New GCP module: gcp_mlengine_version_facts

lib/ansible/modules/cloud/google/gcp_mlengine_version_facts.py

@@ -0,0 +1,257 @@
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2017 Google
+# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
+# ----------------------------------------------------------------------------
+#
+#     ***     AUTO GENERATED CODE    ***    AUTO GENERATED CODE     ***
+#
+# ----------------------------------------------------------------------------
+#
+#     This file is automatically generated by Magic Modules and manual
+#     changes will be clobbered when the file is regenerated.
+#
+#     Please read more about how to change this file at
+#     https://www.github.com/GoogleCloudPlatform/magic-modules
+#
+# ----------------------------------------------------------------------------
+
+from __future__ import absolute_import, division, print_function
+
+__metaclass__ = type
+
+################################################################################
+# Documentation
+################################################################################
+
+ANSIBLE_METADATA = {'metadata_version': '1.1', 'status': ["preview"], 'supported_by': 'community'}
+
+DOCUMENTATION = '''
+---
+module: gcp_mlengine_version_facts
+description:
+- Gather facts for GCP Version
+short_description: Gather facts for GCP Version
+version_added: 2.9
+author: Google Inc. (@googlecloudplatform)
+requirements:
+- python >= 2.6
+- requests >= 2.18.4
+- google-auth >= 1.3.0
+options:
+  model:
+    description:
+    - The model that this version belongs to.
+    - 'This field represents a link to a Model resource in GCP. It can be specified
+      in two ways. First, you can place a dictionary with key ''name'' and value of
+      your resource''s name Alternatively, you can add `register: name-of-resource`
+      to a gcp_mlengine_model task and then set this model field to "{{ name-of-resource
+      }}"'
+    required: true
+    type: dict
+extends_documentation_fragment: gcp
+'''
+
+EXAMPLES = '''
+- name: " a version facts"
+  gcp_mlengine_version_facts:
+    model: "{{ model }}"
+    project: test_project
+    auth_kind: serviceaccount
+    service_account_file: "/tmp/auth.pem"
+    state: facts
+'''
+
+RETURN = '''
+resources:
+  description: List of resources
+  returned: always
+  type: complex
+  contains:
+    name:
+      description:
+      - The name specified for the version when it was created.
+      - The version name must be unique within the model it is created in.
+      returned: success
+      type: str
+    description:
+      description:
+      - The description specified for the version when it was created.
+      returned: success
+      type: str
+    isDefault:
+      description:
+      - If true, this version will be used to handle prediction requests that do not
+        specify a version.
+      returned: success
+      type: bool
+    deploymentUri:
+      description:
+      - The Cloud Storage location of the trained model used to create the version.
+      returned: success
+      type: str
+    createTime:
+      description:
+      - The time the version was created.
+      returned: success
+      type: str
+    lastUseTime:
+      description:
+      - The time the version was last used for prediction.
+      returned: success
+      type: str
+    runtimeVersion:
+      description:
+      - The AI Platform runtime version to use for this deployment.
+      returned: success
+      type: str
+    machineType:
+      description:
+      - The type of machine on which to serve the model. Currently only applies to
+        online prediction service.
+      returned: success
+      type: str
+    state:
+      description:
+      - The state of a version.
+      returned: success
+      type: str
+    errorMessage:
+      description:
+      - The details of a failure or cancellation.
+      returned: success
+      type: str
+    packageUris:
+      description:
+      - Cloud Storage paths (gs://…) of packages for custom prediction routines or
+        scikit-learn pipelines with custom code.
+      returned: success
+      type: list
+    labels:
+      description:
+      - One or more labels that you can add, to organize your model versions.
+      returned: success
+      type: dict
+    framework:
+      description:
+      - The machine learning framework AI Platform uses to train this version of the
+        model.
+      returned: success
+      type: str
+    pythonVersion:
+      description:
+      - The version of Python used in prediction. If not set, the default version
+        is '2.7'. Python '3.5' is available when runtimeVersion is set to '1.4' and
+        above. Python '2.7' works with all supported runtime versions.
+      returned: success
+      type: str
+    serviceAccount:
+      description:
+      - Specifies the service account for resource access control.
+      returned: success
+      type: str
+    autoScaling:
+      description:
+      - Automatically scale the number of nodes used to serve the model in response
+        to increases and decreases in traffic. Care should be taken to ramp up traffic
+        according to the model's ability to scale or you will start seeing increases
+        in latency and 429 response codes.
+      returned: success
+      type: complex
+      contains:
+        minNodes:
+          description:
+          - The minimum number of nodes to allocate for this mode.
+          returned: success
+          type: int
+    manualScaling:
+      description:
+      - Manually select the number of nodes to use for serving the model. You should
+        generally use autoScaling with an appropriate minNodes instead, but this option
+        is available if you want more predictable billing. Beware that latency and
+        error rates will increase if the traffic exceeds that capability of the system
+        to serve it based on the selected number of nodes.
+      returned: success
+      type: complex
+      contains:
+        nodes:
+          description:
+          - The number of nodes to allocate for this model. These nodes are always
+            up, starting from the time the model is deployed.
+          returned: success
+          type: int
+    predictionClass:
+      description:
+      - The fully qualified name (module_name.class_name) of a class that implements
+        the Predictor interface described in this reference field. The module containing
+        this class should be included in a package provided to the packageUris field.
+      returned: success
+      type: str
+    model:
+      description:
+      - The model that this version belongs to.
+      returned: success
+      type: dict
+'''
+
+################################################################################
+# Imports
+################################################################################
+from ansible.module_utils.gcp_utils import navigate_hash, GcpSession, GcpModule, GcpRequest, replace_resource_dict
+import json
+
+################################################################################
+# Main
+################################################################################
+
+
+def main():
+    module = GcpModule(argument_spec=dict(model=dict(required=True, type='dict')))
+
+    if not module.params['scopes']:
+        module.params['scopes'] = ['https://www.googleapis.com/auth/cloud-platform']
+
+    items = fetch_list(module, collection(module))
+    if items.get('versions'):
+        items = items.get('versions')
+    else:
+        items = []
+    return_value = {'resources': items}
+    module.exit_json(**return_value)
+
+
+def collection(module):
+    res = {'project': module.params['project'], 'model': replace_resource_dict(module.params['model'], 'name')}
+    return "https://ml.googleapis.com/v1/projects/{project}/models/{model}/versions".format(**res)
+
+
+def fetch_list(module, link):
+    auth = GcpSession(module, 'mlengine')
+    response = auth.get(link)
+    return return_if_object(module, response)
+
+
+def return_if_object(module, response):
+    # If not found, return nothing.
+    if response.status_code == 404:
+        return None
+
+    # If no content, return nothing.
+    if response.status_code == 204:
+        return None
+
+    try:
+        module.raise_for_status(response)
+        result = response.json()
+    except getattr(json.decoder, 'JSONDecodeError', ValueError) as inst:
+        module.fail_json(msg="Invalid JSON response with error: %s" % inst)
+
+    if navigate_hash(result, ['error', 'errors']):
+        module.fail_json(msg=navigate_hash(result, ['error', 'errors']))
+
+    return result
+
+
+if __name__ == "__main__":
+    main()