Developer Guide

This file contains an overview of architecture, coding design/practices, testing and style.

Before submitting a PR

  • All unit and integration tests must pass (please use the docker based tests; see Software switch testing with docker).
  • You must add a test if FAUCET’s functionality changes (ie. a new feature, or correcting a bug).
  • Please use the supplied git pre-commit hook (see ../git-hook/pre-commit), to automatically run the unit tests and pylint for you at git commit time.
  • Please enable TravisCI testing on your repo, which enables the maintainers to quickly verify that your changes pass all tests in a pristine environment.
  • pylint must show no new errors or warnings.
  • Code must conform to the style guide (see below).

Code style

Please use the coding style documented at Existing code not using this style will be incrementally migrated to comply with it. New code should comply.

Faucet Development Environment

A common way of developing faucet is inside a virtualenv with an IDE such as PyCharm.

Instructions on setting up PyCharm for developing faucet are as follows:

Create a new project in PyCharm

Set the Location of the project to the directory where a checked out copy of the faucet code from git is, for this tutorial I will assume the path is /Dev/faucet/.

Ignore the Project Interpreter settings for now, we will set those up after the project is created.

Click Create when you have completed these steps.

When asked Would you like to create a project from existing sources instead? click Yes.

Create virtual environment

Now that the project is created and source code imported, click the File -> Settings menu. In the dialog box that opens click the Project: faucet -> Project Interpreter sub menu.

Click the cog and select Add...

Under Virtualenv Environment you want to select New environment and select a Location for the virtualenv (which can be inside the directory where the faucet code lives, e.g /Dev/faucet/venv).

The Base interpreter should be set to /usr/bin/python3.

Click Ok which will create the virtualenv.

Now while that virtualenv builds and we still have the settings dialog open we will tweak a few project settings to make them compatible with our code style. Click on the Tools -> Python Integrated Tools menu and change the Docstring format to Google.

Finally, click Ok again to get back to the main screen of PyCharm.

Install requirements

Inside the PyCharm editor window we should now get a bar at the top of the window telling us of missing package requirements, click the Install requirements option to install the dependencies for faucet.

Create log and configuration directories

Now we need to create a log and configuration directory so that faucet can start:

mkdir -p /Dev/faucet/venv/var/log/faucet/
mkdir -p /Dev/faucet/venv/etc/faucet/

Copy the sample faucet configuration file from /Dev/faucet/etc/faucet/faucet.yaml to /Dev/faucet/venv/etc/faucet/ and edit this configuration file as necessary.

Copy the sample gauge configuration file from /Dev/faucet/etc/faucet/gauge.yaml to /Dev/faucet/venv/etc/faucet/ and edit this configuration file as necessary.

Configure PyCharm to run faucet

Now we need to configure PyCharm to run faucet, gauge and the unit tests.

First, click the Run -> Run.. menu, then select the Edit Configurations... option to get to the build settings dialog.

We will edit the default faucet run configuration that has been created for us. First change the Script path to point to ryu-manager inside the virtualenv, for me this was ../venv/bin/ryu-manager. Then set the Parameters to faucet.faucet. Make sure the working directory is set to /Dev/faucet/faucet/.

We will also add a gauge run configuration for starting gauge. First change the Script path to point to ryu-manager inside the virtualenv, for me this was ../venv/bin/ryu-manager. Then set the Parameters to faucet.gauge. Make sure the working directory is set to /Dev/faucet/faucet/.

For running tests we need a few additional dependencies installed, I couldn’t work out how to do this through PyCharm so run this command from a terminal window to install the correct dependencies inside the virtualenv:

/Dev/faucet/venv/bin/pip3 install -r /Dev/faucet/test-requirements.txt

Click the green plus icon to add a new build configuration, select Python tests -> Unittests. You can provide a Name of Faucet Unit Tests for the run configuration. For Target select Script path and enter the path /Dev/faucet/tests/unit. For Pattern enter test_*.py.

You can click Apply and Close now that we’ve added all our new run configuration.

Now that everything is setup you can run either the faucet controller, gauge controller and test suite from the Run menu.


Makefile is provided at the top level of the directory. Output of make is normally stored in dist directory. The following are the targets that can be used:

  • uml: Uses pyreverse to provide code class diagrams.
  • codefmt: Provides command line usage to “Code Style” the Python file
  • codeerrors: Uses pylint on all Python files to generate a code error report and is placed in dist directory.
  • stats: Provides a list of all commits since the last release tag.
  • release: Used for releasing FAUCET to the next version, Requires version and next_version variables.

To directly install faucet from the cloned git repo, you could use sudo python install command from the root of the directory.

To build pip installable package, you could use python sdist command from the root of the directory.

To remove any temporarily created directories and files, you could use rm -rf dist *egg-info command.

Key architectural concepts/assumptions:

FAUCET’s architecture depends on key assumptions, which must be kept in mind at all times.

  • FAUCET is the only controller for the switch, that can add or remove flows.
  • All supported dataplanes must implement OpenFlow functionally (hardware, software or both) identically. No TTP or switch specific drivers.

In addition:

  • FAUCET provisions default deny flows (all traffic not explicitly programmed is dropped).
  • Use of packet in is minimized.

FAUCET depends upon these assumptions to guarantee that the switch is always in a known and consistent state, which in turn is required to support high availability (FAUCET provides high availability, through multiple FAUCET controllers using the same version of configuration - any FAUCET can give the switch a consistent response - no state sharing between controllers is required). The FAUCET user can program customized flows to be added to the switch using FAUCET ACLs (see below).

FAUCET also programs the dataplane to do flooding (where configured). This minimizes the use of packet in. This is necessary to reduce competition between essential control plane messages (adding and removing flows), and traffic from the dataplane on the limited bandwidth OpenFlow control channel. Unconstrained packet in messages impact the switch CPU, may overwhelm the OpenFlow control channel, and will expose the FAUCET controller to unvalidated dataplane packets, all of which are security and reliability concerns. In future versions, packet in will be eliminated altogether. The FAUCET user is expected to use policy based forwarding (eg ACLs that redirect traffic of interest to high performance dataplane ports for NFV offload), not packet in.

FAUCET requires all supported dataplanes to implement OpenFlow (specifically, a subset of OpenFlow 1.3) in a functionally identical way. This means that there is no switch-specific driver layer - the exact same messages are sent, whether the switch is OVS or hardware. While this does prevent some earlier generation OpenFlow switches from being supported, commercially available current hardware does not have as many restrictions, and eliminating the need for a switch-specific (or TTP) layer greatly reduces implementation complexity and increases controller programmer productivity.