About

Gunicorn 'Green Unicorn' is a Python WSGI HTTP Server for UNIX. It's a pre-fork worker model ported from Ruby's Unicorn project. The Gunicorn server is broadly compatible with various web frameworks, simply implemented, light on server resource usage, and fairly speedy.

Feel free to join us in #gunicorn on freenode.

Installation

Gunicorn requires Python 2.x >= 2.5. Python 3.x support is planned.

Install from sources:

$ python setup.py install

Or from Pypi:

$ easy_install -U gunicorn

You may also want to install Eventlet or Gevent if you expect that your application code may need to pause for extended periods of time during request processing. Check out the FAQ for more information on when you'll want to consider one of the alternate worker types.

To install eventlet:

$ easy_install -U eventlet

If you encounter errors when compiling the extensions for Eventlet or Gevent you most likely need to install a newer version of libev or libevent.

Basic Usage

After installing Gunicorn you will have access to three command line scripts that can be used for serving the various supported web frameworks: gunicorn, gunicorn_django, and gunicorn_paster.

Commonly Used Arguments

• -c CONFIG, --config=CONFIG - Specify the path to a config file

• -b BIND, --bind=BIND - Specify a server socket to bind. Server sockets can be any of $(HOST), $(HOST):$(PORT), or unix:$(PATH). An IP is a valid $(HOST).

• -w WORKERS, --workers=WORKERS - The number of worker processes. This number should generally be between 2-4 workers per core in the server. Check the FAQ for ideas on tuning this parameter.

• -k WORKERCLASS, --worker-class=WORKERCLASS - The type of worker process to run. You'll definitely want to read the production page for the implications of this parameter. You can set this to egg:gunicorn#$(NAME) where $(NAME) is one of sync, eventlet, gevent, or tornado. sync is the default.

• -n APP_NAME, --name=APP_NAME - If setproctitle is installed you can adjust the name of Gunicorn process as they appear in the process system table (which affects tools like ps and top).

  sync=gunicorn.workers.sync:SyncWorker eventlet=gunicorn.workers.geventlet:EventletWorker gevent=gunicorn.workers.ggevent:GeventWorker tornado

There are various other parameters that affect user privileges, logging, etc. You can see the complete list with the expected:

$ gunicorn -h

gunicorn

The first and most basic script is used to server 'bare' WSGI applications that don't require a translation layer. Basic usage:

$ gunicorn [OPTIONS] APP_MODULE

Where APP_MODULE is of the pattern $(MODULE_NAME):$(VARIABLE_NAME). The module name can be a full dotted path. The variable name refers to a WSGI callable that should be found in the specified module.

Example with test app:

$ cd examples
$ gunicorn --workers=2 test:app

gunicorn_django

You might not have guessed it, but this script is used to server Django applications. Basic usage:

$ gunicorn_django [OPTIONS] [SETTINGS_PATH]

By default SETTINGS_PATH will look for settings.py in the current directory.

Example with your Django project:

$ cd path/to/yourdjangoproject
$ gunicorn_django --workers=2

Alternatively, you can install some Gunicorn magic directly into your Django project and use the provided command for running the server.

First you'll need to add gunicorn to your INSTALLED_APPS in the settings file:

INSTALLED_APPS = (
    ...
    "gunicorn",
)

Then you can run:

python manage.py run_gunicorn

gunicorn_paster

Yeah, for Paster-compatible frameworks (Pylons, TurboGears 2, ...). We apologize for the lack of script name creativity. And some usage:

$ gunicorn_paster [OPTIONS] paste_config.ini

Simple example:

$ cd yourpasteproject
$ gunicorn_paste --workers=2 development.ini

If you're wanting to keep on keeping on with the usual paster serve command, you can specify the Gunicorn server settings in your configuration file:

[server:main]
use = egg:gunicorn#main
host = 127.0.0.1
port = 5000

And then as per usual:

$ cd yourpasteproject
$ paster serve development.ini workers=2

LICENSE

Gunicorn is released under the MIT License. See the LICENSE file for more details.