Writing Avocado Tests

We are going to write an Avocado test in Python and we are going to inherit from avocado.Test. This makes this test a so-called instrumented test.

Basic example

Let’s re-create an old time favorite, sleeptest [1]. It is so simple, it does nothing besides sleeping for a while:

import time

from avocado import Test

class SleepTest(Test):

    def test(self):
        sleep_length = self.params.get('sleep_length', default=1)
        self.log.debug("Sleeping for %.2f seconds", sleep_length)
        time.sleep(sleep_length)

This is about the simplest test you can write for Avocado, while still leveraging its API power.

What is an Avocado Test

As can be seen in the example above, an Avocado test is a method that starts with test in a class that inherits from avocado.Test.

Multiple tests and naming conventions

You can have multiple tests in a single class.

To do so, just give the methods names that start with test, say test_foo, test_bar and so on. We recommend you follow this naming style, as defined in the PEP8 Function Names section.

For the class name, you can pick any name you like, but we also recommend that it follows the CamelCase convention, also known as CapWords, defined in the PEP 8 document under Class Names.

Convenience Attributes

Note that the test class provides you with a number of convenience attributes:

  • A ready to use log mechanism for your test, that can be accessed by means of self.log. It lets you log debug, info, error and warning messages.
  • A parameter passing system (and fetching system) that can be accessed by means of self.params. This is hooked to the Varianter, about which you can find that more information at Test parameters.
  • And many more (see avocado.core.test.Test)

To minimize the accidental clashes we define the public ones as properties so if you see something like AttributeError: can't set attribute double you are not overriding these.

Test statuses

Avocado supports the most common exit statuses:

  • PASS - test passed, there were no untreated exceptions
  • WARN - a variant of PASS that keeps track of noteworthy events that ultimately do not affect the test outcome. An example could be soft lockup present in the dmesg output. It’s not related to the test results and unless there are failures in the test it means the feature probably works as expected, but there were certain condition which might be nice to review. (some result plugins does not support this and report PASS instead)
  • SKIP - the test’s pre-requisites were not satisfied and the test’s body was not executed (nor its tearDown)
  • FAIL - test did not result in the expected outcome. A failure points at a (possible) bug in the tested subject, and not in the test itself. When the test (and its) execution breaks, an ERROR and not a FAIL is reported.”
  • ERROR - this points (probably) at a bug in the test itself, and not in the subject being tested.It is usually caused by uncaught exception and such failures needs to be thoroughly explored and should lead to test modification to avoid this failure or to use self.fail along with description how the subject under testing failed to perform it’s task.
  • INTERRUPTED - this result can’t be set by the test writer, it is only possible when the timeout is reached or when the user hits CTRL+C while executing this test.
  • other - there are some other internal test statuses, but you should not ever face them.

As you can see the FAIL is a neat status, if tests are developed correctly. When writing tests always think about what its setUp should be, what the test body and is expected to go wrong in the test. To support you Avocado supports several methods:

Test methods

The simplest way to set the status is to use self.fail or self.error directly from test. One can also use self.skip but only from the setUp method.

To remember a warning, one simply writes to self.log.warning logger. This won’t interrupt the test execution, but it will remember the condition and, if there are no failures, will report the test as WARN.

Turning errors into failures

Errors on Python code are commonly signaled in the form of exceptions being thrown. When Avocado runs a test, any unhandled exception will be seen as a test ERROR, and not as a FAIL.

Still, it’s common to rely on libraries, which usually raise custom (or builtin) exceptions. Those exceptions would normally result in ERROR but if you are certain this is an odd behavior of the object under testing, you should catch the exception and explain the failure in self.fail method:

try:
    process.run("stress_my_feature")
except process.CmdError as details:
    self.fail("The stress comamnd failed: %s" % details)

If your test compounds of many executions and you can’t get this exception in other case then expected failure, you can simplify the code by using fail_on decorator:

avocado.fail_on(process.CmdError)
def test(self):
    process.run("first cmd")
    process.run("second cmd")
    process.run("third cmd")

Once again, keeping your tests up-to-date and distinguishing between FAIL and ERROR will save you a lot of time while reviewing the test results.

Saving test generated (custom) data

Each test instance provides a so called whiteboard. It can be accessed through self.whiteboard. This whiteboard is simply a string that will be automatically saved to test results after the test finishes (it’s not synced during the execution so when the machine or python crashes badly it might not be present and one should use direct io to the outputdir for critical data). If you choose to save binary data to the whiteboard, it’s your responsibility to encode it first (base64 is the obvious choice).

Building on the previously demonstrated sleeptest, suppose that you want to save the sleep length to be used by some other script or data analysis tool:

def test(self):
    sleep_length = self.params.get('sleep_length', default=1)
    self.log.debug("Sleeping for %.2f seconds", sleep_length)
    time.sleep(sleep_length)
    self.whiteboard = "%.2f" % sleep_length

The whiteboard can and should be exposed by files generated by the available test result plugins. The results.json file already includes the whiteboard for each test. Additionally, we’ll save a raw copy of the whiteboard contents on a file named whiteboard, in the same level as the results.json file, for your convenience (maybe you want to use the result of a benchmark directly with your custom made scripts to analyze that particular benchmark result).

If you need to attach several output files, you can also use self.outputdir, which points to the $RESULTS/test-results/$TEST_ID/data location and is reserved for arbitrary test result data.

Accessing test parameters

Each test has a set of parameters that can be accessed through self.params.get($name, $path=None, $default=None) where:

  • name - name of the parameter (key)
  • path - where to look for this parameter (when not specified uses mux-path)
  • default - what to return when param not found

The path is a bit tricky. Avocado uses tree to represent parameters. In simple scenarios you don’t need to worry and you’ll find all your values in default path, but eventually you might want to check-out Test parameters to understand the details.

Let’s say your test receives following params (you’ll learn how to execute them in the following section):

$ avocado multiplex -m examples/tests/sleeptenmin.py.data/sleeptenmin.yaml --variants 2
...
Variant 1:    /run/sleeptenmin/builtin, /run/variants/one_cycle
    /run/sleeptenmin/builtin:sleep_method => builtin
    /run/variants/one_cycle:sleep_cycles  => 1
    /run/variants/one_cycle:sleep_length  => 600
...

In test you can access those params by:

.. code-block:: python
self.params.get(“sleep_method”) # returns “builtin” self.params.get(“sleep_cycles”, ‘*’, 10) # returns 1 self.params.get(“sleep_length”, “//variants/” # returns 600

Note

The path is important in complex scenarios where clashes might occur, because when there are multiple values with the same key matching the query avocado raises an exception. As mentioned you can avoid those by using specific paths or by defining custom mux-path which allows specifying resolving hierarchy. More details can be found in Test parameters.

Running multiple variants of tests

In previous section we describe the params handling so let’s have a look on how to produce them and execute your tests with different params.

The variants system is pluggable so you might use custom plugins to produce and feed avocado with your params, but let’s start with the plugin called “yaml_to_mux”, which is shipped with avocado by default. It accepts yaml or even json files where using ordered dicts to create a tree-like structure and storing the non-dict variables as parameters and using custom tags to mark locations as multiplex domains. Let’s use examples/tests/sleeptenmin.py.data/sleeptenmin.yaml file as an example:

.. code-block:: yaml
sleeptenmin: !mux
builtin:
sleep_method: builtin
shell:
sleep_method: shell
variants: !mux
one_cycle:
sleep_cycles: 1 sleep_length: 600
six_cycles:
sleep_cycles: 6 sleep_length: 100
one_hundred_cycles:
sleep_cycles: 100 sleep_length: 6
six_hundred_cycles:
sleep_cycles: 600 sleep_length: 1

Which produces following structure and parameters:

$ avocado multiplex -m examples/tests/sleeptenmin.py.data/sleeptenmin.yaml --summary 2 --variants 2
Multiplex tree representation:
 ┗━━ run
      ┣━━ sleeptenmin
      ┃    ╠══ builtin
      ┃    ║     → sleep_method: builtin
      ┃    ╚══ shell
      ┃          → sleep_method: shell
      ┗━━ variants
           ╠══ one_cycle
           ║     → sleep_length: 600
           ║     → sleep_cycles: 1
           ╠══ six_cycles
           ║     → sleep_length: 100
           ║     → sleep_cycles: 6
           ╠══ one_hundred_cycles
           ║     → sleep_length: 6
           ║     → sleep_cycles: 100
           ╚══ six_hundred_cycles
                 → sleep_length: 1
                 → sleep_cycles: 600

Multiplex variants:

Variant 1:    /run/sleeptenmin/builtin, /run/variants/one_cycle
    /run/sleeptenmin/builtin:sleep_method => builtin
    /run/variants/one_cycle:sleep_cycles  => 1
    /run/variants/one_cycle:sleep_length  => 600

Variant 2:    /run/sleeptenmin/builtin, /run/variants/six_cycles
    /run/sleeptenmin/builtin:sleep_method => builtin
    /run/variants/six_cycles:sleep_cycles => 6
    /run/variants/six_cycles:sleep_length => 100

Variant 3:    /run/sleeptenmin/builtin, /run/variants/one_hundred_cycles
    /run/sleeptenmin/builtin:sleep_method         => builtin
    /run/variants/one_hundred_cycles:sleep_cycles => 100
    /run/variants/one_hundred_cycles:sleep_length => 6

Variant 4:    /run/sleeptenmin/builtin, /run/variants/six_hundred_cycles
    /run/sleeptenmin/builtin:sleep_method         => builtin
    /run/variants/six_hundred_cycles:sleep_cycles => 600
    /run/variants/six_hundred_cycles:sleep_length => 1

Variant 5:    /run/sleeptenmin/shell, /run/variants/one_cycle
    /run/sleeptenmin/shell:sleep_method  => shell
    /run/variants/one_cycle:sleep_cycles => 1
    /run/variants/one_cycle:sleep_length => 600

Variant 6:    /run/sleeptenmin/shell, /run/variants/six_cycles
    /run/sleeptenmin/shell:sleep_method   => shell
    /run/variants/six_cycles:sleep_cycles => 6
    /run/variants/six_cycles:sleep_length => 100

Variant 7:    /run/sleeptenmin/shell, /run/variants/one_hundred_cycles
    /run/sleeptenmin/shell:sleep_method           => shell
    /run/variants/one_hundred_cycles:sleep_cycles => 100
    /run/variants/one_hundred_cycles:sleep_length => 6

Variant 8:    /run/sleeptenmin/shell, /run/variants/six_hundred_cycles
    /run/sleeptenmin/shell:sleep_method           => shell
    /run/variants/six_hundred_cycles:sleep_cycles => 600
    /run/variants/six_hundred_cycles:sleep_length => 1

You can see that it creates all possible variants of each multiplex domain, which are defined by !mux tag in the yaml file and displayed as single lines in tree view (compare to double lines which are individual nodes with values). In total it’ll produce 8 variants of each test:

$ avocado run --mux-yaml examples/tests/sleeptenmin.py.data/sleeptenmin.yaml -- passtest.py
JOB ID     : cc7ef22654c683b73174af6f97bc385da5a0f02f
JOB LOG    : /home/medic/avocado/job-results/job-2017-01-22T11.26-cc7ef22/job.log
 (1/8) passtest.py:PassTest.test;1: PASS (0.01 s)
 (2/8) passtest.py:PassTest.test;2: PASS (0.01 s)
 (3/8) passtest.py:PassTest.test;3: PASS (0.01 s)
 (4/8) passtest.py:PassTest.test;4: PASS (0.01 s)
 (5/8) passtest.py:PassTest.test;5: PASS (0.01 s)
 (6/8) passtest.py:PassTest.test;6: PASS (0.01 s)
 (7/8) passtest.py:PassTest.test;7: PASS (0.01 s)
 (8/8) passtest.py:PassTest.test;8: PASS (0.01 s)
RESULTS    : PASS 8 | ERROR 0 | FAIL 0 | SKIP 0 | WARN 0 | INTERRUPT 0
TESTS TIME : 0.06 s

There are other options to influence the params so please check out avocado run -h and for details use Test parameters.

Advanced logging capabilities

Avocado provides advanced logging capabilities at test run time. These can be combined with the standard Python library APIs on tests.

One common example is the need to follow specific progress on longer or more complex tests. Let’s look at a very simple test example, but one multiple clear stages on a single test:

import logging
import time

from avocado import Test

progress_log = logging.getLogger("progress")

class Plant(Test):

    def test_plant_organic(self):
        rows = self.params.get("rows", default=3)

        # Preparing soil
        for row in range(rows):
            progress_log.info("%s: preparing soil on row %s",
                              self.name, row)

        # Letting soil rest
        progress_log.info("%s: letting soil rest before throwing seeds",
                          self.name)
        time.sleep(2)

        # Throwing seeds
        for row in range(rows):
            progress_log.info("%s: throwing seeds on row %s",
                              self.name, row)

        # Let them grow
        progress_log.info("%s: waiting for Avocados to grow",
                          self.name)
        time.sleep(5)

        # Harvest them
        for row in range(rows):
            progress_log.info("%s: harvesting organic avocados on row %s",
                              self.name, row)

From this point on, you can ask Avocado to show your logging stream, either exclusively or in addition to other builtin streams:

$ avocado --show app,progress run plant.py

The outcome should be similar to:

JOB ID     : af786f86db530bff26cd6a92c36e99bedcdca95b
JOB LOG    : /home/cleber/avocado/job-results/job-2016-03-18T10.29-af786f8/job.log
 (1/1) plant.py:Plant.test_plant_organic: progress: 1-plant.py:Plant.test_plant_organic: preparing soil on row 0
progress: 1-plant.py:Plant.test_plant_organic: preparing soil on row 1
progress: 1-plant.py:Plant.test_plant_organic: preparing soil on row 2
progress: 1-plant.py:Plant.test_plant_organic: letting soil rest before throwing seeds
-progress: 1-plant.py:Plant.test_plant_organic: throwing seeds on row 0
progress: 1-plant.py:Plant.test_plant_organic: throwing seeds on row 1
progress: 1-plant.py:Plant.test_plant_organic: throwing seeds on row 2
progress: 1-plant.py:Plant.test_plant_organic: waiting for Avocados to grow
\progress: 1-plant.py:Plant.test_plant_organic: harvesting organic avocados on row 0
progress: 1-plant.py:Plant.test_plant_organic: harvesting organic avocados on row 1
progress: 1-plant.py:Plant.test_plant_organic: harvesting organic avocados on row 2
PASS (7.01 s)
RESULTS    : PASS 1 | ERROR 0 | FAIL 0 | SKIP 0 | WARN 0 | INTERRUPT 0
TESTS TIME : 7.01 s
JOB HTML   : /home/cleber/avocado/job-results/job-2016-03-18T10.29-af786f8/html/results.html

The custom progress stream is combined with the application output, which may or may not suit your needs or preferences. If you want the progress stream to be sent to a separate file, both for clarity and for persistence, you can run Avocado like this:

$ avocado run plant.py --store-logging-stream progress

The result is that, besides all the other log files commonly generated, there will be another log file named progress.INFO at the job results dir. During the test run, one could watch the progress with:

$ tail -f ~/avocado/job-results/latest/progress.INFO
10:36:59 INFO | 1-plant.py:Plant.test_plant_organic: preparing soil on row 0
10:36:59 INFO | 1-plant.py:Plant.test_plant_organic: preparing soil on row 1
10:36:59 INFO | 1-plant.py:Plant.test_plant_organic: preparing soil on row 2
10:36:59 INFO | 1-plant.py:Plant.test_plant_organic: letting soil rest before throwing seeds
10:37:01 INFO | 1-plant.py:Plant.test_plant_organic: throwing seeds on row 0
10:37:01 INFO | 1-plant.py:Plant.test_plant_organic: throwing seeds on row 1
10:37:01 INFO | 1-plant.py:Plant.test_plant_organic: throwing seeds on row 2
10:37:01 INFO | 1-plant.py:Plant.test_plant_organic: waiting for Avocados to grow
10:37:06 INFO | 1-plant.py:Plant.test_plant_organic: harvesting organic avocados on row 0
10:37:06 INFO | 1-plant.py:Plant.test_plant_organic: harvesting organic avocados on row 1
10:37:06 INFO | 1-plant.py:Plant.test_plant_organic: harvesting organic avocados on row 2

The very same progress logger, could be used across multiple test methods and across multiple test modules. In the example given, the test name is used to give extra context.

unittest.TestCase heritage

Since an Avocado test inherits from unittest.TestCase, you can use all the assertion methods that its parent.

The code example bellow uses assertEqual, assertTrue and assertIsInstace:

from avocado import Test

class RandomExamples(Test):
    def test(self):
        self.log.debug("Verifying some random math...")
        four = 2 * 2
        four_ = 2 + 2
        self.assertEqual(four, four_, "something is very wrong here!")

        self.log.debug("Verifying if a variable is set to True...")
        variable = True
        self.assertTrue(variable)

        self.log.debug("Verifying if this test is an instance of test.Test")
        self.assertIsInstance(self, test.Test)

Running tests under other unittest runners

nose is another Python testing framework that is also compatible with unittest.

Because of that, you can run avocado tests with the nosetests application:

$ nosetests examples/tests/sleeptest.py
.
----------------------------------------------------------------------
Ran 1 test in 1.004s

OK

Conversely, you can also use the standard unittest.main() entry point to run an Avocado test. Check out the following code, to be saved as dummy.py:

from avocado import Test
from unittest import main

class Dummy(Test):
    def test(self):
        self.assertTrue(True)

if __name__ == '__main__':
    main()

It can be run by:

$ python dummy.py
.
----------------------------------------------------------------------
Ran 1 test in 0.000s

OK

But we’d still recommend using avocado.main instead which is our main entry point.

Setup and cleanup methods

If you need to perform setup actions before/after your test, you may do so in the setUp and tearDown methods, respectively. We’ll give examples in the following section.

Running third party test suites

It is very common in test automation workloads to use test suites developed by third parties. By wrapping the execution code inside an Avocado test module, you gain access to the facilities and API provided by the framework. Let’s say you want to pick up a test suite written in C that it is in a tarball, uncompress it, compile the suite code, and then executing the test. Here’s an example that does that:

#!/usr/bin/env python

import os

from avocado import Test
from avocado import main
from avocado.utils import archive
from avocado.utils import build
from avocado.utils import process


class SyncTest(Test):

    """
    Execute the synctest test suite.
    """
    def setUp(self):
        """
        Set default params and build the synctest suite.
        """
        sync_tarball = self.params.get('sync_tarball',
                                       default='synctest.tar.bz2')
        self.sync_length = self.params.get('sync_length', default=100)
        self.sync_loop = self.params.get('sync_loop', default=10)
        # Build the synctest suite
        self.cwd = os.getcwd()
        tarball_path = os.path.join(self.datadir, sync_tarball)
        archive.extract(tarball_path, self.srcdir)
        self.srcdir = os.path.join(self.srcdir, 'synctest')
        build.make(self.srcdir)

    def test(self):
        """
        Execute synctest with the appropriate params.
        """
        os.chdir(self.srcdir)
        cmd = ('./synctest %s %s' %
               (self.sync_length, self.sync_loop))
        process.system(cmd)
        os.chdir(self.cwd)


if __name__ == "__main__":
    main()

Here we have an example of the setUp method in action: Here we get the location of the test suite code (tarball) through avocado.Test.datadir(), then uncompress the tarball through avocado.utils.archive.extract(), an API that will decompress the suite tarball, followed by avocado.utils.build.make(), that will build the suite.

In this example, the test method just gets into the base directory of the compiled suite and executes the ./synctest command, with appropriate parameters, using avocado.utils.process.system().

Fetching asset files

To run third party test suites as mentioned above, or for any other purpose, we offer an asset fetcher as a method of Avocado Test class. The asset method looks for a list of directories in the cache_dirs key, inside the [datadir.paths] section from the configuration files. Read-only directories are also supported. When the asset file is not present in any of the provided directories, we will try to download the file from the provided locations, copying it to the first writable cache directory. Example:

cache_dirs = ['/usr/local/src/', '~/avocado/cache']

In the example above, /usr/local/src/ is a read-only directory. In that case, when we need to fetch the asset from the locations, it will be copied to the ~/avocado/cache directory.

If you don’t provide a cache_dirs, we will create a cache directory inside the avocado data_dir location to put the fetched files in.

  • Use case 1: no cache_dirs key in config files, only the asset name provided in the full url format:

    ...
        def setUp(self):
            stress = 'http://people.seas.harvard.edu/~apw/stress/stress-1.0.4.tar.gz'
            tarball = self.fetch_asset(stress)
            archive.extract(tarball, self.srcdir)
    ...
    

    In this case, fetch_asset() will download the file from the url provided, copying it to the $data_dir/cache directory. tarball variable will contains, for example, /home/user/avocado/data/cache/stress-1.0.4.tar.gz.

  • Use case 2: Read-only cache directory provided. cache_dirs = ['/mnt/files']:

    ...
        def setUp(self):
            stress = 'http://people.seas.harvard.edu/~apw/stress/stress-1.0.4.tar.gz'
            tarball = self.fetch_asset(stress)
            archive.extract(tarball, self.srcdir)
    ...
    

    In this case, we try to find stress-1.0.4.tar.gz file in /mnt/files directory. If it’s not there, since /mnt/files is read-only, we will try to download the asset file to the $data_dir/cache directory.

  • Use case 3: Writable cache directory provided, along with a list of locations. cache_dirs = ['~/avocado/cache']:

    ...
        def setUp(self):
            st_name = 'stress-1.0.4.tar.gz'
            st_hash = 'e1533bc704928ba6e26a362452e6db8fd58b1f0b'
            st_loc = ['http://people.seas.harvard.edu/~apw/stress/stress-1.0.4.tar.gz',
                      'ftp://foo.bar/stress-1.0.4.tar.gz']
            tarball = self.fetch_asset(st_name, asset_hash=st_hash,
                                       locations=st_loc)
            archive.extract(tarball, self.srcdir)
    ...
    

    In this case, we try to download stress-1.0.4.tar.gz from the provided locations list (if it’s not already in ~/avocado/cache). The hash was also provided, so we will verify the hash. To do so, we first look for a hashfile named stress-1.0.4.tar.gz.sha1 in the same directory. If the hashfile is not present we compute the hash and create the hashfile for further usage.

    The resulting tarball variable content will be ~/avocado/cache/stress-1.0.4.tar.gz. An exception will take place if we fail to download or to verify the file.

Detailing the fetch_asset() attributes:

  • name: The name used to name the fetched file. It can also contains a full URL, that will be used as the first location to try (after serching into the cache directories).
  • asset_hash: (optional) The expected file hash. If missing, we skip the check. If provided, before computing the hash, we look for a hashfile to verify the asset. If the hashfile is nor present, we compute the hash and create the hashfile in the same cache directory for further usage.
  • algorithm: (optional) Provided hash algorithm format. Defaults to sha1.
  • locations: (optional) List of locations that will be used to try to fetch the file from. The supported schemes are http://, https://, ftp:// and file://. You’re required to inform the full url to the file, including the file name. The first success will skip the next locations. Notice that for file:// we just create a symbolic link in the cache directory, pointing to the file original location.
  • expire: (optional) time period that the cached file will be considered valid. After that period, the file will be dowloaded again. The value can be an integer or a string containing the time and the unit. Example: ‘10d’ (ten days). Valid units are s (second), m (minute), h (hour) and d (day).

The expected return is the asset file path or an exception.

Test Output Check and Output Record Mode

In a lot of occasions, you want to go simpler: just check if the output of a given application matches an expected output. In order to help with this common use case, we offer the option --output-check-record [mode] to the test runner:

--output-check-record OUTPUT_CHECK_RECORD
                      Record output streams of your tests to reference files
                      (valid options: none (do not record output streams),
                      all (record both stdout and stderr), stdout (record
                      only stderr), stderr (record only stderr). Default:
                      none

If this option is used, it will store the stdout or stderr of the process (or both, if you specified all) being executed to reference files: stdout.expected and stderr.expected. Those files will be recorded in the test data dir. The data dir is in the same directory as the test source file, named [source_file_name.data]. Let’s take as an example the test synctest.py. In a fresh checkout of Avocado, you can see:

examples/tests/synctest.py.data/stderr.expected
examples/tests/synctest.py.data/stdout.expected

From those 2 files, only stdout.expected is non empty:

$ cat examples/tests/synctest.py.data/stdout.expected
PAR : waiting
PASS : sync interrupted

The output files were originally obtained using the test runner and passing the option –output-check-record all to the test runner:

$ scripts/avocado run --output-check-record all synctest.py
JOB ID    : bcd05e4fd33e068b159045652da9eb7448802be5
JOB LOG   : $HOME/avocado/job-results/job-2014-09-25T20.20-bcd05e4/job.log
 (1/1) synctest.py:SyncTest.test: PASS (2.20 s)
RESULTS    : PASS 1 | ERROR 0 | FAIL 0 | SKIP 0 | WARN 0 | INTERRUPT 0
TESTS TIME : 2.20 s

After the reference files are added, the check process is transparent, in the sense that you do not need to provide special flags to the test runner. Now, every time the test is executed, after it is done running, it will check if the outputs are exactly right before considering the test as PASSed. If you want to override the default behavior and skip output check entirely, you may provide the flag --output-check=off to the test runner.

The avocado.utils.process APIs have a parameter allow_output_check (defaults to all), so that you can select which process outputs will go to the reference files, should you chose to record them. You may choose all, for both stdout and stderr, stdout, for the stdout only, stderr, for only the stderr only, or none, to allow neither of them to be recorded and checked.

This process works fine also with simple tests, which are programs or shell scripts that returns 0 (PASSed) or != 0 (FAILed). Let’s consider our bogus example:

$ cat output_record.sh
#!/bin/bash
echo "Hello, world!"

Let’s record the output for this one:

$ scripts/avocado run output_record.sh --output-check-record all
JOB ID    : 25c4244dda71d0570b7f849319cd71fe1722be8b
JOB LOG   : $HOME/avocado/job-results/job-2014-09-25T20.49-25c4244/job.log
 (1/1) output_record.sh: PASS (0.01 s)
RESULTS    : PASS 1 | ERROR 0 | FAIL 0 | SKIP 0 | WARN 0 | INTERRUPT 0
TESTS TIME : 0.01 s

After this is done, you’ll notice that a the test data directory appeared in the same level of our shell script, containing 2 files:

$ ls output_record.sh.data/
stderr.expected  stdout.expected

Let’s look what’s in each of them:

$ cat output_record.sh.data/stdout.expected
Hello, world!
$ cat output_record.sh.data/stderr.expected
$

Now, every time this test runs, it’ll take into account the expected files that were recorded, no need to do anything else but run the test. Let’s see what happens if we change the stdout.expected file contents to Hello, Avocado!:

$ scripts/avocado run output_record.sh
JOB ID    : f0521e524face93019d7cb99c5765aedd933cb2e
JOB LOG   : $HOME/avocado/job-results/job-2014-09-25T20.52-f0521e5/job.log
 (1/1) output_record.sh: FAIL (0.02 s)
RESULTS    : PASS 0 | ERROR 0 | FAIL 1 | SKIP 0 | WARN 0 | INTERRUPT 0
TESTS TIME : 0.02 s

Verifying the failure reason:

$ cat $HOME/avocado/job-results/job-2014-09-25T20.52-f0521e5/job.log
20:52:38 test       L0163 INFO | START 1-output_record.sh
20:52:38 test       L0164 DEBUG|
20:52:38 test       L0165 DEBUG| Test instance parameters:
20:52:38 test       L0173 DEBUG|
20:52:38 test       L0176 DEBUG| Default parameters:
20:52:38 test       L0180 DEBUG|
20:52:38 test       L0181 DEBUG| Test instance params override defaults whenever available
20:52:38 test       L0182 DEBUG|
20:52:38 process    L0242 INFO | Running '$HOME/Code/avocado/output_record.sh'
20:52:38 process    L0310 DEBUG| [stdout] Hello, world!
20:52:38 test       L0565 INFO | Command: $HOME/Code/avocado/output_record.sh
20:52:38 test       L0565 INFO | Exit status: 0
20:52:38 test       L0565 INFO | Duration: 0.00313782691956
20:52:38 test       L0565 INFO | Stdout:
20:52:38 test       L0565 INFO | Hello, world!
20:52:38 test       L0565 INFO |
20:52:38 test       L0565 INFO | Stderr:
20:52:38 test       L0565 INFO |
20:52:38 test       L0060 ERROR|
20:52:38 test       L0063 ERROR| Traceback (most recent call last):
20:52:38 test       L0063 ERROR|   File "$HOME/Code/avocado/avocado/test.py", line 397, in check_reference_stdout
20:52:38 test       L0063 ERROR|     self.assertEqual(expected, actual, msg)
20:52:38 test       L0063 ERROR|   File "/usr/lib64/python2.7/unittest/case.py", line 551, in assertEqual
20:52:38 test       L0063 ERROR|     assertion_func(first, second, msg=msg)
20:52:38 test       L0063 ERROR|   File "/usr/lib64/python2.7/unittest/case.py", line 544, in _baseAssertEqual
20:52:38 test       L0063 ERROR|     raise self.failureException(msg)
20:52:38 test       L0063 ERROR| AssertionError: Actual test sdtout differs from expected one:
20:52:38 test       L0063 ERROR| Actual:
20:52:38 test       L0063 ERROR| Hello, world!
20:52:38 test       L0063 ERROR|
20:52:38 test       L0063 ERROR| Expected:
20:52:38 test       L0063 ERROR| Hello, Avocado!
20:52:38 test       L0063 ERROR|
20:52:38 test       L0064 ERROR|
20:52:38 test       L0529 ERROR| FAIL 1-output_record.sh -> AssertionError: Actual test sdtout differs from expected one:
Actual:
Hello, world!

Expected:
Hello, Avocado!

20:52:38 test       L0516 INFO |

As expected, the test failed because we changed its expectations.

Test log, stdout and stderr in native Avocado modules

If needed, you can write directly to the expected stdout and stderr files from the native test scope. It is important to make the distinction between the following entities:

  • The test logs
  • The test expected stdout
  • The test expected stderr

The first one is used for debugging and informational purposes. Additionally writing to self.log.warning causes test to be marked as dirty and when everything else goes well the test ends with WARN. This means that the test passed but there were non-related unexpected situations described in warning log.

You may log something into the test logs using the methods in avocado.Test.log class attributes. Consider the example:

class output_test(Test):

    def test(self):
        self.log.info('This goes to the log and it is only informational')
        self.log.warn('Oh, something unexpected, non-critical happened, '
                      'but we can continue.')
        self.log.error('Describe the error here and don't forget to raise '
                       'an exception yourself. Writing to self.log.error '
                       'won't do that for you.')
        self.log.debug('Everybody look, I had a good lunch today...')

If you need to write directly to the test stdout and stderr streams, Avocado makes two preconfigured loggers available for that purpose, named avocado.test.stdout and avocado.test.stderr. You can use Python’s standard logging API to write to them. Example:

import logging

class output_test(Test):

    def test(self):
        stdout = logging.getLogger('avocado.test.stdout')
        stdout.info('Informational line that will go to stdout')
        ...
        stderr = logging.getLogger('avocado.test.stderr')
        stderr.info('Informational line that will go to stderr')

Avocado will automatically save anything a test generates on STDOUT into a stdout file, to be found at the test results directory. The same applies to anything a test generates on STDERR, that is, it will be saved into a stderr file at the same location.

Additionally, when using the runner’s output recording features, namely the --output-check-record argument with values stdout, stderr or all, everything given to those loggers will be saved to the files stdout.expected and stderr.expected at the test’s data directory (which is different from the job/test results directory).

Setting a Test Timeout

Sometimes your test suite/test might get stuck forever, and this might impact your test grid. You can account for that possibility and set up a timeout parameter for your test. The test timeout can be set through the multiplex, as shown below.

sleep_length: 5
timeout: 3
$ avocado run sleeptest.py --mux-yaml /tmp/sleeptest-example.yaml
JOB ID     : c78464bde9072a0b5601157989a99f0ba32a288e
JOB LOG    : $HOME/avocado/job-results/job-2016-11-02T11.13-c78464b/job.log
 (1/1) sleeptest.py:SleepTest.test: INTERRUPTED (3.04 s)
RESULTS    : PASS 0 | ERROR 0 | FAIL 0 | SKIP 0 | WARN 0 | INTERRUPT 1
TESTS TIME : 3.04 s
JOB HTML   : $HOME/avocado/job-results/job-2016-11-02T11.13-c78464b/html/results.html
$ cat $HOME/avocado/job-results/job-2016-11-02T11.13-c78464b/job.log
2016-11-02 11:13:01,133 job              L0384 INFO | Multiplex tree representation:
2016-11-02 11:13:01,133 job              L0386 INFO |  \-- run
2016-11-02 11:13:01,133 job              L0386 INFO |         -> sleep_length: 5
2016-11-02 11:13:01,133 job              L0386 INFO |         -> timeout: 3
2016-11-02 11:13:01,133 job              L0387 INFO |
2016-11-02 11:13:01,134 job              L0391 INFO | Temporary dir: /var/tmp/avocado_PqDEyC
2016-11-02 11:13:01,134 job              L0392 INFO |
2016-11-02 11:13:01,134 job              L0399 INFO | Variant 1:    /run
2016-11-02 11:13:01,134 job              L0402 INFO |
2016-11-02 11:13:01,134 job              L0311 INFO | Job ID: c78464bde9072a0b5601157989a99f0ba32a288e
2016-11-02 11:13:01,134 job              L0314 INFO |
2016-11-02 11:13:01,345 sysinfo          L0107 DEBUG| Not logging /proc/pci (file does not exist)
2016-11-02 11:13:01,351 sysinfo          L0105 DEBUG| Not logging /proc/slabinfo (lack of permissions)
2016-11-02 11:13:01,355 sysinfo          L0107 DEBUG| Not logging /sys/kernel/debug/sched_features (file does not exist)
2016-11-02 11:13:01,388 sysinfo          L0388 INFO | Commands configured by file: /etc/avocado/sysinfo/commands
2016-11-02 11:13:01,388 sysinfo          L0399 INFO | Files configured by file: /etc/avocado/sysinfo/files
2016-11-02 11:13:01,388 sysinfo          L0419 INFO | Profilers configured by file: /etc/avocado/sysinfo/profilers
2016-11-02 11:13:01,388 sysinfo          L0427 INFO | Profiler disabled
2016-11-02 11:13:01,394 multiplexer      L0166 DEBUG| PARAMS (key=timeout, path=*, default=None) => 3
2016-11-02 11:13:01,395 test             L0216 INFO | START 1-sleeptest.py:SleepTest.test
2016-11-02 11:13:01,396 multiplexer      L0166 DEBUG| PARAMS (key=sleep_length, path=*, default=1) => 5
2016-11-02 11:13:01,396 sleeptest        L0022 DEBUG| Sleeping for 5.00 seconds
2016-11-02 11:13:04,411 stacktrace       L0038 ERROR|
2016-11-02 11:13:04,412 stacktrace       L0041 ERROR| Reproduced traceback from: $HOME/src/avocado/avocado/core/test.py:454
2016-11-02 11:13:04,412 stacktrace       L0044 ERROR| Traceback (most recent call last):
2016-11-02 11:13:04,413 stacktrace       L0044 ERROR|   File "/usr/share/avocado/tests/sleeptest.py", line 23, in test
2016-11-02 11:13:04,413 stacktrace       L0044 ERROR|     time.sleep(sleep_length)
2016-11-02 11:13:04,413 stacktrace       L0044 ERROR|   File "$HOME/src/avocado/avocado/core/runner.py", line 293, in sigterm_handler
2016-11-02 11:13:04,413 stacktrace       L0044 ERROR|     raise SystemExit("Test interrupted by SIGTERM")
2016-11-02 11:13:04,414 stacktrace       L0044 ERROR| SystemExit: Test interrupted by SIGTERM
2016-11-02 11:13:04,414 stacktrace       L0045 ERROR|
2016-11-02 11:13:04,414 test             L0459 DEBUG| Local variables:
2016-11-02 11:13:04,440 test             L0462 DEBUG|  -> self <class 'sleeptest.SleepTest'>: 1-sleeptest.py:SleepTest.test
2016-11-02 11:13:04,440 test             L0462 DEBUG|  -> sleep_length <type 'int'>: 5
2016-11-02 11:13:04,440 test             L0592 ERROR| ERROR 1-sleeptest.py:SleepTest.test -> TestError: SystemExit('Test interrupted by SIGTERM',): Test interrupted by SIGTERM

If you pass that multiplex file to the runner multiplexer, this will register a timeout of 3 seconds before Avocado ends the test forcefully by sending a signal.SIGTERM to the test, making it raise a avocado.core.exceptions.TestTimeoutError.

Skipping Tests

Avocado offers some options for the test writers to skip a test:

Test skip() Method

Using the skip() method available in the Test API is only allowed inside the setUp() method. Calling skip() from inside the test is not allowed as, by concept, you cannot skip a test after it’s already initiated.

The test below:

import avocado

class MyTestClass(avocado.Test):

    def setUp(self):
        if self.check_condition():
            self.skip('Test skipped due to the condition.')

    def test(self):
        pass

    def check_condition(self):
        return True

Will produce the following result:

$ avocado run test_skip_method.py
JOB ID     : 1bd8642400e3b6c584979504cafc4318f7a5fb65
JOB LOG    : $HOME/avocado/job-results/job-2017-02-03T17.16-1bd8642/job.log
 (1/1) test_skip_method.py:MyTestClass.test: SKIP
RESULTS    : PASS 0 | ERROR 0 | FAIL 0 | SKIP 1 | WARN 0 | INTERRUPT 0
TESTS TIME : 0.00 s
JOB HTML   : $HOME/avocado/job-results/job-2017-02-03T17.16-1bd8642/html/results.html

Avocado Skip Decorators

Another way to skip tests is by using the Avocado skip decorators:

  • @avocado.skip(reason): Skips a test.
  • @avocado.skipIf(condition, reason): Skips a test if the condition is True.
  • @avocado.skipUnless(condition, reason): Skips a test if the condition is False

Those decorators can be used with both setUp() method and/or and in the test*() methods. The test below:

import avocado

class MyTest(avocado.Test):

    @avocado.skipIf(1 == 1, 'Skipping on True condition.')
    def test1(self):
        pass

    @avocado.skip("Don't want this test now.")
    def test2(self):
        pass

    @avocado.skipUnless(1 == 1, 'Skipping on False condition.')
    def test3(self):
        pass

Will produce the following result:

$ avocado run  test_skip_decorators.py
JOB ID     : 59c815f6a42269daeaf1e5b93e52269fb8a78119
JOB LOG    : $HOME/avocado/job-results/job-2017-02-03T17.41-59c815f/job.log
 (1/3) test_skip_decorators.py:MyTest.test1: SKIP
 (2/3) test_skip_decorators.py:MyTest.test2: SKIP
 (3/3) test_skip_decorators.py:MyTest.test3: PASS (0.02 s)
RESULTS    : PASS 1 | ERROR 0 | FAIL 0 | SKIP 2 | WARN 0 | INTERRUPT 0
TESTS TIME : 0.03 s
JOB HTML   : $HOME/avocado/job-results/job-2017-02-03T17.41-59c815f/html/results.html

Notice the test3 was not skipped because the provided condition was not False.

Docstring Directives

Some Avocado features, usually only available to instrumented tests, depend on setting directives on the test’s class docstring. The standard prefix used is :avocado: followed by the directive itself, such as :avocado: directive.

This is similar to docstring directives such as :param my_param: description and shouldn’t be a surprise to most Python developers.

The reason Avocado uses those docstring directives (instead of real Python code) is that the inspection done while looking for tests does not involve any execution of code.

Now let’s follow with some docstring directives examples.

Explicitly enabling or disabling tests

If your test is a method in a class that directly inherits from avocado.Test, then Avocado will find it as one would expect.

Now, the need may arise for more complex tests, to use more advanced Python features such as inheritance. For those tests that are written in a class not directly inherting from avocado.Test, Avocado may need your help, because Avocado uses only static analysis to examine the files.

For example, suppose that you define a new test class that inherits from the Avocado base test class, that is, avocado.Test, and put it in mylibrary.py:

from avocado import Test


class MyOwnDerivedTest(Test):
    def __init__(self, methodName='test', name=None, params=None,
                 base_logdir=None, job=None, runner_queue=None):
        super(MyOwnDerivedTest, self).__init__(methodName, name, params,
                                               base_logdir, job,
                                               runner_queue)
        self.log('Derived class example')

Then you implement your actual test using that derived class, in mytest.py:

import mylibrary


class MyTest(mylibrary.MyOwnDerivedTest):

    def test1(self):
        self.log('Testing something important')

    def test2(self):
        self.log('Testing something even more important')

If you try to list the tests in that file, this is what you’ll get:

scripts/avocado list mytest.py -V
Type       Test
NOT_A_TEST mytest.py

ACCESS_DENIED: 0
BROKEN_SYMLINK: 0
EXTERNAL: 0
FILTERED: 0
INSTRUMENTED: 0
MISSING: 0
NOT_A_TEST: 1
SIMPLE: 0
VT: 0

You need to give avocado a little help by adding a docstring directive. That docstring directive is :avocado: enable. It tells the Avocado safe test detection code to consider it as an avocado test, regardless of what the (admittedly simple) detection code thinks of it. Let’s see how that works out. Add the docstring, as you can see the example below:

import mylibrary


class MyTest(mylibrary.MyOwnDerivedTest):
    """
    :avocado: enable
    """
    def test1(self):
        self.log('Testing something important')

    def test2(self):
        self.log('Testing something even more important')

Now, trying to list the tests on the mytest.py file again:

scripts/avocado list mytest.py -V
Type         Test
INSTRUMENTED mytest.py:MyTest.test1
INSTRUMENTED mytest.py:MyTest.test2

ACCESS_DENIED: 0
BROKEN_SYMLINK: 0
EXTERNAL: 0
FILTERED: 0
INSTRUMENTED: 2
MISSING: 0
NOT_A_TEST: 0
SIMPLE: 0
VT: 0

You can also use the :avocado: disable docstring directive, that works the opposite way: something that would be considered an Avocado test, but we force it to not be listed as one.

Categorizing tests

Avocado allows tests to be given tags, which can be used to create test categories. With tags set, users can select a subset of the tests found by the test resolver (also known as test loader).

To make this feature easier to grasp, let’s work with an example: a single Python source code file, named perf.py, that contains both disk and network performance tests:

from avocado import Test

class Disk(Test):

    """
    Disk performance tests

    :avocado: tags=disk,slow,superuser,unsafe
    """

    def test_device(self):
        device = self.params.get('device', default='/dev/vdb')
        self.whiteboard = measure_write_to_disk(device)


class Network(Test):

    """
    Network performance tests

    :avocado: tags=net,fast,safe
    """

    def test_latency(self):
        self.whiteboard = measure_latency()

    def test_throughput(self):
        self.whiteboard = measure_throughput()


class Idle(Test):

    """
    Idle tests
    """

    def test_idle(self):
        self.whiteboard = "test achieved nothing"

Warning

All docstring directives in Avocado require a strict format, that is, :avocado: followed by one or more spaces, and then followed by a single value with no white spaces in between. This means that an attempt to write a docstring directive like :avocado: tags=foo, bar will be interpreted as :avocado: tags=foo,.

Usually, listing and executing tests with the Avocado test runner would reveal all three tests:

$ avocado list perf.py
INSTRUMENTED perf.py:Disk.test_device
INSTRUMENTED perf.py:Network.test_latency
INSTRUMENTED perf.py:Network.test_throughput
INSTRUMENTED perf.py:Idle.test_idle

If you want to list or run only the network based tests, you can do so by requesting only tests that are tagged with net:

$ avocado list perf.py --filter-by-tags=net
INSTRUMENTED perf.py:Network.test_latency
INSTRUMENTED perf.py:Network.test_throughput

Now, suppose you’re not in an environment where you’re confortable running a test that will write to your raw disk devices (such as your development workstation). You know that some tests are tagged with safe while others are tagged with unsafe. To only select the “safe” tests you can run:

$ avocado list perf.py --filter-by-tags=safe
INSTRUMENTED perf.py:Network.test_latency
INSTRUMENTED perf.py:Network.test_throughput

But you could also say that you do not want the “unsafe” tests (note the minus sign before the tag):

$ avocado list perf.py --filter-by-tags=-unsafe
INSTRUMENTED perf.py:Network.test_latency
INSTRUMENTED perf.py:Network.test_throughput

Tip

The - sign may cause issues with some shells. One know error condition is to use spaces between --filter-by-tags and the negated tag, that is, --filter-by-tags -unsafe will most likely not work. To be on the safe side, use --filter-by-tags=-tag.

If you require tests to be tagged with multiple tags, just add them separate by commas. Example:

$ avocado list perf.py --filter-by-tags=disk,slow,superuser,unsafe
INSTRUMENTED perf.py:Disk.test_device

If no test contains all tags given on a single –filter-by-tags parameter, no test will be included:

$ avocado list perf.py --filter-by-tags=disk,slow,superuser,safe | wc -l
0

Multiple –filter-by-tags

While multiple tags in a single option will require tests with all the given tags (effectively a logical AND operation), it’s also possible to use multiple --filter-by-tags (effectively a logical OR operation).

For instance To include all tests that have the disk tag and all tests that have the net tag, you can run:

$ avocado list perf.py --filter-by-tags=disk --filter-by-tags=net
INSTRUMENTED perf.py:Disk.test_device
INSTRUMENTED perf.py:Network.test_latency
INSTRUMENTED perf.py:Network.test_throughput

Including tests without tags

The normal behavior when using –filter-by-tags is to require the given tags on all tests. In some situations, though, it may be desirable to include tests that have no tags set.

For instance, you may want to include tests of certain types that do not have support for tags (such as SIMPLE tests) or tests that have not (yet) received tags. Consider this command:

$ avocado list perf.py /bin/true --filter-by-tags=disk
INSTRUMENTED perf.py:Disk.test_device

Since it requires the disk tag, only one test was returned. By using the –filter-by-tags-include-empty option, you can force the inclusion of tests without tags:

$ avocado list perf.py /bin/true --filter-by-tags=disk --filter-by-tags-include-empty
SIMPLE       /bin/true
INSTRUMENTED perf.py:Idle.test_idle
INSTRUMENTED perf.py:Disk.test_device

Python unittest Compatibility Limitations And Caveats

When executing tests, Avocado uses different techniques than most other Python unittest runners. This brings some compatibility limitations that Avocado users should be aware.

Execution Model

One of the main differences is a consequence of the Avocado design decision that tests should be self contained and isolated from other tests. Additionally, the Avocado test runner runs each test in a separate process.

If you have a unittest class with many test methods and run them using most test runners, you’ll find that all test methods run under the same process. To check that behavior you could add to your setUp method:

def setUp(self):
    print("PID: %s", os.getpid())

If you run the same test under Avocado, you’ll find that each test is run on a separate process.

Class Level setUp and tearDown

Because of Avocado’s test execution model (each test is run on a separate process), it doesn’t make sense to support unittest’s unittest.TestCase.setUpClass() and unittest.TestCase.tearDownClass(). Test classes are freshly instantiated for each test, so it’s pointless to run code in those methods, since they’re supposed to keep class state between tests.

The setUp method is the only place in avocado where you are allowed to call the skip method, given that, if a test started to be executed, by definition it can’t be skipped anymore. Avocado will do its best to enforce this boundary, so that if you use skip outside setUp, the test upon execution will be marked with the ERROR status, and the error message will instruct you to fix your test’s code.

If you require a common setup to a number of tests, the current recommended approach is to to write regular setUp and tearDown code that checks if a given state was already set. One example for such a test that requires a binary installed by a package:

from avocado import Test

from avocado.utils import software_manager
from avocado.utils import path as utils_path
from avocado.utils import process


class BinSleep(Test):

    """
    Sleeps using the /bin/sleep binary
    """
    def setUp(self):
        self.sleep = None
        try:
            self.sleep = utils_path.find_command('sleep')
        except utils_path.CmdNotFoundError:
            software_manager.install_distro_packages({'fedora': ['coreutils']})
            self.sleep = utils_path.find_command('sleep')

    def test(self):
        process.run("%s 1" % self.sleep)

If your test setup is some kind of action that will last accross processes, like the installation of a software package given in the previous example, you’re pretty much covered here.

If you need to keep other type of data a class across test executions, you’ll have to resort to saving and restoring the data from an outside source (say a “pickle” file). Finding and using a reliable and safe location for saving such data is currently not in the Avocado supported use cases.

Environment Variables for Simple Tests

Avocado exports Avocado variables and multiplexed variables as BASH environment to the running test. Those variables are interesting to simple tests, because they can not make use of Avocado API directly with Python, like the native tests can do and also they can modify the test parameters.

Here are the current variables that Avocado exports to the tests:

Environemnt Variable Meaning Example
AVOCADO_VERSION Version of Avocado test runner 0.12.0
AVOCADO_TEST_BASEDIR Base directory of Avocado tests $HOME/Downloads/avocado-source/avocado
AVOCADO_TEST_DATADIR Data directory for the test $AVOCADO_TEST_BASEDIR/my_test.sh.data
AVOCADO_TEST_WORKDIR Work directory for the test /var/tmp/avocado_Bjr_rd/my_test.sh
AVOCADO_TEST_SRCDIR Source directory for the test /var/tmp/avocado_Bjr_rd/my-test.sh/src
AVOCADO_TESTS_COMMON_TMPDIR Temporary directory created by the teststmpdir plugin. The directory is persistent throughout the tests in the same Job /var/tmp/avocado_XhEdo/
AVOCADO_TEST_LOGDIR Log directory for the test $HOME/logs/job-results/job-2014-09-16T14.38-ac332e6/test-results/$HOME/my_test.sh.1
AVOCADO_TEST_LOGFILE Log file for the test $HOME/logs/job-results/job-2014-09-16T14.38-ac332e6/test-results/$HOME/my_test.sh.1/debug.log
AVOCADO_TEST_OUTPUTDIR Output directory for the test $HOME/logs/job-results/job-2014-09-16T14.38-ac332e6/test-results/$HOME/my_test.sh.1/data
AVOCADO_TEST_SYSINFODIR The system information directory $HOME/logs/job-results/job-2014-09-16T14.38-ac332e6/test-results/$HOME/my_test.sh.1/sysinfo
*** All variables from –mux-yaml TIMEOUT=60; IO_WORKERS=10; VM_BYTES=512M; ...

Simple Tests BASH extensions

To enhance simple tests one can use supported set of libraries we created. The only requirement is to use:

PATH=$(avocado "exec-path"):$PATH

which injects path to Avocado utils into shell PATH. Take a look into avocado exec-path to see list of available functions and take a look at examples/tests/simplewarning.sh for inspiration.

Wrap Up

We recommend you take a look at the example tests present in the examples/tests directory, that contains a few samples to take some inspiration from. That directory, besides containing examples, is also used by the Avocado self test suite to do functional testing of Avocado itself.

It is also recommended that you take a look at the API Reference. for more possibilities.

[1]sleeptest is a functional test for Avocado. It’s “old” because we also have had such a test for Autotest for a long time.