How to Get Current CPU and RAM Usage in Python

Summary: Learn how to monitor your system's CPU and RAM usage using Python with practical code examples and explanations. Perfect for developers looking to integrate resource monitoring into their applications.
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Monitoring system resources like CPU and RAM usage is crucial for optimizing performance, troubleshooting issues, and ensuring the stability of applications. Python, with its rich ecosystem of libraries, offers simple and effective ways to retrieve this information. In this post, we'll explore how to get current CPU and RAM usage in Python using the psutil library.

Installing psutil

First, you'll need to install the psutil library, which provides an interface for retrieving information on system utilization. You can install it using pip:

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Getting CPU Usage

To get the current CPU usage, you can use the cpu_percent() function from the psutil library. This function returns the percentage of CPU usage.

Here's a basic example:

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In this example, the interval parameter specifies the duration (in seconds) for which the CPU usage is calculated. A value of 1 means the function will measure the CPU usage over one second.

Getting RAM Usage

For RAM usage, the virtual_memory() function in psutil provides a detailed breakdown of memory statistics. The most relevant attributes are total, available, percent, used, and free.

Here's how you can get and print the current RAM usage:

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In this example, the memory values are converted from bytes to gigabytes for easier reading. The percent attribute gives the current RAM usage as a percentage of the total RAM.

Combining CPU and RAM Usage

You can combine both CPU and RAM usage information into a single script:

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This script provides a snapshot of the system's current CPU and RAM usage, which can be useful for monitoring and debugging purposes.

Conclusion

Monitoring CPU and RAM usage in Python is straightforward with the psutil library. By integrating these snippets into your applications, you can keep track of resource usage and ensure your programs run efficiently. Whether you're developing performance-critical applications or just curious about your system's resource utilization, these tools can provide valuable insights.