[api] Initial API deprecations for Ray 1.0 (#10325)

python/ray/experimental/__init__.py

@@ -1,10 +1,8 @@
-from .api import get, wait
 from .dynamic_resources import set_resource
 from .object_spilling import force_spill_objects, force_restore_spilled_objects
 from .placement_group import (placement_group, placement_group_table,
                               remove_placement_group)
 __all__ = [
-    "get", "wait", "set_resource", "force_spill_objects",
-    "force_restore_spilled_objects", "placement_group",
-    "placement_group_table", "remove_placement_group"
+    "set_resource", "force_spill_objects", "force_restore_spilled_objects",
+    "placement_group", "placement_group_table", "remove_placement_group"
 ]

python/ray/experimental/api.py

@@ -1,59 +0,0 @@
-import ray
-import numpy as np
-
-
-def get(object_refs):
-    """Get a single or a collection of remote objects from the object store.
-
-    This method is identical to `ray.get` except it adds support for tuples,
-    ndarrays and dictionaries.
-
-    Args:
-        object_refs: Object ref of the object to get, a list, tuple, ndarray of
-            object refs to get or a dict of {key: object ref}.
-
-    Returns:
-        A Python object, a list of Python objects or a dict of {key: object}.
-    """
-    if isinstance(object_refs, (tuple, np.ndarray)):
-        return ray.get(list(object_refs))
-    elif isinstance(object_refs, dict):
-        keys_to_get = [
-            k for k, v in object_refs.items() if isinstance(v, ray.ObjectRef)
-        ]
-        ids_to_get = [
-            v for k, v in object_refs.items() if isinstance(v, ray.ObjectRef)
-        ]
-        values = ray.get(ids_to_get)
-
-        result = object_refs.copy()
-        for key, value in zip(keys_to_get, values):
-            result[key] = value
-        return result
-    else:
-        return ray.get(object_refs)
-
-
-def wait(object_refs, num_returns=1, timeout=None):
-    """Return a list of IDs that are ready and a list of IDs that are not.
-
-    This method is identical to `ray.wait` except it adds support for tuples
-    and ndarrays.
-
-    Args:
-        object_refs (List[ObjectRef], Tuple(ObjectRef), np.array(ObjectRef)):
-            List like of object refs for objects that may or may not be ready.
-            Note that these IDs must be unique.
-        num_returns (int): The number of object refs that should be returned.
-        timeout (float): The maximum amount of time in seconds to wait before
-            returning.
-
-    Returns:
-        A list of object refs that are ready and a list of the remaining object
-            IDs.
-    """
-    if isinstance(object_refs, (tuple, np.ndarray)):
-        return ray.wait(
-            list(object_refs), num_returns=num_returns, timeout=timeout)
-
-    return ray.wait(object_refs, num_returns=num_returns, timeout=timeout)