Resolving the Duplicated Process Issue with Hypercorn in Python

Learn how to address and prevent duplicated processes when using Hypercorn with FastAPI on Python 3.8. This guide walks you through the steps to correctly implement and manage your server processes.
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Resolving the Duplicated Process Issue with Hypercorn in Python

When setting up a server with Hypercorn and FastAPI, you might stumble upon an unexpected issue: duplicated processes running in the background. This can lead to various problems, such as executing the same task multiple times and unnecessary resource consumption. If you've encountered this issue and are looking for a solution, you're in the right place! In this guide, we will delve into the root causes of the duplicated process problem and explore how to effectively address it.

Understanding the Duplicated Process Behavior

When running Hypercorn, it operates by creating a master process that supervises multiple worker processes. The master process handles incoming requests and delegates them to worker processes. Here’s a quick breakdown of the common processes you might see when running Hypercorn:

Master Process: This is the main process that oversees everything.

Worker Processes: These are child processes that handle the actual requests.

When using Hypercorn, you might see additional worker processes that are forked for handling various tasks. It's important to distinguish between these processes to avoid running into issues where the same task is processed multiple times.

Identifying the Problem

To identify the different processes involved in Hypercorn, you can execute a simple code snippet that checks if the current process is a daemon process. Add this code within your application:

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

This will output False for the master process and True for the worker processes. If you run your application with additional workers using hypercorn -w5 your_app:app, you should see multiple True outputs indicating the number of worker processes created.

Best Practices to Avoid Duplicated Processes

To prevent duplicated processes and to ensure stable and manageable execution in a production environment, follow these guidelines:

Use Process Guards: Place the implementation code inside the if __name__ == '__main__': guard to prevent it from being run multiple times when Hypercorn imports the module.

Here's an example for a FastAPI application:

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

Utilize a Process Manager: Instead of relying solely on Hypercorn to manage your background tasks, consider using process management tools like systemd or supervisord. These tools can help you ensure that your service is always running and can handle restarts gracefully.

Lifecycle Events: Implement lifecycle event handlers such as startup and shutdown within your FastAPI application to handle tasks and resource management more effectively during the application lifecycle.

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Testing Your Application

After implementing the above modifications, run your application with multiple workers:

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

This command will start your application with two worker processes, and you should see distinct outputs indicating the master and worker processes.

Conclusion

By understanding the process management of Hypercorn and implementing the recommended best practices, you can prevent duplicated processes in your application. This will not only enhance the stability of your server but also optimize its resource usage, making your FastAPI application more efficient in a production environment.

If you still face challenges or have specific concerns regarding Hypercorn's behavior, feel free to share your experience and we can troubleshoot further together!