diff --git a/.github/workflows/lint.yaml b/.github/workflows/lint.yaml
index fd5ff69..da34cf9 100644
--- a/.github/workflows/lint.yaml
+++ b/.github/workflows/lint.yaml
@@ -21,10 +21,10 @@ jobs:
     - name: Install Python dependencies
       run: |
         python -m pip install --upgrade pip
-        python -m pip install 'isort==5.12.0' 'ruff==0.1.15'
+        python -m pip install 'isort==5.12.0' 'black==23.10.0' 'ruff==0.1.15'
     - name: isort
       run: python -m isort . --check --diff
-    # - name: black
-    #   run: python -m black --check --diff .
+    - name: black
+      run: python -m black --check --diff .
     - name: ruff
       run: ruff check .
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index af61341..9607ecd 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -51,7 +51,7 @@ repos:
     hooks:
       - id: auto-smart-commit
   - repo: https://github.com/psf/black
-    rev: 23.10.0
+    rev: "23.10.0"
     hooks:
       - id: black
         language_version: python3.9
diff --git a/pyproject.toml b/pyproject.toml
index 4145b12..98b6556 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -68,6 +68,10 @@ junit_logging = "log"  # Include logging output in JUnit XML report
 profile = "black"
 
 
+[tool.black]
+line-length = 99
+
+
 [tool.ruff]
 # line-length = 100
 
@@ -77,4 +81,3 @@ ignore = [
   "E501",  # Ignore "line-too-long" issues, let black handle that.
 ]
 
-
diff --git a/src/openeo_gfmap/backend.py b/src/openeo_gfmap/backend.py
index f63e054..ba8cdb8 100644
--- a/src/openeo_gfmap/backend.py
+++ b/src/openeo_gfmap/backend.py
@@ -33,9 +33,7 @@ class BackendContext:
     backend: Backend
 
 
-def _create_connection(
-    url: str, *, env_var_suffix: str, connect_kwargs: Optional[dict] = None
-):
+def _create_connection(url: str, *, env_var_suffix: str, connect_kwargs: Optional[dict] = None):
     """
     Generic helper to create an openEO connection
     with support for multiple client credential configurations from environment variables
@@ -63,9 +61,7 @@ def _create_connection(
 
         # Use a shorter max poll time by default to alleviate the default impression that the test seem to hang
         # because of the OIDC device code poll loop.
-        max_poll_time = int(
-            os.environ.get("OPENEO_OIDC_DEVICE_CODE_MAX_POLL_TIME") or 30
-        )
+        max_poll_time = int(os.environ.get("OPENEO_OIDC_DEVICE_CODE_MAX_POLL_TIME") or 30)
         connection.authenticate_oidc(max_poll_time=max_poll_time)
     return connection
 
diff --git a/src/openeo_gfmap/extractions/s2.py b/src/openeo_gfmap/extractions/s2.py
index bce191c..342f963 100644
--- a/src/openeo_gfmap/extractions/s2.py
+++ b/src/openeo_gfmap/extractions/s2.py
@@ -76,9 +76,7 @@ def s2_l2a_fetch_default(
             ), "CRS not defined within GeoJSON collection."
             spatial_extent = dict(spatial_extent)
 
-        cube = connection.load_collection(
-            collection_name, spatial_extent, temporal_extent, bands
-        )
+        cube = connection.load_collection(collection_name, spatial_extent, temporal_extent, bands)
 
         # Apply if the collection is a GeoJSON Feature collection
         if isinstance(spatial_extent, GeoJSON):
diff --git a/src/openeo_gfmap/features/feature_extractor.py b/src/openeo_gfmap/features/feature_extractor.py
index 28ceb7a..28f6b79 100644
--- a/src/openeo_gfmap/features/feature_extractor.py
+++ b/src/openeo_gfmap/features/feature_extractor.py
@@ -75,9 +75,7 @@ class FeatureExtractor(ABC):
     point based extraction or dense Cubes for tile/polygon based extraction.
     """
 
-    def _common_preparations(
-        self, inarr: xr.DataArray, parameters: dict
-    ) -> xr.DataArray:
+    def _common_preparations(self, inarr: xr.DataArray, parameters: dict) -> xr.DataArray:
         """Common preparations to be executed before the feature extractor is
         executed. This method should be called by the `_execute` method of the
         feature extractor.
@@ -102,8 +100,7 @@ def output_labels(self) -> list:
 
     def _execute(self, cube: XarrayDataCube, parameters: dict) -> XarrayDataCube:
         raise NotImplementedError(
-            "FeatureExtractor is a base abstract class, please implement the "
-            "_execute method."
+            "FeatureExtractor is a base abstract class, please implement the " "_execute method."
         )
 
 
@@ -130,8 +127,7 @@ def get_latlons(self, inarr: xr.DataArray) -> xr.DataArray:
 
         if self.epsg is None:
             raise Exception(
-                "EPSG code was not defined, cannot extract lat/lon array "
-                "as the CRS is unknown."
+                "EPSG code was not defined, cannot extract lat/lon array " "as the CRS is unknown."
             )
 
         # If the coordiantes are not in EPSG:4326, we need to reproject them
@@ -257,9 +253,7 @@ def apply_feature_extractor(
     udf = openeo.UDF(code=udf_code, context=parameters)
 
     cube = cube.apply_neighborhood(process=udf, size=size, overlap=overlap)
-    return cube.rename_labels(
-        dimension="bands", target=feature_extractor_class().output_labels()
-    )
+    return cube.rename_labels(dimension="bands", target=feature_extractor_class().output_labels())
 
 
 def apply_feature_extractor_local(
diff --git a/src/openeo_gfmap/fetching/commons.py b/src/openeo_gfmap/fetching/commons.py
index a589dc8..898c86d 100644
--- a/src/openeo_gfmap/fetching/commons.py
+++ b/src/openeo_gfmap/fetching/commons.py
@@ -128,8 +128,7 @@ def load_collection(
     pre_mask = params.get("pre_mask", None)
     if pre_mask is not None:
         assert isinstance(pre_mask, openeo.DataCube), (
-            f"The 'pre_mask' parameter must be an openeo datacube, "
-            f"got {pre_mask}."
+            f"The 'pre_mask' parameter must be an openeo datacube, " f"got {pre_mask}."
         )
         cube = cube.mask(pre_mask.resample_cube_spatial(cube))
 
diff --git a/src/openeo_gfmap/fetching/s1.py b/src/openeo_gfmap/fetching/s1.py
index 4fcee4f..cf061fb 100644
--- a/src/openeo_gfmap/fetching/s1.py
+++ b/src/openeo_gfmap/fetching/s1.py
@@ -84,9 +84,7 @@ def s1_grd_fetch_default(
     return s1_grd_fetch_default
 
 
-def get_s1_grd_default_processor(
-    collection_name: str, fetch_type: FetchType
-) -> Callable:
+def get_s1_grd_default_processor(collection_name: str, fetch_type: FetchType) -> Callable:
     """Builds the preprocessing function from the collection name as it is stored
     in the target backend.
     """
@@ -113,9 +111,7 @@ def s1_grd_default_processor(cube: openeo.DataCube, **params):
         )
 
         cube = resample_reproject(
-            cube,
-            params.get("target_resolution", 10.0),
-            params.get("target_crs", None)
+            cube, params.get("target_resolution", 10.0), params.get("target_crs", None)
         )
 
         cube = rename_bands(cube, BASE_SENTINEL1_GRD_MAPPING)
@@ -128,15 +124,11 @@ def s1_grd_default_processor(cube: openeo.DataCube, **params):
 SENTINEL1_GRD_BACKEND_MAP = {
     Backend.TERRASCOPE: {
         "default": partial(get_s1_grd_default_fetcher, collection_name="SENTINEL1_GRD"),
-        "preprocessor": partial(
-            get_s1_grd_default_processor, collection_name="SENTINEL1_GRD"
-        ),
+        "preprocessor": partial(get_s1_grd_default_processor, collection_name="SENTINEL1_GRD"),
     },
     Backend.CDSE: {
         "default": partial(get_s1_grd_default_fetcher, collection_name="SENTINEL1_GRD"),
-        "preprocessor": partial(
-            get_s1_grd_default_processor, collection_name="SENTINEL1_GRD"
-        ),
+        "preprocessor": partial(get_s1_grd_default_processor, collection_name="SENTINEL1_GRD"),
     },
 }
 
diff --git a/src/openeo_gfmap/fetching/s2.py b/src/openeo_gfmap/fetching/s2.py
index de7e201..0f7b3b3 100644
--- a/src/openeo_gfmap/fetching/s2.py
+++ b/src/openeo_gfmap/fetching/s2.py
@@ -114,9 +114,7 @@ def s2_l2a_fetch_default(
     return s2_l2a_fetch_default
 
 
-def get_s2_l2a_element84_fetcher(
-    collection_name: str, fetch_type: FetchType
-) -> Callable:
+def get_s2_l2a_element84_fetcher(collection_name: str, fetch_type: FetchType) -> Callable:
     """Fetches the collections from the Sentinel-2 Cloud-Optimized GeoTIFFs
     bucket provided by Amazon and managed by Element84.
     """
@@ -157,9 +155,7 @@ def s2_l2a_element84_fetcher(
     return s2_l2a_element84_fetcher
 
 
-def get_s2_l2a_default_processor(
-    collection_name: str, fetch_type: FetchType
-) -> Callable:
+def get_s2_l2a_default_processor(collection_name: str, fetch_type: FetchType) -> Callable:
     """Builds the preprocessing function from the collection name as it stored
     in the target backend.
     """
@@ -188,15 +184,11 @@ def s2_l2a_default_processor(cube: openeo.DataCube, **params):
 SENTINEL2_L2A_BACKEND_MAP = {
     Backend.TERRASCOPE: {
         "fetch": partial(get_s2_l2a_default_fetcher, collection_name="SENTINEL2_L2A"),
-        "preprocessor": partial(
-            get_s2_l2a_default_processor, collection_name="SENTINEL2_L2A"
-        ),
+        "preprocessor": partial(get_s2_l2a_default_processor, collection_name="SENTINEL2_L2A"),
     },
     Backend.CDSE: {
         "fetch": partial(get_s2_l2a_default_fetcher, collection_name="SENTINEL2_L2A"),
-        "preprocessor": partial(
-            get_s2_l2a_default_processor, collection_name="SENTINEL2_L2A"
-        ),
+        "preprocessor": partial(get_s2_l2a_default_processor, collection_name="SENTINEL2_L2A"),
     },
 }
 
diff --git a/src/openeo_gfmap/inference/inference_models.py b/src/openeo_gfmap/inference/inference_models.py
index e5f60f4..e83d676 100644
--- a/src/openeo_gfmap/inference/inference_models.py
+++ b/src/openeo_gfmap/inference/inference_models.py
@@ -29,9 +29,7 @@ class ModelInference(ABC):
     methods and attributes to be used by other model inference classes.
     """
 
-    def _common_preparations(
-        self, inarr: xr.DataArray, parameters: dict
-    ) -> xr.DataArray:
+    def _common_preparations(self, inarr: xr.DataArray, parameters: dict) -> xr.DataArray:
         """Common preparations for all inference models. This method will be
         executed at the very beginning of the process.
         """
diff --git a/src/openeo_gfmap/preprocessing/cloudmasking.py b/src/openeo_gfmap/preprocessing/cloudmasking.py
index 3cbdeed..e605689 100644
--- a/src/openeo_gfmap/preprocessing/cloudmasking.py
+++ b/src/openeo_gfmap/preprocessing/cloudmasking.py
@@ -33,9 +33,7 @@ def mask_scl_dilation(cube: openeo.DataCube, **params: dict) -> openeo.DataCube:
     )
 
     nonoptical_cube = cube.filter_bands(
-        bands=list(
-            filter(lambda band: not band.startswith("S2"), cube.metadata.band_names)
-        )
+        bands=list(filter(lambda band: not band.startswith("S2"), cube.metadata.band_names))
     )
 
     optical_cube = optical_cube.process(
@@ -224,9 +222,7 @@ def bap_masking(cube: openeo.DataCube, period: Union[str, list], **params: dict)
     )
 
     nonoptical_cube = cube.filter_bands(
-        bands=list(
-            filter(lambda band: not band.startswith("S2"), cube.metadata.band_names)
-        )
+        bands=list(filter(lambda band: not band.startswith("S2"), cube.metadata.band_names))
     )
 
     rank_mask = get_bap_mask(optical_cube, period, **params)
diff --git a/src/openeo_gfmap/preprocessing/compositing.py b/src/openeo_gfmap/preprocessing/compositing.py
index 5f7eaf4..a0b12f2 100644
--- a/src/openeo_gfmap/preprocessing/compositing.py
+++ b/src/openeo_gfmap/preprocessing/compositing.py
@@ -14,6 +14,7 @@ def median_compositing(cube: openeo.DataCube, period: Union[str, list]) -> opene
     elif isinstance(period, list):
         return cube.aggregate_temporal(intervals=period, reducer="median", dimension="t")
 
+
 def mean_compositing(cube: openeo.DataCube, period: str) -> openeo.DataCube:
     """Perfrom mean compositing on the given datacube."""
     if isinstance(period, str):
diff --git a/src/openeo_gfmap/preprocessing/interpolation.py b/src/openeo_gfmap/preprocessing/interpolation.py
index bffaa49..c404403 100644
--- a/src/openeo_gfmap/preprocessing/interpolation.py
+++ b/src/openeo_gfmap/preprocessing/interpolation.py
@@ -4,6 +4,8 @@
 import openeo
 
 
-def linear_interpolation(cube: openeo.DataCube,) -> openeo.DataCube:
+def linear_interpolation(
+    cube: openeo.DataCube,
+) -> openeo.DataCube:
     """Perform linear interpolation on the given datacube."""
     return cube.apply_dimension(dimension="t", process="array_interpolate_linear")
diff --git a/src/openeo_gfmap/preprocessing/udf_rank.py b/src/openeo_gfmap/preprocessing/udf_rank.py
index b68dad1..7271b61 100644
--- a/src/openeo_gfmap/preprocessing/udf_rank.py
+++ b/src/openeo_gfmap/preprocessing/udf_rank.py
@@ -1,4 +1,3 @@
-
 import numpy as np
 import xarray as xr
 from openeo.udf import XarrayDataCube
@@ -31,9 +30,7 @@ def select_maximum(score: xr.DataArray):
         # Convert YYYY-mm-dd to datetime64 objects
         time_bins = [np.datetime64(interval[0]) for interval in intervals]
 
-        rank_mask = bap_score.groupby_bins('t', bins=time_bins).map(
-            select_maximum
-        )
+        rank_mask = bap_score.groupby_bins("t", bins=time_bins).map(select_maximum)
     else:
         raise ValueError("Period is not defined in the UDF. Cannot run it.")
 
diff --git a/src/openeo_gfmap/preprocessing/udf_score.py b/src/openeo_gfmap/preprocessing/udf_score.py
index 578a5b9..ab72f65 100644
--- a/src/openeo_gfmap/preprocessing/udf_score.py
+++ b/src/openeo_gfmap/preprocessing/udf_score.py
@@ -11,9 +11,9 @@ def apply_datacube(cube: XarrayDataCube, context: dict) -> XarrayDataCube:
     cube_array: xr.DataArray = cube.get_array()
     cube_array = cube_array.transpose("t", "bands", "y", "x")
 
-    clouds = np.logical_or(
-        np.logical_and(cube_array < 11, cube_array >= 8), cube_array == 3
-    ).isel(bands=0)
+    clouds = np.logical_or(np.logical_and(cube_array < 11, cube_array >= 8), cube_array == 3).isel(
+        bands=0
+    )
 
     weights = [1, 0.8, 0.5]
 
@@ -21,11 +21,7 @@ def apply_datacube(cube: XarrayDataCube, context: dict) -> XarrayDataCube:
     times = cube_array.t.dt.day.values  # returns day of the month for each date
     sigma = 5
     mu = 15
-    score_doy = (
-        1
-        / (sigma * math.sqrt(2 * math.pi))
-        * np.exp(-0.5 * ((times - mu) / sigma) ** 2)
-    )
+    score_doy = 1 / (sigma * math.sqrt(2 * math.pi)) * np.exp(-0.5 * ((times - mu) / sigma) ** 2)
     score_doy = np.broadcast_to(
         score_doy[:, np.newaxis, np.newaxis],
         [cube_array.sizes["t"], cube_array.sizes["y"], cube_array.sizes["x"]],
@@ -77,9 +73,9 @@ def erode(image, selem):
     )
 
     # Final score is weighted average
-    score = (
-        weights[0] * score_clouds + weights[1] * score_doy + weights[2] * score_cov
-    ) / sum(weights)
+    score = (weights[0] * score_clouds + weights[1] * score_doy + weights[2] * score_cov) / sum(
+        weights
+    )
     score = np.where(cube_array.values[:, 0, :, :] == 0, 0, score)
 
     score_da = xr.DataArray(
diff --git a/src/openeo_gfmap/utils/catalogue.py b/src/openeo_gfmap/utils/catalogue.py
index 9e35244..e420a05 100644
--- a/src/openeo_gfmap/utils/catalogue.py
+++ b/src/openeo_gfmap/utils/catalogue.py
@@ -160,9 +160,7 @@ def s1_area_per_orbitstate(
             )
         )
     else:
-        raise NotImplementedError(
-            f"This feature is not supported for backend: {backend.backend}."
-        )
+        raise NotImplementedError(f"This feature is not supported for backend: {backend.backend}.")
 
     # Builds the shape of the spatial extent and computes the area
     spatial_extent = spatial_extent.to_geometry()
@@ -179,15 +177,13 @@ def s1_area_per_orbitstate(
         "ASCENDING": {
             "full_overlap": ascending_covers,
             "area": sum(
-                product.intersection(spatial_extent).area
-                for product in ascending_products
+                product.intersection(spatial_extent).area for product in ascending_products
             ),
         },
         "DESCENDING": {
             "full_overlap": descending_covers,
             "area": sum(
-                product.intersection(spatial_extent).area
-                for product in descending_products
+                product.intersection(spatial_extent).area for product in descending_products
             ),
         },
     }
diff --git a/src/openeo_gfmap/utils/tile_processing.py b/src/openeo_gfmap/utils/tile_processing.py
index b763be4..fa1efab 100644
--- a/src/openeo_gfmap/utils/tile_processing.py
+++ b/src/openeo_gfmap/utils/tile_processing.py
@@ -20,9 +20,7 @@ def normalize_array(inarr: xr.DataArray, percentile: float = 0.99) -> xr.DataArr
 def select_optical_bands(inarr: xr.DataArray) -> xr.DataArray:
     """Filters and keep only the optical bands for a given array."""
     return inarr.sel(
-        bands=[
-            band for band in inarr.coords["bands"].to_numpy() if band.startswith("S2-B")
-        ]
+        bands=[band for band in inarr.coords["bands"].to_numpy() if band.startswith("S2-B")]
     )
 
 
@@ -30,9 +28,7 @@ def select_sar_bands(inarr: xr.DataArray) -> xr.DataArray:
     """Filters and keep only the SAR bands for a given array."""
     return inarr.sel(
         bands=[
-            band
-            for band in inarr.coords["bands"].to_numpy()
-            if band in ["VV", "VH", "HH", "HV"]
+            band for band in inarr.coords["bands"].to_numpy() if band in ["VV", "VH", "HH", "HV"]
         ]
     )
 
@@ -47,9 +43,7 @@ def array_bounds(inarr: xr.DataArray) -> tuple:
     )
 
 
-def arrays_cosine_similarity(
-    first_array: xr.DataArray, second_array: xr.DataArray
-) -> float:
+def arrays_cosine_similarity(first_array: xr.DataArray, second_array: xr.DataArray) -> float:
     """Returns a similarity score based on normalized cosine distance. The
     input arrays must have similar ranges to obtain a valid score.
     1.0 represents the best score (same tiles), while 0.0 is the worst score.
diff --git a/tests/test_openeo_gfmap/test_cloud_masking.py b/tests/test_openeo_gfmap/test_cloud_masking.py
index e0c3db4..2328f9d 100644
--- a/tests/test_openeo_gfmap/test_cloud_masking.py
+++ b/tests/test_openeo_gfmap/test_cloud_masking.py
@@ -53,9 +53,7 @@ def test_bap_score(backend: Backend):
     bap_score = get_bap_score(cube, **preprocessing_parameters)
     ndvi = cube.ndvi(nir="S2-B08", red="S2-B04")
 
-    cube = bap_score.merge_cubes(ndvi).rename_labels(
-        "bands", ["S2-BAPSCORE", "S2-NDVI"]
-    )
+    cube = bap_score.merge_cubes(ndvi).rename_labels("bands", ["S2-BAPSCORE", "S2-NDVI"])
 
     job = cube.create_job(
         title="BAP score unittest",
@@ -66,9 +64,7 @@ def test_bap_score(backend: Backend):
 
     for asset in job.get_results().get_assets():
         if asset.metadata["type"].startswith("application/x-netcdf"):
-            asset.download(
-                Path(__file__).parent / f"results/bap_score_{backend.value}.nc"
-            )
+            asset.download(Path(__file__).parent / f"results/bap_score_{backend.value}.nc")
 
 
 @pytest.mark.parametrize("backend", backends)
@@ -100,9 +96,7 @@ def test_bap_masking(backend: Backend):
     cube = cube.linear_scale_range(0, 65535, 0, 65535)
 
     # Remove SCL
-    cube = cube.filter_bands(
-        [band for band in cube.metadata.band_names if band != "S2-SCL"]
-    )
+    cube = cube.filter_bands([band for band in cube.metadata.band_names if band != "S2-SCL"])
 
     job = cube.create_job(
         title="BAP compositing unittest",
@@ -113,9 +107,7 @@ def test_bap_masking(backend: Backend):
 
     for asset in job.get_results().get_assets():
         if asset.metadata["type"].startswith("application/x-netcdf"):
-            asset.download(
-                Path(__file__).parent / f"results/bap_composited_{backend.value}.nc"
-            )
+            asset.download(Path(__file__).parent / f"results/bap_composited_{backend.value}.nc")
 
 
 @pytest.mark.parametrize("backend", backends)
@@ -124,12 +116,8 @@ def test_bap_quintad(backend: Backend):
     backend_context = BackendContext(backend=backend)
 
     # Additional parameters
-    fetching_parameters = {
-        "fetching_resolution": 10.0
-    }
-    preprocessing_parameters = {
-        "apply_scl_dilation": True
-    }
+    fetching_parameters = {"fetching_resolution": 10.0}
+    preprocessing_parameters = {"apply_scl_dilation": True}
 
     # Fetch the datacube
     s2_extractor = build_sentinel2_l2a_extractor(
@@ -173,9 +161,7 @@ def test_bap_quintad(backend: Backend):
     assert compositing_intervals == expected_intervals
 
     # Perform masking with BAP, masking optical bands
-    bap_mask = get_bap_mask(
-        cube, period=compositing_intervals, **preprocessing_parameters
-    )
+    bap_mask = get_bap_mask(cube, period=compositing_intervals, **preprocessing_parameters)
 
     # Create a new extractor for the whole data now
     fetching_parameters = {
@@ -206,6 +192,4 @@ def test_bap_quintad(backend: Backend):
 
     for asset in job.get_results().get_assets():
         if asset.metadata["type"].startswith("application/x-netcdf"):
-            asset.download(
-                Path(__file__).parent / f"results/bap_quintad_{backend.value}.nc"
-            )
+            asset.download(Path(__file__).parent / f"results/bap_quintad_{backend.value}.nc")
diff --git a/tests/test_openeo_gfmap/test_feature_extractors.py b/tests/test_openeo_gfmap/test_feature_extractors.py
index d984bf6..621c010 100644
--- a/tests/test_openeo_gfmap/test_feature_extractors.py
+++ b/tests/test_openeo_gfmap/test_feature_extractors.py
@@ -43,9 +43,7 @@ def execute(self, inarr: xr.DataArray):
                 )
 
         # Compute the median on the time band
-        rgb_bands = rgb_bands.median(dim="t").assign_coords(
-            {"bands": ["red", "green", "blue"]}
-        )
+        rgb_bands = rgb_bands.median(dim="t").assign_coords({"bands": ["red", "green", "blue"]})
 
         # Returns the rgb bands only in the feature, y, x order
         return rgb_bands.transpose("bands", "y", "x")
@@ -83,9 +81,7 @@ def test_patch_feature_udf(backend: Backend, connection_fn: Callable):
     bands_to_extract = ["S2-B04", "S2-B03", "S2-B02"]
 
     # Setup the RGB cube extraction
-    extractor = build_sentinel2_l2a_extractor(
-        backend_context, bands_to_extract, FetchType.TILE
-    )
+    extractor = build_sentinel2_l2a_extractor(backend_context, bands_to_extract, FetchType.TILE)
 
     rgb_cube = extractor.get_cube(connection, SPATIAL_CONTEXT, TEMPORAL_EXTENT)
 
@@ -122,15 +118,11 @@ def test_latlon_extractor(backend: Backend, connection_fn: Callable):
     connection = connection_fn()
     output_path = Path(__file__).parent / f"results/latlon_features_{backend.value}.nc"
 
-    REDUCED_TEMPORAL_CONTEXT = TemporalContext(
-        start_date="2023-06-01", end_date="2023-06-30"
-    )
+    REDUCED_TEMPORAL_CONTEXT = TemporalContext(start_date="2023-06-01", end_date="2023-06-30")
 
     bands_to_extract = ["S2-B04"]
 
-    extractor = build_sentinel2_l2a_extractor(
-        backend_context, bands_to_extract, FetchType.TILE
-    )
+    extractor = build_sentinel2_l2a_extractor(backend_context, bands_to_extract, FetchType.TILE)
 
     cube = extractor.get_cube(connection, SPATIAL_CONTEXT, REDUCED_TEMPORAL_CONTEXT)
 
@@ -165,9 +157,9 @@ def test_patch_feature_local():
 
     inds = xr.open_dataset(input_path).to_array(dim="bands")
 
-    inds = inds.sel(
-        bands=[band for band in inds.bands.to_numpy() if band != "crs"]
-    ).transpose("bands", "t", "y", "x")
+    inds = inds.sel(bands=[band for band in inds.bands.to_numpy() if band != "crs"]).transpose(
+        "bands", "t", "y", "x"
+    )
 
     features = apply_feature_extractor_local(DummyPatchExtractor, inds, parameters={})
 
diff --git a/tests/test_openeo_gfmap/test_s1_fetchers.py b/tests/test_openeo_gfmap/test_s1_fetchers.py
index d0bbcf2..bf1c7d9 100644
--- a/tests/test_openeo_gfmap/test_s1_fetchers.py
+++ b/tests/test_openeo_gfmap/test_s1_fetchers.py
@@ -76,14 +76,9 @@ def sentinel1_grd(
 
         cube = extractor.get_cube(connection, spatial_extent, temporal_extent)
 
-        output_file = (
-            Path(__file__).parent
-            / f"results/{country}_{backend.value}_sentinel1_grd.nc"
-        )
+        output_file = Path(__file__).parent / f"results/{country}_{backend.value}_sentinel1_grd.nc"
 
-        job = cube.create_job(
-            title="Sentinel1 GRD tile extraction", out_format="NetCDF"
-        )
+        job = cube.create_job(title="Sentinel1 GRD tile extraction", out_format="NetCDF")
 
         job.start_and_wait()
 
@@ -113,8 +108,7 @@ def compare_sentinel1_tiles():
             loaded_tiles = []
             for backend in backend_types:
                 tile_path = (
-                    Path(__file__).parent
-                    / f"results/{country}_{backend.value}_sentinel1_grd.nc"
+                    Path(__file__).parent / f"results/{country}_{backend.value}_sentinel1_grd.nc"
                 )
                 loaded_tiles.append(xr.open_dataset(tile_path, engine="h5netcdf"))
 
@@ -182,9 +176,7 @@ def sentinel1_grd_point_based(
 
         cube = cube.aggregate_spatial(spatial_context, reducer="mean")
 
-        output_file = (
-            Path(__file__).parent / f"results/points_{backend.value}_sentinel1_grd.nc"
-        )
+        output_file = Path(__file__).parent / f"results/points_{backend.value}_sentinel1_grd.nc"
 
         cube.download(output_file, format="JSON")
 
@@ -247,23 +239,17 @@ def sentinel1_grd_polygon_based(
         results.download_files(output_folder)
 
         # List all the files available in the folder
-        extracted_files = list(
-            filter(lambda file: file.suffix == ".nc", output_folder.iterdir())
-        )
+        extracted_files = list(filter(lambda file: file.suffix == ".nc", output_folder.iterdir()))
         # Check if there is one file for each polygon
         assert len(extracted_files) == len(spatial_context["features"])
 
 
-@pytest.mark.parametrize(
-    "spatial_context, temporal_context, backend", test_configurations
-)
+@pytest.mark.parametrize("spatial_context, temporal_context, backend", test_configurations)
 def test_sentinel1_grd(
     spatial_context: SpatialContext, temporal_context: TemporalContext, backend: Backend
 ):
     connection = BACKEND_CONNECTIONS[backend]()
-    TestS1Extractors.sentinel1_grd(
-        spatial_context, temporal_context, backend, connection
-    )
+    TestS1Extractors.sentinel1_grd(spatial_context, temporal_context, backend, connection)
 
 
 @pytest.mark.depends(on=["test_sentinel1_grd"])
diff --git a/tests/test_openeo_gfmap/test_s2_fetchers.py b/tests/test_openeo_gfmap/test_s2_fetchers.py
index 59e9749..c6bbfe7 100644
--- a/tests/test_openeo_gfmap/test_s2_fetchers.py
+++ b/tests/test_openeo_gfmap/test_s2_fetchers.py
@@ -50,14 +50,10 @@
 TEMPORAL_EXTENT_2 = ["2023-01-01", "2023-02-01"]
 
 # Dataset of polygons for POINT based extraction
-POINT_EXTRACTION_DF = (
-    Path(__file__).parent / "resources/malawi_extraction_polygons.gpkg"
-)
+POINT_EXTRACTION_DF = Path(__file__).parent / "resources/malawi_extraction_polygons.gpkg"
 
 # Datase of polygons for Polygon based extraction
-POLYGON_EXTRACTION_DF = (
-    Path(__file__).parent / "resources/puglia_extraction_polygons.gpkg"
-)
+POLYGON_EXTRACTION_DF = Path(__file__).parent / "resources/puglia_extraction_polygons.gpkg"
 
 # test_backends = [Backend.TERRASCOPE, Backend.CDSE]
 test_backends = [Backend.CDSE]
@@ -100,9 +96,7 @@ def sentinel2_l2a(
             "S2-AOT",
         ]
         fetching_parameters = (
-            {"target_resolution": 10.0, "target_crs": 3035}
-            if country == "Belgium"
-            else {}
+            {"target_resolution": 10.0, "target_crs": 3035} if country == "Belgium" else {}
         )
         extractor: CollectionFetcher = build_sentinel2_l2a_extractor(
             context=context,
@@ -125,10 +119,7 @@ def sentinel2_l2a(
 
         cube = extractor.get_cube(connection, spatial_extent, temporal_extent)
 
-        output_file = (
-            Path(__file__).parent
-            / f"results/{country}_{backend.value}_sentinel2_l2a.nc"
-        )
+        output_file = Path(__file__).parent / f"results/{country}_{backend.value}_sentinel2_l2a.nc"
 
         cube.download(output_file, format="NetCDF")
 
@@ -153,8 +144,7 @@ def compare_sentinel2_tiles():
                 if backend == Backend.EODC:  # TODO fix EDOC backend first
                     continue
                 tile_path = (
-                    Path(__file__).parent
-                    / f"results/{country}_{backend.value}_sentinel2_l2a.nc"
+                    Path(__file__).parent / f"results/{country}_{backend.value}_sentinel2_l2a.nc"
                 )
                 loaded_tiles.append(xr.open_dataset(tile_path, engine="h5netcdf"))
 
@@ -216,9 +206,7 @@ def sentinel2_l2a_point_based(
 
         cube = cube.aggregate_spatial(spatial_context, reducer="mean")
 
-        output_file = (
-            Path(__file__).parent / f"results/points_{backend.value}_sentinel2_l2a.json"
-        )
+        output_file = Path(__file__).parent / f"results/points_{backend.value}_sentinel2_l2a.json"
 
         cube.download(output_file, format="JSON")
 
@@ -273,23 +261,17 @@ def sentinel2_l2a_polygon_based(
         results.download_files(output_folder)
 
         # List all the files available in the folder
-        extracted_files = list(
-            filter(lambda file: file.suffix == ".nc", output_folder.iterdir())
-        )
+        extracted_files = list(filter(lambda file: file.suffix == ".nc", output_folder.iterdir()))
         # Check if there is one file for each polygon
         assert len(extracted_files) == len(spatial_context["features"])
 
 
-@pytest.mark.parametrize(
-    "spatial_context, temporal_context, backend", test_configurations
-)
+@pytest.mark.parametrize("spatial_context, temporal_context, backend", test_configurations)
 def test_sentinel2_l2a(
     spatial_context: SpatialContext, temporal_context: TemporalContext, backend: Backend
 ):
     connection = BACKEND_CONNECTIONS[backend]()
-    TestS2Extractors.sentinel2_l2a(
-        spatial_context, temporal_context, backend, connection
-    )
+    TestS2Extractors.sentinel2_l2a(spatial_context, temporal_context, backend, connection)
 
 
 @pytest.mark.depends(on=["test_sentinel2_l2a"])
diff --git a/tests/test_openeo_gfmap/test_utils.py b/tests/test_openeo_gfmap/test_utils.py
index 598de11..2eb574c 100644
--- a/tests/test_openeo_gfmap/test_utils.py
+++ b/tests/test_openeo_gfmap/test_utils.py
@@ -2,9 +2,7 @@
 from openeo_gfmap.utils.catalogue import s1_area_per_orbitstate, select_S1_orbitstate
 
 # Region of Paris, France
-SPATIAL_CONTEXT = BoundingBoxExtent(
-    west=1.979, south=48.705, east=2.926, north=49.151, epsg=4326
-)
+SPATIAL_CONTEXT = BoundingBoxExtent(west=1.979, south=48.705, east=2.926, north=49.151, epsg=4326)
 
 # Summer 2023
 TEMPORAL_CONTEXT = TemporalContext(start_date="2023-06-21", end_date="2023-09-21")