fix: convert zarr Array to numpy before __setitem__ async dispatch

When the value passed to Array.__setitem__ is itself a zarr Array, the
codec pipeline later calls value[...] from inside an already-running
async event loop, which raises SyncError.  Convert the value to a
NumPy array eagerly before entering the async context to avoid this.

Closes #3611

Made-with: Cursor

Author: Leo Ji

changes/3611.bugfix.md

@@ -0,0 +1 @@
+Fix `SyncError` raised when assigning a `zarr.Array` as the value in a `__setitem__` call (e.g. `dst[:] = src` where `src` is a zarr array). The source array is now converted to a NumPy array before entering the async codec pipeline.

src/zarr/core/array.py

@@ -2929,6 +2929,12 @@ def __setitem__(self, selection: Selection, value: npt.ArrayLike) -> None:
         [blocks][zarr.Array.blocks], [__getitem__][zarr.Array.__getitem__]
 
         """
+        # Converting a zarr Array to numpy here avoids a SyncError that occurs when
+        # value.__getitem__ is called inside the async codec pipeline (which already
+        # runs within a running event loop).  np.asarray triggers Array.__array__,
+        # which reads the data synchronously before we enter the async context.
+        if isinstance(value, Array):
+            value = np.asarray(value)
         fields, pure_selection = pop_fields(selection)
         if is_pure_fancy_indexing(pure_selection, self.ndim):
             self.vindex[cast("CoordinateSelection | MaskSelection", selection)] = value

tests/test_indexing.py

@@ -444,6 +444,24 @@ def test_orthogonal_indexing_fallback_on_getitem_2d(
 
 
 @pytest.mark.skip(reason="fails on ubuntu, windows; numpy=2.2; in CI")
+def test_setitem_zarr_array_as_value() -> None:
+    # Regression test for https://github.com/zarr-developers/zarr-python/issues/3611
+    # Assigning a zarr Array as the value used to raise
+    # SyncError("Calling sync() from within a running loop") because the codec
+    # pipeline tried to index the zarr array inside an already-running async loop.
+    src = zarr.array(np.arange(10), chunks=(5,))
+    dst = zarr.zeros(10, chunks=(5,), dtype=src.dtype)
+
+    # Full assignment
+    dst[:] = src
+    assert_array_equal(dst[:], np.arange(10))
+
+    # Slice assignment
+    dst2 = zarr.zeros(10, chunks=(5,), dtype=src.dtype)
+    dst2[2:7] = src[2:7]
+    assert_array_equal(dst2[2:7], np.arange(2, 7))
+
+
 def test_setitem_repeated_index():
     array = zarr.array(data=np.zeros((4,)), chunks=(1,))
     indexer = np.array([-1, -1, 0, 0])