[minor] Remove get_global_worker(), RuntimeContext (#7638)

python/ray/__init__.py

@@ -96,7 +96,6 @@ import ray.projects  # noqa: E402
 # some functions in the worker.
 import ray.actor  # noqa: F401
 from ray.actor import method  # noqa: E402
-from ray.runtime_context import _get_runtime_context  # noqa: E402
 from ray.cross_language import java_function, java_actor_class  # noqa: E402
 from ray import util  # noqa: E402
 

python/ray/_raylet.pyx

@@ -953,7 +953,7 @@ cdef class CoreWorker:
             CObjectID c_outer_object_id = (outer_object_id.native() if
                                            outer_object_id else
                                            CObjectID.Nil())
-        worker = ray.worker.get_global_worker()
+        worker = ray.worker.global_worker
         worker.check_connected()
         manager = worker.function_actor_manager
         c_actor_id = self.core_worker.get().DeserializeAndRegisterActorHandle(

python/ray/actor.py

@@ -463,7 +463,7 @@ class ActorClass:
         if max_concurrency < 1:
             raise ValueError("max_concurrency must be >= 1")
 
-        worker = ray.worker.get_global_worker()
+        worker = ray.worker.global_worker
         if worker.mode is None:
             raise RuntimeError("Actors cannot be created before ray.init() "
                                "has been called.")
@@ -655,7 +655,7 @@ class ActorHandle:
     def __del__(self):
         # Mark that this actor handle has gone out of scope. Once all actor
         # handles are out of scope, the actor will exit.
-        worker = ray.worker.get_global_worker()
+        worker = ray.worker.global_worker
         if worker.connected and hasattr(worker, "core_worker"):
             worker.core_worker.remove_actor_handle_reference(
                 self._ray_actor_id)
@@ -682,7 +682,7 @@ class ActorHandle:
             object_ids: A list of object IDs returned by the remote actor
                 method.
         """
-        worker = ray.worker.get_global_worker()
+        worker = ray.worker.global_worker
 
         args = args or []
         kwargs = kwargs or {}
@@ -776,7 +776,7 @@ class ActorHandle:
         Returns:
             A dictionary of the information needed to reconstruct the object.
         """
-        worker = ray.worker.get_global_worker()
+        worker = ray.worker.global_worker
         worker.check_connected()
 
         if hasattr(worker, "core_worker"):
@@ -809,7 +809,7 @@ class ActorHandle:
                 the actor handle.
 
         """
-        worker = ray.worker.get_global_worker()
+        worker = ray.worker.global_worker
         worker.check_connected()
 
         if hasattr(worker, "core_worker"):
@@ -859,7 +859,7 @@ def modify_class(cls):
         __ray_actor_class__ = cls  # The original actor class
 
         def __ray_terminate__(self):
-            worker = ray.worker.get_global_worker()
+            worker = ray.worker.global_worker
             if worker.mode != ray.LOCAL_MODE:
                 ray.actor.exit_actor()
 
@@ -937,8 +937,6 @@ def exit_actor():
         raise TypeError("exit_actor called on a non-actor worker.")
 
 
-ray.worker.global_worker.make_actor = make_actor
-
 CheckpointContext = namedtuple(
     "CheckpointContext",
     [

python/ray/exceptions.py

@@ -11,6 +11,11 @@ class RayError(Exception):
     pass
 
 
+class RayConnectionError(RayError):
+    """Raised when ray is not yet connected but needs to be."""
+    pass
+
+
 class RayTaskError(RayError):
     """Indicates that a task threw an exception during execution.
 

python/ray/experimental/internal_kv.py

@@ -4,14 +4,14 @@ _local = {}  # dict for local mode
 
 
 def _internal_kv_initialized():
-    worker = ray.worker.get_global_worker()
+    worker = ray.worker.global_worker
     return hasattr(worker, "mode") and worker.mode is not None
 
 
 def _internal_kv_get(key):
     """Fetch the value of a binary key."""
 
-    worker = ray.worker.get_global_worker()
+    worker = ray.worker.global_worker
     if worker.mode == ray.worker.LOCAL_MODE:
         return _local.get(key)
 
@@ -27,7 +27,7 @@ def _internal_kv_put(key, value, overwrite=False):
         already_exists (bool): whether the value already exists.
     """
 
-    worker = ray.worker.get_global_worker()
+    worker = ray.worker.global_worker
     if worker.mode == ray.worker.LOCAL_MODE:
         exists = key in _local
         if not exists or overwrite:

python/ray/internal/internal_api.py

@@ -7,7 +7,7 @@ __all__ = ["free", "global_gc"]
 def global_gc():
     """Trigger gc.collect() on all workers in the cluster."""
 
-    worker = ray.worker.get_global_worker()
+    worker = ray.worker.global_worker
     worker.core_worker.global_gc()
 
 
@@ -54,7 +54,7 @@ def free(object_ids, local_only=False, delete_creating_tasks=False):
         delete_creating_tasks (bool): Whether also delete the object creating
             tasks.
     """
-    worker = ray.worker.get_global_worker()
+    worker = ray.worker.global_worker
 
     if isinstance(object_ids, ray.ObjectID):
         object_ids = [object_ids]

python/ray/remote_function.py

@@ -150,7 +150,7 @@ class RemoteFunction:
                 resources=None,
                 max_retries=None):
         """Submit the remote function for execution."""
-        worker = ray.worker.get_global_worker()
+        worker = ray.worker.global_worker
         worker.check_connected()
 
         # If this function was not exported in this session and job, we need to

python/ray/runtime_context.py

@@ -1,30 +0,0 @@
-import ray.worker
-
-
-class RuntimeContext:
-    """A class used for getting runtime context."""
-
-    def __init__(self, worker=None):
-        self.worker = worker
-
-    @property
-    def current_driver_id(self):
-        """Get current driver ID for this worker or driver.
-
-        Returns:
-            If called by a driver, this returns the driver ID. If called in
-                a task, return the driver ID of the associated driver.
-        """
-        assert self.worker is not None
-        return self.worker.current_job_id
-
-
-_runtime_context = None
-
-
-def _get_runtime_context():
-    global _runtime_context
-    if _runtime_context is None:
-        _runtime_context = RuntimeContext(ray.worker.get_global_worker())
-
-    return _runtime_context

python/ray/serialization.py

@@ -164,7 +164,7 @@ class SerializationContext:
             # TODO(swang): Remove this check. Otherwise, we will not be able to
             # handle serialized plasma IDs correctly.
             if obj.is_direct_call_type():
-                worker = ray.worker.get_global_worker()
+                worker = ray.worker.global_worker
                 worker.check_connected()
                 obj, owner_id, owner_address = (
                     worker.core_worker.serialize_and_promote_object_id(obj))
@@ -184,7 +184,7 @@ class SerializationContext:
             # somewhere, which causes an error.
             context = ray.worker.global_worker.get_serialization_context()
             if owner_id:
-                worker = ray.worker.get_global_worker()
+                worker = ray.worker.global_worker
                 worker.check_connected()
                 # UniqueIDs are serialized as
                 # (class name, (unique bytes,)).
@@ -250,7 +250,7 @@ class SerializationContext:
             # cloudpickle directly or captured in a remote function/actor),
             # then pin the object for the lifetime of this worker by adding
             # a local reference that won't ever be removed.
-            ray.worker.get_global_worker().core_worker.add_object_id_reference(
+            ray.worker.global_worker.core_worker.add_object_id_reference(
                 object_id)
 
     def _deserialize_pickle5_data(self, data):

python/ray/tests/test_advanced_3.py

@@ -299,12 +299,12 @@ def test_specific_job_id():
     ray.init(num_cpus=1, job_id=dummy_driver_id)
 
     # in driver
-    assert dummy_driver_id == ray._get_runtime_context().current_driver_id
+    assert dummy_driver_id == ray.worker.global_worker.current_job_id
 
     # in worker
     @ray.remote
     def f():
-        return ray._get_runtime_context().current_driver_id
+        return ray.worker.global_worker.current_job_id
 
     assert dummy_driver_id == ray.get(f.remote())
 

python/ray/worker.py

@@ -42,6 +42,7 @@ from ray import import_thread
 from ray import profiling
 
 from ray.exceptions import (
+    RayConnectionError,
     RayError,
     RayTaskError,
     ObjectStoreFullError,
@@ -108,7 +109,6 @@ class Worker:
         self.mode = None
         self.cached_functions_to_run = []
         self.actor_init_error = None
-        self.make_actor = None
         self.actors = {}
         # Information used to maintain actor checkpoints.
         self.actor_checkpoint_info = {}
@@ -496,10 +496,6 @@ _global_node = None
 """ray.node.Node: The global node object that is created by ray.init()."""
 
 
-class RayConnectionError(Exception):
-    pass
-
-
 def print_failed_task(task_status):
     """Print information about failed tasks.
 
@@ -886,6 +882,7 @@ def shutdown(exiting_interpreter=False):
 atexit.register(shutdown, True)
 
 
+# TODO(edoakes): this should only be set in the driver.
 def sigterm_handler(signum, frame):
     sys.exit(signal.SIGTERM)
 
@@ -1675,7 +1672,8 @@ def kill(actor):
         raise ValueError("ray.kill() only supported for actors. "
                          "Got: {}.".format(type(actor)))
 
-    worker = ray.worker.get_global_worker()
+    worker = ray.worker.global_worker
+    worker.check_connected()
     worker.core_worker.kill_actor(actor._ray_actor_id, False)
 
 
@@ -1690,10 +1688,6 @@ def _mode(worker=global_worker):
     return worker.mode
 
 
-def get_global_worker():
-    return global_worker
-
-
 def make_decorator(num_return_vals=None,
                    num_cpus=None,
                    num_gpus=None,
@@ -1725,9 +1719,9 @@ def make_decorator(num_return_vals=None,
                 raise TypeError("The keyword 'max_calls' is not "
                                 "allowed for actors.")
 
-            return worker.make_actor(function_or_class, num_cpus, num_gpus,
-                                     memory, object_store_memory, resources,
-                                     max_reconstructions)
+            return ray.actor.make_actor(function_or_class, num_cpus, num_gpus,
+                                        memory, object_store_memory, resources,
+                                        max_reconstructions)
 
         raise TypeError("The @ray.remote decorator must be applied to "
                         "either a function or to a class.")
@@ -1815,7 +1809,7 @@ def remote(*args, **kwargs):
     work and then shut down. If you want to kill them immediately, you can
     also call ``ray.kill(actor)``.
     """
-    worker = get_global_worker()
+    worker = global_worker
 
     if len(args) == 1 and len(kwargs) == 0 and callable(args[0]):
         # This is the case where the decorator is just @ray.remote.