=====================
Overview and Tutorial
=====================

Welcome to Fabric!

This document is a whirlwind tour of Fabric's features and a quick guide to its
use. Additional documentation (which is linked to throughout) can be found in
the :ref:`usage documentation <usage-docs>` -- please make sure to check it out.


What is Fabric?
===============

As the ``README`` says:

    .. include:: ../../README.rst
        :end-before: It provides

More specifically, Fabric is:

* A tool that lets you execute **arbitrary Python functions** via the **command
  line**;
* A library of subroutines (built on top of a lower-level library) to make
  executing shell commands over SSH **easy** and **Pythonic**.

Naturally, most users combine these two things, using Fabric to write and
execute Python functions, or **tasks**, to automate interactions with remote
servers. Let's take a look.


Hello, ``fab``
==============

This wouldn't be a proper tutorial without "the usual"::

    def hello():
        print("Hello world!")

Placed in a Python module file named ``fabfile.py`` in your current working
directory, that ``hello`` function can be executed with the ``fab`` tool
(installed as part of Fabric) and does just what you'd expect::

    $ fab hello
    Hello world!

    Done.

That's all there is to it. This functionality allows Fabric to be used as a
(very) basic build tool even without importing any of its API.

.. note::

    The ``fab`` tool simply imports your fabfile and executes the function or
    functions you instruct it to. There's nothing magic about it -- anything
    you can do in a normal Python script can be done in a fabfile!

.. seealso:: :ref:`execution-strategy`, :doc:`/usage/tasks`, :doc:`/usage/fab`


Task arguments
==============

It's often useful to pass runtime parameters into your tasks, just as you might
during regular Python programming. Fabric has basic support for this using a
shell-compatible notation: ``<task name>:<arg>,<kwarg>=<value>,...``. It's
contrived, but let's extend the above example to say hello to you personally::

    def hello(name="world"):
        print("Hello %s!" % name)

By default, calling ``fab hello`` will still behave as it did before; but now
we can personalize it::

    $ fab hello:name=Jeff
    Hello Jeff!

    Done.

Those already used to programming in Python might have guessed that this
invocation behaves exactly the same way::

    $ fab hello:Jeff
    Hello Jeff!

    Done.

For the time being, your argument values will always show up in Python as
strings and may require a bit of string manipulation for complex types such
as lists. Future versions may add a typecasting system to make this easier.

.. seealso:: :ref:`task-arguments`

Local commands
==============

As used above, ``fab`` only really saves a couple lines of
``if __name__ == "__main__"`` boilerplate. It's mostly designed for use with
Fabric's API, which contains functions (or **operations**) for executing shell
commands, transferring files, and so forth.

Let's build a hypothetical Web application fabfile. This example scenario is
as follows: The Web application is managed via Git on a remote host
``vcshost``. On ``localhost``, we have a local clone of said Web application.
When we push changes back to ``vcshost``, we want to be able to immediately
install these changes on a remote host ``my_server`` in an automated fashion.
We will do this by automating the local and remote Git commands.

Fabfiles usually work best at the root of a project::

    .
    |-- __init__.py
    |-- app.wsgi
    |-- fabfile.py <-- our fabfile!
    |-- manage.py
    `-- my_app
        |-- __init__.py
        |-- models.py
        |-- templates
        |   `-- index.html
        |-- tests.py
        |-- urls.py
        `-- views.py

.. note::

    We're using a Django application here, but only as an example -- Fabric is
    not tied to any external codebase, save for its SSH library.

For starters, perhaps we want to run our tests and commit to our VCS so we're
ready for a deploy::

    from fabric.api import local

    def prepare_deploy():
        local("./manage.py test my_app")
        local("git add -p && git commit")
        local("git push")

The output of which might look a bit like this::

    $ fab prepare_deploy
    [localhost] run: ./manage.py test my_app
    Creating test database...
    Creating tables
    Creating indexes
    ..........................................
    ----------------------------------------------------------------------
    Ran 42 tests in 9.138s

    OK
    Destroying test database...

    [localhost] run: git add -p && git commit

    <interactive Git add / git commit edit message session>

    [localhost] run: git push

    <git push session, possibly merging conflicts interactively>

    Done.

The code itself is straightforward: import a Fabric API function,
`~fabric.operations.local`, and use it to run and interact with local shell
commands. The rest of Fabric's API is similar -- it's all just Python.

.. seealso:: :doc:`api/core/operations`, :ref:`fabfile-discovery`


Organize it your way
====================

Because Fabric is "just Python" you're free to organize your fabfile any way
you want. For example, it's often useful to start splitting things up into
subtasks::

    from fabric.api import local

    def test():
        local("./manage.py test my_app")

    def commit():
        local("git add -p && git commit")

    def push():
        local("git push")

    def prepare_deploy():
        test()
        commit()
        push()

The ``prepare_deploy`` task can be called just as before, but now you can make
a more granular call to one of the sub-tasks, if desired.


Failure
=======

Our base case works fine now, but what happens if our tests fail?  Chances are
we want to put on the brakes and fix them before deploying.

Fabric checks the return value of programs called via operations and will abort
if they didn't exit cleanly. Let's see what happens if one of our tests
encounters an error::

    $ fab prepare_deploy
    [localhost] run: ./manage.py test my_app
    Creating test database...
    Creating tables
    Creating indexes
    .............E............................
    ======================================================================
    ERROR: testSomething (my_project.my_app.tests.MainTests)
    ----------------------------------------------------------------------
    Traceback (most recent call last):
    [...]

    ----------------------------------------------------------------------
    Ran 42 tests in 9.138s

    FAILED (errors=1)
    Destroying test database...

    Fatal error: local() encountered an error (return code 2) while executing './manage.py test my_app'

    Aborting.

Great! We didn't have to do anything ourselves: Fabric detected the failure and
aborted, never running the ``commit`` task.

.. seealso:: :ref:`Failure handling (usage documentation) <failures>`

Failure handling
----------------

But what if we wanted to be flexible and give the user a choice? A setting
(or **environment variable**, usually shortened to **env var**) called
:ref:`warn_only` lets you turn aborts into warnings, allowing flexible error
handling to occur.

Let's flip this setting on for our ``test`` function, and then inspect the
result of the `~fabric.operations.local` call ourselves::

    from __future__ import with_statement
    from fabric.api import local, settings, abort
    from fabric.contrib.console import confirm

    def test():
        with settings(warn_only=True):
            result = local('./manage.py test my_app', capture=True)
        if result.failed and not confirm("Tests failed. Continue anyway?"):
            abort("Aborting at user request.")

    [...]

In adding this new feature we've introduced a number of new things:

* The ``__future__`` import required to use ``with:`` in Python 2.5;
* Fabric's `contrib.console <fabric.contrib.console>` submodule, containing the
  `~fabric.contrib.console.confirm` function, used for simple yes/no prompts;
* The `~fabric.context_managers.settings` context manager, used to apply
  settings to a specific block of code;
* Command-running operations like `~fabric.operations.local` can return objects
  containing info about their result (such as ``.failed``, or
  ``.return_code``);
* And the `~fabric.utils.abort` function, used to manually abort execution.

However, despite the additional complexity, it's still pretty easy to follow,
and is now much more flexible.

.. seealso:: :doc:`api/core/context_managers`, :ref:`env-vars`


Making connections
==================

Let's start wrapping up our fabfile by putting in the keystone: a ``deploy``
task that is destined to run on one or more remote server(s), and ensures the
code is up to date::

    def deploy():
        code_dir = '/srv/django/myproject'
        with cd(code_dir):
            run("git pull")
            run("touch app.wsgi")

Here again, we introduce a handful of new concepts:

* Fabric is just Python -- so we can make liberal use of regular Python code
  constructs such as variables and string interpolation;
* `~fabric.context_managers.cd`, an easy way of prefixing commands with a ``cd
  /to/some/directory`` call. This is similar to  `~fabric.context_managers.lcd`
  which does the same locally.
* `~fabric.operations.run`, which is similar to `~fabric.operations.local` but
  runs **remotely** instead of locally.

We also need to make sure we import the new functions at the top of our file::

    from __future__ import with_statement
    from fabric.api import local, settings, abort, run, cd
    from fabric.contrib.console import confirm

With these changes in place, let's deploy::

    $ fab deploy
    No hosts found. Please specify (single) host string for connection: my_server
    [my_server] run: git pull
    [my_server] out: Already up-to-date.
    [my_server] out:
    [my_server] run: touch app.wsgi

    Done.

We never specified any connection info in our fabfile, so Fabric doesn't know
on which host(s) the remote command should be executed. When this happens,
Fabric prompts us at runtime. Connection definitions use SSH-like "host
strings" (e.g. ``user@host:port``) and will use your local username as a
default -- so in this example, we just had to specify the hostname,
``my_server``.


Remote interactivity
--------------------

``git pull`` works fine if you've already got a checkout of your source code --
but what if this is the first deploy? It'd be nice to handle that case too and
do the initial ``git clone``::

    def deploy():
        code_dir = '/srv/django/myproject'
        with settings(warn_only=True):
            if run("test -d %s" % code_dir).failed:
                run("git clone user@vcshost:/path/to/repo/.git %s" % code_dir)
        with cd(code_dir):
            run("git pull")
            run("touch app.wsgi")

As with our calls to `~fabric.operations.local` above, `~fabric.operations.run`
also lets us construct clean Python-level logic based on executed shell
commands. However, the interesting part here is the ``git clone`` call: since
we're using Git's SSH method of accessing the repository on our Git server,
this means our remote `~fabric.operations.run` call will need to authenticate
itself.

Older versions of Fabric (and similar high level SSH libraries) run remote
programs in limbo, unable to be touched from the local end. This is
problematic when you have a serious need to enter passwords or otherwise
interact with the remote program.

Fabric 1.0 and later breaks down this wall and ensures you can always talk to
the other side. Let's see what happens when we run our updated ``deploy`` task
on a new server with no Git checkout::

    $ fab deploy
    No hosts found. Please specify (single) host string for connection: my_server
    [my_server] run: test -d /srv/django/myproject

    Warning: run() encountered an error (return code 1) while executing 'test -d /srv/django/myproject'

    [my_server] run: git clone user@vcshost:/path/to/repo/.git /srv/django/myproject
    [my_server] out: Cloning into /srv/django/myproject...
    [my_server] out: Password: <enter password>
    [my_server] out: remote: Counting objects: 6698, done.
    [my_server] out: remote: Compressing objects: 100% (2237/2237), done.
    [my_server] out: remote: Total 6698 (delta 4633), reused 6414 (delta 4412)
    [my_server] out: Receiving objects: 100% (6698/6698), 1.28 MiB, done.
    [my_server] out: Resolving deltas: 100% (4633/4633), done.
    [my_server] out:
    [my_server] run: git pull
    [my_server] out: Already up-to-date.
    [my_server] out:
    [my_server] run: touch app.wsgi

    Done.

Notice the ``Password:`` prompt -- that was our remote ``git`` call on our Web server, asking for the password to the Git server. We were able to type it in and the clone continued normally.

.. seealso:: :doc:`/usage/interactivity`


.. _defining-connections:

Defining connections beforehand
-------------------------------

Specifying connection info at runtime gets old real fast, so Fabric provides a
handful of ways to do it in your fabfile or on the command line. We won't cover
all of them here, but we will show you the most common one: setting the global
host list, :ref:`env.hosts <hosts>`.

:doc:`env <usage/env>` is a global dictionary-like object driving many of
Fabric's settings, and can be written to with attributes as well (in fact,
`~fabric.context_managers.settings`, seen above, is simply a wrapper for this.)
Thus, we can modify it at module level near the top of our fabfile like so::

    from __future__ import with_statement
    from fabric.api import *
    from fabric.contrib.console import confirm

    env.hosts = ['my_server']

    def test():
        do_test_stuff()

When ``fab`` loads up our fabfile, our modification of ``env`` will execute,
storing our settings change. The end result is exactly as above: our ``deploy``
task will run against the ``my_server`` server.

This is also how you can tell Fabric to run on multiple remote systems at once:
because ``env.hosts`` is a list, ``fab`` iterates over it, calling the given
task once for each connection.

.. seealso:: :doc:`usage/env`, :ref:`host-lists`


Conclusion
==========

Our completed fabfile is still pretty short, as such things go. Here it is in
its entirety::

    from __future__ import with_statement
    from fabric.api import *
    from fabric.contrib.console import confirm

    env.hosts = ['my_server']

    def test():
        with settings(warn_only=True):
            result = local('./manage.py test my_app', capture=True)
        if result.failed and not confirm("Tests failed. Continue anyway?"):
            abort("Aborting at user request.")

    def commit():
        local("git add -p && git commit")

    def push():
        local("git push")

    def prepare_deploy():
        test()
        commit()
        push()

    def deploy():
        code_dir = '/srv/django/myproject'
        with settings(warn_only=True):
            if run("test -d %s" % code_dir).failed:
                run("git clone user@vcshost:/path/to/repo/.git %s" % code_dir)
        with cd(code_dir):
            run("git pull")
            run("touch app.wsgi")

This fabfile makes use of a large portion of Fabric's feature set:

* defining fabfile tasks and running them with :doc:`fab <usage/fab>`;
* calling local shell commands with `~fabric.operations.local`;
* modifying env vars with `~fabric.context_managers.settings`;
* handling command failures, prompting the user, and manually aborting;
* and defining host lists and `~fabric.operations.run`-ning remote commands.

However, there's still a lot more we haven't covered here! Please make sure you
follow the various "see also" links, and check out the documentation table of
contents on :doc:`the main index page <index>`.

Thanks for reading!
