chore: import upstream snapshot with attribution

python/ray/experimental/job/example_job/demo_script.py

@@ -0,0 +1,77 @@
+# Regular ray application that user wrote and runs on local cluster.
+# intermediate status are dumped to GCS
+import argparse
+import time
+
+import ray
+import ray.experimental.internal_kv as ray_kv
+
+
+@ray.remote
+class StepActor:
+    def __init__(self, interval_s=1, total_steps=3):
+        self.interval_s = interval_s
+        self.stopped = False
+        self.current_step = 1
+        self.total_steps = total_steps
+
+        worker = ray._private.worker.global_worker
+        worker_id = worker.core_worker.get_actor_id()
+        ray_kv._internal_kv_put(f"JOB:{worker_id}", self.current_step, overwrite=True)
+
+    def run(self):
+        worker = ray._private.worker.global_worker
+        worker_id = worker.core_worker.get_actor_id()
+
+        while self.current_step <= self.total_steps:
+            if not self.stopped:
+                print(
+                    f"Sleeping {self.interval_s} secs to executing "
+                    f"step {self.current_step}"
+                )
+                time.sleep(self.interval_s)
+                self.current_step += 1
+                ray_kv._internal_kv_put(
+                    f"JOB:{worker_id}", self.current_step, overwrite=True
+                )
+            else:
+                print("Stop called or reached final step.")
+                break
+
+        self.stopped = True
+        ray_kv._internal_kv_put(f"JOB:{worker_id}", "DONE", overwrite=True)
+        return "DONE"
+
+    def get_step(self):
+        return self.current_step
+
+    def stop(self):
+        self.stopped = True
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--interval-s",
+        required=False,
+        type=int,
+        default=1,
+        help="Address to use to connect to Ray",
+    )
+    parser.add_argument(
+        "--total-steps",
+        required=False,
+        type=int,
+        default=3,
+        help="Password for connecting to Redis",
+    )
+    args, _ = parser.parse_known_args()
+
+    ray.init()
+    step_actor = StepActor.remote(
+        interval_s=args.interval_s, total_steps=args.total_steps
+    )
+    ref = step_actor.run.remote()
+    print(ray.get([ref]))
+    job_key = ray_kv._internal_kv_list("JOB:")[0]
+    print(f"{job_key}, {ray_kv._internal_kv_get(job_key)}")

python/ray/experimental/job/example_job/job_config.yaml

@@ -0,0 +1,5 @@
+name: example_job
+command: python demo_script.py
+runtime_env:
+    working_dir: .
+    docker: anyscale-ml/ray-ml:nightly-py38-cpu