feat: add IndexTransform library for composable, lazy coordinate mappings

src/zarr/api/synchronous.py

@@ -1138,20 +1138,20 @@ def from_array(
     ... )
     >>> arr2 = zarr.from_array(store, data=arr, overwrite=True)
     >>> arr2
-    <Array file://example_from_array.zarr shape=(100, 100) dtype=int32>
+    <Array file://example_from_array.zarr shape=(100, 100) dtype=int32 domain={ [0, 100), [0, 100) }>
     >>> asyncio.run(store.clear())  # Remove files generated by test
 
     Create an array from an existing NumPy array:
 
     >>> import numpy as np
     >>> zarr.from_array({}, data=np.arange(10000, dtype="i4").reshape(100, 100))
-    <Array memory://... shape=(100, 100) dtype=int32>
+    <Array memory://... shape=(100, 100) dtype=int32 domain={ [0, 100), [0, 100) }>
 
     Create an array from any array-like object:
 
     >>> arr3 = zarr.from_array({}, data=[[1, 2], [3, 4]])
     >>> arr3
-    <Array memory://... shape=(2, 2) dtype=int64>
+    <Array memory://... shape=(2, 2) dtype=int64 domain={ [0, 2), [0, 2) }>
     >>> arr3[...]
     array([[1, 2], [3, 4]])
 
@@ -1160,7 +1160,7 @@ def from_array(
     >>> arr4 = zarr.from_array({}, data=[[1, 2], [3, 4]])
     >>> arr5 = zarr.from_array({}, data=arr4, write_data=False)
     >>> arr5
-    <Array memory://... shape=(2, 2) dtype=int64>
+    <Array memory://... shape=(2, 2) dtype=int64 domain={ [0, 2), [0, 2) }>
     >>> arr5[...]
     array([[0, 0], [0, 0]])
     """