File: rm-iris.patch

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python-xarray 2025.12.0-1
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Description: Remove references that break because iris module, etc not installed
Author: Alastair McKinstry <mckinstry@debian.org>
Last-Updated: 2025-12-05
Forwarded: not-needed

--- a/doc/user-guide/io.rst
+++ b/doc/user-guide/io.rst
@@ -13,8 +13,6 @@
 
     import os
 
-    import iris
-    import ncdata.iris_xarray
     import numpy as np
     import pandas as pd
     import xarray as xr
@@ -1304,13 +1302,13 @@
 
 .. jupyter-execute::
 
-    ds_kerchunked = xr.open_dataset(
-        "./combined.json",
-        engine="kerchunk",
-        storage_options={},
-    )
+    #ds_kerchunked = xr.open_dataset(
+    #    "./combined.json",
+    #    engine="kerchunk",
+    #    storage_options={},
+    #)
 
-    ds_kerchunked
+    #ds_kerchunked
 
 .. note::
 
@@ -1334,22 +1332,22 @@
 
 .. jupyter-execute::
 
-    da = xr.DataArray(
-        np.random.rand(4, 5),
-        dims=["x", "y"],
-        coords=dict(x=[10, 20, 30, 40], y=pd.date_range("2000-01-01", periods=5)),
-    )
+    #da = xr.DataArray(
+    #    np.random.rand(4, 5),
+    #    dims=["x", "y"],
+    #    coords=dict(x=[10, 20, 30, 40], y=pd.date_range("2000-01-01", periods=5)),
+    #)
 
-    cube = da.to_iris()
-    print(cube)
+    #cube = da.to_iris()
+    #print(cube)
 
 Conversely, we can create a new ``DataArray`` object from a ``Cube`` using
 :py:meth:`DataArray.from_iris`:
 
 .. jupyter-execute::
 
-    da_cube = xr.DataArray.from_iris(cube)
-    da_cube
+    #da_cube = xr.DataArray.from_iris(cube)
+    #da_cube
 
 Ncdata
 ~~~~~~
@@ -1363,23 +1361,23 @@
 .. jupyter-execute::
     :stderr:
 
-    ds = xr.tutorial.open_dataset("air_temperature_gradient")
-    cubes = ncdata.iris_xarray.cubes_from_xarray(ds)
-    print(cubes)
+    #ds = xr.tutorial.open_dataset("air_temperature_gradient")
+    #cubes = ncdata.iris_xarray.cubes_from_xarray(ds)
+    #print(cubes)
 
 .. jupyter-execute::
 
-    print(cubes[1])
+    #print(cubes[1])
 
 And we can convert the cubes back to an xarray dataset:
 
 .. jupyter-execute::
 
     # ensure dataset-level and variable-level attributes loaded correctly
-    iris.FUTURE.save_split_attrs = True
+    #iris.FUTURE.save_split_attrs = True
 
-    ds = ncdata.iris_xarray.cubes_to_xarray(cubes)
-    ds
+    #ds = ncdata.iris_xarray.cubes_to_xarray(cubes)
+    #ds
 
 Ncdata can also adjust file data within load and save operations, to fix data loading
 problems or provide exact save formatting without needing to modify files on disk.