add tests for synchronous create_array

Author: d-v-b

src/zarr/api/synchronous.py

@@ -14,6 +14,7 @@
 if TYPE_CHECKING:
     from collections.abc import Iterable
 
+    import numpy as np
     import numpy.typing as npt
 
     from zarr.abc.codec import Codec
@@ -744,8 +745,9 @@ def create_array(
     store: str | StoreLike,
     *,
     name: str | None = None,
-    shape: ShapeLike,
-    dtype: npt.DTypeLike,
+    shape: ShapeLike | None = None,
+    dtype: npt.DTypeLike | None = None,
+    data: np.ndarray[Any, np.dtype[Any]] | None = None,
     chunks: ChunkCoords | Literal["auto"] = "auto",
     shards: ShardsLike | None = None,
     filters: FiltersLike = "auto",
@@ -772,10 +774,13 @@ def create_array(
     name : str or None, optional
         The name of the array within the store. If ``name`` is ``None``, the array will be located
         at the root of the store.
-    shape : ChunkCoords
-        Shape of the array.
-    dtype : npt.DTypeLike
-        Data type of the array.
+    shape : ChunkCoords, optional
+        Shape of the array. Can be ``None`` if ``data`` is provided.
+    dtype : npt.DTypeLike, optional
+        Data type of the array. Can be ``None`` if ``data`` is provided.
+    data : Array-like data to use for initializing the array. If this parameter is provided, the
+        ``shape`` and ``dtype`` parameters must be identical to ``data.shape`` and ``data.dtype``,
+        or ``None``.
     chunks : ChunkCoords, optional
         Chunk shape of the array.
         If not specified, default are guessed based on the shape and dtype.
@@ -874,6 +879,7 @@ def create_array(
                 name=name,
                 shape=shape,
                 dtype=dtype,
+                data=data,
                 chunks=chunks,
                 shards=shards,
                 filters=filters,

src/zarr/core/array.py

@@ -4035,10 +4035,10 @@ async def create_array(
     name : str or None, optional
         The name of the array within the store. If ``name`` is ``None``, the array will be located
         at the root of the store.
-    shape : ChunkCoords | None
-        Shape of the array.
+    shape : ChunkCoords, optional
+        Shape of the array. Can be ``None`` if ``data`` is provided.
     dtype : npt.DTypeLike | None
-        Data type of the array.
+        Data type of the array. Can be ``None`` if ``data`` is provided.
     data : Array-like data to use for initializing the array. If this parameter is provided, the
         ``shape`` and ``dtype`` parameters must be identical to ``data.shape`` and ``data.dtype``,
         or ``None``.

tests/test_array.py

@@ -11,6 +11,7 @@
 import pytest
 
 import zarr.api.asynchronous
+import zarr.api.synchronous as sync_api
 from zarr import Array, AsyncArray, Group
 from zarr.abc.store import Store
 from zarr.codecs import (
@@ -38,13 +39,14 @@
 from zarr.core.common import JSON, MemoryOrder, ZarrFormat
 from zarr.core.group import AsyncGroup
 from zarr.core.indexing import BasicIndexer, ceildiv
-from zarr.core.metadata.v3 import DataType
+from zarr.core.metadata.v3 import ArrayV3Metadata, DataType
 from zarr.core.sync import sync
 from zarr.errors import ContainsArrayError, ContainsGroupError
 from zarr.storage import LocalStore, MemoryStore, StorePath
 
 if TYPE_CHECKING:
     from zarr.core.array_spec import ArrayConfigLike
+    from zarr.core.metadata.v2 import ArrayV2Metadata
 
 
 @pytest.mark.parametrize("store", ["local", "memory", "zip"], indirect=["store"])
@@ -1259,16 +1261,26 @@ async def test_create_array_v2_no_shards(store: MemoryStore) -> None:
 
 
 @pytest.mark.parametrize("store", ["memory"], indirect=True)
-async def test_create_array_data(store: Store) -> None:
+@pytest.mark.parametrize("impl", ["sync", "async"])
+async def test_create_array_data(impl: Literal["sync", "async"], store: Store) -> None:
     """
     Test that we can invoke ``create_array`` with a ``data`` parameter.
     """
     data = np.arange(10)
-    arr = await create_array(store, name="foo", data=data)
-    stored = await arr._get_selection(
-        BasicIndexer(..., shape=arr.shape, chunk_grid=arr.metadata.chunk_grid),
-        prototype=default_buffer_prototype(),
-    )
+    name = "foo"
+    arr: AsyncArray[ArrayV2Metadata] | AsyncArray[ArrayV3Metadata] | Array
+    if impl == "sync":
+        arr = sync_api.create_array(store, name=name, data=data)
+        stored = arr[:]
+    elif impl == "async":
+        arr = await create_array(store, name=name, data=data, zarr_format=3)
+        stored = await arr._get_selection(
+            BasicIndexer(..., shape=arr.shape, chunk_grid=arr.metadata.chunk_grid),
+            prototype=default_buffer_prototype(),
+        )
+    else:
+        raise ValueError(f"Invalid impl: {impl}")
+
     assert np.array_equal(stored, data)