For a completely new strategy, new classes are often best going into new files.
Follow the example of existing files but concentrate on just the __init__
functions and imports at this stage. Adding the summary and description
elements should help you identify how to divide the work between the classes.
Create a device configuration YAML file with the help of the Online YAML parser using examples of existing files.
See also
Create a job submission YAML file, again with the parser and existing examples.
At each stage, consider which elements of the job and device configuration may need to be overridden by test writers and instance admins.
It may seem strange to add one or more unit test files at this stage but it helps write the validate functions which come up next. Adapt an existing Factory class to load the device configuration file and sample job file and then create a Job. In the test cases, inspect the pipeline created from these YAML files. Whenever the validate or populate functions are modified, add checks to the unit test that the new data exists in the correct type and content. Re-run the unit test each time to spot regressions.
There are a number of unit tests which parse all jobs and devices in the test
directories, so ensure that the new additions do not interfere with the
existing tests. This is the basis of what needs to go into the accepts
function of the Strategy class and into the job and device YAML. Make sure that
there is sufficient differentiation between the new files and the existing
files without causing duplication.
If the new classes are properly aligned with the workload of the test job, the sections of the test script will fall naturally into the classes in the same sequence.
parameters in the validate
function. It is often useful to assemble some these parameters into member
variables, checking that the final form is correct in the test case.self.errors in validate instead of raising an exception
of allowing calls within validate from raising unhandled exceptions. If
validate should not continue executing after a particular error, always
ensure that an error is set before returning from validate early.job.validate(). The
simplest way to do this is to inspect the job.pipeline.actions using a
list comprehension based on the action name.run function (which does not need
to be completed at this stage).utils.constants will provide
a way for instance admins to make changes. If there is a chance that either a
different device-type or a different test job plan, then add the default to
the job or device file and fetch the value in the parameters. Ensure that
validate shows that the correct value is available.just works, e.g. by adding
DownloadAction to a populate function.pylint can be annoying but it is also useful - providing that some of the
warnings and errors are disabled. Check similar files but do be cautious about
disabling lots of warnings in the early stages. Pay particular attention to
missing imports, unused variables, unused imports, and invalid names. Logging
not lazy is less relevant, overall, in the LAVA codebase - there are situations
where lazy logging results in the wrong values being entered into the logs.
Warning
pep8 is essential - no reviews will be accepted if there
are pep8 errors beyond line-too-long (E501). This is the first check
performed by ./ci-run (which must also pass).
From this point, standard code development takes over. To get the code accepted, some guidelines must be followed:
./ci-run must complete without errors