chore: import upstream snapshot with attribution

python/ray/tests/autoscaler/test_providers.py

@@ -0,0 +1,38 @@
+import unittest
+
+import yaml
+
+from ray.autoscaler._private.providers import (
+    _DEFAULT_CONFIGS,
+    _NODE_PROVIDERS,
+    _PROVIDER_PRETTY_NAMES,
+)
+
+
+class TestProviders(unittest.TestCase):
+    def test_node_providers(self):
+        for provider_name, provider_cls in _NODE_PROVIDERS.items():
+            config = {"module": "ray.autoscaler._private"}
+
+            try:
+                provider_cls(config)
+            except ImportError as e:
+                if f"ray.autoscaler.{provider_name}" in str(e):
+                    self.fail(
+                        f"Unexpected import error for provider {provider_name}: {e}"
+                    )
+
+    def test_provider_pretty_names(self):
+        self.assertEqual(
+            set(_NODE_PROVIDERS.keys()), set(_PROVIDER_PRETTY_NAMES.keys())
+        )
+
+    def test_default_configs(self):
+        for config_loader in _DEFAULT_CONFIGS.values():
+            config_path = config_loader()
+            with open(config_path) as f:
+                yaml.safe_load(f)
+
+
+if __name__ == "__main__":
+    unittest.main()

python/ray/tests/autoscaler/util.py

@@ -0,0 +1,68 @@
+import unittest
+from unittest.mock import Mock
+
+from ray.autoscaler._private.util import get_per_node_breakdown_as_dict
+
+
+class TestGetPerNodeBreakdown(unittest.TestCase):
+    def setUp(self):
+        # Create a mock LoadMetricsSummary object with the required attributes
+        lm_summary_mock_data = {
+            "e9919752e5e8d757765d97d8bec910a2e78e8826f20bce46fd58f92e": {
+                "node:172.31.6.57": [0.0, 1.0],
+                "object_store_memory": [0.0, 13984228147.0],
+                "memory": [0.0, 27968456295.0],
+                "node:__internal_head__": [0.0, 1.0],
+                "CPU": [0.0, 8.0],
+            }
+        }
+        self.lm_summary_mock = Mock()
+        self.lm_summary_mock.usage_by_node = lm_summary_mock_data
+
+    def test_get_per_node_breakdown_as_dict(self):
+        result = get_per_node_breakdown_as_dict(self.lm_summary_mock)
+
+        expected_output = {
+            "e9919752e5e8d757765d97d8bec910a2e78e8826f20bce46fd58f92e": (
+                "0.0/8.0 CPU\n0B/26.05GiB memory\n0B/13.02GiB object_store_memory"
+            )
+        }
+
+        self.assertEqual(result, expected_output)
+
+    def test_get_per_node_breakdown_as_dict_empty_summary(self):
+        # Test with an empty lm_summary
+        lm_summary_mock_data = {}
+        self.lm_summary_mock.usage_by_node = lm_summary_mock_data
+
+        result = get_per_node_breakdown_as_dict(self.lm_summary_mock)
+
+        expected_output = {}
+
+        self.assertEqual(result, expected_output)
+
+    def test_get_per_node_breakdown_as_dict_missing_usage(self):
+        # Test with missing usage data for a node
+        lm_summary_mock_data = {
+            "e9919752e5e8d757765d97d8bec910a2e78e8826f20bce46fd58f92e": {
+                "node:172.31.6.57": [0.0, 1.0],
+                "object_store_memory": [0.0, 13984228147.0],
+                # 'memory': [0.0, 27968456295.0],  # Missing memory data
+                "node:__internal_head__": [0.0, 1.0],
+                "CPU": [0.0, 8.0],
+            }
+        }
+        self.lm_summary_mock.usage_by_node = lm_summary_mock_data
+
+        result = get_per_node_breakdown_as_dict(self.lm_summary_mock)
+
+        expected_output = {
+            "e9919752e5e8d757765d97d8bec910a2e78e8826f20bce46fd58f92e": "0.0/8.0 CPU\n"
+            "0B/13.02GiB object_store_memory"
+        }
+
+        self.assertEqual(result, expected_output)
+
+
+if __name__ == "__main__":
+    unittest.main()