Скачать или смотреть Running Multiple Commands with Python's subprocess Without Waiting

Discover how to run multiple commands simultaneously in Python using the `subprocess` module. Learn to optimize your script to execute tasks in parallel for increased efficiency.
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Running Multiple Commands with Python's subprocess Without Waiting: A Complete Guide

When working on tasks in Python that require executing commands on multiple cloud instances (like the Google Cloud Platform or GCP), you may find yourself facing a frustrating bottleneck: each command waits for the previous one to complete. This sequential processing can severely limit efficiency, especially when dealing with long-running scripts that can take days to complete. In this guide, we’ll explore how to overcome this challenge by running multiple commands simultaneously with Python’s subprocess module.

The Problem Explained

Imagine you have two Python scripts:

First Script: A long-running process that takes a considerable amount of time to complete. In this scenario, it needs to run in 29 different regions on GCP.

Second Script: A utility that connects to each of these cloud instances via SSH and starts the first script.

The key issue arises when you execute the first script through the second script. By default, the subprocess.run() function causes your second script to wait for the first script to finish before starting the next one in the subsequent region. This not only delays your overall execution time but also adds unnecessary complexity and frustration.

The Solution: Using Popen for Parallel Execution

To enable your second script to start the first script on all regions without waiting for each to finish, you can use the Popen function from Python's subprocess module instead of subprocess.run(). This allows the tasks to run in parallel.

Implementation Steps

Here is how to modify your second script to achieve parallel execution:

Import the necessary module.
Make sure to import Popen from the subprocess module:

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

Change the command execution method.
Instead of using subprocess.run(command_lst), use Popen() to initiate processes. Here’s a simple example of how you can implement it:

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

Handle multiple processes.
If you need to manage the processes later, you might want to keep track of them:

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

Important Tips

Use shell=True with caution: When using shell=True, ensure that your commands and arguments are properly sanitized to avoid security risks.

Monitor process outputs: If you need to capture outputs from these processes, consider using subprocess.PIPE and then process.communicate().

Error handling: Implement error handling to manage failed processes effectively.

Conclusion

By switching from subprocess.run() to Popen in your Python scripts, you can significantly enhance the efficiency of your operations in multi-region environments. This allows your long-running scripts to execute concurrently, saving you precious time and resources in environments like Google Cloud Platform.

This approach not only streamlines your workflow but also optimizes your resource utilization across different instances. With these tips, you'll be able to tackle similar challenges in your future projects with ease!