Decorators

Convenience decorators for use in fabfiles.

fabric.decorators.hosts(*host_list)

Decorator defining which host or hosts to execute the wrapped function on.

For example, the following will ensure that, barring an override on the command line, my_func will be run on host1, host2 and host3, and with specific users on host1 and host3:

@hosts('user1@host1', 'host2', 'user2@host3')
def my_func():
    pass

hosts may be invoked with either an argument list (@hosts('host1'), @hosts('host1', 'host2')) or a single, iterable argument (@hosts(['host1', 'host2'])).

Note that this decorator actually just sets the function’s .hosts attribute, which is then read prior to executing the function.

fabric.decorators.parallel(pool_size=None)

Forces the wrapped function to run in parallel, instead of sequentially.

This decorator takes precedence over the global value of env.parallel. It also takes precedence over serial if a task is decorated with both.

New in version 1.3.

fabric.decorators.roles(*role_list)

Decorator defining a list of role names, used to look up host lists.

A role is simply defined as a key in env whose value is a list of one or more host connection strings. For example, the following will ensure that, barring an override on the command line, my_func will be executed against the hosts listed in the webserver and dbserver roles:

env.roledefs.update({
    'webserver': ['www1', 'www2'],
    'dbserver': ['db1']
})

@roles('webserver', 'dbserver')
def my_func():
    pass

As with hosts, roles may be invoked with either an argument list or a single, iterable argument. Similarly, this decorator uses the same mechanism as hosts and simply sets <function>.roles.

fabric.decorators.runs_once(func)

Decorator preventing wrapped function from running more than once.

By keeping internal state, this decorator allows you to mark a function such that it will only run once per Python interpreter session, which in typical use means “once per invocation of the fab program”.

Any function wrapped with this decorator will silently fail to execute the 2nd, 3rd, …, Nth time it is called, and will return the value of the original run.

Note

runs_once does not work with parallel task execution.

fabric.decorators.serial(func)

Forces the wrapped function to always run sequentially, never in parallel.

This decorator takes precedence over the global value of env.parallel. However, if a task is decorated with both serial and parallel, parallel wins.

New in version 1.3.

fabric.decorators.task(*args, **kwargs)

Decorator declaring the wrapped function to be a new-style task.

May be invoked as a simple, argument-less decorator (i.e. @task) or with arguments customizing its behavior (e.g. @task(alias='myalias')).

Please see the new-style task documentation for details on how to use this decorator.

Changed in version 1.2: Added the alias, aliases, task_class and default keyword arguments. See Arguments for details.

Changed in version 1.5: Added the name keyword argument.

See also

unwrap_tasks, WrappedCallableTask

fabric.decorators.with_settings(*arg_settings, **kw_settings)

Decorator equivalent of fabric.context_managers.settings.

Allows you to wrap an entire function as if it was called inside a block with the settings context manager. This may be useful if you know you want a given setting applied to an entire function body, or wish to retrofit old code without indenting everything.

For example, to turn aborts into warnings for an entire task function:

@with_settings(warn_only=True)
def foo():
    ...

See also

settings