Feature/high cpu mem analysis

notebooks/Efficiency Analysis.ipynb

@@ -90,18 +90,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# Automatically reload modules before executing code (set this up BEFORE imports)\n",
+    "%load_ext autoreload\n",
+    "%autoreload 2\n",
+    "\n",
     "# Add project root to sys.path for module imports\n",
     "if project_root not in sys.path:\n",
     "    sys.path.insert(0, project_root)\n",
     "\n",
     "from src.analysis import efficiency_analysis as ea\n",
     "from src.visualization import JobsWithMetricsVisualizer, UsersWithMetricsVisualizer\n",
-    "\n",
-    "# Automatically reload modules before executing code\n",
-    "# This is useful for development to see changes without restarting the kernel.\n",
-    "%load_ext autoreload\n",
-    "# Reload all modules imported with %aimport every time before executing the Python code typed.\n",
-    "%autoreload 2"
+    "from src.config.enum_constants import MetricsDataFrameNameEnum, ResourceHoardingDataFrameNameEnum"
    ]
   },
   {
@@ -135,7 +134,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "efficiency_analysis = ea.EfficiencyAnalysis(jobs_df=preprocessed_jobs_df)"
+    "efficiency_analysis = ea.EfficiencyAnalysis(\n",
+    "    jobs_df=preprocessed_jobs_df, metrics_df_name_enum=ResourceHoardingDataFrameNameEnum\n",
+    ")"
    ]
   },
   {
@@ -215,7 +216,7 @@
    "outputs": [],
    "source": [
     "inefficient_jobs_vram_hours = efficiency_analysis.sort_and_filter_records_with_metrics(\n",
-    "    metrics_df_name_enum=ea.MetricsDataFrameNameEnum.JOBS,\n",
+    "    metrics_df_name_enum=MetricsDataFrameNameEnum.JOBS,\n",
     "    sorting_key=\"vram_hours\",\n",
     "    ascending=False,  # Sort by vram_hours in descending order\n",
     "    filter_criteria={\n",
@@ -608,7 +609,11 @@
    ]
   }
  ],
- "metadata": {},
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
  "nbformat": 4,
  "nbformat_minor": 5
 }