Python Environment

Kallithea is written entirely in Python and requires Python version 2.6 or higher. Python 3.x is currently not supported.

Given a Python installation, there are different ways of providing the environment for running Python applications. Each of them pretty much corresponds to a site-packages directory somewhere where packages can be installed.

Kallithea itself can be run from source or be installed, but even when running from source, there are some dependencies that must be installed in the Python environment used for running Kallithea.

• Packages could be installed in Python's site-packages directory ... but that would require running pip as root and it would be hard to uninstall or upgrade and is probably not a good idea unless using a package manager.
• Packages could also be installed in ~/.local ... but that is probably only a good idea if using a dedicated user per application or instance.
• Finally, it can be installed in a virtualenv. That is a very lightweight "container" where each Kallithea instance can get its own dedicated and self-contained virtual environment.

We recommend using virtualenv for installing Kallithea.

Installation Methods

Kallithea must be installed on a server. Kallithea is installed in a Python environment so it can use packages that are installed there and make itself available for other packages.

Two different cases will pretty much cover the options for how it can be installed.

• The Kallithea source repository can be cloned and used - it is kept stable and can be used in production. The Kallithea maintainers use the development branch in production. The advantage of installation from source and regularly updating it is that you take advantage of the most recent improvements. Using it directly from a DVCS also means that it is easy to track local customizations.

  Running setup.py develop in the source will use pip to install the necessary dependencies in the Python environment and create a .../site-packages/Kallithea.egg-link file there that points at the Kallithea source.

• Kallithea can also be installed from ready-made packages using a package manager. The official released versions are available on PyPI and can be downloaded and installed with all dependencies using pip install kallithea.

  With this method, Kallithea is installed in the Python environment as any other package, usually as a .../site-packages/Kallithea-X-py2.7.egg/ directory with Python files and everything else that is needed.

  (pip install kallithea from a source tree will do pretty much the same but build the Kallithea package itself locally instead of downloading it.)

Web Server

Kallithea is (primarily) a WSGI application that must be run from a web server that expose WSGI as HTTP.

• Kallithea uses the Paste tool for some admin tasks. Paste provides paste serve as a convenient way to launch Python WSGI / web servers. This method is perfect for development but can also be used for production.

  paste is a command line tool. Using it in production requires some way to wrap it as a managable service.

  Paste come with its own web server but Kallithea defaults to use Waitress. Gunicorn is also an option. These web servers have different limited feature sets.

  It is also common/mandatory to put another web server or (reverse) proxy in front of these Python web servers. Nginx is a common choice. This simple setup will thus often end up being quite complex.

  The configuration of which web server to use is in the ini file passed to paste. The entry point for the WSGI application is configured in setup.py as kallithea.config.middleware:make_app.

• Apache httpd can serve WSGI applications directly using mod_wsgi and a simple Python file with the necessary configuration. This is a good option if Apache is an option.

• IIS can also server WSGI applications directly using isapi-wsgi.

• UWSGI is also an option.

The best option depends on what you are familiar with and the requirements for performance and stability. Also, keep in mind that Kallithea mainly is serving custom data generated from relatively slow Python process. Kallithea is also often used inside organizations with a limited amount of users and thus no continuous hammering from the internet.