speed up map_blocks (#4149)

* replace the object array with generator expressions and zip/enumerate

* remove a leftover grouping pair of parentheses

* reuse is_array instead of comparing again

xarray/core/parallel.py

@@ -34,11 +34,8 @@
 T_DSorDA = TypeVar("T_DSorDA", DataArray, Dataset)
 
 
-def to_object_array(iterable):
-    # using empty_like calls compute
-    npargs = np.empty((len(iterable),), dtype=np.object)
-    npargs[:] = iterable
-    return npargs
+def unzip(iterable):
+    return zip(*iterable)
 
 
 def assert_chunks_compatible(a: Dataset, b: Dataset):
@@ -335,23 +332,33 @@ def _wrapper(
     if not dask.is_dask_collection(obj):
         return func(obj, *args, **kwargs)
 
-    npargs = to_object_array([obj] + list(args))
-    is_xarray = [isinstance(arg, (Dataset, DataArray)) for arg in npargs]
-    is_array = [isinstance(arg, DataArray) for arg in npargs]
+    all_args = [obj] + list(args)
+    is_xarray = [isinstance(arg, (Dataset, DataArray)) for arg in all_args]
+    is_array = [isinstance(arg, DataArray) for arg in all_args]
+
+    # there should be a better way to group this. partition?
+    xarray_indices, xarray_objs = unzip(
+        (index, arg) for index, arg in enumerate(all_args) if is_xarray[index]
+    )
+    others = [
+        (index, arg) for index, arg in enumerate(all_args) if not is_xarray[index]
+    ]
 
     # all xarray objects must be aligned. This is consistent with apply_ufunc.
-    aligned = align(*npargs[is_xarray], join="exact")
-    # assigning to object arrays works better when RHS is object array
-    # https://stackoverflow.com/questions/43645135/boolean-indexing-assignment-of-a-numpy-array-to-a-numpy-array
-    npargs[is_xarray] = to_object_array(aligned)
-    npargs[is_array] = to_object_array(
-        [dataarray_to_dataset(da) for da in npargs[is_array]]
+    aligned = align(*xarray_objs, join="exact")
+    xarray_objs = tuple(
+        dataarray_to_dataset(arg) if is_da else arg
+        for is_da, arg in zip(is_array, aligned)
+    )
+
+    _, npargs = unzip(
+        sorted(list(zip(xarray_indices, xarray_objs)) + others, key=lambda x: x[0])
     )
 
     # check that chunk sizes are compatible
     input_chunks = dict(npargs[0].chunks)
     input_indexes = dict(npargs[0].indexes)
-    for arg in npargs[1:][is_xarray[1:]]:
+    for arg in xarray_objs[1:]:
         assert_chunks_compatible(npargs[0], arg)
         input_chunks.update(arg.chunks)
         input_indexes.update(arg.indexes)