f015d3b55d
First pack of changes in upcoming chain to redesign Rally docs.
All information related to Rally plugins separated and refactored.
Modified files fit 80 symbols margin where possible.
[TODO] continue with other parts of the docs:
- Contribute to Rally
- Request New Features
- Project Info
[TODO] add 80 symbols margin check similar to what
Performance Documentation has
Change-Id: I5d19a2bbbcdd9be463793bce50de62c5608b6157
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3.2 KiB
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110 lines
3.2 KiB
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Copyright 2016 Mirantis Inc. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may
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not use this file except in compliance with the License. You may obtain
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a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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License for the specific language governing permissions and limitations
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under the License.
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.. _plugins_runner_plugin:
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Scenario runner as a plugin
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===========================
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Let's create a scenario runner plugin that runs a given benchmark
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scenario a random number of times (chosen at random from a given
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range).
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Creation
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^^^^^^^^
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Inherit a class for your plugin from the base *ScenarioRunner* class
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and implement its API (the *_run_scenario()* method):
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.. code-block:: python
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import random
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from rally.task import runner
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from rally import consts
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@runner.configure(name="random_times")
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class RandomTimesScenarioRunner(runner.ScenarioRunner):
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"""Sample scenario runner plugin.
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Run scenario random number of times, which is chosen between min_times and
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max_times.
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"""
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CONFIG_SCHEMA = {
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"type": "object",
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"$schema": consts.JSON_SCHEMA,
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"properties": {
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"type": {
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"type": "string"
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},
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"min_times": {
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"type": "integer",
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"minimum": 1
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},
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"max_times": {
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"type": "integer",
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"minimum": 1
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}
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},
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"additionalProperties": True
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}
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def _run_scenario(self, cls, method_name, context, args):
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# runners settings are stored in self.config
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min_times = self.config.get('min_times', 1)
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max_times = self.config.get('max_times', 1)
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for i in range(random.randrange(min_times, max_times)):
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run_args = (i, cls, method_name,
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runner._get_scenario_context(context), args)
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result = runner._run_scenario_once(run_args)
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# use self.send_result for result of each iteration
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self._send_result(result)
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Usage
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^^^^^
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You can refer to your scenario runner in the benchmark task
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configuration files in the same way as any other runners. Don't forget
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to put your runner-specific parameters in the configuration as well
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(*"min_times"* and *"max_times"* in our example):
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.. code-block:: json
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{
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"Dummy.dummy": [
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{
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"runner": {
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"type": "random_times",
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"min_times": 10,
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"max_times": 20,
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},
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"context": {
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"users": {
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"tenants": 1,
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"users_per_tenant": 1
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}
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}
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}
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]
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}
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Different plugin samples are available `here <https://github.com/openstack/rally/tree/master/samples/plugins>`_.
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