Numpy array context rebased

arraycontext/__init__.py

@@ -32,6 +32,8 @@
     ArrayContainer,
     ArrayContainerT,
     NotAnArrayContainerError,
+    SerializationKey,
+    SerializedContainer,
     deserialize_container,
     get_container_context_opt,
     get_container_context_recursively,
@@ -41,7 +43,9 @@
     register_multivector_as_array_container,
     serialize_container,
 )
-from .container.arithmetic import with_container_arithmetic
+from .container.arithmetic import (
+    with_container_arithmetic,
+)
 from .container.dataclass import dataclass_array_container
 from .container.traversal import (
     flat_size_and_dtype,
@@ -78,6 +82,7 @@
     tag_axes,
 )
 from .impl.jax import EagerJAXArrayContext
+from .impl.numpy import NumpyArrayContext
 from .impl.pyopencl import PyOpenCLArrayContext
 from .impl.pytato import PytatoJAXArrayContext, PytatoPyOpenCLArrayContext
 from .loopy import make_loopy_program
@@ -91,7 +96,6 @@
 
 
 __all__ = (
-    "Array",
     "Array",
     "ArrayContainer",
     "ArrayContainerT",
@@ -105,14 +109,16 @@
     "EagerJAXArrayContext",
     "ElementwiseMapKernelTag",
     "NotAnArrayContainerError",
+    "NumpyArrayContext",
     "PyOpenCLArrayContext",
     "PytatoJAXArrayContext",
     "PytatoPyOpenCLArrayContext",
     "PytestArrayContextFactory",
     "PytestPyOpenCLArrayContextFactory",
     "Scalar",
-    "Scalar",
     "ScalarLike",
+    "SerializationKey",
+    "SerializedContainer",
     "dataclass_array_container",
     "deserialize_container",
     "flat_size_and_dtype",
@@ -146,7 +152,7 @@
     "to_numpy",
     "unflatten",
     "with_array_context",
-    "with_container_arithmetic"
+    "with_container_arithmetic",
 )
 
 

arraycontext/container/__init__.py

@@ -12,6 +12,9 @@
 
 Serialization/deserialization
 -----------------------------
+
+.. autoclass:: SerializationKey
+.. autoclass:: SerializedContainer
 .. autofunction:: is_array_container_type
 .. autofunction:: serialize_container
 .. autofunction:: deserialize_container
@@ -39,6 +42,14 @@
 .. class:: ArrayOrContainerT
 
     :canonical: arraycontext.ArrayOrContainerT
+
+.. class:: SerializationKey
+
+    :canonical: arraycontext.SerializationKey
+
+.. class:: SerializedContainer
+
+    :canonical: arraycontext.SerializedContainer
 """
 
 from __future__ import annotations
@@ -69,12 +80,23 @@
 """
 
 from functools import singledispatch
-from typing import TYPE_CHECKING, Any, Iterable, Optional, Protocol, Tuple, TypeVar
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Hashable,
+    Iterable,
+    Optional,
+    Protocol,
+    Sequence,
+    Tuple,
+    TypeVar,
+)
 
 # For use in singledispatch type annotations, because sphinx can't figure out
 # what 'np' is.
 import numpy
 import numpy as np
+from typing_extensions import TypeAlias
 
 from arraycontext.context import ArrayContext
 
@@ -142,23 +164,27 @@ class NotAnArrayContainerError(TypeError):
     """:class:`TypeError` subclass raised when an array container is expected."""
 
 
+SerializationKey: TypeAlias = Hashable
+SerializedContainer: TypeAlias = Sequence[Tuple[SerializationKey, "ArrayOrContainer"]]
+
+
 @singledispatch
 def serialize_container(
-        ary: ArrayContainer) -> Iterable[Tuple[Any, ArrayOrContainer]]:
-    r"""Serialize the array container into an iterable over its components.
+        ary: ArrayContainer) -> SerializedContainer:
+    r"""Serialize the array container into a sequence over its components.
 
     The order of the components and their identifiers are entirely under
     the control of the container class. However, the order is required to be
     deterministic, i.e. two calls to :func:`serialize_container` on
     array containers of the same types with the same number of
-    sub-arrays must result in an iterable with the keys in the same
+    sub-arrays must result in a sequence with the keys in the same
     order.
 
     If *ary* is mutable, the serialization function is not required to ensure
     that the serialization result reflects the array state at the time of the
     call to :func:`serialize_container`.
 
-    :returns: an :class:`Iterable` of 2-tuples where the first
+    :returns: a :class:`Sequence` of 2-tuples where the first
         entry is an identifier for the component and the second entry
         is an array-like component of the :class:`ArrayContainer`.
         Components can themselves be :class:`ArrayContainer`\ s, allowing
@@ -172,13 +198,13 @@ def serialize_container(
 @singledispatch
 def deserialize_container(
         template: ArrayContainerT,
-        iterable: Iterable[Tuple[Any, Any]]) -> ArrayContainerT:
-    """Deserialize an iterable into an array container.
+        serialized: SerializedContainer) -> ArrayContainerT:
+    """Deserialize a sequence into an array container following a *template*.
 
     :param template: an instance of an existing object that
         can be used to aid in the deserialization. For a similar choice
         see :attr:`~numpy.class.__array_finalize__`.
-    :param iterable: an iterable that mirrors the output of
+    :param serialized: a sequence that mirrors the output of
         :meth:`serialize_container`.
     """
     raise NotAnArrayContainerError(
@@ -218,7 +244,11 @@ def is_array_container(ary: Any) -> bool:
             "cheaper option, see is_array_container_type.",
             DeprecationWarning, stacklevel=2)
     return (serialize_container.dispatch(ary.__class__)
-            is not serialize_container.__wrapped__)       # type:ignore[attr-defined]
+            is not serialize_container.__wrapped__       # type:ignore[attr-defined]
+            # numpy values with scalar elements aren't array containers
+            and not (isinstance(ary, np.ndarray)
+                     and ary.dtype.kind != "O")
+            )
 
 
 @singledispatch
@@ -238,7 +268,7 @@ def get_container_context_opt(ary: ArrayContainer) -> Optional[ArrayContext]:
 
 @serialize_container.register(np.ndarray)
 def _serialize_ndarray_container(
-        ary: numpy.ndarray) -> Iterable[Tuple[Any, ArrayOrContainer]]:
+        ary: numpy.ndarray) -> SerializedContainer:
     if ary.dtype.char != "O":
         raise NotAnArrayContainerError(
                 f"cannot serialize '{type(ary).__name__}' with dtype '{ary.dtype}'")
@@ -252,20 +282,20 @@ def _serialize_ndarray_container(
                 for j in range(ary.shape[1])
                 ]
     else:
-        return np.ndenumerate(ary)
+        return list(np.ndenumerate(ary))
 
 
 @deserialize_container.register(np.ndarray)
 # https://github.com/python/mypy/issues/13040
 def _deserialize_ndarray_container(  # type: ignore[misc]
         template: numpy.ndarray,
-        iterable: Iterable[Tuple[Any, ArrayOrContainer]]) -> numpy.ndarray:
+        serialized: SerializedContainer) -> numpy.ndarray:
     # disallow subclasses
     assert type(template) is np.ndarray
     assert template.dtype.char == "O"
 
     result = type(template)(template.shape, dtype=object)
-    for i, subary in iterable:
+    for i, subary in serialized:
         result[i] = subary
 
     return result