Scenario

Scenario is a state-transition, functional testing framework for Operator Framework charms.

Where the Harness enables you to procedurally mock pieces of the state the charm needs to function, Scenario tests allow you to declaratively define the state all at once, and use it as a sort of context against which you can fire a single event on the charm and execute its logic.

This puts scenario tests somewhere in between unit and integration tests: some say 'functional', some say 'contract'.

Scenario tests nudge you into thinking of a charm as an input->output function. Input is what we call a Scene: the union of an Event (why am I being executed) and a State (am I leader? what is my relation data? what is my config?...). The output is another context instance: the context after the charm has had a chance to interact with the mocked juju model and affect the state back.

Scenario-testing a charm, then, means verifying that:

• the charm does not raise uncaught exceptions while handling the scene
• the output state (or the diff with the input state) is as expected.

Core concepts as a metaphor

I like metaphors, so here we go:

• There is a theatre stage.
• You pick an actor (a Charm) to put on the stage. Not just any actor: an improv one.
• You arrange the stage with content that the actor will have to interact with. This consists of selecting:
  • An initial situation (State) in which the actor is, e.g. is the actor the main role or an NPC (is_leader), or what other actors are there around it, what is written in those pebble-shaped books on the table?
  • Something that has just happened (an Event) and to which the actor has to react (e.g. one of the NPCs leaves the stage (relation-departed), or the content of one of the books changes).
• How the actor will react to the event will have an impact on the context: e.g. the actor might knock over a table (a container), or write something down into one of the books.

Core concepts not as a metaphor

Scenario tests are about running assertions on atomic state transitions treating the charm being tested like a black box. An initial state goes in, an event occurs (say, 'start') and a new state comes out. Scenario tests are about validating the transition, that is, consistency-checking the delta between the two states, and verifying the charm author's expectations.

Comparing scenario tests with Harness tests:

• Harness exposes an imperative API: the user is expected to call methods on the Harness driving it to the desired state, then verify its validity by calling charm methods or inspecting the raw data.
• Harness instantiates the charm once, then allows you to fire multiple events on the charm, which is breeding ground for subtle bugs. Scenario tests are centered around testing single state transitions, that is, one event at a time. This ensures that the execution environment is as clean as possible (for a unit test).
• Harness maintains a model of the juju Model, which is a maintenance burden and adds complexity. Scenario mocks at the level of hook tools and stores all mocking data in a monolithic data structure (the State), which makes it more lightweight and portable.
• TODO: Scenario can mock at the level of hook tools. Decoupling charm and context allows us to swap out easily any part of this flow, and even share context data across charms, codebases, teams...

Writing scenario tests

A scenario test consists of three broad steps:

• Arrange:
  • declare the input state
  • select an event to fire
• Act:
  • run the state (i.e. obtain the output state)
  • optionally, use pre-event and post-event hooks to get a hold of the charm instance and run assertions on internal APIs
• Assert:
  • verify that the output state (or the delta with the input state) is how you expect it to be
  • verify that the charm has seen a certain sequence of statuses, events, and juju-log calls

The most basic scenario is the so-called null scenario: one in which all is defaulted and barely any data is available. The charm has no config, no relations, no networks, and no leadership.

With that, we can write the simplest possible scenario test:

from scenario import State, Context
from ops.charm import CharmBase
from ops.model import UnknownStatus


class MyCharm(CharmBase):
    pass


def test_scenario_base():
    ctx = Context(MyCharm,
                  meta={"name": "foo"})
    out = ctx.run('start', State())
    assert out.unit_status == UnknownStatus()

Now let's start making it more complicated. Our charm sets a special state if it has leadership on 'start':

import pytest
from scenario import State, Context
from ops.charm import CharmBase
from ops.model import ActiveStatus


class MyCharm(CharmBase):
    def __init__(self, ...):
        self.framework.observe(self.on.start, self._on_start)

    def _on_start(self, _):
        if self.unit.is_leader():
            self.unit.status = ActiveStatus('I rule')
        else:
            self.unit.status = ActiveStatus('I am ruled')


@pytest.mark.parametrize('leader', (True, False))
def test_status_leader(leader):
    ctx = Context(MyCharm,
                  meta={"name": "foo"})
    out = ctx.run('start', State(leader=leader))
    assert out.unit_status == ActiveStatus('I rule' if leader else 'I am ruled')

By defining the right state we can programmatically define what answers will the charm get to all the questions it can ask the juju model: am I leader? What are my relations? What is the remote unit I'm talking to? etc...

Statuses

One of the simplest types of black-box testing available to charmers is to execute the charm and verify that the charm sets the expected unit/application status. We have seen a simple example above including leadership. But what if the charm transitions through a sequence of statuses?

from ops.model import MaintenanceStatus, ActiveStatus, WaitingStatus, BlockedStatus


# charm code:
def _on_event(self, _event):
    self.unit.status = MaintenanceStatus('determining who the ruler is...')
    try:
        if self._call_that_takes_a_few_seconds_and_only_passes_on_leadership:
            self.unit.status = ActiveStatus('I rule')
        else:
            self.unit.status = WaitingStatus('checking this is right...')
            self._check_that_takes_some_more_time()
            self.unit.status = ActiveStatus('I am ruled')
    except:
        self.unit.status = BlockedStatus('something went wrong')

More broadly, often we want to test 'side effects' of executing a charm, such as what events have been emitted, what statuses it went through, etc... Before we get there, we have to explain what the Context represents, and its relationship with the State.

Context and State

Consider the following tests. Suppose we want to verify that while handling a given toplevel juju event:

• a specific chain of (custom) events was emitted on the charm
• the charm juju-logged these specific strings
• the charm went through this sequence of app/unit statuses (e.g. maintenance, then waiting, then active)

These types of test have a place in Scenario, but that is not State: the contents of the juju log or the status history are side effects of executing a charm, but are not persisted in a charm-accessible "state" in any meaningful way. In other words: those data streams are, from the charm's perspective, write-only.

As such, they do not belong in scenario.State but in scenario.Context: the object representing the charm's execution context.

Status history

You can verify that the charm has followed the expected path by checking the unit/app status history like so:

from charm import MyCharm
from ops.model import MaintenanceStatus, ActiveStatus, WaitingStatus, UnknownStatus
from scenario import State, Context


def test_statuses():
    ctx = Context(MyCharm,
                  meta={"name": "foo"})
    ctx.run('start', State(leader=False))
    assert ctx.unit_status_history == [
        UnknownStatus(),
        MaintenanceStatus('determining who the ruler is...'),
        WaitingStatus('checking this is right...'),
        ActiveStatus("I am ruled"),
    ]

    assert ctx.app_status_history == [
        UnknownStatus(),
        ActiveStatus(""),
    ]

Note that the current status is not in the unit status history.

Also note that, unless you initialize the State with a preexisting status, the first status in the history will always be unknown. That is because, so far as scenario is concerned, each event is "the first event this charm has ever seen".

If you want to simulate a situation in which the charm already has seen some event, and is in a status other than Unknown (the default status every charm is born with), you will have to pass the 'initial status' to State.

from ops.model import ActiveStatus
from scenario import State, Status

# ...
ctx.run('start', State(unit_status=ActiveStatus('foo')))
assert ctx.unit_status_history == [
    ActiveStatus('foo'),  # now the first status is active: 'foo'!
    # ...
]

Workload version history

Using a similar api to *_status_history, you can assert that the charm has set one or more workload versions during a hook execution:

from scenario import Context

# ...
ctx: Context
assert ctx.workload_version_history == ['1', '1.2', '1.5']
# ...

Emitted events

If your charm deals with deferred events, custom events, and charm libs that in turn emit their own custom events, it can be hard to examine the resulting control flow. In these situations it can be useful to verify that, as a result of a given juju event triggering (say, 'start'), a specific chain of deferred and custom events is emitted on the charm. The resulting state, black-box as it is, gives little insight into how exactly it was obtained.

from scenario import Context
from ops.charm import StartEvent


def test_foo():
    ctx = Context(...)
    ctx.run('start', ...)

    assert len(ctx.emitted_events) == 1
    assert isinstance(ctx.emitted_events[0], StartEvent)

Low-level access: using directly capture_events

If you need more control over what events are captured (or you're not into pytest), you can use directly the context manager that powers the emitted_events fixture: scenario.capture_events. This context manager allows you to intercept any events emitted by the framework.

Usage:

from ops.charm import StartEvent, UpdateStatusEvent
from scenario import State, Context, DeferredEvent, capture_events

with capture_events() as emitted:
    ctx = Context(...)
    state_out = ctx.run(
        "update-status",
        State(deferred=[DeferredEvent("start", ...)])
    )

# deferred events get reemitted first
assert isinstance(emitted[0], StartEvent)
# the main juju event gets emitted next
assert isinstance(emitted[1], UpdateStatusEvent)
# possibly followed by a tail of all custom events that the main juju event triggered in turn
# assert isinstance(emitted[2], MyFooEvent)
# ...

You can filter events by type like so:

from ops.charm import StartEvent, RelationEvent
from scenario import capture_events

with capture_events(StartEvent, RelationEvent) as emitted:
    # capture all `start` and `*-relation-*` events.
    pass

Configuration:

• Passing no event types, like: capture_events(), is equivalent to capture_events(EventBase).
• By default, framework events (PreCommit, Commit) are not considered for inclusion in the output list even if they match the instance check. You can toggle that by passing: capture_events(include_framework=True).
• By default, deferred events are included in the listing if they match the instance check. You can toggle that by passing: capture_events(include_deferred=True).

Relations

You can write scenario tests to verify the shape of relation data:

from ops.charm import CharmBase

from scenario import Relation, State, Context


# This charm copies over remote app data to local unit data
class MyCharm(CharmBase):
    ...

    def _on_event(self, e):
        rel = e.relation
        assert rel.app.name == 'remote'
        assert rel.data[self.unit]['abc'] == 'foo'
        rel.data[self.unit]['abc'] = rel.data[e.app]['cde']


def test_relation_data():
    state_in = State(relations=[
        Relation(
            endpoint="foo",
            interface="bar",
            remote_app_name="remote",
            local_unit_data={"abc": "foo"},
            remote_app_data={"cde": "baz!"},
        ),
    ])
    ctx = Context(MyCharm,
                  meta={"name": "foo"})

    state_out = ctx.run('start', state_in)

    assert state_out.relations[0].local_unit_data == {"abc": "baz!"}
    # you can do this to check that there are no other differences:
    assert state_out.relations == [
        Relation(
            endpoint="foo",
            interface="bar",
            remote_app_name="remote",
            local_unit_data={"abc": "baz!"},
            remote_app_data={"cde": "baz!"},
        ),
    ]

# which is very idiomatic and superbly explicit. Noice.

The only mandatory argument to Relation (and other relation types, see below) is endpoint. The interface will be derived from the charm's metadata.yaml. When fully defaulted, a relation is 'empty'. There are no remote units, the remote application is called 'remote' and only has a single unit remote/0, and nobody has written any data to the databags yet.

That is typically the state of a relation when the first unit joins it.

When you use Relation, you are specifying a regular (conventional) relation. But that is not the only type of relation. There are also peer relations and subordinate relations. While in the background the data model is the same, the data access rules and the consistency constraints on them are very different. For example, it does not make sense for a peer relation to have a different 'remote app' than its 'local app', because it's the same application.

PeerRelation

To declare a peer relation, you should use scenario.state.PeerRelation. The core difference with regular relations is that peer relations do not have a "remote app" (it's this app, in fact). So unlike Relation, a PeerRelation does not have remote_app_name or remote_app_data arguments. Also, it talks in terms of peers:

• Relation.remote_unit_ids maps to PeerRelation.peers_ids
• Relation.remote_units_data maps to PeerRelation.peers_data

from scenario.state import PeerRelation

relation = PeerRelation(
    endpoint="peers",
    peers_data={1: {}, 2: {}, 42: {'foo': 'bar'}},
)

be mindful when using PeerRelation not to include "this unit"'s ID in peers_data or peers_ids, as that would be flagged by the Consistency Checker:

from scenario import State, PeerRelation, Context

state_in = State(relations=[
    PeerRelation(
        endpoint="peers",
        peers_data={1: {}, 2: {}, 42: {'foo': 'bar'}},
    )],
    unit_id=1)

Context(...).run("start", state_in)  # invalid: this unit's id cannot be the ID of a peer.

SubordinateRelation

To declare a subordinate relation, you should use scenario.state.SubordinateRelation. The core difference with regular relations is that subordinate relations always have exactly one remote unit (there is always exactly one primary unit that this unit can see). So unlike Relation, a SubordinateRelation does not have a remote_units_data argument. Instead, it has a remote_unit_data taking a single Dict[str:str], and takes the primary unit ID as a separate argument. Also, it talks in terms of primary:

• Relation.remote_unit_ids becomes SubordinateRelation.primary_id (a single ID instead of a list of IDs)
• Relation.remote_units_data becomes SubordinateRelation.remote_unit_data (a single databag instead of a mapping from unit IDs to databags)
• Relation.remote_app_name maps to SubordinateRelation.primary_app_name

from scenario.state import SubordinateRelation

relation = SubordinateRelation(
    endpoint="peers",
    remote_unit_data={"foo": "bar"},
    remote_app_name="zookeeper",
    remote_unit_id=42
)
relation.remote_unit_name  # "zookeeper/42"

Triggering Relation Events

If you want to trigger relation events, the easiest way to do so is get a hold of the Relation instance and grab the event from one of its aptly-named properties:

from scenario import Relation

relation = Relation(endpoint="foo", interface="bar")
changed_event = relation.changed_event
joined_event = relation.joined_event
# ...

This is in fact syntactic sugar for:

from scenario import Relation, Event

relation = Relation(endpoint="foo", interface="bar")
changed_event = Event('foo-relation-changed', relation=relation)

The reason for this construction is that the event is associated with some relation-specific metadata, that Scenario needs to set up the process that will run ops.main with the right environment variables.

Working with relation IDs

Every time you instantiate Relation (or peer, or subordinate), the new instance will be given a unique relation_id. To inspect the ID the next relation instance will have, you can call state.next_relation_id.

from scenario import Relation
from scenario.state import next_relation_id
next_id = next_relation_id(update=False)
rel = Relation('foo')
assert rel.relation_id == next_id

This can be handy when using replace to create new relations, to avoid relation ID conflicts:

from scenario import Relation
from scenario.state import next_relation_id
rel = Relation('foo')
rel2 = rel.replace(local_app_data={"foo": "bar"}, relation_id=next_relation_id())
assert rel2.relation_id == rel.relation_id + 1 

If you don't do this, and pass both relations into a State, you will trigger a consistency checker error.

Additional event parameters

All relation events have some additional metadata that does not belong in the Relation object, such as, for a relation-joined event, the name of the (remote) unit that is joining the relation. That is what determines what ops.model.Unit you get when you get RelationJoinedEvent().unit in an event handler.

In order to supply this parameter, you will have to call the event object and pass as remote_unit_id the id of the remote unit that the event is about. The reason that this parameter is not supplied to Relation but to relation events, is that the relation already ties 'this app' to some 'remote app' (cfr. the Relation.remote_app_name attr), but not to a specific unit. What remote unit this event is about is not a State concern but an Event one.

The remote_unit_id will default to the first ID found in the relation's remote_unit_ids, but if the test you are writing is close to that domain, you should probably override it and pass it manually.

from scenario import Relation, Event

relation = Relation(endpoint="foo", interface="bar")
remote_unit_2_is_joining_event = relation.joined_event(remote_unit_id=2)

# which is syntactic sugar for:
remote_unit_2_is_joining_event = Event('foo-relation-changed', relation=relation, relation_remote_unit_id=2)

Containers

When testing a kubernetes charm, you can mock container interactions. When using the null state (State()), there will be no containers. So if the charm were to self.unit.containers, it would get back an empty dict.

To give the charm access to some containers, you need to pass them to the input state, like so: State(containers=[...])

An example of a scene including some containers:

from scenario.state import Container, State

state = State(containers=[
    Container(name="foo", can_connect=True),
    Container(name="bar", can_connect=False)
])

In this case, self.unit.get_container('foo').can_connect() would return True, while for 'bar' it would give False.

You can configure a container to have some files in it:

from pathlib import Path

from scenario.state import Container, State, Mount

local_file = Path('/path/to/local/real/file.txt')

container = Container(name="foo", can_connect=True, mounts={'local': Mount('/local/share/config.yaml', local_file)})
state = State(containers=[container])

In this case, if the charm were to:

def _on_start(self, _):
    foo = self.unit.get_container('foo')
    content = foo.pull('/local/share/config.yaml').read()

then content would be the contents of our locally-supplied file.txt. You can use tempdir for nicely wrapping data and passing it to the charm via the container.

container.push works similarly, so you can write a test like:

import tempfile
from ops.charm import CharmBase
from scenario import State, Container, Mount, Context


class MyCharm(CharmBase):
    def __init__(self, *args):
        super().__init__(*args)
        self.framework.observe(self.on.foo_pebble_ready, self._on_pebble_ready)

    def _on_pebble_ready(self, _):
        foo = self.unit.get_container('foo')
        foo.push('/local/share/config.yaml', "TEST", make_dirs=True)


def test_pebble_push():
    with tempfile.NamedTemporaryFile() as local_file:
        container = Container(name='foo',
                              can_connect=True,
                              mounts={'local': Mount('/local/share/config.yaml', local_file.name)})
        state_in = State(
            containers=[container]
        )
        Context(
            MyCharm,
            meta={"name": "foo", "containers": {"foo": {}}}).run(
            "start",
            state_in,
        )
        assert local_file.read().decode() == "TEST"

container.pebble_ready_event is syntactic sugar for: Event("foo-pebble-ready", container=container). The reason we need to associate the container with the event is that the Framework uses an envvar to determine which container the pebble-ready event is about (it does not use the event name). Scenario needs that information, similarly, for injecting that envvar into the charm's runtime.

container.exec is a tad more complicated, but if you get to this low a level of simulation, you probably will have far worse issues to deal with. You need to specify, for each possible command the charm might run on the container, what the result of that would be: its return code, what will be written to stdout/stderr.

from ops.charm import CharmBase

from scenario import State, Container, ExecOutput, Context

LS_LL = """
.rw-rw-r--  228 ubuntu ubuntu 18 jan 12:05 -- charmcraft.yaml
.rw-rw-r--  497 ubuntu ubuntu 18 jan 12:05 -- config.yaml
.rw-rw-r--  900 ubuntu ubuntu 18 jan 12:05 -- CONTRIBUTING.md
drwxrwxr-x    - ubuntu ubuntu 18 jan 12:06 -- lib
"""


class MyCharm(CharmBase):
    def _on_start(self, _):
        foo = self.unit.get_container('foo')
        proc = foo.exec(['ls', '-ll'])
        stdout, _ = proc.wait_output()
        assert stdout == LS_LL


def test_pebble_exec():
    container = Container(
        name='foo',
        exec_mock={
            ('ls', '-ll'):  # this is the command we're mocking
                ExecOutput(return_code=0,  # this data structure contains all we need to mock the call.
                           stdout=LS_LL)
        }
    )
    state_in = State(
        containers=[container]
    )
    state_out = Context(
        MyCharm,
        meta={"name": "foo", "containers": {"foo": {}}},
    ).run(
        container.pebble_ready_event,
        state_in,
    )

Ports

Since ops 2.6.0, charms can invoke the open-port, close-port, and opened-ports hook tools to manage the ports opened on the host vm/container. Using the State.opened_ports api, you can:

• simulate a charm run with a port opened by some previous execution

from scenario import State, Port, Context

ctx = Context(MyCharm)
ctx.run("start", State(opened_ports=[Port("tcp", 42)]))

• assert that a charm has called open-port or close-port:

from scenario import State, Port, Context

ctx = Context(MyCharm)
state1 = ctx.run("start", State())
assert state1.opened_ports == [Port("tcp", 42)]

state2 = ctx.run("stop", state1)
assert state2.opened_ports == []

Secrets

Scenario has secrets. Here's how you use them.

from scenario import State, Secret

state = State(
    secrets=[
        Secret(
            id='foo',
            contents={0: {'key': 'public'}}
        )
    ]
)

The only mandatory arguments to Secret are its secret ID (which should be unique) and its 'contents': that is, a mapping from revision numbers (integers) to a str:str dict representing the payload of the revision.

By default, the secret is not owned by this charm nor is it granted to it. Therefore, if charm code attempted to get that secret revision, it would get a permission error: we didn't grant it to this charm, nor we specified that the secret is owned by it.

To specify a secret owned by this unit (or app):

from scenario import State, Secret

state = State(
    secrets=[
        Secret(
            id='foo',
            contents={0: {'key': 'public'}},
            owner='unit',  # or 'app'
            remote_grants={0: {"remote"}}
            # the secret owner has granted access to the "remote" app over some relation with ID 0
        )
    ]
)

To specify a secret owned by some other application and give this unit (or app) access to it:

from scenario import State, Secret

state = State(
    secrets=[
        Secret(
            id='foo',
            contents={0: {'key': 'public'}},
            # owner=None, which is the default
            granted="unit",  # or "app",
            revision=0,  # the revision that this unit (or app) is currently tracking
        )
    ]
)

Actions

An action is a special sort of event, even though ops handles them almost identically. In most cases, you'll want to inspect the 'results' of an action, or whether it has failed or logged something while executing. Many actions don't have a direct effect on the output state. For this reason, the output state is less prominent in the return type of Context.run_action.

How to test actions with scenario:

Actions without parameters

from scenario import Context, State, ActionOutput
from charm import MyCharm


def test_backup_action():
    ctx = Context(MyCharm)

    # If you didn't declare do_backup in the charm's `actions.yaml`, 
    # the `ConsistencyChecker` will slap you on the wrist and refuse to proceed.
    out: ActionOutput = ctx.run_action("do_backup_action", State())

    # you can assert action results, logs, failure using the ActionOutput interface
    assert out.results == {'foo': 'bar'}
    assert out.logs == ['baz', 'qux']
    assert out.failure == 'boo-hoo'

Parametrized Actions

If the action takes parameters, you'll need to instantiate an Action.

from scenario import Action, Context, State, ActionOutput
from charm import MyCharm


def test_backup_action():
    # define an action
    action = Action('do_backup', params={'a': 'b'})
    ctx = Context(MyCharm)

    # if the parameters (or their type) don't match what declared in actions.yaml, 
    # the `ConsistencyChecker` will slap you on the other wrist. 
    out: ActionOutput = ctx.run_action(action, State())

    # ...

Deferred events

Scenario allows you to accurately simulate the Operator Framework's event queue. The event queue is responsible for keeping track of the deferred events. On the input side, you can verify that if the charm triggers with this and that event in its queue (they would be there because they had been deferred in the previous run), then the output state is valid.

from scenario import State, deferred, Context


class MyCharm(...):
    ...

    def _on_update_status(self, e):
        e.defer()

    def _on_start(self, e):
        e.defer()


def test_start_on_deferred_update_status(MyCharm):
    """Test charm execution if a 'start' is dispatched when in the previous run an update-status had been deferred."""
    state_in = State(
        deferred=[
            deferred('update_status',
                     handler=MyCharm._on_update_status)
        ]
    )
    state_out = Context(MyCharm).run('start', state_in)
    assert len(state_out.deferred) == 1
    assert state_out.deferred[0].name == 'start'

You can also generate the 'deferred' data structure (called a DeferredEvent) from the corresponding Event (and the handler):

from scenario import Event, Relation


class MyCharm(...):
    ...


deferred_start = Event('start').deferred(MyCharm._on_start)
deferred_install = Event('install').deferred(MyCharm._on_start)

relation events:

foo_relation = Relation('foo')
deferred_relation_changed_evt = foo_relation.changed_event.deferred(handler=MyCharm._on_foo_relation_changed)

On the output side, you can verify that an event that you expect to have been deferred during this trigger, has indeed been deferred.

from scenario import State, Context


class MyCharm(...):
    ...

    def _on_start(self, e):
        e.defer()


def test_defer(MyCharm):
    out = Context(MyCharm).run('start', State())
    assert len(out.deferred) == 1
    assert out.deferred[0].name == 'start'

Deferring relation events

If you want to test relation event deferrals, some extra care needs to be taken. RelationEvents hold references to the Relation instance they are about. So do they in Scenario. You can use the deferred helper to generate the data structure:

from scenario import State, Relation, deferred


class MyCharm(...):
    ...

    def _on_foo_relation_changed(self, e):
        e.defer()


def test_start_on_deferred_update_status(MyCharm):
    foo_relation = Relation('foo')
    State(
        relations=[foo_relation],
        deferred=[
            deferred('foo_relation_changed',
                     handler=MyCharm._on_foo_relation_changed,
                     relation=foo_relation)
        ]
    )

but you can also use a shortcut from the relation event itself, as mentioned above:

from scenario import Relation


class MyCharm(...):
    ...


foo_relation = Relation('foo')
foo_relation.changed_event.deferred(handler=MyCharm._on_foo_relation_changed)

Fine-tuning

The deferred helper Scenario provides will not support out of the box all custom event subclasses, or events emitted by charm libraries or objects other than the main charm class.

For general-purpose usage, you will need to instantiate DeferredEvent directly.

from scenario import DeferredEvent

my_deferred_event = DeferredEvent(
    handle_path='MyCharm/MyCharmLib/on/database_ready[1]',
    owner='MyCharmLib',  # the object observing the event. Could also be MyCharm.
    observer='_on_database_ready'
)

StoredState

Scenario can simulate StoredState. You can define it on the input side as:

from ops.charm import CharmBase
from ops.framework import StoredState as Ops_StoredState, Framework
from scenario import State, StoredState


class MyCharmType(CharmBase):
    my_stored_state = Ops_StoredState()

    def __init__(self, framework: Framework):
        super().__init__(framework)
        assert self.my_stored_state.foo == 'bar'  # this will pass!


state = State(stored_state=[
    StoredState(
        owner_path="MyCharmType",
        name="my_stored_state",
        content={
            'foo': 'bar',
            'baz': {42: 42},
        })
])

And the charm's runtime will see self.stored_State.foo and .baz as expected. Also, you can run assertions on it on the output side the same as any other bit of state.

Emitting custom events

While the main use case of Scenario is to emit juju events, i.e. the built-in start, install, *-relation-changed, etc..., it can be sometimes handy to directly trigger custom events defined on arbitrary Objects in your hierarchy.

Suppose your charm uses a charm library providing an ingress_provided event. The 'proper' way to emit it is to run the event that causes that custom event to be emitted by the library, whatever that may be, for example a foo-relation-changed.

However, that may mean that you have to set up all sorts of State and mocks so that the right preconditions are met and the event is emitted at all.

If for whatever reason you don't want to do that and you attempt to run that event directly you will get an error:

from scenario import Context, State
Context(...).run("ingress_provided", State())  # raises scenario.ops_main_mock.NoObserverError

This happens because the framework, by default, searches for an event source named ingress_provided in charm.on, but since the event is defined on another Object, it will fail to find it.

You can prefix the event name with the path leading to its owner to tell Scenario where to find the event source:

from scenario import Context, State
Context(...).run("my_charm_lib.on.ingress_provided", State())

This will instruct Scenario to emit my_charm.my_charm_lib.on.foo.

(always omit the 'root', i.e. the charm framework key, from the path)

The virtual charm root

Before executing the charm, Scenario writes the metadata, config, and actions yamls to a temporary directory. The charm will see that tempdir as its 'root'. This allows us to keep things simple when dealing with metadata that can be either inferred from the charm type being passed to Context or be passed to it as an argument, thereby overriding the inferred one. This also allows you to test with charms defined on the fly, as in:

from ops.charm import CharmBase
from scenario import State, Context


class MyCharmType(CharmBase):
    pass


ctx = Context(charm_type=MyCharmType,
              meta={'name': 'my-charm-name'})
ctx.run('start', State())

A consequence of this fact is that you have no direct control over the tempdir that we are creating to put the metadata you are passing to trigger (because ops expects it to be a file...). That is, unless you pass your own:

from ops.charm import CharmBase
from scenario import State, Context
import tempfile


class MyCharmType(CharmBase):
    pass


td = tempfile.TemporaryDirectory()
state = Context(
    charm_type=MyCharmType,
    meta={'name': 'my-charm-name'},
    charm_root=td.name
).run('start', State())

Do this, and you will be able to set up said directory as you like before the charm is run, as well as verify its contents after the charm has run. Do keep in mind that the metadata files will be overwritten by Scenario, and therefore ignored.

Immutability

All of the data structures in state, e.g. State, Relation, Container, etc... are immutable (implemented as frozen dataclasses).

This means that all components of the state that goes into a context.run() call are not mutated by the call, and the state that you obtain in return is a different instance, and all parts of it have been (deep)copied. This ensures that you can do delta-based comparison of states without worrying about them being mutated by scenario.

If you want to modify any of these data structures, you will need to either reinstantiate it from scratch, or use the replace api.

from scenario import Relation
relation = Relation('foo', remote_app_data={"1":"2"})
# make a copy of relation, but with remote_app_data set to {"3", "4"} 
relation2 = relation.replace(remote_app_data={"3", "4"})

Consistency checks

A Scenario, that is, the combination of an event, a state, and a charm, is consistent if it's plausible in JujuLand. For example, Juju can't emit a foo-relation-changed event on your charm unless your charm has declared a foo relation endpoint in its metadata.yaml. If that happens, that's a juju bug. Scenario however assumes that Juju is bug-free, therefore, so far as we're concerned, that can't happen, and therefore we help you verify that the scenarios you create are consistent and raise an exception if that isn't so.

That happens automatically behind the scenes whenever you trigger an event; scenario.consistency_checker.check_consistency is called and verifies that the scenario makes sense.

Caveats:

• False positives: not all checks are implemented yet; more will come.
• False negatives: it is possible that a scenario you know to be consistent is seen as inconsistent. That is probably a bug in the consistency checker itself, please report it.
• Inherent limitations: if you have a custom event whose name conflicts with a builtin one, the consistency constraints of the builtin one will apply. For example: if you decide to name your custom event bar-pebble-ready, but you are working on a machine charm or don't have either way a bar container in your metadata.yaml, Scenario will flag that as inconsistent.

Bypassing the checker

If you have a clear false negative, are explicitly testing 'edge', inconsistent situations, or for whatever reason the checker is in your way, you can set the SCENARIO_SKIP_CONSISTENCY_CHECKS envvar and skip it altogether. Hopefully you don't need that.

Snapshot

Scenario comes with a cli tool called snapshot. Assuming you've pip-installed ops-scenario, you should be able to reach the entry point by typing scenario snapshot in a shell so long as the install dir is in your PATH.

Snapshot's purpose is to gather the State data structure from a real, live charm running in some cloud your local juju client has access to. This is handy in case:

• you want to write a test about the state the charm you're developing is currently in
• your charm is bork or in some inconsistent state, and you want to write a test to check the charm will handle it correctly the next time around (aka regression testing)
• you are new to Scenario and want to quickly get started with a real-life example.

Suppose you have a Juju model with a prometheus-k8s unit deployed as prometheus-k8s/0. If you type scenario snapshot prometheus-k8s/0, you will get a printout of the State object. Pipe that out into some file, import all you need from scenario, and you have a working State that you can Context.run events with.

You can also pass a --format flag to obtain instead:

• a jsonified State data structure, for portability
• a full-fledged pytest test case (with imports and all), where you only have to fill in the charm type and the event that you wish to trigger.