CommandTracker 0.1.5

Paquete para ejecutar comandos y monitorear uso de CPU y memoria

CommandTracker

CommandTracker is a Python tool designed to execute a command and monitor its resource usage in real time. It tracks CPU and memory consumption, providing valuable performance metrics like average CPU load and peak memory usage. This tool is ideal for developers and system administrators looking to optimize the performance of commands or processes.

Features

• Monitor CPU and memory usage of any command.
• Real-time resource tracking during command execution.
• Provides performance statistics, including average CPU usage and peak memory consumption.
• Generation of graphs to visualize resource usage.
• Historical logging of command execution.

Installation

You can install CommandTracker via pip:

pip install CommandTracker

Usage

Once installed, you can use ctracker to monitor a command’s resource usage:

ctracker monitor <command>

For example:

ctracker monitor php artisan calc --date=2024-01-01

Example Output:

Starting process with PID 12345...

Output of your command...

Process finished.
Total execution time: 10.25 seconds.

Resource usage statistics:
Average CPU usage: 35.67%
Maximum memory usage: 120.45 MB

Use -g or --graph to generate graphs.

ctracker monitor -g <command>

For example:

ctracker monitor -g php artisan calc --date=2024-01-01

Example Output:

CPU usage graph:

Memory usage graph:

History logs

Use ctracker history to see the all command history.

ctracker history

Example Output:

  2024-10-02 09:12:30 python3 script.py --input=data.csv --output=result.txt Total execution time: 25.78 seconds. Average CPU usage: 3.12% Maximum memory usage: 75.34 MB
  2024-10-02 09:15:45 php74 artisan migrate --force Total execution time: 12.43 seconds. Average CPU usage: 1.58% Maximum memory usage: 65.12 MB
  2024-10-02 09:20:10 node server.js Total execution time: 50.92 seconds. Average CPU usage: 4.67% Maximum memory usage: 120.87 MB
  2024-10-02 09:25:00 bash backup.sh --full Total execution time: 105.34 seconds. Average CPU usage: 2.87% Maximum memory usage: 200.45 MB
  2024-10-02 09:30:40 ruby script.rb --optimize Total execution time: 30.22 seconds. Average CPU usage: 2.45% Maximum memory usage: 78.65 MB

For find command history:

ctracker history <command>

For example:

ctracker history python3 script.py --input=data.csv --output=result.txt

Example Output:

  2024-10-02 09:12:30 python3 script.py --input=data.csv --output=result.txt Total execution time: 25.78 seconds. Average CPU usage: 3.12% Maximum memory usage: 75.34 MB
  2024-10-02 09:14:15 python3 script.py --input=data.csv --output=result.txt Total execution time: 30.21 seconds. Average CPU usage: 4.10% Maximum memory usage: 80.45 MB
  2024-10-02 09:16:05 python3 script.py --input=data.csv --output=result.txt Total execution time: 22.56 seconds. Average CPU usage: 2.98% Maximum memory usage: 72.15 MB
  2024-10-02 09:18:50 python3 script.py --input=data.csv --output=result.txt Total execution time: 28.90 seconds. Average CPU usage: 3.54% Maximum memory usage: 78.22 MB
  2024-10-02 09:21:33 python3 script.py --input=data.csv --output=result.txt Total execution time: 35.67 seconds. Average CPU usage: 4.75% Maximum memory usage: 82.90 MB
  2024-10-02 09:23:25 python3 script.py --input=data.csv --output=result.txt Total execution time: 18.45 seconds. Average CPU usage: 2.65% Maximum memory usage: 68.12 MB
  2024-10-02 09:25:12 python3 script.py --input=data.csv --output=result.txt Total execution time: 29.88 seconds. Average CPU usage: 3.87% Maximum memory usage: 77.56 MB

Requirements

• Python 3.6+
• psutil library

Contributing

Feel free to contribute by submitting issues or pull requests. More features and optimizations will be added in future versions.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Future Enhancements

Planned features for future releases include:

• Automatic alerts if a process exceeds certain CPU or memory thresholds. • Stress testing to simulate intensive workloads.