def execute(task, *args, **kwargs):
"""
Execute ``task`` (callable or name), honoring host/role decorators, etc.
``task`` may be an actual callable object, or it may be a registered task
name, which is used to look up a callable just as if the name had been
given on the command line (including :ref:`namespaced tasks <namespaces>`,
e.g. ``"deploy.migrate"``.
The task will then be executed once per host in its host list, which is
(again) assembled in the same manner as CLI-specified tasks: drawing from
:option:`-H`, :ref:`env.hosts <hosts>`, the `~fabric.decorators.hosts` or
`~fabric.decorators.roles` decorators, and so forth.
``host``, ``hosts``, ``role``, ``roles`` and ``exclude_hosts`` kwargs will
be stripped out of the final call, and used to set the task's host list, as
if they had been specified on the command line like e.g. ``fab
taskname:host=hostname``.
Any other arguments or keyword arguments will be passed verbatim into
``task`` (the function itself -- not the ``@task`` decorator wrapping your
function!) when it is called, so ``execute(mytask, 'arg1',
kwarg1='value')`` will (once per host) invoke ``mytask('arg1',
kwarg1='value')``.
:returns:
a dictionary mapping host strings to the given task's return value for
that host's execution run. For example, ``execute(foo, hosts=['a',
'b'])`` might return ``{'a': None, 'b': 'bar'}`` if ``foo`` returned
nothing on host `a` but returned ``'bar'`` on host `b`.
In situations where a task execution fails for a given host but overall
progress does not abort (such as when :ref:`env.skip_bad_hosts
<skip-bad-hosts>` is True) the return value for that host will be the
error object or message.
.. seealso::
:ref:`The execute usage docs <execute>`, for an expanded explanation
and some examples.
.. versionadded:: 1.3
.. versionchanged:: 1.4
Added the return value mapping; previously this function had no defined
return value.
"""
my_env = {'clean_revert': True}
results = {}
# Obtain task
is_callable = callable(task)
if not (is_callable or _is_task(task)):
# Assume string, set env.command to it
my_env['command'] = task
task = crawl(task, state.commands)
if task is None:
msg = "%r is not callable or a valid task name" % (
my_env['command'], )
if state.env.get('skip_unknown_tasks', False):
warn(msg)
return
else:
abort(msg)
# Set env.command if we were given a real function or callable task obj
else:
dunder_name = getattr(task, '__name__', None)
my_env['command'] = getattr(task, 'name', dunder_name)
# Normalize to Task instance if we ended up with a regular callable
if not _is_task(task):
task = WrappedCallableTask(task)
# Filter out hosts/roles kwargs
new_kwargs, hosts, roles, exclude_hosts = parse_kwargs(kwargs)
# Set up host list
my_env['all_hosts'], my_env[
'effective_roles'] = task.get_hosts_and_effective_roles(
hosts, roles, exclude_hosts, state.env)
parallel = requires_parallel(task)
if parallel:
# Import multiprocessing if needed, erroring out usefully
# if it can't.
try:
import multiprocessing
except ImportError:
import traceback
tb = traceback.format_exc()
abort(tb + """
At least one task needs to be run in parallel, but the
multiprocessing module cannot be imported (see above
traceback.) Please make sure the module is installed
or that the above ImportError is fixed.""")
else:
multiprocessing = None
# Get pool size for this task
pool_size = task.get_pool_size(my_env['all_hosts'], state.env.pool_size)
# Set up job queue in case parallel is needed
queue = multiprocessing.Queue() if parallel else None
jobs = JobQueue(pool_size, queue)
if state.output.debug:
jobs._debug = True
# Call on host list
if my_env['all_hosts']:
# Attempt to cycle on hosts, skipping if needed
for host in my_env['all_hosts']:
try:
results[host] = _execute(task, host, my_env, args, new_kwargs,
jobs, queue, multiprocessing)
except NetworkError as e:
results[host] = e
# Backwards compat test re: whether to use an exception or
# abort
if not state.env.use_exceptions_for['network']:
func = warn if state.env.skip_bad_hosts else abort
error(e.message, func=func, exception=e.wrapped)
else:
raise
# If requested, clear out connections here and not just at the end.
if state.env.eagerly_disconnect:
disconnect_all()
# If running in parallel, block until job queue is emptied
if jobs:
err = "One or more hosts failed while executing task '%s'" % (
my_env['command'])
jobs.close()
# Abort if any children did not exit cleanly (fail-fast).
# This prevents Fabric from continuing on to any other tasks.
# Otherwise, pull in results from the child run.
ran_jobs = jobs.run()
for name, d in six.iteritems(ran_jobs):
if d['exit_code'] != 0:
if isinstance(d['results'], NetworkError) and \
_is_network_error_ignored():
error(d['results'].message,
func=warn,
exception=d['results'].wrapped)
elif isinstance(d['results'], BaseException):
error(err, exception=d['results'])
else:
error(err)
results[name] = d['results']
# Or just run once for local-only
else:
with settings(**my_env):
results['<local-only>'] = task.run(*args, **new_kwargs)
# Return what we can from the inner task executions
return results
def execute(task, *args, **kwargs):
"""
Execute ``task`` (callable or name), honoring host/role decorators, etc.
``task`` may be an actual callable object, or it may be a registered task
name, which is used to look up a callable just as if the name had been
given on the command line (including :ref:`namespaced tasks <namespaces>`,
e.g. ``"deploy.migrate"``.
The task will then be executed once per host in its host list, which is
(again) assembled in the same manner as CLI-specified tasks: drawing from
:option:`-H`, :ref:`env.hosts <hosts>`, the `~fabric.decorators.hosts` or
`~fabric.decorators.roles` decorators, and so forth.
``host``, ``hosts``, ``role``, ``roles`` and ``exclude_hosts`` kwargs will
be stripped out of the final call, and used to set the task's host list, as
if they had been specified on the command line like e.g. ``fab
taskname:host=hostname``.
Any other arguments or keyword arguments will be passed verbatim into
``task`` (the function itself -- not the ``@task`` decorator wrapping your
function!) when it is called, so ``execute(mytask, 'arg1',
kwarg1='value')`` will (once per host) invoke ``mytask('arg1',
kwarg1='value')``.
:returns:
a dictionary mapping host strings to the given task's return value for
that host's execution run. For example, ``execute(foo, hosts=['a',
'b'])`` might return ``{'a': None, 'b': 'bar'}`` if ``foo`` returned
nothing on host `a` but returned ``'bar'`` on host `b`.
In situations where a task execution fails for a given host but overall
progress does not abort (such as when :ref:`env.skip_bad_hosts
<skip-bad-hosts>` is True) the return value for that host will be the
error object or message.
.. seealso::
:ref:`The execute usage docs <execute>`, for an expanded explanation
and some examples.
.. versionadded:: 1.3
.. versionchanged:: 1.4
Added the return value mapping; previously this function had no defined
return value.
"""
my_env = {'clean_revert': True}
results = {}
# Obtain task
is_callable = callable(task)
if not (is_callable or _is_task(task)):
# Assume string, set env.command to it
my_env['command'] = task
task = crawl(task, state.commands)
if task is None:
msg = "%r is not callable or a valid task name" % (my_env['command'],)
if state.env.get('skip_unknown_tasks', False):
warn(msg)
return
else:
abort(msg)
# Set env.command if we were given a real function or callable task obj
else:
dunder_name = getattr(task, '__name__', None)
my_env['command'] = getattr(task, 'name', dunder_name)
# Normalize to Task instance if we ended up with a regular callable
if not _is_task(task):
task = WrappedCallableTask(task)
# Filter out hosts/roles kwargs
new_kwargs, hosts, roles, exclude_hosts = parse_kwargs(kwargs)
# Set up host list
my_env['all_hosts'], my_env['effective_roles'] = task.get_hosts_and_effective_roles(hosts, roles,
exclude_hosts, state.env)
parallel = requires_parallel(task)
if parallel:
# Import multiprocessing if needed, erroring out usefully
# if it can't.
try:
import multiprocessing
except ImportError:
import traceback
tb = traceback.format_exc()
abort(tb + """
At least one task needs to be run in parallel, but the
multiprocessing module cannot be imported (see above
traceback.) Please make sure the module is installed
or that the above ImportError is fixed.""")
else:
multiprocessing = None
# Get pool size for this task
pool_size = task.get_pool_size(my_env['all_hosts'], state.env.pool_size)
# Set up job queue in case parallel is needed
queue = multiprocessing.Queue() if parallel else None
jobs = JobQueue(pool_size, queue)
if state.output.debug:
jobs._debug = True
# Call on host list
if my_env['all_hosts']:
# Attempt to cycle on hosts, skipping if needed
for host in my_env['all_hosts']:
try:
results[host] = _execute(
task, host, my_env, args, new_kwargs, jobs, queue,
multiprocessing
)
except NetworkError as e:
results[host] = e
# Backwards compat test re: whether to use an exception or
# abort
if not state.env.use_exceptions_for['network']:
func = warn if state.env.skip_bad_hosts else abort
error(e.message, func=func, exception=e.wrapped)
else:
raise
# If requested, clear out connections here and not just at the end.
if state.env.eagerly_disconnect:
disconnect_all()
# If running in parallel, block until job queue is emptied
if jobs:
err = "One or more hosts failed while executing task '%s'" % (
my_env['command']
)
jobs.close()
# Abort if any children did not exit cleanly (fail-fast).
# This prevents Fabric from continuing on to any other tasks.
# Otherwise, pull in results from the child run.
ran_jobs = jobs.run()
for name, d in ran_jobs.items():
if d['exit_code'] != 0:
if isinstance(d['results'], NetworkError) and \
_is_network_error_ignored():
error(d['results'].message, func=warn, exception=d['results'].wrapped)
elif isinstance(d['results'], BaseException):
error(err, exception=d['results'])
else:
error(err)
results[name] = d['results']
# Or just run once for local-only
else:
with settings(**my_env):
results['<local-only>'] = task.run(*args, **new_kwargs)
# Return what we can from the inner task executions
return results
def execute(task, *args, **kwargs):
"""
Execute ``task`` (callable or name), honoring host/role decorators, etc.
``task`` may be an actual callable object, or it may be a registered task
name, which is used to look up a callable just as if the name had been
given on the command line (including :ref:`namespaced tasks <namespaces>`,
e.g. ``"deploy.migrate"``.
The task will then be executed once per host in its host list, which is
(again) assembled in the same manner as CLI-specified tasks: drawing from
:option:`-H`, :ref:`env.hosts <hosts>`, the `~fabric.decorators.hosts` or
`~fabric.decorators.roles` decorators, and so forth.
``host``, ``hosts``, ``role``, ``roles`` and ``exclude_hosts`` kwargs will
be stripped out of the final call, and used to set the task's host list, as
if they had been specified on the command line like e.g. ``fab
taskname:host=hostname``.
Any other arguments or keyword arguments will be passed verbatim into
``task`` when it is called, so ``execute(mytask, 'arg1', kwarg1='value')``
will (once per host) invoke ``mytask('arg1', kwarg1='value')``.
.. seealso::
:ref:`The execute usage docs <execute>`, for an expanded explanation
and some examples.
.. versionadded:: 1.3
"""
my_env = {}
# Obtain task
if not callable(task):
# Assume string, set env.command to it
my_env["command"] = task
task = crawl(task, state.commands)
if task is None:
abort("%r is not callable or a valid task name" % (task,))
# Set env.command if we were given a real function or callable task obj
else:
dunder_name = getattr(task, "__name__", None)
my_env["command"] = getattr(task, "name", dunder_name)
# Normalize to Task instance
if not hasattr(task, "run"):
task = WrappedCallableTask(task)
# Filter out hosts/roles kwargs
new_kwargs, hosts, roles, exclude_hosts = parse_kwargs(kwargs)
# Set up host list
my_env["all_hosts"] = task.get_hosts(hosts, roles, exclude_hosts, state.env)
# Get pool size for this task
pool_size = task.get_pool_size(my_env["all_hosts"], state.env.pool_size)
# Set up job queue in case parallel is needed
jobs = JobQueue(pool_size)
if state.output.debug:
jobs._debug = True
# Call on host list
if my_env["all_hosts"]:
for host in my_env["all_hosts"]:
# Log to stdout
if state.output.running and not hasattr(task, "return_value"):
print ("[%s] Executing task '%s'" % (host, my_env["command"]))
# Create per-run env with connection settings
local_env = to_dict(host)
local_env.update(my_env)
state.env.update(local_env)
# Handle parallel execution
if requires_parallel(task):
# Import multiprocessing if needed, erroring out usefully
# if it can't.
try:
import multiprocessing
except ImportError, e:
msg = "At least one task needs to be run in parallel, but the\nmultiprocessing module cannot be imported:"
msg += "\n\n\t%s\n\n" % e
msg += "Please make sure the module is installed or that the above ImportError is\nfixed."
abort(msg)
# Wrap in another callable that nukes the child's cached
# connection object, if needed, to prevent shared-socket
# problems.
def inner(*args, **kwargs):
key = normalize_to_string(state.env.host_string)
state.connections.pop(key, "")
task.run(*args, **kwargs)
# Stuff into Process wrapper
p = multiprocessing.Process(target=inner, args=args, kwargs=new_kwargs)
# Name/id is host string
p.name = local_env["host_string"]
# Add to queue
jobs.append(p)
# Handle serial execution
else:
task.run(*args, **new_kwargs)
# If running in parallel, block until job queue is emptied
if jobs:
jobs.close()
exitcodes = jobs.run()
# Abort if any children did not exit cleanly (fail-fast).
# This prevents Fabric from continuing on to any other tasks.
if any([x != 0 for x in exitcodes]):
abort("One or more hosts failed while executing task '%s'" % (my_env["command"]))
def execute(task, *args, **kwargs):
"""
Execute ``task`` (callable or name), honoring host/role decorators, etc.
``task`` may be an actual callable object, or it may be a registered task
name, which is used to look up a callable just as if the name had been
given on the command line (including :ref:`namespaced tasks <namespaces>`,
e.g. ``"deploy.migrate"``.
The task will then be executed once per host in its host list, which is
(again) assembled in the same manner as CLI-specified tasks: drawing from
:option:`-H`, :ref:`env.hosts <hosts>`, the `~fabric.decorators.hosts` or
`~fabric.decorators.roles` decorators, and so forth.
``host``, ``hosts``, ``role``, ``roles`` and ``exclude_hosts`` kwargs will
be stripped out of the final call, and used to set the task's host list, as
if they had been specified on the command line like e.g. ``fab
taskname:host=hostname``.
Any other arguments or keyword arguments will be passed verbatim into
``task`` when it is called, so ``execute(mytask, 'arg1', kwarg1='value')``
will (once per host) invoke ``mytask('arg1', kwarg1='value')``.
.. seealso::
:ref:`The execute usage docs <execute>`, for an expanded explanation
and some examples.
.. versionadded:: 1.3
"""
my_env = {}
# Obtain task
if not callable(task):
# Assume string, set env.command to it
my_env['command'] = task
task = crawl(task, state.commands)
if task is None:
abort("%r is not callable or a valid task name" % (task,))
# Set env.command if we were given a real function or callable task obj
else:
dunder_name = getattr(task, '__name__', None)
my_env['command'] = getattr(task, 'name', dunder_name)
# Normalize to Task instance
if not hasattr(task, 'run'):
task = WrappedCallableTask(task)
# Filter out hosts/roles kwargs
new_kwargs, hosts, roles, exclude_hosts = parse_kwargs(kwargs)
# Set up host list
my_env['all_hosts'] = task.get_hosts(hosts, roles, exclude_hosts, state.env)
# Get pool size for this task
pool_size = task.get_pool_size(my_env['all_hosts'], state.env.pool_size)
# Set up job queue in case parallel is needed
jobs = JobQueue(pool_size)
if state.output.debug:
jobs._debug = True
# Call on host list
if my_env['all_hosts']:
# Attempt to cycle on hosts, skipping if needed
for host in my_env['all_hosts']:
try:
_execute(task, host, my_env, args, new_kwargs)
except NetworkError, e:
# Backwards compat test re: whether to use an exception or
# abort
if not state.env.use_exceptions_for['network']:
func = warn if state.env.skip_bad_hosts else abort
error(e.message, func=func, exception=e.wrapped)
else:
raise
# If running in parallel, block until job queue is emptied
if jobs:
jobs.close()
exitcodes = jobs.run()
# Abort if any children did not exit cleanly (fail-fast).
# This prevents Fabric from continuing on to any other tasks.
if any([x != 0 for x in exitcodes]):
abort("One or more hosts failed while executing task '%s'" % (
my_env['command']
))
def execute(task, *args, **kwargs):
"""
Execute ``task`` (callable or name), honoring host/role decorators, etc.
``task`` may be an actual callable object, or it may be a registered task
name, which is used to look up a callable just as if the name had been
given on the command line (including :ref:`namespaced tasks <namespaces>`,
e.g. ``"deploy.migrate"``.
The task will then be executed once per host in its host list, which is
(again) assembled in the same manner as CLI-specified tasks: drawing from
:option:`-H`, :ref:`env.hosts <hosts>`, the `~fabric.decorators.hosts` or
`~fabric.decorators.roles` decorators, and so forth.
``host``, ``hosts``, ``role``, ``roles`` and ``exclude_hosts`` kwargs will
be stripped out of the final call, and used to set the task's host list, as
if they had been specified on the command line like e.g. ``fab
taskname:host=hostname``.
Any other arguments or keyword arguments will be passed verbatim into
``task`` when it is called, so ``execute(mytask, 'arg1', kwarg1='value')``
will (once per host) invoke ``mytask('arg1', kwarg1='value')``.
.. seealso::
:ref:`The execute usage docs <execute>`, for an expanded explanation
and some examples.
.. versionadded:: 1.3
"""
my_env = {}
# Obtain task
if not callable(task):
# Assume string, set env.command to it
my_env['command'] = task
task = crawl(task, state.commands)
if task is None:
abort("%r is not callable or a valid task name" % (task, ))
# Set env.command if we were given a real function or callable task obj
else:
dunder_name = getattr(task, '__name__', None)
my_env['command'] = getattr(task, 'name', dunder_name)
# Normalize to Task instance
if not hasattr(task, 'run'):
task = WrappedCallableTask(task)
# Filter out hosts/roles kwargs
new_kwargs, hosts, roles, exclude_hosts = parse_kwargs(kwargs)
# Set up host list
my_env['all_hosts'] = task.get_hosts(hosts, roles, exclude_hosts,
state.env)
# Get pool size for this task
pool_size = task.get_pool_size(my_env['all_hosts'], state.env.pool_size)
# Set up job queue in case parallel is needed
jobs = JobQueue(pool_size)
if state.output.debug:
jobs._debug = True
# Call on host list
if my_env['all_hosts']:
for host in my_env['all_hosts']:
# Log to stdout
if state.output.running and not hasattr(task, 'return_value'):
print("[%s] Executing task '%s'" % (host, my_env['command']))
# Create per-run env with connection settings
local_env = to_dict(host)
local_env.update(my_env)
state.env.update(local_env)
# Handle parallel execution
if requires_parallel(task):
# Set a few more env flags for parallelism
state.env.parallel = True # triggers some extra aborts, etc
state.env.linewise = True # to mirror -P behavior
# Import multiprocessing if needed, erroring out usefully
# if it can't.
try:
import multiprocessing
except ImportError:
import traceback
tb = traceback.format_exc()
abort(tb + """
At least one task needs to be run in parallel, but the
multiprocessing module cannot be imported (see above
traceback.) Please make sure the module is installed
or that the above ImportError is fixed.""")
# Wrap in another callable that nukes the child's cached
# connection object, if needed, to prevent shared-socket
# problems.
def inner(*args, **kwargs):
key = normalize_to_string(state.env.host_string)
state.connections.pop(key, "")
task.run(*args, **kwargs)
# Stuff into Process wrapper
p = multiprocessing.Process(target=inner,
args=args,
kwargs=new_kwargs)
# Name/id is host string
p.name = local_env['host_string']
# Add to queue
jobs.append(p)
# Handle serial execution
else:
task.run(*args, **new_kwargs)
# If running in parallel, block until job queue is emptied
if jobs:
jobs.close()
exitcodes = jobs.run()
# Abort if any children did not exit cleanly (fail-fast).
# This prevents Fabric from continuing on to any other tasks.
if any([x != 0 for x in exitcodes]):
abort("One or more hosts failed while executing task '%s'" %
(my_env['command']))
# Or just run once for local-only
else:
state.env.update(my_env)
task.run(*args, **new_kwargs)
def execute(task, *args, **kwargs):
"""
Execute ``task`` (callable or name), honoring host/role decorators, etc.
``task`` may be an actual callable object, or it may be a registered task
name, which is used to look up a callable just as if the name had been
given on the command line (including :ref:`namespaced tasks <namespaces>`,
e.g. ``"deploy.migrate"``.
The task will then be executed once per host in its host list, which is
(again) assembled in the same manner as CLI-specified tasks: drawing from
:option:`-H`, :ref:`env.hosts <hosts>`, the `~fabric.decorators.hosts` or
`~fabric.decorators.roles` decorators, and so forth.
``host``, ``hosts``, ``role``, ``roles`` and ``exclude_hosts`` kwargs will
be stripped out of the final call, and used to set the task's host list, as
if they had been specified on the command line like e.g. ``fab
taskname:host=hostname``.
Any other arguments or keyword arguments will be passed verbatim into
``task`` when it is called, so ``execute(mytask, 'arg1', kwarg1='value')``
will (once per host) invoke ``mytask('arg1', kwarg1='value')``.
.. seealso::
:ref:`The execute usage docs <execute>`, for an expanded explanation
and some examples.
.. versionadded:: 1.3
"""
my_env = {}
# Obtain task
if not callable(task):
# Assume string, set env.command to it
my_env['command'] = task
task = crawl(task, state.commands)
if task is None:
abort("%r is not callable or a valid task name" % (task, ))
# Set env.command if we were given a real function or callable task obj
else:
dunder_name = getattr(task, '__name__', None)
my_env['command'] = getattr(task, 'name', dunder_name)
# Normalize to Task instance
if not hasattr(task, 'run'):
task = WrappedCallableTask(task)
# Filter out hosts/roles kwargs
new_kwargs, hosts, roles, exclude_hosts = parse_kwargs(kwargs)
# Set up host list
my_env['all_hosts'] = task.get_hosts(hosts, roles, exclude_hosts,
state.env)
# Get pool size for this task
pool_size = task.get_pool_size(my_env['all_hosts'], state.env.pool_size)
# Set up job queue in case parallel is needed
jobs = JobQueue(pool_size)
if state.output.debug:
jobs._debug = True
# Call on host list
if my_env['all_hosts']:
# Attempt to cycle on hosts, skipping if needed
for host in my_env['all_hosts']:
try:
_execute(task, host, my_env, args, new_kwargs)
except NetworkError, e:
# Backwards compat test re: whether to use an exception or
# abort
if not state.env.use_exceptions_for['network']:
func = warn if state.env.skip_bad_hosts else abort
error(e.message, func=func, exception=e.wrapped)
else:
raise
# If running in parallel, block until job queue is emptied
if jobs:
jobs.close()
exitcodes = jobs.run()
# Abort if any children did not exit cleanly (fail-fast).
# This prevents Fabric from continuing on to any other tasks.
if any([x != 0 for x in exitcodes]):
abort("One or more hosts failed while executing task '%s'" %
(my_env['command']))