test', *args])
         except MisconfigurationException:
             pass
         try:
-            main(['predict'] + args)
+            main(['predict', *args])
         except MisconfigurationException:
             pass
 

tests/trainers/test_iobench.py

@@ -27,12 +27,12 @@ def test_trainer(self, name: str, fast_dev_run: bool) -> None:
             '1',
         ]
 
-        main(['fit'] + args)
+        main(['fit', *args])
         try:
-            main(['test'] + args)
+            main(['test', *args])
         except MisconfigurationException:
             pass
         try:
-            main(['predict'] + args)
+            main(['predict', *args])
         except MisconfigurationException:
             pass

tests/trainers/test_moco.py

@@ -63,7 +63,7 @@ def test_trainer(
             '1',
         ]
 
-        main(['fit'] + args)
+        main(['fit', *args])
 
     def test_version_warnings(self) -> None:
         with pytest.warns(UserWarning, match='MoCo v1 uses a memory bank'):

tests/trainers/test_regression.py

@@ -84,13 +84,13 @@ def test_trainer(
             '1',
         ]
 
-        main(['fit'] + args)
+        main(['fit', *args])
         try:
-            main(['test'] + args)
+            main(['test', *args])
         except MisconfigurationException:
             pass
         try:
-            main(['predict'] + args)
+            main(['predict', *args])
         except MisconfigurationException:
             pass
 
@@ -237,13 +237,13 @@ def test_trainer(
             '1',
         ]
 
-        main(['fit'] + args)
+        main(['fit', *args])
         try:
-            main(['test'] + args)
+            main(['test', *args])
         except MisconfigurationException:
             pass
         try:
-            main(['predict'] + args)
+            main(['predict', *args])
         except MisconfigurationException:
             pass
 

tests/trainers/test_segmentation.py

@@ -108,13 +108,13 @@ def test_trainer(
             '1',
         ]
 
-        main(['fit'] + args)
+        main(['fit', *args])
         try:
-            main(['test'] + args)
+            main(['test', *args])
         except MisconfigurationException:
             pass
         try:
-            main(['predict'] + args)
+            main(['predict', *args])
         except MisconfigurationException:
             pass
 

tests/trainers/test_simclr.py

@@ -63,7 +63,7 @@ def test_trainer(
             '1',
         ]
 
-        main(['fit'] + args)
+        main(['fit', *args])
 
     def test_version_warnings(self) -> None:
         with pytest.warns(UserWarning, match='SimCLR v1 only uses 2 layers'):

torchgeo/datamodules/seco.py

@@ -37,7 +37,7 @@ def __init__(
         seasons = kwargs.get('seasons', 1)
 
         # Normalization only available for RGB dataset, defined here:
-        # https://github.com/ServiceNow/seasonal-contrast/blob/8285173ec205b64bc3e53b880344dd6c3f79fa7a/datasets/seco_dataset.py  # noqa: E501
+        # https://github.com/ServiceNow/seasonal-contrast/blob/8285173ec205b64bc3e53b880344dd6c3f79fa7a/datasets/seco_dataset.py
         if bands == SeasonalContrastS2.rgb_bands:
             _min = torch.tensor([3, 2, 0])
             _max = torch.tensor([88, 103, 129])

torchgeo/datamodules/so2sat.py

@@ -3,7 +3,7 @@
 
 """So2Sat datamodule."""
 
-from typing import Any
+from typing import Any, ClassVar
 
 import torch
 from torch import Generator, Tensor
@@ -21,7 +21,7 @@ class So2SatDataModule(NonGeoDataModule):
     "train" set and use the "test" set as the test set.
     """
 
-    means_per_version: dict[str, Tensor] = {
+    means_per_version: ClassVar[dict[str, Tensor]] = {
         '2': torch.tensor(
             [
                 -0.00003591224260,
@@ -91,7 +91,7 @@ class So2SatDataModule(NonGeoDataModule):
     }
     means_per_version['3_culture_10'] = means_per_version['2']
 
-    stds_per_version: dict[str, Tensor] = {
+    stds_per_version: ClassVar[dict[str, Tensor]] = {
         '2': torch.tensor(
             [
                 0.17555201,

torchgeo/datamodules/ssl4eo.py

@@ -45,7 +45,7 @@ class SSL4EOS12DataModule(NonGeoDataModule):
     .. versionadded:: 0.5
     """
 
-    # https://github.com/zhu-xlab/SSL4EO-S12/blob/d2868adfada65e40910bfcedfc49bc3b20df2248/src/benchmark/transfer_classification/datasets/EuroSat/eurosat_dataset.py#L97  # noqa: E501
+    # https://github.com/zhu-xlab/SSL4EO-S12/blob/d2868adfada65e40910bfcedfc49bc3b20df2248/src/benchmark/transfer_classification/datasets/EuroSat/eurosat_dataset.py#L97
     mean = torch.tensor(0)
     std = torch.tensor(10000)
 

torchgeo/datasets/advance.py

@@ -63,14 +63,14 @@ class ADVANCE(NonGeoDataset):
         * `scipy <https://pypi.org/project/scipy/>`_ to load the audio files to tensors
     """
 
-    urls = [
+    urls = (
         'https://zenodo.org/record/3828124/files/ADVANCE_vision.zip?download=1',
         'https://zenodo.org/record/3828124/files/ADVANCE_sound.zip?download=1',
-    ]
-    filenames = ['ADVANCE_vision.zip', 'ADVANCE_sound.zip']
-    md5s = ['a9e8748219ef5864d3b5a8979a67b471', 'a2d12f2d2a64f5c3d3a9d8c09aaf1c31']
-    directories = ['vision', 'sound']
-    classes = [
+    )
+    filenames = ('ADVANCE_vision.zip', 'ADVANCE_sound.zip')
+    md5s = ('a9e8748219ef5864d3b5a8979a67b471', 'a2d12f2d2a64f5c3d3a9d8c09aaf1c31')
+    directories = ('vision', 'sound')
+    classes: tuple[str, ...] = (
         'airport',
         'beach',
         'bridge',
@@ -84,7 +84,7 @@ class ADVANCE(NonGeoDataset):
         'sparse shrub land',
         'sports land',
         'train station',
-    ]
+    )
 
     def __init__(
         self,
@@ -119,7 +119,7 @@ def __init__(
             raise DatasetNotFoundError(self)
 
         self.files = self._load_files(self.root)
-        self.classes = sorted({f['cls'] for f in self.files})
+        self.classes = tuple(sorted({f['cls'] for f in self.files}))
         self.class_to_idx: dict[str, int] = {c: i for i, c in enumerate(self.classes)}
 
     def __getitem__(self, index: int) -> dict[str, Tensor]:

torchgeo/datasets/agb_live_woody_density.py

@@ -46,7 +46,7 @@ class AbovegroundLiveWoodyBiomassDensity(RasterDataset):
 
     is_image = False
 
-    url = 'https://opendata.arcgis.com/api/v3/datasets/e4bdbe8d6d8d4e32ace7d36a4aec7b93_0/downloads/data?format=geojson&spatialRefId=4326'  # noqa: E501
+    url = 'https://opendata.arcgis.com/api/v3/datasets/e4bdbe8d6d8d4e32ace7d36a4aec7b93_0/downloads/data?format=geojson&spatialRefId=4326'
 
     base_filename = 'Aboveground_Live_Woody_Biomass_Density.geojson'