ansible/lib/ansible/executor/task_executor.py
2016-07-14 09:05:01 -04:00

712 lines
32 KiB
Python

# (c) 2012-2014, Michael DeHaan <michael.dehaan@gmail.com>
#
# This file is part of Ansible
#
# Ansible is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# Ansible is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with Ansible. If not, see <http://www.gnu.org/licenses/>.
# Make coding more python3-ish
from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
import base64
import json
import subprocess
import sys
import time
import traceback
from ansible.compat.six import iteritems, string_types, binary_type
from ansible import constants as C
from ansible.errors import AnsibleError, AnsibleParserError, AnsibleUndefinedVariable, AnsibleConnectionFailure
from ansible.executor.task_result import TaskResult
from ansible.playbook.conditional import Conditional
from ansible.playbook.task import Task
from ansible.template import Templar
from ansible.utils.encrypt import key_for_hostname
from ansible.utils.listify import listify_lookup_plugin_terms
from ansible.utils.unicode import to_unicode, to_bytes
from ansible.vars.unsafe_proxy import UnsafeProxy, wrap_var
try:
from __main__ import display
except ImportError:
from ansible.utils.display import Display
display = Display()
__all__ = ['TaskExecutor']
class TaskExecutor:
'''
This is the main worker class for the executor pipeline, which
handles loading an action plugin to actually dispatch the task to
a given host. This class roughly corresponds to the old Runner()
class.
'''
# Modules that we optimize by squashing loop items into a single call to
# the module
SQUASH_ACTIONS = frozenset(C.DEFAULT_SQUASH_ACTIONS)
def __init__(self, host, task, job_vars, play_context, new_stdin, loader, shared_loader_obj, rslt_q):
self._host = host
self._task = task
self._job_vars = job_vars
self._play_context = play_context
self._new_stdin = new_stdin
self._loader = loader
self._shared_loader_obj = shared_loader_obj
self._connection = None
self._rslt_q = rslt_q
def run(self):
'''
The main executor entrypoint, where we determine if the specified
task requires looping and either runs the task with self._run_loop()
or self._execute(). After that, the returned results are parsed and
returned as a dict.
'''
display.debug("in run()")
try:
# get search path for this task to pass to lookup plugins
self._job_vars['ansible_search_path'] = self._task.get_search_path()
items = self._get_loop_items()
if items is not None:
if len(items) > 0:
item_results = self._run_loop(items)
# loop through the item results, and remember the changed/failed
# result flags based on any item there.
changed = False
failed = False
for item in item_results:
if 'changed' in item and item['changed']:
changed = True
if 'failed' in item and item['failed']:
failed = True
# create the overall result item, and set the changed/failed
# flags there to reflect the overall result of the loop
res = dict(results=item_results)
if changed:
res['changed'] = True
if failed:
res['failed'] = True
res['msg'] = 'One or more items failed'
else:
res['msg'] = 'All items completed'
else:
res = dict(changed=False, skipped=True, skipped_reason='No items in the list', results=[])
else:
display.debug("calling self._execute()")
res = self._execute()
display.debug("_execute() done")
# make sure changed is set in the result, if it's not present
if 'changed' not in res:
res['changed'] = False
def _clean_res(res):
if isinstance(res, dict):
for k in res.keys():
res[k] = _clean_res(res[k])
elif isinstance(res, list):
for idx,item in enumerate(res):
res[idx] = _clean_res(item)
elif isinstance(res, UnsafeProxy):
return res._obj
elif isinstance(res, binary_type):
return to_unicode(res, errors='strict')
return res
display.debug("dumping result to json")
res = _clean_res(res)
display.debug("done dumping result, returning")
return res
except AnsibleError as e:
return dict(failed=True, msg=to_unicode(e, nonstring='simplerepr'))
except Exception as e:
return dict(failed=True, msg='Unexpected failure during module execution.', exception=to_unicode(traceback.format_exc()), stdout='')
finally:
try:
self._connection.close()
except AttributeError:
pass
except Exception as e:
display.debug(u"error closing connection: %s" % to_unicode(e))
def _get_loop_items(self):
'''
Loads a lookup plugin to handle the with_* portion of a task (if specified),
and returns the items result.
'''
# save the play context variables to a temporary dictionary,
# so that we can modify the job vars without doing a full copy
# and later restore them to avoid modifying things too early
play_context_vars = dict()
self._play_context.update_vars(play_context_vars)
old_vars = dict()
for k in play_context_vars.keys():
if k in self._job_vars:
old_vars[k] = self._job_vars[k]
self._job_vars[k] = play_context_vars[k]
templar = Templar(loader=self._loader, shared_loader_obj=self._shared_loader_obj, variables=self._job_vars)
items = None
if self._task.loop:
if self._task.loop in self._shared_loader_obj.lookup_loader:
#TODO: remove convert_bare true and deprecate this in with_
if self._task.loop == 'first_found':
# first_found loops are special. If the item is undefined
# then we want to fall through to the next value rather
# than failing.
loop_terms = listify_lookup_plugin_terms(terms=self._task.loop_args, templar=templar, loader=self._loader, fail_on_undefined=False, convert_bare=True)
loop_terms = [t for t in loop_terms if not templar._contains_vars(t)]
else:
try:
loop_terms = listify_lookup_plugin_terms(terms=self._task.loop_args, templar=templar, loader=self._loader, fail_on_undefined=True, convert_bare=True)
except AnsibleUndefinedVariable as e:
display.deprecated("Skipping task due to undefined Error, in the future this will be a fatal error.: %s" % to_bytes(e))
return None
# get lookup
mylookup = self._shared_loader_obj.lookup_loader.get(self._task.loop, loader=self._loader, templar=templar)
# give lookup task 'context' for subdir (mostly needed for first_found)
for subdir in ['template', 'var', 'file']: #TODO: move this to constants?
if subdir in self._task.name:
break
setattr(mylookup,'_subdir', subdir + 's')
# run lookup
items = mylookup.run(terms=loop_terms, variables=self._job_vars, wantlist=True)
else:
raise AnsibleError("Unexpected failure in finding the lookup named '%s' in the available lookup plugins" % self._task.loop)
# now we restore any old job variables that may have been modified,
# and delete them if they were in the play context vars but not in
# the old variables dictionary
for k in play_context_vars.keys():
if k in old_vars:
self._job_vars[k] = old_vars[k]
else:
del self._job_vars[k]
if items:
from ansible.vars.unsafe_proxy import UnsafeProxy
for idx, item in enumerate(items):
if item is not None and not isinstance(item, UnsafeProxy):
items[idx] = UnsafeProxy(item)
return items
def _run_loop(self, items):
'''
Runs the task with the loop items specified and collates the result
into an array named 'results' which is inserted into the final result
along with the item for which the loop ran.
'''
results = []
# make copies of the job vars and task so we can add the item to
# the variables and re-validate the task with the item variable
#task_vars = self._job_vars.copy()
task_vars = self._job_vars
loop_var = 'item'
if self._task.loop_control:
# the value may be 'None', so we still need to default it back to 'item'
loop_var = self._task.loop_control.loop_var or 'item'
if loop_var in task_vars:
display.warning("The loop variable '%s' is already in use. You should set the `loop_var` value in the `loop_control` option for the task to something else to avoid variable collisions and unexpected behavior." % loop_var)
items = self._squash_items(items, loop_var, task_vars)
for item in items:
task_vars[loop_var] = item
try:
tmp_task = self._task.copy()
tmp_play_context = self._play_context.copy()
except AnsibleParserError as e:
results.append(dict(failed=True, msg=to_unicode(e)))
continue
# now we swap the internal task and play context with their copies,
# execute, and swap them back so we can do the next iteration cleanly
(self._task, tmp_task) = (tmp_task, self._task)
(self._play_context, tmp_play_context) = (tmp_play_context, self._play_context)
res = self._execute(variables=task_vars)
(self._task, tmp_task) = (tmp_task, self._task)
(self._play_context, tmp_play_context) = (tmp_play_context, self._play_context)
# now update the result with the item info, and append the result
# to the list of results
res[loop_var] = item
res['_ansible_item_result'] = True
self._rslt_q.put(TaskResult(self._host, self._task, res), block=False)
results.append(res)
del task_vars[loop_var]
return results
def _squash_items(self, items, loop_var, variables):
'''
Squash items down to a comma-separated list for certain modules which support it
(typically package management modules).
'''
name = None
try:
# _task.action could contain templatable strings (via action: and
# local_action:) Template it before comparing. If we don't end up
# optimizing it here, the templatable string might use template vars
# that aren't available until later (it could even use vars from the
# with_items loop) so don't make the templated string permanent yet.
templar = Templar(loader=self._loader, shared_loader_obj=self._shared_loader_obj, variables=variables)
task_action = self._task.action
if templar._contains_vars(task_action):
task_action = templar.template(task_action, fail_on_undefined=False)
if len(items) > 0 and task_action in self.SQUASH_ACTIONS:
if all(isinstance(o, string_types) for o in items):
final_items = []
for allowed in ['name', 'pkg', 'package']:
name = self._task.args.pop(allowed, None)
if name is not None:
break
# This gets the information to check whether the name field
# contains a template that we can squash for
template_no_item = template_with_item = None
if name:
if templar._contains_vars(name):
variables[loop_var] = '\0$'
template_no_item = templar.template(name, variables, cache=False)
variables[loop_var] = '\0@'
template_with_item = templar.template(name, variables, cache=False)
del variables[loop_var]
# Check if the user is doing some operation that doesn't take
# name/pkg or the name/pkg field doesn't have any variables
# and thus the items can't be squashed
if template_no_item != template_with_item:
for item in items:
variables[loop_var] = item
if self._task.evaluate_conditional(templar, variables):
new_item = templar.template(name, cache=False)
final_items.append(new_item)
self._task.args['name'] = final_items
# Wrap this in a list so that the calling function loop
# executes exactly once
return [final_items]
else:
# Restore the name parameter
self._task.args['name'] = name
#elif:
# Right now we only optimize single entries. In the future we
# could optimize more types:
# * lists can be squashed together
# * dicts could squash entries that match in all cases except the
# name or pkg field.
except:
# Squashing is an optimization. If it fails for any reason,
# simply use the unoptimized list of items.
# Restore the name parameter
if name is not None:
self._task.args['name'] = name
return items
def _execute(self, variables=None):
'''
The primary workhorse of the executor system, this runs the task
on the specified host (which may be the delegated_to host) and handles
the retry/until and block rescue/always execution
'''
if variables is None:
variables = self._job_vars
templar = Templar(loader=self._loader, shared_loader_obj=self._shared_loader_obj, variables=variables)
context_validation_error = None
try:
# apply the given task's information to the connection info,
# which may override some fields already set by the play or
# the options specified on the command line
self._play_context = self._play_context.set_task_and_variable_override(task=self._task, variables=variables, templar=templar)
# fields set from the play/task may be based on variables, so we have to
# do the same kind of post validation step on it here before we use it.
self._play_context.post_validate(templar=templar)
# now that the play context is finalized, if the remote_addr is not set
# default to using the host's address field as the remote address
if not self._play_context.remote_addr:
self._play_context.remote_addr = self._host.address
# We also add "magic" variables back into the variables dict to make sure
# a certain subset of variables exist.
self._play_context.update_vars(variables)
except AnsibleError as e:
# save the error, which we'll raise later if we don't end up
# skipping this task during the conditional evaluation step
context_validation_error = e
# Evaluate the conditional (if any) for this task, which we do before running
# the final task post-validation. We do this before the post validation due to
# the fact that the conditional may specify that the task be skipped due to a
# variable not being present which would otherwise cause validation to fail
try:
if not self._task.evaluate_conditional(templar, variables):
display.debug("when evaluation failed, skipping this task")
return dict(changed=False, skipped=True, skip_reason='Conditional check failed', _ansible_no_log=self._play_context.no_log)
except AnsibleError:
# skip conditional exception in the case of includes as the vars needed might not be avaiable except in the included tasks or due to tags
if self._task.action != 'include':
raise
# if we ran into an error while setting up the PlayContext, raise it now
if context_validation_error is not None:
raise context_validation_error
# if this task is a TaskInclude, we just return now with a success code so the
# main thread can expand the task list for the given host
if self._task.action == 'include':
include_variables = self._task.args.copy()
include_file = include_variables.pop('_raw_params', None)
if not include_file:
return dict(failed=True, msg="No include file was specified to the include")
include_file = templar.template(include_file)
return dict(include=include_file, include_variables=include_variables)
# Now we do final validation on the task, which sets all fields to their final values.
self._task.post_validate(templar=templar)
if '_variable_params' in self._task.args:
variable_params = self._task.args.pop('_variable_params')
if isinstance(variable_params, dict):
display.deprecated("Using variables for task params is unsafe, especially if the variables come from an external source like facts")
variable_params.update(self._task.args)
self._task.args = variable_params
# get the connection and the handler for this execution
if not self._connection or not getattr(self._connection, 'connected', False) or self._play_context.remote_addr != self._connection._play_context.remote_addr:
self._connection = self._get_connection(variables=variables, templar=templar)
self._connection.set_host_overrides(host=self._host, hostvars=variables.get('hostvars', {}).get(self._host.name, {}))
else:
# if connection is reused, its _play_context is no longer valid and needs
# to be replaced with the one templated above, in case other data changed
self._connection._play_context = self._play_context
self._handler = self._get_action_handler(connection=self._connection, templar=templar)
# And filter out any fields which were set to default(omit), and got the omit token value
omit_token = variables.get('omit')
if omit_token is not None:
self._task.args = dict((i[0], i[1]) for i in iteritems(self._task.args) if i[1] != omit_token)
# Read some values from the task, so that we can modify them if need be
if self._task.until:
retries = self._task.retries + 1
if retries is None:
retries = 3
elif retries <= 0:
retries = 1
else:
retries = 1
delay = self._task.delay
if delay < 0:
delay = 1
# make a copy of the job vars here, in case we need to update them
# with the registered variable value later on when testing conditions
vars_copy = variables.copy()
display.debug("starting attempt loop")
result = None
for attempt in range(1, retries + 1):
display.debug("running the handler")
try:
result = self._handler.run(task_vars=variables)
except AnsibleConnectionFailure as e:
return dict(unreachable=True, msg=to_unicode(e))
display.debug("handler run complete")
# preserve no log
result["_ansible_no_log"] = self._play_context.no_log
# update the local copy of vars with the registered value, if specified,
# or any facts which may have been generated by the module execution
if self._task.register:
vars_copy[self._task.register] = wrap_var(result.copy())
if self._task.async > 0:
if self._task.poll > 0:
result = self._poll_async_result(result=result, templar=templar)
# ensure no log is preserved
result["_ansible_no_log"] = self._play_context.no_log
# helper methods for use below in evaluating changed/failed_when
def _evaluate_changed_when_result(result):
if self._task.changed_when is not None and self._task.changed_when:
cond = Conditional(loader=self._loader)
cond.when = self._task.changed_when
result['changed'] = cond.evaluate_conditional(templar, vars_copy)
def _evaluate_failed_when_result(result):
if self._task.failed_when:
cond = Conditional(loader=self._loader)
cond.when = self._task.failed_when
failed_when_result = cond.evaluate_conditional(templar, vars_copy)
result['failed_when_result'] = result['failed'] = failed_when_result
else:
failed_when_result = False
return failed_when_result
if 'ansible_facts' in result:
vars_copy.update(result['ansible_facts'])
# set the failed property if the result has a non-zero rc. This will be
# overridden below if the failed_when property is set
if result.get('rc', 0) != 0:
result['failed'] = True
# if we didn't skip this task, use the helpers to evaluate the changed/
# failed_when properties
if 'skipped' not in result:
_evaluate_changed_when_result(result)
_evaluate_failed_when_result(result)
if retries > 1:
cond = Conditional(loader=self._loader)
cond.when = self._task.until
if cond.evaluate_conditional(templar, vars_copy):
break
else:
# no conditional check, or it failed, so sleep for the specified time
if attempt < retries:
result['attempts'] = attempt
result['_ansible_retry'] = True
result['retries'] = retries
display.debug('Retrying task, attempt %d of %d' % (attempt, retries))
self._rslt_q.put(TaskResult(self._host, self._task, result), block=False)
time.sleep(delay)
else:
if retries > 1:
# we ran out of attempts, so mark the result as failed
result['failed'] = True
# do the final update of the local variables here, for both registered
# values and any facts which may have been created
if self._task.register:
variables[self._task.register] = wrap_var(result)
if 'ansible_facts' in result:
variables.update(result['ansible_facts'])
# save the notification target in the result, if it was specified, as
# this task may be running in a loop in which case the notification
# may be item-specific, ie. "notify: service {{item}}"
if self._task.notify is not None:
result['_ansible_notify'] = self._task.notify
# add the delegated vars to the result, so we can reference them
# on the results side without having to do any further templating
# FIXME: we only want a limited set of variables here, so this is currently
# hardcoded but should be possibly fixed if we want more or if
# there is another source of truth we can use
delegated_vars = variables.get('ansible_delegated_vars', dict()).get(self._task.delegate_to, dict()).copy()
if len(delegated_vars) > 0:
result["_ansible_delegated_vars"] = dict()
for k in ('ansible_host', ):
result["_ansible_delegated_vars"][k] = delegated_vars.get(k)
# and return
display.debug("attempt loop complete, returning result")
return result
def _poll_async_result(self, result, templar):
'''
Polls for the specified JID to be complete
'''
async_jid = result.get('ansible_job_id')
if async_jid is None:
return dict(failed=True, msg="No job id was returned by the async task")
# Create a new psuedo-task to run the async_status module, and run
# that (with a sleep for "poll" seconds between each retry) until the
# async time limit is exceeded.
async_task = Task().load(dict(action='async_status jid=%s' % async_jid))
# Because this is an async task, the action handler is async. However,
# we need the 'normal' action handler for the status check, so get it
# now via the action_loader
normal_handler = self._shared_loader_obj.action_loader.get(
'normal',
task=async_task,
connection=self._connection,
play_context=self._play_context,
loader=self._loader,
templar=templar,
shared_loader_obj=self._shared_loader_obj,
)
time_left = self._task.async
while time_left > 0:
time.sleep(self._task.poll)
async_result = normal_handler.run()
# We do not bail out of the loop in cases where the failure
# is associated with a parsing error. The async_runner can
# have issues which result in a half-written/unparseable result
# file on disk, which manifests to the user as a timeout happening
# before it's time to timeout.
if int(async_result.get('finished', 0)) == 1 or ('failed' in async_result and async_result.get('parsed', True)) or 'skipped' in async_result:
break
time_left -= self._task.poll
if int(async_result.get('finished', 0)) != 1:
if async_result.get('parsed'):
return dict(failed=True, msg="async task did not complete within the requested time")
else:
return dict(failed=True, msg="async task produced unparseable results", async_result=async_result)
else:
return async_result
def _get_connection(self, variables, templar):
'''
Reads the connection property for the host, and returns the
correct connection object from the list of connection plugins
'''
if self._task.delegate_to is not None:
# since we're delegating, we don't want to use interpreter values
# which would have been set for the original target host
for i in variables.keys():
if isinstance(i, string_types) and i.startswith('ansible_') and i.endswith('_interpreter'):
del variables[i]
# now replace the interpreter values with those that may have come
# from the delegated-to host
delegated_vars = variables.get('ansible_delegated_vars', dict()).get(self._task.delegate_to, dict())
if isinstance(delegated_vars, dict):
for i in delegated_vars:
if isinstance(i, string_types) and i.startswith("ansible_") and i.endswith("_interpreter"):
variables[i] = delegated_vars[i]
conn_type = self._play_context.connection
if conn_type == 'smart':
conn_type = 'ssh'
if sys.platform.startswith('darwin') and self._play_context.password:
# due to a current bug in sshpass on OSX, which can trigger
# a kernel panic even for non-privileged users, we revert to
# paramiko on that OS when a SSH password is specified
conn_type = "paramiko"
else:
# see if SSH can support ControlPersist if not use paramiko
try:
cmd = subprocess.Popen(['ssh','-o','ControlPersist'], stdout=subprocess.PIPE, stderr=subprocess.PIPE)
(out, err) = cmd.communicate()
err = to_unicode(err)
if u"Bad configuration option" in err or u"Usage:" in err:
conn_type = "paramiko"
except OSError:
conn_type = "paramiko"
connection = self._shared_loader_obj.connection_loader.get(conn_type, self._play_context, self._new_stdin)
if not connection:
raise AnsibleError("the connection plugin '%s' was not found" % conn_type)
if self._play_context.accelerate:
# accelerate is deprecated as of 2.1...
display.deprecated('Accelerated mode is deprecated. Consider using SSH with ControlPersist and pipelining enabled instead')
# launch the accelerated daemon here
ssh_connection = connection
handler = self._shared_loader_obj.action_loader.get(
'normal',
task=self._task,
connection=ssh_connection,
play_context=self._play_context,
loader=self._loader,
templar=templar,
shared_loader_obj=self._shared_loader_obj,
)
key = key_for_hostname(self._play_context.remote_addr)
accelerate_args = dict(
password=base64.b64encode(key.__str__()),
port=self._play_context.accelerate_port,
minutes=C.ACCELERATE_DAEMON_TIMEOUT,
ipv6=self._play_context.accelerate_ipv6,
debug=self._play_context.verbosity,
)
connection = self._shared_loader_obj.connection_loader.get('accelerate', self._play_context, self._new_stdin)
if not connection:
raise AnsibleError("the connection plugin '%s' was not found" % conn_type)
try:
connection._connect()
except AnsibleConnectionFailure:
display.debug('connection failed, fallback to accelerate')
res = handler._execute_module(module_name='accelerate', module_args=accelerate_args, task_vars=variables, delete_remote_tmp=False)
display.debug(res)
connection._connect()
return connection
def _get_action_handler(self, connection, templar):
'''
Returns the correct action plugin to handle the requestion task action
'''
if self._task.action in self._shared_loader_obj.action_loader:
if self._task.async != 0:
raise AnsibleError("async mode is not supported with the %s module" % self._task.action)
handler_name = self._task.action
elif self._task.async == 0:
handler_name = 'normal'
else:
handler_name = 'async'
handler = self._shared_loader_obj.action_loader.get(
handler_name,
task=self._task,
connection=connection,
play_context=self._play_context,
loader=self._loader,
templar=templar,
shared_loader_obj=self._shared_loader_obj,
)
if not handler:
raise AnsibleError("the handler '%s' was not found" % handler_name)
return handler