Benoit Chesneau

Gunicorn is known as a Python WSGI HTTP Server for UNIX. But today the WSGI specification shows its limits and people wants more. This talk will introduce the new Gunicorn released in January with a new IPC library usable in others Python programs to handle the concurrency and support HTTP2.

Gunicorn handles the concurrency using a pre-fork worker model: workers are spawned processes managed by a main process. Until now there is no dialog between workers and the master which can trigger some issues like the thundering herd. To solve it and prepare gunicorn to support new protocols like HTTP2, a new IPC library has been specifically written in pure python. Mostly inspired from imsg in OpenBSD (but also Mojo), this new library is entirely written in Python and can be used outside of Gunicorn.

This talk will present the following:

1) The design of Gunicorn 1, its pros and cons 2) Description of the new IPC library how you can use it in your own projects 3) The design of Gunicorn 2 and its usage of the new IPC library, how it can do more than simply WSGI and HTTP 1.1.

Most people know Gunicorn as a Python WSGI HTTP Server engine, but a lot ignore it can be used for more usages. With this talk you will discover how you can use it to fit your own needs/business or simply distribute extensions for it.

Most people know Gunicorn as a Python WSGI HTTP Server engine, but a lot ignore it can be used for more usages.

This talk will show you how you can use the current Gunicorn version for different usages, from embedding it in your application to extend it with your own TCP workers or logging modules. This talk will also provide a quick glance (with demo) of the new gunicorn engine, a fully featured process and sockets supervisor engine allowing more customisations.

Concurrent programming in Python may be hard. A lot of solutions exists though. Most of them are based on an eventloop. In this I talk will present what I discovered and tested along the time with code examples, from asyncore to asyncio, passing by gevent, eventlet, twisted, and some new alternatives like evergreen or gruvi. I will also present my little experiment in porting the Go concurrency model in Python named "offset", how it progressed in 1 year and how it became a fully usable library at the time of this talk.

Lot of people are trying to port the actor pattern to Python, but this pattern isn't really designed for such langages. On the contrary the Go concurrency moded has some attractives points that can be easily ported to Python. This talk will describe the go concurrency model and my own experimenration actually named flower (http://github.com/benoitc/flower) to port it in Python. In this talk you will see how I am using greenlets or generators to handle corountines and optionnaly use pyuv to manage a non blocking IO poll server.

A demo showing how ls IO in the Raspberry Pi are handled by the coroutines allowing each to be messaged individually using channels will be done.

While gaffer (https://gaffer.readthedocs.org/) started as a set of Python modules and tools to easily maintain and interact with your processes, it is slowly becoming a solution to deploy, supervise and monitor processes and applications in a decentralized fashion without SPOF (Single Point Of Failure). Gaffer is already used in production behind some services.

The talk will present how to build such tool in Python using pyuv, tornado and other python libraries. How to make it scalable due to a simple design and what we did to make it compatible with Python 2 and Python 3.x .

While gaffer (https://gaffer.readthedocs.org/) started as a set of Python modules and tools to easily maintain and interact with your processes, it is slowly becoming a solution to deploy, supervise and monitor processes and applications in a decentralized fashion without SPOF (Single Point Of Failure). Gaffer is already used in production behind some services.

The talk will present how to build such tool in Python using pyuv, tornado and other python libraries. How to make it scalable due to a simple design and what we did to make it compatible with Python 2 and Python 3.x .