fix/shard iteration redux (#3422)

* iterate over shards instead of chunks in second branch

* add test

* parametrize over array type

* changelog

* appease mypy

Author: d-v-b

changes/3422.bugfix.rst

@@ -0,0 +1,4 @@
+Fix a potential race condition when using :func:`zarr.create_array` with the ``data`` parameter
+set to a NumPy array. Previously Zarr was iterating over the newly created array with a granularity
+that was too low. Now Zarr chooses a granularity that matches the size of the stored objects for
+that array.

src/zarr/core/array.py

@@ -4421,7 +4421,7 @@ async def _copy_arraylike_region(chunk_coords: slice, _data: NDArrayLike) -> Non
 
             # Stream data from the source array to the new array
             await concurrent_map(
-                [(region, data) for region in result._iter_chunk_regions()],
+                [(region, data) for region in result._iter_shard_regions()],
                 _copy_arraylike_region,
                 zarr.core.config.config.get("async.concurrency"),
             )

tests/test_array.py

@@ -74,6 +74,7 @@
     ZarrUserWarning,
 )
 from zarr.storage import LocalStore, MemoryStore, StorePath
+from zarr.storage._logging import LoggingStore
 
 from .test_dtype.conftest import zdtype_examples
 
@@ -2119,3 +2120,28 @@ def test_iter_chunk_regions(
     assert observed == expected
     assert observed == tuple(arr._iter_chunk_regions())
     assert observed == tuple(arr._async_array._iter_chunk_regions())
+
+
+@pytest.mark.parametrize("num_shards", [1, 3])
+@pytest.mark.parametrize("array_type", ["numpy", "zarr"])
+def test_create_array_with_data_num_gets(
+    num_shards: int, array_type: Literal["numpy", "zarr"]
+) -> None:
+    """
+    Test that creating an array with data only invokes a single get request per stored object
+    """
+    store = LoggingStore(store=MemoryStore())
+
+    chunk_shape = (1,)
+    shard_shape = (100,)
+    shape = (shard_shape[0] * num_shards,)
+    data: Array | npt.NDArray[np.int64]
+    if array_type == "numpy":
+        data = np.zeros(shape[0], dtype="int64")
+    else:
+        data = zarr.zeros(shape, dtype="int64")
+
+    zarr.create_array(store, data=data, chunks=chunk_shape, shards=shard_shape, fill_value=-1)  # type: ignore[arg-type]
+    # one get for the metadata and one per shard.
+    # Note: we don't actually need one get per shard, but this is the current behavior
+    assert store.counter["get"] == 1 + num_shards