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Thomas De Schampheleire
utils: move repo_name_slug to utils2 to prevent import cycle on setup_db

After commit 57a733313e4f, 'gearbox setup-db -c my.ini' fails with an import
cycle as follows:

Traceback (most recent call last):
File "/home/tdescham/repo/contrib/kallithea/venv/kallithea-release/bin/gearbox", line 11, in <module>
sys.exit(main())
File "/home/tdescham/repo/contrib/kallithea/venv/kallithea-release/lib/python2.7/site-packages/gearbox/main.py", line 199, in main
return gearbox.run(args)
File "/home/tdescham/repo/contrib/kallithea/venv/kallithea-release/lib/python2.7/site-packages/gearbox/main.py", line 145, in run
return self._run_subcommand(remainder)
File "/home/tdescham/repo/contrib/kallithea/venv/kallithea-release/lib/python2.7/site-packages/gearbox/main.py", line 149, in _run_subcommand
subcommand = self.command_manager.find_command(argv)
File "/home/tdescham/repo/contrib/kallithea/venv/kallithea-release/lib/python2.7/site-packages/gearbox/commandmanager.py", line 78, in find_command
cmd_factory = cmd_ep.resolve()
File "/home/tdescham/repo/contrib/kallithea/venv/kallithea-release/lib/python2.7/site-packages/pkg_resources/__init__.py", line 2324, in resolve
module = __import__(self.module_name, fromlist=['__name__'], level=0)
File "/home/tdescham/repo/contrib/kallithea/kallithea-release/kallithea/lib/paster_commands/setup_db.py", line 27, in <module>
from kallithea.lib.db_manage import DbManage
File "/home/tdescham/repo/contrib/kallithea/kallithea-release/kallithea/lib/db_manage.py", line 47, in <module>
from kallithea.model.repo_group import RepoGroupModel
File "/home/tdescham/repo/contrib/kallithea/kallithea-release/kallithea/model/repo_group.py", line 35, in <module>
import kallithea.lib.utils
File "/home/tdescham/repo/contrib/kallithea/kallithea-release/kallithea/lib/utils.py", line 48, in <module>
from kallithea.model.repo_group import RepoGroupModel
ImportError: cannot import name RepoGroupModel


i.e. kallithea.model.repo_group wants to import kallithea.lib.utils which
in turn wants to import kallithea.model.repo_group.

In fact there exists kallithea.lib.utils and kallithea.lib.utils2.
The current split is that 'utils2' contains 'simple' utilities, none of which
depend on kallithea models, controllers, ... In contrast, 'utils' does rely
on such kallithea classes.

As kallithea.model.repo_group was only include kallithea.lib.utils for its
repo_name_slug method, which has no dependency on other kallithea classes,
move that method (and its dependent recursive_replace) to
kallithea.lib.utils2 instead. This fixes the import cycle.
.. _overview:

=====================
Installation overview
=====================

Some overview and some details that can help understanding the options when
installing Kallithea.


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 ``pip install -e .`` 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.)

.. note:: The front-end code is built with Node. Currently, it must be built
          locally after installing Kallithea. Assuming Node and the Node
          Package Manager is available, other tools and source code will be
          downloaded and installed. The front-end code can then be built from
          source locally.


Web server
----------

Kallithea is (primarily) a WSGI_ application that must be run from a web
server that serves WSGI applications over HTTP.

Kallithea itself is not serving HTTP (or HTTPS); that is the web server's
responsibility. Kallithea does however need to know its own user facing URL
(protocol, address, port and path) for each HTTP request. Kallithea will
usually use its own HTML/cookie based authentication but can also be configured
to use web server authentication.

There are several web server options:

- Kallithea uses the Gearbox_ tool as command line interface. Gearbox provides
  ``gearbox serve`` as a convenient way to launch a Python WSGI / web server
  from the command line. That is perfect for development and evaluation.
  Actual use in production might have different requirements and need extra
  work to make it manageable as a scalable system service.

  Gearbox comes with its own built-in web server but Kallithea defaults to use
  Waitress_. Gunicorn_ is also an option. These web servers have different
  limited feature sets.

  The web server used by ``gearbox`` is configured in the ``.ini`` file passed
  to it. 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.

- uWSGI_ is also a full web server with built-in WSGI module.

- IIS_ can also server WSGI applications directly using isapi-wsgi_.

- A `reverse HTTP proxy <https://en.wikipedia.org/wiki/Reverse_proxy>`_
  can be put in front of another web server which has WSGI support.
  Such a layered setup can be complex but might in some cases be the right
  option, for example to standardize on one internet-facing web server, to add
  encryption or special authentication or for other security reasons, to
  provide caching of static files, or to provide load balancing or fail-over.
  Nginx_, Varnish_ and HAProxy_ are often used for this purpose, often in front
  of a ``gearbox serve`` that somehow is wrapped as a service.

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
dynamically generated pages from a 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.


.. _Python: http://www.python.org/
.. _Gunicorn: http://gunicorn.org/
.. _Waitress: http://waitress.readthedocs.org/en/latest/
.. _virtualenv: http://pypi.python.org/pypi/virtualenv
.. _Gearbox: http://turbogears.readthedocs.io/en/latest/turbogears/gearbox.html
.. _PyPI: https://pypi.python.org/pypi
.. _Apache httpd: http://httpd.apache.org/
.. _mod_wsgi: https://code.google.com/p/modwsgi/
.. _isapi-wsgi: https://github.com/hexdump42/isapi-wsgi
.. _uWSGI: https://uwsgi-docs.readthedocs.org/en/latest/
.. _nginx: http://nginx.org/en/
.. _iis: http://en.wikipedia.org/wiki/Internet_Information_Services
.. _pip: http://en.wikipedia.org/wiki/Pip_%28package_manager%29
.. _WSGI: http://en.wikipedia.org/wiki/Web_Server_Gateway_Interface
.. _HAProxy: http://www.haproxy.org/
.. _Varnish: https://www.varnish-cache.org/