Скачать или смотреть How to Easily Get CPU Stats Every 15 Seconds Using Python

Learn how to monitor CPU usage with a simple Python script that fetches CPU statistics every 15 seconds using the `psutil` library.
---
This video is based on the question https://stackoverflow.com/q/71028846/ asked by the user 'codery' ( https://stackoverflow.com/u/17893920/ ) and on the answer https://stackoverflow.com/a/71028977/ provided by the user 'NameError' ( https://stackoverflow.com/u/16289704/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: how to get cpu stats every 15 seconds ? python

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Monitoring CPU Stats Every 15 Seconds with Python

Keeping an eye on your system's CPU usage is essential for performance optimization and resource management. You might find yourself asking: How can I get CPU stats every 15 seconds using Python? Luckily, with the help of the psutil library, this can be achieved quite easily.

In this guide, we will walk through a step-by-step approach to implement this functionality. Whether you're a beginner in Python or just need a refresher, this guide should help you monitor CPU statistics effectively.

What is psutil?

Before we dive into the code, let's briefly discuss what psutil is:

psutil: This is a cross-platform library used for retrieving information on system utilization (CPU, memory, disks, network, sensors) in Python. It provides an easy interface to access various system statistics, including CPU percentages.

How to Get CPU Stats Every 15 Seconds

Here's a simple and effective solution that incorporates a continuous loop to capture CPU usage every 15 seconds.

Step 1: Import Required Libraries

To start, ensure that you have the psutil library installed. If you haven't installed it yet, you can do this via pip:

[[See Video to Reveal this Text or Code Snippet]]

Next, let's start writing our Python script:

[[See Video to Reveal this Text or Code Snippet]]

Step 2: Creating the Loop

Now, we will use a while loop that will run indefinitely to fetch the CPU statistics every 15 seconds:

[[See Video to Reveal this Text or Code Snippet]]

Code Explanation

Infinite Loop (while True): The script will continue running until it's manually stopped (e.g., hitting Ctrl+ C).

Getting CPU Statistics:

Each call to psutil.cpu_percent(interval) calculates the CPU usage over the specified interval. In this case, we choose an interval of 1.5 seconds.

Calculating the Average: The script collects four samples of CPU usage and calculates their average to provide a more stable representation of CPU performance over time.

Time Delay: time.sleep(15) ensures there’s a 15-second delay before the next fetch of CPU statistics.

Exception Handling: The try-except block handles any potential errors smoothly without crashing the program.

Running the Script

Simply copy and paste the above code into a Python script file (e.g., monitor_cpu.py) and run it using the Python interpreter:

[[See Video to Reveal this Text or Code Snippet]]

Now you can monitor your system's CPU usage every 15 seconds!

Conclusion

With just a few lines of Python code, you can effectively monitor CPU statistics at regular intervals. Utilizing the psutil library simplifies the process and enriches your programming experience. Whether you're working on a performance-intensive application or simply want to keep an eye on your system resources, this approach provides a straightforward solution.

Feel free to enhance the script further, perhaps by logging the data to a file or even integrating with a graphical interface for better visualization. Happy coding!