mirror of
https://github.com/ansible-collections/community.general.git
synced 2024-09-14 20:13:21 +02:00
cb939cbb75
use dict comprehension in plugins, part 4 (#8858)
* use dict comprehension in plugins, part 4
* add changelog frag
(cherry picked from commit 94472dd7e5)
Co-authored-by: Alexei Znamensky <103110+russoz@users.noreply.github.com>
392 lines
12 KiB
Python
392 lines
12 KiB
Python
#!/usr/bin/python
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# -*- coding: utf-8 -*-
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#
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# Scaleway Serverless function management module
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#
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# Copyright (c) 2022, Guillaume MARTINEZ <lunik@tiwabbit.fr>
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# GNU General Public License v3.0+ (see LICENSES/GPL-3.0-or-later.txt or https://www.gnu.org/licenses/gpl-3.0.txt)
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# SPDX-License-Identifier: GPL-3.0-or-later
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from __future__ import absolute_import, division, print_function
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__metaclass__ = type
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DOCUMENTATION = '''
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---
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module: scaleway_function
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short_description: Scaleway Function management
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version_added: 6.0.0
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author: Guillaume MARTINEZ (@Lunik)
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description:
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- This module manages function on Scaleway account.
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extends_documentation_fragment:
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- community.general.scaleway
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- community.general.scaleway_waitable_resource
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- community.general.attributes
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requirements:
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- passlib[argon2] >= 1.7.4
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attributes:
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check_mode:
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support: full
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diff_mode:
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support: none
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options:
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state:
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type: str
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description:
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- Indicate desired state of the function.
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default: present
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choices:
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- present
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- absent
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namespace_id:
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type: str
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description:
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- Function namespace identifier.
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required: true
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region:
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type: str
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description:
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- Scaleway region to use (for example V(fr-par)).
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required: true
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choices:
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- fr-par
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- nl-ams
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- pl-waw
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name:
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type: str
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description:
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- Name of the function.
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required: true
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description:
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description:
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- Description of the function.
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type: str
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default: ''
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min_scale:
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description:
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- Minimum number of replicas for the function.
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type: int
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max_scale:
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description:
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- Maximum number of replicas for the function.
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type: int
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environment_variables:
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description:
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- Environment variables of the function.
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- Injected in function at runtime.
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type: dict
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default: {}
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secret_environment_variables:
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description:
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- Secret environment variables of the function.
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- Updating those values will not output a C(changed) state in Ansible.
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- Injected in function at runtime.
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type: dict
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default: {}
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runtime:
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description:
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- Runtime of the function
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- See U(https://www.scaleway.com/en/docs/compute/functions/reference-content/functions-lifecycle/) for all available runtimes
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type: str
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required: true
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memory_limit:
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description:
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- Resources define performance characteristics of your function.
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- They are allocated to your function at runtime.
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type: int
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function_timeout:
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description:
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- The length of time your handler can spend processing a request before being stopped.
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type: str
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handler:
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description:
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- The C(module-name.export) value in your function.
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type: str
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privacy:
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description:
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- Privacy policies define whether a function can be executed anonymously.
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- Choose V(public) to enable anonymous execution, or V(private) to protect your function with an authentication mechanism provided by the Scaleway API.
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type: str
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default: public
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choices:
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- public
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- private
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redeploy:
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description:
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- Redeploy the function if update is required.
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type: bool
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default: false
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'''
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EXAMPLES = '''
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- name: Create a function
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community.general.scaleway_function:
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namespace_id: '{{ scw_function_namespace }}'
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region: fr-par
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state: present
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name: my-awesome-function
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runtime: python3
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environment_variables:
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MY_VAR: my_value
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secret_environment_variables:
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MY_SECRET_VAR: my_secret_value
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register: function_creation_task
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- name: Make sure function is deleted
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community.general.scaleway_function:
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namespace_id: '{{ scw_function_namespace }}'
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region: fr-par
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state: absent
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name: my-awesome-function
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'''
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RETURN = '''
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function:
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description: The function information.
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returned: when O(state=present)
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type: dict
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sample:
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cpu_limit: 140
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description: Function used for testing scaleway_function ansible module
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domain_name: fnansibletestfxamabuc-fn-ansible-test.functions.fnc.fr-par.scw.cloud
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environment_variables:
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MY_VAR: my_value
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error_message: null
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handler: handler.handle
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http_option: ""
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id: ceb64dc4-4464-4196-8e20-ecef705475d3
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max_scale: 5
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memory_limit: 256
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min_scale: 0
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name: fn-ansible-test
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namespace_id: 82737d8d-0ebb-4d89-b0ad-625876eca50d
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privacy: public
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region: fr-par
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runtime: python310
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runtime_message: ""
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secret_environment_variables:
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- key: MY_SECRET_VAR
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value: $argon2id$v=19$m=65536,t=1,p=2$tb6UwSPWx/rH5Vyxt9Ujfw$5ZlvaIjWwNDPxD9Rdght3NarJz4IETKjpvAU3mMSmFg
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status: created
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timeout: 300s
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'''
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from copy import deepcopy
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from ansible_collections.community.general.plugins.module_utils.scaleway import (
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SCALEWAY_REGIONS, scaleway_argument_spec, Scaleway,
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scaleway_waitable_resource_argument_spec, resource_attributes_should_be_changed,
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SecretVariables
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)
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from ansible.module_utils.basic import AnsibleModule
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STABLE_STATES = (
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"ready",
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"created",
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"absent"
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)
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VERIFIABLE_MUTABLE_ATTRIBUTES = (
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"description",
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"min_scale",
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"max_scale",
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"environment_variables",
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"runtime",
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"memory_limit",
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"timeout",
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"handler",
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"privacy",
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"secret_environment_variables"
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)
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MUTABLE_ATTRIBUTES = VERIFIABLE_MUTABLE_ATTRIBUTES + (
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"redeploy",
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)
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def payload_from_wished_fn(wished_fn):
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payload = {
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"namespace_id": wished_fn["namespace_id"],
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"name": wished_fn["name"],
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"description": wished_fn["description"],
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"min_scale": wished_fn["min_scale"],
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"max_scale": wished_fn["max_scale"],
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"runtime": wished_fn["runtime"],
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"memory_limit": wished_fn["memory_limit"],
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"timeout": wished_fn["timeout"],
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"handler": wished_fn["handler"],
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"privacy": wished_fn["privacy"],
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"redeploy": wished_fn["redeploy"],
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"environment_variables": wished_fn["environment_variables"],
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"secret_environment_variables": SecretVariables.dict_to_list(wished_fn["secret_environment_variables"])
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}
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return payload
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def absent_strategy(api, wished_fn):
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changed = False
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fn_list = api.fetch_all_resources("functions")
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fn_lookup = {fn["name"]: fn for fn in fn_list}
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if wished_fn["name"] not in fn_lookup:
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return changed, {}
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target_fn = fn_lookup[wished_fn["name"]]
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changed = True
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if api.module.check_mode:
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return changed, {"status": "Function would be destroyed"}
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api.wait_to_complete_state_transition(resource=target_fn, stable_states=STABLE_STATES, force_wait=True)
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response = api.delete(path=api.api_path + "/%s" % target_fn["id"])
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if not response.ok:
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api.module.fail_json(msg='Error deleting function [{0}: {1}]'.format(
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response.status_code, response.json))
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api.wait_to_complete_state_transition(resource=target_fn, stable_states=STABLE_STATES)
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return changed, response.json
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def present_strategy(api, wished_fn):
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changed = False
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fn_list = api.fetch_all_resources("functions")
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fn_lookup = {fn["name"]: fn for fn in fn_list}
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payload_fn = payload_from_wished_fn(wished_fn)
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if wished_fn["name"] not in fn_lookup:
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changed = True
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if api.module.check_mode:
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return changed, {"status": "A function would be created."}
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# Creation doesn't support `redeploy` parameter
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del payload_fn["redeploy"]
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# Create function
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api.warn(payload_fn)
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creation_response = api.post(path=api.api_path,
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data=payload_fn)
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if not creation_response.ok:
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msg = "Error during function creation: %s: '%s' (%s)" % (creation_response.info['msg'],
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creation_response.json['message'],
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creation_response.json)
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api.module.fail_json(msg=msg)
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api.wait_to_complete_state_transition(resource=creation_response.json, stable_states=STABLE_STATES)
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response = api.get(path=api.api_path + "/%s" % creation_response.json["id"])
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return changed, response.json
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target_fn = fn_lookup[wished_fn["name"]]
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decoded_target_fn = deepcopy(target_fn)
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decoded_target_fn["secret_environment_variables"] = SecretVariables.decode(decoded_target_fn["secret_environment_variables"],
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payload_fn["secret_environment_variables"])
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patch_payload = resource_attributes_should_be_changed(target=decoded_target_fn,
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wished=payload_fn,
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verifiable_mutable_attributes=VERIFIABLE_MUTABLE_ATTRIBUTES,
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mutable_attributes=MUTABLE_ATTRIBUTES)
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if not patch_payload:
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return changed, target_fn
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changed = True
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if api.module.check_mode:
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return changed, {"status": "Function attributes would be changed."}
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fn_patch_response = api.patch(path=api.api_path + "/%s" % target_fn["id"],
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data=patch_payload)
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if not fn_patch_response.ok:
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api.module.fail_json(msg='Error during function attributes update: [{0}: {1}]'.format(
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fn_patch_response.status_code, fn_patch_response.json['message']))
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api.wait_to_complete_state_transition(resource=target_fn, stable_states=STABLE_STATES)
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response = api.get(path=api.api_path + "/%s" % target_fn["id"])
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return changed, response.json
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state_strategy = {
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"present": present_strategy,
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"absent": absent_strategy
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}
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def core(module):
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SecretVariables.ensure_scaleway_secret_package(module)
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region = module.params["region"]
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wished_function = {
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"state": module.params["state"],
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"namespace_id": module.params["namespace_id"],
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"name": module.params["name"],
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"description": module.params['description'],
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"min_scale": module.params['min_scale'],
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"max_scale": module.params['max_scale'],
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"runtime": module.params["runtime"],
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"memory_limit": module.params["memory_limit"],
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"timeout": module.params["function_timeout"],
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"handler": module.params["handler"],
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"privacy": module.params["privacy"],
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"redeploy": module.params["redeploy"],
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"environment_variables": module.params['environment_variables'],
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"secret_environment_variables": module.params['secret_environment_variables']
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}
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api = Scaleway(module=module)
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api.api_path = "functions/v1beta1/regions/%s/functions" % region
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changed, summary = state_strategy[wished_function["state"]](api=api, wished_fn=wished_function)
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module.exit_json(changed=changed, function=summary)
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def main():
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argument_spec = scaleway_argument_spec()
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argument_spec.update(scaleway_waitable_resource_argument_spec())
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argument_spec.update(dict(
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state=dict(type='str', default='present', choices=['absent', 'present']),
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namespace_id=dict(type='str', required=True),
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region=dict(type='str', required=True, choices=SCALEWAY_REGIONS),
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name=dict(type='str', required=True),
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description=dict(type='str', default=''),
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min_scale=dict(type='int'),
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max_scale=dict(type='int'),
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runtime=dict(type='str', required=True),
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memory_limit=dict(type='int'),
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function_timeout=dict(type='str'),
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handler=dict(type='str'),
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privacy=dict(type='str', default='public', choices=['public', 'private']),
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redeploy=dict(type='bool', default=False),
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environment_variables=dict(type='dict', default={}),
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secret_environment_variables=dict(type='dict', default={}, no_log=True)
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))
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module = AnsibleModule(
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argument_spec=argument_spec,
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supports_check_mode=True,
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)
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core(module)
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if __name__ == '__main__':
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main()
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