Use sertit 1.43.2

eoreader/products/optical/s3_product.py

@@ -43,7 +43,6 @@
 from rasterio.errors import NotGeoreferencedWarning
 from sertit import path, types, vectors, xml
 from sertit.misc import ListEnum
-from sertit.rasters import MAX_CORES
 from sertit.types import AnyPathStrType, AnyPathType
 from shapely.geometry import Polygon, box
 
@@ -674,7 +673,7 @@ def _geocode(
                     resampler.load_resampling_info(cache_file)
 
                 band_arr_resampled = resampler.resample(
-                    band_arr.squeeze(), nprocs=MAX_CORES, fill_value=nodata
+                    band_arr.squeeze(), nprocs=utils.get_max_cores(), fill_value=nodata
                 )
 
                 # Save resampling info if needed
@@ -858,8 +857,17 @@ def _read_nc(
 
                     nc.load()
             else:
-                # No need to load here
-                nc = xr.open_dataset(nc_path, mask_and_scale=True, engine="h5netcdf")
+                with warnings.catch_warnings():
+                    # Ignore UserWarning: Duplicate dimension names present: dimensions {'bands'} appear more than once in dims=('bands', 'bands').
+                    # We do not yet support duplicate dimension names, but we do allow initial construction of the object.
+                    # We recommend you rename the dims immediately to become distinct, as most xarray functionality is likely to fail silently if you do not.
+                    # To rename the dimensions you will need to set the ``.dims`` attribute of each variable, ``e.g. var.dims=('x0', 'x1')``.
+                    warnings.simplefilter("ignore", category=UserWarning)
+
+                    # No need to load here
+                    nc = xr.open_dataset(
+                        nc_path, mask_and_scale=True, engine="h5netcdf"
+                    )
 
                 if subdataset:
                     nc = nc[subdataset]

eoreader/products/optical/vhr_product.py

@@ -35,7 +35,6 @@
 from rasterio.enums import Resampling
 from rasterio.vrt import WarpedVRT
 from sertit import AnyPath, path, rasters, rasters_rio
-from sertit.snap import MAX_CORES
 from sertit.types import AnyPathStrType, AnyPathType
 
 from eoreader import EOREADER_NAME, utils
@@ -305,7 +304,7 @@ def _reproject(
             dst_crs=self.crs(),
             dst_resolution=self.pixel_size,
             dst_nodata=self._raw_nodata,  # input data should be in integer
-            num_threads=MAX_CORES,
+            num_threads=utils.get_max_cores(),
             resampling=Resampling.bilinear,
             **kwargs,
         )
@@ -596,7 +595,7 @@ def _warp_band(
                 * int(os.getenv(TILE_SIZE, DEFAULT_TILE_SIZE)) ** 2
                 / 1e6,
                 "dtype": src.meta["dtype"],
-                "num_threads": MAX_CORES,
+                "num_threads": utils.get_max_cores(),
             }
             with rasterio.Env(
                 **{"GDAL_NUM_THREADS": "ALL_CPUS", "NUM_THREADS": "ALL_CPUS"}

eoreader/utils.py

@@ -31,6 +31,7 @@
 from rasterio.errors import NotGeoreferencedWarning
 from rasterio.rpc import RPC
 from sertit import AnyPath, geometry, logs, path, rasters
+from sertit.snap import SU_MAX_CORE
 from sertit.types import AnyPathStrType, AnyPathType
 
 from eoreader import EOREADER_NAME
@@ -508,3 +509,7 @@ def load_np(path_to_load: AnyPathStrType, output: AnyPathStrType) -> np.ndarray:
     if path.is_cloud_path(path_to_load):
         path_to_load = path_to_load.download_to(output)
     return np.load(str(path_to_load))
+
+
+def get_max_cores():
+    return int(os.getenv(SU_MAX_CORE, os.cpu_count() - 2))

requirements.txt

@@ -39,7 +39,7 @@ shapely>=2.0.0
 spyndex>=0.3.0
 
 # SERTIT libs
-sertit[full]>=1.42.1
+sertit[full]>=1.42.2
 
 # Optimizations
 dask[complete]>=2024.5.1  # numpy >= 2

setup.py

@@ -34,7 +34,7 @@
         "rioxarray>=0.10.0",
         "odc-geo>=0.4.6",
         "geopandas>=0.14.4",
-        "sertit[full]>=1.42.1",
+        "sertit[full]>=1.42.2",
         "spyndex>=0.3.0",
         "pyresample",
         "zarr",