This section details the avocado.core.nrunner module, which contains a proposal for the next Avocado test runner implementation.


There are a number of reasons for introducing a different runner architecture and implementation. Some of them are related to limitations found in the current implementation, that were found to be too hard to remove without major breakage. Other reasons are closely related to missing features that are deemed important.

For instance, these are the current limitations of the Avocado test runner:

  • Test execution limited to the same machine, given that the communication between runner and test is a Python queue (the remote runner plugins actually execute an Avocado Job remotely, with all the overhead and complications that it brings)
  • Test execution is limited to a single test at a time (non-parallel)
  • Test processes are not properly isolated and can affect the test runner (including the “UI”)

And these are some features which it’s believed to be more easily implemented under a different architecture and implementation:

  • Remote execution
  • Different test execution isolation models provided by the test runner (process, container, virtual machine)
  • Distributed execution of tests across a pool of any combination of processes, containers, virtual machines, etc.
  • Parallel execution of tests
  • Optimized runners for a given environment and or test type (for instance, a runner written in RUST to run tests written in RUST in an environment that already has RUST installed but not much else)
  • Notification of execution results to many simultaneous “status servers”
  • Disconnected test execution, so that results can be saved to a device and collected by the runner
  • Simplified and automated deployment of the runner component into execution environments such as containers and virtual machines



A runnable is a description of an entity that can be executed and produce some kind of result. It’s a passive entity that can not execute itself and can not produce results itself.

This description of a runnable is abstract on purpose. While the most common use case for a Runnable is to describe how to execute a test, there seems to be no reason to bind that concept to a test. Other Avocado subsystems, such as sysinfo, could very well leverage the same concept to describe say, commands to be executed.

A Runnable’s kind

The most important information about a runnable is the declaration of its kind. A kind should be a globally unique name across the entire Avocado community and users.

When choosing a Runnable kind name, it’s advisable that it should be:

  • Informative
  • Succinct
  • Unique

If a kind is thought to be generally useful to more than one user (where a user may mean a project using Avocado), it’s a good idea to also have a generic name. For instance, if a Runnable is going to describe how to run native tests for the Go programming language, its kind should probably be go.

On the other hand, if a Runnable is going to be used to describe tests that behave in a very peculiar way for a specific project, it’s probably a good idea to map its kind name to the project name. For instance, if one is describing how to run an iotest that is part of the QEMU project, it may be a good idea to name this kind qemu-iotest.

A Runnable’s uri

Besides a kind, each runnable kind may require a different amount of information to be provided so that it can be instantiated.

Based on the accumulated experience so far, it’s expected that a Runnable’s uri is always going to be required. Think of the URI as the one piece of information that can uniquely distinguish the entity (of a given kind) that will be executed.

If, for instance, a given runnable describes the execution of a executable file already present in the system, it may use its path, say /bin/true, as its uri value. If a runnable describes a web service endpoint, its uri value may just as well be its network URI, such as https://example.org:8080.

Runnable examples

Possibly the simplest example for the use of a Runnable is to describe how to run a standalone executable, such as the ones available on your /bin directory.

As stated earlier, a runnable must declare its kind. For standalone executables, a name such as exec fulfills the naming suggestions given earlier.

A Runnable can be created in a number of ways. The first one is through avocado.core.nrunner.Runnable, a very low level (and internal) API. Still, it serves as an example:

>>> from avocado.core import nrunner
>>> runnable = nrunner.Runnable('exec', '/bin/true')
>>> runnable
<Runnable kind="exec" uri="/bin/true" args="()" kwargs="{}" tags="None">

The second way is through a JSON based file, which, for the lack of a better term, we’re calling a (Runnable) “recipe”. The recipe file itself will look like:

{"kind": "exec", "uri": "/bin/true"}

And example the code to create it:

>>> from avocado.core import nrunner
>>> runnable = nrunner.Runnable.from_recipe("/path/to/recipe.json")
>>> runnable
>>> <Runnable kind="exec" uri="/bin/true" args="()" kwargs="{}" tags="None">

The third way to create a Runnable, is even more internal. Its usage is discouraged, unless you are creating a tool that needs to create Runnables based on the user’s input from the command line:

>>> from avocado.core import nrunner
>>> runnable = nrunner.Runnable.from_args({kind: 'exec', uri: '/bin/true'})
>>> runnable
>>> <Runnable kind="exec" uri="/bin/true" args="()" kwargs="{}" tags="None">


A Runner, within the context of the N(ext)Runner architecture, is an active entity that acts on the information that a runnable contains, and quite simply, should be able to run what the Runnable describes.

A Runner will usually be tied to a specific kind of Runnable. That type of relationship (Runner is capable of running kind “foo” and Runnable is of the same kind “foo”) is the expected mechanism that will be employed when selecting a Runner.

A Runner can take different forms, depending on which layer one is interacting with. At the lowest layer, a Runner may be a Python class that inherits from avocado.core.nrunner.BaseRunner, and implements at least a matching constructor method, and a run() method that should yield dictionary(ies) as result(s).

At a different level, a runner can take the form of an executable that follows the avocado-runner-$KIND naming pattern and conforms to a given interface/behavior, including accepting standardized command line arguments and producing standardized output.


for a very basic example of the interface expected, refer to selftests/functional/test_nrunner_interface.py on the Avocado source code tree.

Runner output

A Runner should, if possible, produce status information on the progress of the execution of a Runnable. While the Runner is executing what a Runnable describes, should it produce interesting information, the Runner should attempt to forward that along its generated status.

For instance, using the exec Runner example, it’s helpful to start producing status that the process has been created and it’s running as soon as possible, even if no other output has been produced by the executable itself. These can be as simple as a sequence of:

{"status": "running"}
{"status": "running"}

When the process is finished, the Runner may return:

{"status": "finished", "returncode": 0, 'stdout': b'', 'stderr': b''}


Besides the status of finished, and a return code which can be used to determine a success or failure status, a Runner may not be obliged to determine the overall PASS/FAIL outcome. Whoever called the runner may be responsible to determine its overall result, including a PASS/FAIL judgement.

Even though this level of information is expected to be generated by the Runner, whoever is calling a Runner, should be prepared to receive as little information as possible, and act accordingly. That includes receiving no information at all.

For instance, if a Runner fails to produce any information within a given amount of time, it may be considered faulty and be completely discarded. This would probably end up being represented as a TIMED_OUT kind of status on a higher layer (say at the “Job” layer).


A task is one specific instance/occurrence of the execution of a runnable with its respective runner. They should have a unique identifier, although a task by itself wont’t enforce its uniqueness in a process or any other type of collection.

A task is responsible for producing and reporting status updates. This status updates are in a format similar to those received from a runner, but will add more information to them, such as its unique identifier.

A different agreggate structure should be used to keep track of the execution of tasks.


A recipe is the serialization of the runnable information in a file. The format chosen is JSON, and that should allow both quick and easy machine handling and also manual creation of recipes when necessary.


A runner can be capable of running one or many different kinds of runnables. A runner should implement a capabilities command that returns, among other info, a list of runnable kinds that it can (to the best of its knowledge) run. Example:

python3 -m avocado.core.nrunner capabilities
{'runnables': ['noop', 'exec', 'exec-test', 'python-unittest'],
 'commands': ['capabilities', 'runnable-run', 'runnable-run-recipe',
 'task-run', 'task-run-recipe', 'status-server']}

Runner scripts

The primary runner implementation is a Python module that can be run, as shown before, with the avocado.core.nrunner module name. Additionally it’s also available as the avocado-runner script.

Runner Execution

While the exec runner given as example before will need to create an extra process to actually run the standalone executable given, that is an implementation detail of that specific runner. Other types of runners may be able to run the code the users expects it to run, while still providing feedback about it in the same process.

The runner’s main method (run()) operates like a generator, and yields results which are dictionaries with relevant information about it.

Trying it out - standalone

It’s possible to interact with the runner features by using the command line. This interface is not stable at all, and may be changed or removed in the future.

You can run a “noop” runner with:

python3 -m avocado.core.nrunner runnable-run -k noop

You can run an “exec” runner with:

python3 -m avocado.core.nrunner runnable-run -k exec -u /bin/uname --args='-a'

You can run an “exec-test” runner with:

python3 -m avocado.core.nrunner runnable-run -k exec-test -u /bin/true

You can run a “python-unittest” runner with:

python3 -m avocado.core.nrunner runnable-run -k python-unittest -u unittest.TestCase

Trying it out - Avocado Plugins

Simple Avocado plugins for the runner features are also available.

Runnables from parameters

You can run a “noop” runner with:

avocado runnable-run -k noop

You can run an “exec” runner with:

avocado runnable-run -k exec -u /bin/sleep -a 3

You can run an “exec-test” runner with:

avocado runnable-run -k exec-test -u /bin/true

You can run a “python-unittest” runner with:

avocado runnable-run python-unittest unittest.TestCase

Runnables from recipes

You can run a “noop” recipe with:

avocado runnable-run-recipe examples/recipes/runnables/noop.json

You can run an “exec” runner with:

avocado runnable-run-recipe examples/recipes/runnables/exec_sleep_3.json

You can run a “python-unittest” runner with:

avocado runnable-run-recipe examples/recipes/runnables/python_unittest.json