Readme, example: How to enable/disable optimization via API funcs.

README.rst

@@ -23,7 +23,7 @@ After that, optimization will be attempted for any slicing of a dataset (of the
 
 .. _hdf5plugin: https://github.com/silx-kit/hdf5plugin
 
-Even if the module is imported and the ``Dataset`` class is patched, you may still force-disable the optimization by setting ``BLOSC2_FILTER=1`` in the environment.
+You may globally disable the optimization after importing ``b2h5py`` by calling ``b2h5py.unpatch_dataset_class()``, and enable it again with ``b2h5py.patch_dataset_class()``. Even if the module is imported and the ``Dataset`` class is patched, you may still force-disable the optimization by setting ``BLOSC2_FILTER=1`` in the environment.
 
 Building
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examples/blosc2_optimized_slicing.py

@@ -95,3 +95,14 @@
     print("Slice from dataset:", slice_, sep='\n')
     print("Slice from input array:", data[150:, 150:], sep='\n')
 os.environ['BLOSC2_FILTER'] = '0'  # back to normal
+# Utility functions are also provided to enable and disable optimization
+# (`BLOSC2_FILTER` still takes priority, though).
+print("Disabling Blosc2 optimized slicing via API.")
+with h5py.File(file_name, 'r') as f:
+    import b2h5py
+    b2h5py.unpatch_dataset_class()
+    dataset = f[dataset_name]
+    slice_ = dataset[150:, 150:]
+    print("Slice from dataset:", slice_, sep='\n')
+    print("Slice from input array:", data[150:, 150:], sep='\n')
+    b2h5py.patch_dataset_class()  # back to normal