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# 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/>.
from __future__ import annotations
import multiprocessing
import multiprocessing.pool as mp
# timeout function to make sure some fact gathering
# steps do not exceed a time limit
GATHER_TIMEOUT = None
DEFAULT_GATHER_TIMEOUT = 10
class TimeoutError(Exception):
pass
def timeout(seconds=None, error_message="Timer expired"):
"""
Timeout decorator to expire after a set number of seconds. This raises an
ansible.module_utils.facts.TimeoutError if the timeout is hit before the
function completes.
"""
def decorator(func):
def wrapper(*args, **kwargs):
timeout_value = seconds
if timeout_value is None:
timeout_value = globals().get('GATHER_TIMEOUT') or DEFAULT_GATHER_TIMEOUT
pool = mp.ThreadPool(processes=1)
res = pool.apply_async(func, args, kwargs)
pool.close()
try:
return res.get(timeout_value)
except multiprocessing.TimeoutError:
# This is an ansible.module_utils.common.facts.timeout.TimeoutError
raise TimeoutError(f'{error_message} after {timeout_value} seconds')
finally:
pool.terminate()
return wrapper
# If we were called as @timeout, then the first parameter will be the
# function we are to wrap instead of the number of seconds. Detect this
# and correct it by setting seconds to our default value and return the
# inner decorator function manually wrapped around the function
if callable(seconds):
func = seconds
seconds = None
return decorator(func)
# If we were called as @timeout([...]) then python itself will take
# care of wrapping the inner decorator around the function
return decorator
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