What better way to understand how an Avocado plugin works than creating one? Let's use another old time favorite for that, the "Print hello world" theme.
Let's say you want to write a plugin that adds a new subcommand to the test
runner, hello. This is how you'd do it:
.. literalinclude:: ../../../../../examples/plugins/cli-cmd/hello/hello.py
This plugins inherits from :class:`avocado.core.plugin_interfaces.CLICmd`. This specific base class allows for the creation of new commands for the Avocado CLI tool. The only mandatory method to be implemented is :func:`run <avocado.core.plugin_interfaces.CLICmd.run>` and it's the plugin main entry point.
This plugin uses :py:data:`avocado.core.output.LOG_UI` to produce the hello world output in the console.
Note
Different loggers can be used in other contexts and for different purposes. One such example is :py:data:`avocado.core.output.LOG_JOB`, which can be used to output to job log files when running a job.
It is usual for a plugin to allow users to do some degree of configuration based on command-line options and/or configuration options. A plugin might change its behavior depending on a specific configuration option.
Frequently, those settings come from configuration files and, sometimes, from the command-line arguments. Like in most UNIX-like tools, command-line options will override values defined inside the configuration files.
You, as a plugin writer, don’t need to handle this configuration by yourself. Avocado provides a common API that can be used by plugins in order to register options and get values.
If your plugin has options available to the users, register it using the :meth:`.Settings.register_option()` method during your plugin configuration stage. The options are parsed and provided to the plugin as a config dictionary.
Let’s take our Hello World example and change the message based on a “message” option:
.. literalinclude:: ../../../../../examples/plugins/cli-cmd/hello_option/hello_option.py
The code in the example above registers a configuration namespace (hello.message) inside the configuration file only. A namespace is a section (hello) followed by a key (message). In other words, the following entry in your configuration file is also valid and will be parsed:
[hello] message = My custom message
As you can see in the example above, you need to set a default value and this value will be used if the option is not present in the configuration file. This means that you can have a very small configuration file or even an empty one.
This is a very basic example of how to configure options inside your plugin.
Now, let’s say you would like to also allow this change via the command-line option of your plugin (if your plugin is a command-line plugin). You need to register in any case and use the same method to connect your option namespace with your command-line option.
.. literalinclude:: ../../../../../examples/plugins/cli-cmd/hello_parser/hello_parser.py
Note
Keep in mind that not all options should have a “command-line” option. Try to keep the command-line as clean as possible. We use command-line only for options that constantly need to change and when editing the configuration file is not handy.
For more information about how this registration process works, visit the :meth:`.Settings.register_option()` method documentation.
Avocado makes use of the setuptools and its entry points to register and find Python objects. So, to make your new plugin visible to Avocado, you need to add to your setuptools based setup.py file something like:
.. literalinclude:: ../../../../../examples/plugins/cli-cmd/hello/setup.py
Then, by running either $ python setup.py install or $ python setup.py
develop your plugin should be visible to Avocado.
The plugin registry mentioned earlier, (setuptools and its entry points) is
global to a given Python installation. Avocado uses the namespace prefix
avocado.plugins. to avoid name clashes with other software. Now, inside
Avocado itself, there's no need keep using the avocado.plugins. prefix.
Take for instance, the Job Pre/Post plugins are defined on setup.py:
'avocado.plugins.job.prepost': [ 'jobscripts = avocado.plugins.jobscripts:JobScripts' ]
The setuptools entry point namespace is composed of the mentioned prefix
avocado.plugins., which is then followed by the Avocado plugin type, in
this case, job.prepost.
Inside Avocado itself, the fully qualified name for a plugin is the plugin
type, such as job.prepost concatenated to the name used in the entry point
definition itself, in this case, jobscripts.
To summarize, still using the same example, the fully qualified Avocado plugin
name is going to be job.prepost.jobscripts.
Plugins can extend the list of config files parsed by Settings objects by
dropping the individual config files into /etc/avocado/conf.d
(linux/posix-way) or they can take advantages of the Python entry point using
avocado.plugins.settings.
- /etc/avocado/conf.d:
In order to not disturb the main Avocado config file, those plugins, if they
wish so, may install additional config files to
/etc/avocado/conf.d/[pluginname].conf, that will be parsed after the system
wide config file. Users can override those values as well at the local config
file level. Considering the config for the hypothethical plugin salad:
[salad.core]
base = caesar
dressing = caesarIf you want, you may change dressing in your config file by simply adding a
[salad.core] new section in your local config file, and set a different
value for dressing there.
- avocado.plugins.settings:
This entry-point uses avocado.core.plugin_interfaces.Settings-like object
to extend the list of parsed files. It only accepts individual files, but you
can use something like glob.glob("*.conf") to add all config files inside a
directory.
You need to create the plugin (eg. my_plugin/settings.py):
from avocado.core.plugin_interfaces import Settings
class MyPluginSettings(Settings):
def adjust_settings_paths(self, paths):
paths.extend(glob.glob("/etc/my_plugin/conf.d/*.conf"))
And register it in your setup.py entry-points:
from setuptools import setup
...
setup(name="my-plugin",
entry_points={
'avocado.plugins.settings': [
"my-plugin-settings = my_plugin.settings.MyPluginSettings",
],
...
Which extends the list of files to be parsed by settings object. Note this has to be executed early in the code so try to keep the required deps minimal (for example the avocado.core.settings.settings is not yet available).
Avocado lets plugin developers to define plugin priority, which ensures the default execution order.The plugins with higher priority will be executed earlier than the plugins with lower priority. The priorities are on the scale between 0-100 and as default all plugins have priority set to NORMAL (50). For easier usage, avocado has predefined values in:
.. autoclass:: avocado.core.extension_manager.PluginPriority :noindex: :members: :undoc-members:
To define a priority for plugin, you have to create class attribute priority
same as you're defining name and description:
.. literalinclude:: ../../../../../examples/plugins/cli-cmd/hello_priority/hello_priority.py
Now, the plugin HelloWorld has priority high and will be executed before
every plugin without priority variable (default priority).
As a plugin developer, you have to consider that users can change the execution
order by plugins.$type.order option. In such case, at first will be executed
the plugins from plugins.$type.order and then the rest of plugins by its
priority. For example the default order is [plugin1, plugin2, plugin3, plugin4]
the plugins.$type.order is [plugin2, plugin4] then the real order will be
[plugin2, plugin4, plugin1, plugin3]
The results of Pre-test and Post-test plugins defined in :class:`avocado.core.plugin_interfaces.PreTest` and :class:`avocado.core.plugin_interfaces.PostTest` can be saved in cache. This is very useful If the results can be used by other tests or even other avocado executions. As an example of such plugin is Dependency resolver in :ref:`managing-requirements` which installs dependencies for test into the test environment.
As a default, all pre- / post-plugins are noncacheable. To make plugin cacheable you have to set plugin variable is_cacheable to True, like this:
.. literalinclude:: ../../../../../examples/plugins/test-pre-post/hello/hello.py
For a new test type to be recognized and executed by Avocado's nrunner architecture, there needs to be two types of plugins and one optional:
- resolvers: they resolve references into proper test descriptions that Avocado can run.
- discoverers (optional): They are doing the same job as resolvers but without a reference. They are used when the tests can be created from different data e.g. config files.
- runners: these make use of the resolutions made by resolvers and actually execute the tests, reporting the results back to Avocado
The following example shows real code for a resolver and a runner for a magic test type. This magic test simply passes or fails depending on the test reference.
The resolver implementation will simply set the test type (magic) and transform the reference given into its url:
.. literalinclude:: ../../../../../examples/plugins/tests/magic/avocado_magic/resolver.py
A magic test does not depend on a file, only on the "magic" word
(either "pass" or "fail"). Because of that, there's no need to
provide information at resolution time about the file(s) comprising
the magic tests.
For most other test types, though, the test will be contained within a file, and/or may be comprised by many supplemental files containing test specific data. While local execution of a test will easily find those files, in order to be prepared for the execution of a test in different environments (by different spawners), it's recommended that the resolver (and discoverer) provide that kind of information.
A feature that is strongly recommended to be implemented by resolvers
and discoverers of tests that are file-based is the .data
directory support. Whenever a test contained in a file has a matching
directory with the .data :data:`suffix
<avocado.core.test.TestData.SUFFIX>`, the test can get quick access to
these files with the :meth:`get_data
<avocado.core.test.TestData.get_data>` method.
To do so, use the assets keyword argument when creating
:class:`Runnable <avocado.core.nrunner.runnable.Runnable>` instances.
The assets keyword argument takes a list of tuples with (type,
path) tuples, which will then be available at the :data:`Runnable
<avocado.core.nrunner.runnable.Runnable.assets>` attribute.
Actual examples are available in the implementation of the
exec-test and similar builtin resolvers.
For the file that contains the test, it's recommended that resolvers and discoverers use the type :data:`avocado.core.resolver.ReferenceResolutionAssetType.TEST_FILE`. For other data files, use the :data:`avocado.core.resolver.ReferenceResolutionAssetType.DATA_FILE`.
The runner will receive the :class:`avocado.core.nrunner.runnable.Runnable` information created by the resolver plugin. Runners can be written in any language, but this implementation reuses some base Python classes.
First, :class:`avocado.core.nrunner.runner.BaseRunner` is used to write the
runner class. And second, the
:class:`avocado.core.nrunner.app.BaseRunnerApp` is used to create the command
line application, which uses the previously implemented runner class
for magic test types.
.. literalinclude:: ../../../../../examples/plugins/tests/magic/avocado_magic/runner.py
A runner is free to make use of all the information in the :class:`avocado.core.nrunner.runnable.Runnable` that the resolver implementation populates. In this particular example it only makes use of the :attr:`uri <avocado.core.nrunner.runnable.Runnable.uri>` attribute. If a runner needs to behave accordingly to some Avocado configuration, you need to declare that configuration in the :attr:`CONFIGURATION_USED <avocado.core.nrunner.runner.BaseRunner.CONFIGURATION_USED>` class attribute and then you can access it in :attr:`config <avocado.core.nrunner.runnable.Runnable.config>`.
The plugins need to be registered so that Avocado knows about it. See :ref:`registering-plugins` for more information. This is the code that can be used to register these plugins:
.. literalinclude:: ../../../../../examples/plugins/tests/magic/setup.py
With that, you need to either run python setup.py install or
python setup.py develop.
Note
The last entry, registering a console_script, is
recommended because it allows one to experiment with the
runner as a command line application
(avocado-runner-magic in this case). Also, depending on
the spawner implementation used to run the tests, having a
runner that can be executed as an application (and not a
Python class) is a requirement.
With the plugins activated, you should be able to run avocado plugins and
find (among other output):
Plugins that resolve test references (resolver): ... magic Test resolver for magic words ...
Resolving the "pass" and "fail" references that the magic plugin knows about
can be seen by running avocado list magic:pass magic:fail:
magic magic:pass magic magic:fail
And you may get more insight into the resolution results, by adding a
verbose parameter and another reference. Try running avocado -V
list magic:pass magic:fail magic:foo something-else:
Reference magic:foo might be resolved by magic resolver, but the file is corrupted: Word "magic:foo" is magic type but the foo is not a valid magic word Type Test Tag(s) magic magic:pass magic magic:fail Resolver Reference Info avocado-instrumented magic:pass File "magic" does not end with ".py" golang magic:pass go binary not found avocado-instrumented magic:fail File "magic" does not end with ".py" golang magic:fail go binary not found avocado-instrumented magic:foo File "magic" does not end with ".py" golang magic:foo go binary not found magic magic:foo Word "magic:foo" is magic type but the foo is not a valid magic word avocado-instrumented something-else File "something-else" does not end with ".py" golang something-else go binary not found magic something-else Word "something-else" is not a valid magic word python-unittest something-else File "something-else" does not end with ".py" robot something-else File "something-else" does not end with ".robot" rogue something-else Word "something-else" is not the magic word exec-test something-else File "something-else" does not exist or is not a executable file tap something-else File "something-else" does not exist or is not a executable file TEST TYPES SUMMARY ================== magic: 2
It's worth realizing that magic (and other plugins) were asked to
resolve the magic:foo and something-else references, but couldn't:
Resolver Reference Info ... magic magic:foo Word "magic:foo" is magic type but the foo is not a valid magic word ... magic something-else Word "something-else" is not a valid magic word ...
We can see that the reference "magic:foo" resembles the magic words by
type but it is not magic words pass or fail. Consequently,
the resolver can provide the user with information about potentially
corrupted references. This can assist the user in identifying typos
or reference mistakes. As the creator of the resolver, you can use the
:data:`avocado.core.resolver.ReferenceResolutionResult.CORRUPT` variable
to notify the user of such a situation.
The common way of running Avocado tests is to run them through
avocado run. To run both the pass and fail magic tests,
you'd run avocado run -- magic:pass magic:fail:
$ avocado run -- magic:pass magic:fail JOB ID : 86fd45f8c1f2fe766c252eefbcac2704c2106db9 JOB LOG : $HOME/avocado/job-results/job-2021-02-05T12.43-86fd45f/job.log (1/2) magic:pass: STARTED (1/2) magic:pass: PASS (0.00 s) (2/2) magic:fail: STARTED (2/2) magic:fail: FAIL (0.00 s) RESULTS : PASS 1 | ERROR 0 | FAIL 1 | SKIP 0 | WARN 0 | INTERRUPT 0 | CANCEL 0 JOB HTML : $HOME/avocado/job-results/job-2021-02-05T12.43-86fd45f/results.html JOB TIME : 1.83 s