CPU and Memory usage monitoring script for ROS

engineering_tools/monitor-ros-cpu.py

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+#!/usr/bin/env python3
+
+"""
+CARMA Platform CPU Monitor Script
+
+Requirements:
+    - Python 3.6 or higher
+    - psutil package (install with: pip3 install psutil)
+
+Usage:
+    1. Open a new terminal before starting CARMA Platform
+    2. Navigate to the directory containing this script:
+       cd /path/to/script/
+
+    3. Run this script:
+       python3 monitor-ros-cpu.py
+
+    4. In a different terminal, start CARMA Platform:
+       ./carma start all
+
+    5. The script will automatically monitor and log CPU/memory usage
+       of all ROS2 nodes and related processes during CARMA operation
+
+    6. To stop monitoring:
+       - Press Ctrl+C in the monitoring terminal
+       - The CSV output file will be saved in the current directory as:
+         'cpu_usage_ros2_nodes.csv' or 'cpu_usage_ros2_nodes-N.csv'
+
+Output:
+    - CSV file containing timestamp, process info, CPU and memory usage
+    - Data can be used to analyze CARMA Platform resource utilization
+"""
+
+import psutil
+import subprocess
+import time
+import csv
+import os
+from datetime import datetime
+
+
+# Function to create a unique filename by appending a number
+def get_unique_filename(base_filename):
+    counter = 1
+    filename, file_extension = os.path.splitext(base_filename)
+
+    # Loop until a file with a unique name is found
+    while os.path.isfile(base_filename):
+        base_filename = f"{filename}-{counter}{file_extension}"
+        counter += 1
+    return base_filename
+
+
+# Base path to save the CSV file
+base_output_file = "cpu_usage_ros2_nodes.csv"
+
+# Get a unique filename
+output_file = get_unique_filename(base_output_file)
+
+# Open CSV file to store process usage data
+with open(output_file, mode="a") as file:
+    writer = csv.writer(file)
+
+    # Write the header since it's a new file
+    writer.writerow(
+        [
+            "Timestamp",
+            "PID",
+            "Process Name",
+            "CPU (%)",
+            "Memory (%)",
+            "Command Line",
+            "Total CPU (%)",
+        ]
+    )
+
+    while True:
+        # Get the current time with milliseconds
+        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S.%f")[:-3]
+
+        # Get total CPU usage (overall system CPU usage)
+        total_cpu_percent = psutil.cpu_percent(interval=None)  # Get immediate CPU usage
+
+        # Get list of running processes
+        for proc in psutil.process_iter(
+            ["pid", "name", "cpu_percent", "memory_percent", "cmdline"]
+        ):
+            try:
+                # Get CPU and memory usage of the process
+                cmdline = " ".join(proc.info["cmdline"])  # Convert list to string
+                if (
+                    "ros" in proc.info["name"]
+                    or "node" in proc.info["name"]
+                    or "node" in cmdline
+                    or "python3" in proc.info["name"]
+                    or "ros" in cmdline
+                ) and not ("code" in proc.info["name"]):
+                    pid = proc.info["pid"]
+                    name = proc.info["name"]
+                    cpu_percent = proc.info["cpu_percent"]
+                    memory_percent = proc.info["memory_percent"]
+
+                    # Write process data to CSV, including the total CPU usage
+                    writer.writerow(
+                        [
+                            timestamp,
+                            pid,
+                            name,
+                            cpu_percent,
+                            memory_percent,
+                            cmdline,
+                            total_cpu_percent,
+                        ]
+                    )
+
+            except (psutil.NoSuchProcess, psutil.AccessDenied, psutil.ZombieProcess):
+                # Handle any processes that may have terminated or restricted access
+                continue
+
+        # Sleep for 1 second before the next iteration
+        time.sleep(1)