community.general/lib/ansible/plugins/lookup/flattened.py

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# (c) 2013, Serge van Ginderachter <serge@vanginderachter.be>
#
# 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/>.
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from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
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from ansible.errors import *
from ansible.plugins.lookup import LookupBase
from ansible.utils.listify import listify_lookup_plugin_terms
class LookupModule(LookupBase):
def _check_list_of_one_list(self, term):
# make sure term is not a list of one (list of one..) item
# return the final non list item if so
if isinstance(term,list) and len(term) == 1:
term = term[0]
if isinstance(term,list):
term = self._check_list_of_one_list(term)
return term
def _do_flatten(self, terms, variables):
ret = []
for term in terms:
term = self._check_list_of_one_list(term)
if term == 'None' or term == 'null':
# ignore undefined items
break
if isinstance(term, basestring):
# convert a variable to a list
term2 = listify_lookup_plugin_terms(term, templar=self._templar, loader=self._loader)
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# but avoid converting a plain string to a list of one string
if term2 != [ term ]:
term = term2
if isinstance(term, list):
# if it's a list, check recursively for items that are a list
term = self._do_flatten(term, variables)
ret.extend(term)
else:
ret.append(term)
return ret
def run(self, terms, variables, **kwargs):
if not isinstance(terms, list):
raise AnsibleError("with_flattened expects a list")
return self._do_flatten(terms, variables)