From 16047aa90c4f4d22a61df2aa3624a302c639473d Mon Sep 17 00:00:00 2001
From: BRAUN REMI <remi.braun@unistra.fr>
Date: Mon, 6 Jan 2025 13:58:25 +0100
Subject: [PATCH] FIX: Simplify decorator function of `rasters.read`, to have
 clearer name and clearer exceptions

---
 CHANGES.md         |  1 +
 ci/test_rasters.py |  2 +-
 sertit/rasters.py  | 64 +++++++++++++++++++++++-----------------------
 3 files changed, 34 insertions(+), 33 deletions(-)

diff --git a/CHANGES.md b/CHANGES.md
index e06d41c..05448f7 100644
--- a/CHANGES.md
+++ b/CHANGES.md
@@ -3,6 +3,7 @@
 ## 1.44.3 (2025-mm-dd)
 
 - FIX: Manage case where we have a `pd.Dataframe` instead of a `gpd.GeoDataFrame` in `vectors.read` (reading a `.dbf` file for instance)
+- FIX: Simplify decorator function of `rasters.read`, to better check the input types and to have a clearer function name and clearer exceptions
 
 ## 1.44.2 (2024-12-23)
 
diff --git a/ci/test_rasters.py b/ci/test_rasters.py
index d09addd..08337d0 100644
--- a/ci/test_rasters.py
+++ b/ci/test_rasters.py
@@ -612,7 +612,7 @@ def test_merge_different_crs_gtiff(tmp_path):
 
 
 def _test_raster_after_write(test_path, dtype, nodata_val):
-    with rasterio.open(test_path) as ds:
+    with rasterio.open(str(test_path)) as ds:
         assert ds.meta["dtype"] == dtype or ds.meta["dtype"] == dtype.__name__
         assert ds.meta["nodata"] == nodata_val
         assert ds.read()[:, 0, 0] == nodata_val  # Check value
diff --git a/sertit/rasters.py b/sertit/rasters.py
index 09482e3..3401dde 100644
--- a/sertit/rasters.py
+++ b/sertit/rasters.py
@@ -781,7 +781,7 @@ def crop(
     )
 
 
-def _any_raster_to_rio_ds(function: Callable) -> Callable:
+def __read__any_raster_to_rio_ds(function: Callable) -> Callable:
     """
     Specific declination of rasters_rio.any_raster_to_rio_ds for this specific case, handling the xarray object differently.
 
@@ -827,37 +827,37 @@ def wrapper(any_raster_type: AnyRasterType, *args, **kwargs) -> Any:
         Returns:
             Any: regular output
         """
-        try:
-            out = function(any_raster_type, *args, **kwargs)
-        except Exception as ex:
-            if path.is_path(any_raster_type):
-                with rasterio.open(str(any_raster_type)) as ds:
-                    out = function(ds, *args, **kwargs)
-            elif isinstance(any_raster_type, tuple):
+        # Input is a path: open it with rasterio
+        if path.is_path(any_raster_type):
+            with rasterio.open(str(any_raster_type)) as ds:
+                out = function(ds, *args, **kwargs)
+        # Input is a tuple: we consider it's composed of an output of rasterio.read function, a numpy array and a metadata dict
+        elif isinstance(any_raster_type, tuple):
+            try:
                 arr, meta = any_raster_type
-                from rasterio import MemoryFile
-
-                with (
-                    MemoryFile() as memfile,
-                    memfile.open(**meta, BIGTIFF=rasters_rio.bigtiff_value(arr)) as ds,
-                ):
-                    ds.write(arr)
-                    out = function(ds, *args, **kwargs)
-            else:
-                # Try if xarray is importable
-                try:
-                    if isinstance(any_raster_type, (xr.DataArray, xr.Dataset)):
-                        try:
-                            file_path = any_raster_type.encoding["source"]
-                            with rasterio.open(file_path) as ds:
-                                out = function(ds, *args, **kwargs)
-                        except Exception:
-                            # Return given xarray object
-                            return any_raster_type
-                    else:
-                        raise ex
-                except Exception as exc:
-                    raise ex from exc
+                assert isinstance(arr, np.ndarray)
+                assert isinstance(meta, dict)
+            except (ValueError, AssertionError) as exc:
+                raise TypeError(
+                    "Input tuple should be composed of a numpy array of your data and the corresponding metadata dictionary, is rasterio's sense."
+                ) from exc
+
+            from rasterio import MemoryFile
+
+            with (
+                MemoryFile() as memfile,
+                memfile.open(**meta, BIGTIFF=rasters_rio.bigtiff_value(arr)) as ds,
+            ):
+                ds.write(arr)
+                out = function(ds, *args, **kwargs)
+
+        # Return given xarray object as is
+        elif isinstance(any_raster_type, (xr.DataArray, xr.Dataset)):
+            out = any_raster_type
+
+        # Run the fct directly on the input (which should be a rasterio Dataset). If not, this will fail and it's expected.
+        else:
+            out = function(any_raster_type, *args, **kwargs)
         return out
 
     return wrapper
@@ -883,7 +883,7 @@ def wrapper(xda: xr.DataArray, *_args, **_kwargs):
     return wrapper
 
 
-@_any_raster_to_rio_ds
+@__read__any_raster_to_rio_ds
 def read(
     ds: AnyRasterType,
     resolution: Union[tuple, list, float] = None,