Gunicorn

Here's a quick rundown on how to get gunicorn with Gunicorn. For more details read the documentation, gunicorn. We strongly advise you to use nginx.

Up to this point, with all the tutorials in the docs, you have probably been running a server program like Uvicorn, running a single process. When deploying applications you will probably want to have some replication of processes to take advantage of multiple cores and to be able to handle more requests. As you saw in the previous chapter about Deployment Concepts , there are multiple strategies you can use. Here I'll show you how to use Gunicorn with Uvicorn worker processes. In particular, when running on Kubernetes you will probably not want to use Gunicorn and instead run a single Uvicorn process per container , but I'll tell you about it later in that chapter. Gunicorn is mainly an application server using the WSGI standard. That means that Gunicorn can serve applications like Flask and Django.

Gunicorn

It has no dependencies and can be installed using pip. Install gunicorn by running python -m pip install gunicorn. For more details, see the gunicorn documentation. When Gunicorn is installed, a gunicorn command is available which starts the Gunicorn server process. The simplest invocation of gunicorn is to pass the location of a module containing a WSGI application object named application , which for a typical Django project would look like:. This will start one process running one thread listening on It requires that your project be on the Python path; the simplest way to ensure that is to run this command from the same directory as your manage. Offline Django 5. Django is a registered trademark of the Django Software Foundation. Django The web framework for perfectionists with deadlines. Menu Toggle theme current theme: auto. Documentation Search: Search.

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Web applications that process incoming HTTP requests concurrently make much more efficient use of dyno resources than web applications that only process one request at a time. Because of this, we recommend using web servers that support concurrent request processing whenever developing and running production services. The Django and Flask web frameworks feature convenient built-in web servers, but these blocking servers only process a single request at a time. If you deploy with one of these servers on Heroku, your dyno resources will be underutilized and your application will feel unresponsive. It allows you to run any Python application concurrently by running multiple Python processes within a single dyno. It provides a perfect balance of performance, flexibility, and configuration simplicity. This guide will walk you through deploying a new Python application to Heroku using the Gunicorn web server.

Flask is a popular web framework for building web applications in Python. It is considered a microframework because it provides only the bare essentials for web development, focusing on simplicity and extensibility. Flask also has a server to do local deployments and test the application, but no one would go with it to production. In this tutorial, you will learn how to create a Flask application, configure it to Gunicorn, and containerize it. Create a new file with the name requirements. Then update the pip dependencies and install the dependencies by running the following command:. So far, so good, but as the log message says, we need another way to use a WSGI server for going to production.

Gunicorn

You take it as a given, and just hope that your web app will work as expected when you deploy it. That sounds like a lot of work. And a lot of work which is the same across most web applications you might come up with. This is good news! Because those problems are so common, you can build tools which take care of them. The web server accepts requests, takes care of general domain logic and takes care of handling https connections. Only requests which are meant to arrive at the application are passed on toward the application server and the application itself.

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If you deploy with one of these servers on Heroku, your dyno resources will be underutilized and your application will feel unresponsive. We recommend knowing the memory requirements of your processes and setting this configuration variable accordingly. How to deploy with WSGI. So, if you want to have a process manager at this level at the Python level , then it might be better to try with Gunicorn as the process manager. Nov 23, Project links Homepage Documentation Issue tracker Source code. Gunicorn would also take care of managing dead processes and restarting new ones if needed to keep the number of workers. Aug 6, Released: Jul 19, Docker and Kubernetes.

Now the problem is a python web application cannot be deployed on traditional web servers such as Apache because they are designed to serve static web pages created using HTML and CSS. Python web applications are more complex than static web pages, so you need a WSGI server like Gunicorn specifically intended for Python web applications and frameworks. If your application contains static content, you can usually use a server such as Nginx to serve the static content.

But Gunicorn supports working as a process manager and allowing users to tell it which specific worker process class to use. You will see that those tools have simple ways to solve the other deployment concepts as well. You can imagine that main:app is equivalent to a Python import statement like:. Support Django! Aug 13, Aug 27, Aug 22, In particular, when running on Kubernetes you will probably not want to use Gunicorn and instead run a single Uvicorn process per container , but I'll tell you about it later in that chapter. Install gunicorn by running python -m pip install gunicorn. May 15, Dec 25, If you expect your application to respond quickly to constant incoming flow of requests, try experimenting with a lower timeout configuration. Navigation Project description Release history Download files. Nov 9, Nov 23,