Update resource_manager.py

restored parallel processing

lxc_autoscale/resource_manager.py

@@ -11,20 +11,24 @@
 from scaling_manager import manage_horizontal_scaling, adjust_resources  # Import scaling management functions
 from notification import send_notification  # Import notification function
 from config import HORIZONTAL_SCALING_GROUPS, IGNORE_LXC, DEFAULTS  # Import configuration constants
+from concurrent.futures import ThreadPoolExecutor, as_completed
 
-def collect_container_data():
+def collect_data_for_container(ctid):
     """
-    Collect resource usage data for all LXC containers.
+    Collect resource usage data for a single LXC container.
+    
+    Args:
+        ctid (str): The container ID.
     
     Returns:
-        dict: A dictionary where the keys are container IDs and the values are their respective data.
+        dict: The data collected for the container, or None if the container is not running.
     """
-    containers = {}
-    for ctid in get_containers():
-        if not is_container_running(ctid):
-            continue
-        logging.debug(f"Collecting data for container {ctid}...")
-        
+    if not is_container_running(ctid):
+        return None
+
+    logging.debug(f"Collecting data for container {ctid}...")
+
+    try:
         # Retrieve the current configuration of the container
         cores = int(run_command(f"pct config {ctid} | grep cores | awk '{{print $2}}'"))
         memory = int(run_command(f"pct config {ctid} | grep memory | awk '{{print $2}}'"))
@@ -34,14 +38,38 @@ def collect_container_data():
         backup_container_settings(ctid, settings)
 
         # Collect CPU and memory usage data
-        containers[ctid] = {
-            "cpu": get_cpu_usage(ctid),
-            "mem": get_memory_usage(ctid),
-            "initial_cores": cores,
-            "initial_memory": memory,
+        return {
+            ctid: {
+                "cpu": get_cpu_usage(ctid),
+                "mem": get_memory_usage(ctid),
+                "initial_cores": cores,
+                "initial_memory": memory,
+            }
         }
+    except Exception as e:
+        logging.error(f"Error collecting data for container {ctid}: {e}")
+        return None
+
+def collect_container_data():
+    """
+    Collect resource usage data for all LXC containers.
+    
+    Returns:
+        dict: A dictionary where the keys are container IDs and the values are their respective data.
+    """
+    containers = {}
+    with ThreadPoolExecutor(max_workers=8) as executor:  # Adjust max_workers based on your CPU capability
+        futures = {executor.submit(collect_data_for_container, ctid): ctid for ctid in get_containers()}
+        for future in as_completed(futures):
+            container_data = future.result()
+            if container_data:
+                containers.update(container_data)
     return containers
 
+
+
+
+
 def main_loop(poll_interval, energy_mode):
     """
     Main loop that handles the resource allocation and scaling process.