def jobs(
draw,
ids=uuids(),
statuses=sampled_from(JobInterface.JobStatus),
parameters=dictionaries(text(), text()),
results=dictionaries(text(), text()),
dates_submitted=datetimes(),
registration_schemas=dictionaries(text(), text()),
result_schemas=dictionaries(text(), text())
) -> JobInterface:
"""
:param draw: A function that can take a strategy and draw a datum from it
:param ids: A hypothesis strategy (statisticians should read "random
variable"), that represents the set of all valid job IDs
:param statuses: A hypothesis strategy that samples from the set of all
allowed job statuses
:param parameters: A hypothesis strategy that samples from all job
parameters
:param results: A hypothesis strategy that represents the possible results
:param dates_submitted: A hypothesis strategy that represents the
possible dates that can be submitted
:param registration_schemas: The possible job registration schemas
:param result_schemas: The possible job result schemas
:return: A randomly-generated implementation of :class:`JobInterface`
"""
return Job(
draw(ids), draw(statuses), draw(parameters), draw(results),
draw(dates_submitted),
draw(registration_schemas),
draw(result_schemas)
)
def test_dictionary(dict_class):
assert minimal(dictionaries(keys=integers(), values=text(), dict_class=dict_class)) == dict_class()
x = minimal(dictionaries(keys=integers(), values=text(), dict_class=dict_class), lambda t: len(t) >= 3)
assert isinstance(x, dict_class)
assert set(x.values()) == set((u"",))
for k in x:
if k < 0:
assert k + 1 in x
if k > 0:
assert k - 1 in x
def _valid_post_requests(
draw,
names: str=text(),
descriptions: str=text(),
job_registration_schemas: dict=dictionaries(text(), text()),
job_result_schemas: dict=dictionaries(text(), text())
) -> dict:
return {
'name': draw(names),
'description': draw(descriptions),
'job_registration_schema': draw(job_registration_schemas),
'job_result_schema': draw(job_result_schemas)
}
def services(
draw,
names=text(),
descriptions=text(),
registration=dictionaries(text(), text()),
results=dictionaries(text(), text())
) -> Service:
return Service.new(
name=draw(names),
description=draw(descriptions),
registration_schema=draw(registration),
result_schema=draw(results)
)
def http_headers():
"""
Strategy for generating ``Headers`` populated with random HTTP
headers.
This could probably use some more work.
"""
return dictionaries(
keys=sampled_from((
b"accept",
b"accept-charset",
b"accept-encoding",
b"accept-language",
b"accept-ranges",
b"age",
b"allow",
b"authorization",
b"cache-control",
b"connection",
b"content-encoding",
b"content-language",
# XXX The rest, I guess, plus randomly generate some?
)),
values=text().map(lambda x: x.encode("utf-8")),
).map(
lambda h: Headers({k: [v] for (k, v) in h.items()})
)
def jenkins_build_results(inQueue=None, builds=None):
"""Create a strategy for generating Jenkins API information for a job.
:param strategy inQueue: strategy for the inQueue key, or None to use
the default.
:param strategy builds: strategy for populating the builds key, or None
for the default. The special value `NO_BUILDS` will mean that the
builds key is not in the resulting dict at all.
:return strategy: a strategy.
"""
strats = []
if inQueue is None:
inQueue = booleans()
strats.append(just(pmap()))
without_builds = fixed_dictionaries(dict(
inQueue=inQueue))
if builds is None or builds is NO_BUILDS:
strats.append(without_builds)
if builds is None:
builds = lists(jenkins_builds, average_size=1)
if builds is not NO_BUILDS:
with_builds = fixed_dictionaries(dict(
inQueue=inQueue,
builds=builds,
property=dictionaries(
text(max_size=2), text(max_size=2),
average_size=1, max_size=2)))
strats.append(with_builds)
return one_of(*strats)
def valid_dictionaries(keys, values):
return dictionaries(keys, values, average_size=5).filter(
lambda data: (
sum(len(key.encode('utf-8')) for key in data) <=
MAX_TOTAL_NAME_LENGTH
),
)
def services(
draw,
ids=uuids(),
names=text(),
descriptions=text(),
registration_schemas=dictionaries(text(), text()),
result_schemas=dictionaries(text(), text()),
are_available=booleans(),
service_job_lists=job_lists(),
timeouts=timedeltas()
) -> ServiceInterface:
return Service(
draw(ids), draw(names), draw(descriptions),
draw(registration_schemas), draw(result_schemas),
draw(are_available), draw(service_job_lists),
draw(timeouts)
)
def http_query_args():
"""
Strategy for generating some UTF-8 key/value-list pairs usable as
query arguments in a request path.
"""
return dictionaries(
keys=text().map(lambda x: x.encode("utf-8")),
values=lists(text().map(lambda x: x.encode("utf-8")), min_size=1),
)
def test_dictionaries_of_fixed_length(n):
x = set(find(
dictionaries(integers(), booleans(), min_size=n, max_size=n),
lambda x: True).keys())
if not n:
assert x == set()
else:
assert x == set(range(min(x), min(x) + n))
def timedelta(draw):
"""
Timedelta strategy that limits the maximum timedelta to being positive and
abs max is about 100 weeks + 100 days + 100 hours + a bit
"""
keys = st.sampled_from(['days', 'seconds', 'microseconds', 'milliseconds',
'minutes', 'hours', 'weeks'])
values = st.floats(min_value=0, max_value=100)
return datetime.timedelta(**draw(st.dictionaries(keys, values)))
def jobs(
draw,
services=service_generator(),
parameters=dictionaries(text(), text()),
) -> Job:
return Job.new(
draw(services),
draw(parameters)
)
def visit_map(self, shape):
if shape.name in self.active:
return strategies.fixed_dictionaries({})
self.active.add(shape.name)
try:
return strategies.dictionaries(
keys=self.visit(shape.key_shape),
values=self.visit(shape.value_shape),
)
finally:
self.active.remove(shape.name)
def simple_attrs_with_metadata(draw):
"""
Create a simple attribute with arbitrary metadata.
"""
c_attr = draw(simple_attrs)
keys = st.booleans() | st.binary() | st.integers() | st.text()
vals = st.booleans() | st.binary() | st.integers() | st.text()
metadata = draw(st.dictionaries(keys=keys, values=vals))
return attr.ib(c_attr._default, c_attr._validator, c_attr.repr,
c_attr.cmp, c_attr.hash, c_attr.init, c_attr.convert,
metadata)
def jsonComposites(children):
"""
Creates a Hypothesis strategy that constructs composite
JSON-serializable objects (e.g., lists).
@param children: A strategy from which each composite object's
children will be drawn.
@return: The composite objects strategy.
"""
return (st.lists(children) |
st.dictionaries(st.text(printable), children) |
st.tuples(children))
def monoids():
base = many_one_of(
strat.integers(),
strat.lists(strat.integers()),
strat.lists(strat.integers()).map(tuple),
strat.text(),
strat.integers().map(MonoidProduct),
strat.dictionaries(strat.integers(), strat.integers()),
)
def recurse(substrat):
return stream_apply_strat(maybes(), substrat)
return strat.recursive(base, recurse)
def test_non_trivial_json():
json = st.deferred(lambda: st.none() | st.floats() | st.text() | lists | objects)
lists = st.lists(json)
objects = st.dictionaries(st.text(), json)
assert minimal(json) is None
small_list = minimal(json, lambda x: isinstance(x, list) and x)
assert small_list == [None]
x = minimal(json, lambda x: isinstance(x, dict) and isinstance(x.get(""), list))
assert x == {"": []}
def export(cls):
"""
Strategy that generates :py:class:`scality_manila_utils.export.Export`.
"""
export_point = cls.path()
host = cls.host()
options = sets(cls.options(), average_size=3)
clients = dictionaries(
keys=host,
values=options,
min_size=1,
average_size=5
)
return builds(Export, export_point, clients)
def TimeDelta(draw):
"""
Timedelta strategy that limits the maximum timedelta to being positive and
abs max is about 10 weeks + 10 days + 10 hours + 10 minutes + a bit
"""
keys = st.sampled_from(['weeks', 'days', 'hours', 'minutes', 'seconds'])
values = st.floats(min_value=1, max_value=10)
delta = datetime.timedelta(**draw(st.dictionaries(keys, values)))
delta = astropy.time.TimeDelta(delta, format='datetime')
# We don't want a 0 timedelta
assume(delta.sec > 0)
return delta
def type_to_strat(x, opts): # type: (type) -> SearchStrategy
'''
Given a type, return a strategy which yields a value of that type. Types maybe complex: Union, NamedTuple, etc.
For more information, see https://docs.python.org/3/library/typing.html
Usage:
>>> type_to_strat(Union[int,str]).exmample()
. . . 3
'''
recur = lambda y: type_to_strat(y, opts)
if x in primitives:
prim = primitives[x].filter(opts.get(x, lambda x: x))
return prim
elif hasattr(x, '_fields'):# NamedTuple isn't a type, it's a function
#elif isinstance(x, Callable): #this catches List[T] for some reason
name = x.__name__
fts = OrderedDict(x._field_types)
vals = map(recur, fts.values())
# `NamedTuple` is actually a ... `namedtuple` itself
toArgDict = lambda xs: dict(zip(fts.keys(), xs))
return st.tuples(*vals).map(lambda ys: x(**toArgDict(ys)))
elif issubclass(x, Dict):
return st.dictionaries(*map(recur, x.__parameters__))
elif issubclass(x, Tuple):
if x.__tuple_use_ellipsis__: # variable lenth tuple
element_type = x.__tuple_params__[0]
return recur(List[element_type]).map(tuple)
return st.tuples(*map(recur, x.__tuple_params__))
elif issubclass(x, Union):
return reduce(operator.ior, map(recur, x.__union_params__))
elif issubclass(x, Optional):
# Optional[X] is equivalent to Union[X, type(None)]. second param is always Nonetype.
value = x.__union_params__[0]
return (recur(value) | st.none()) # type: SearchStrategy
else:
element_type = recur(x.__parameters__[0])
if issubclass(x, list):
return st.lists(element_type)
elif issubclass(x, set):
return st.sets(element_type)
elif issubclass(x, Sequence):
anySizeTuple = recur(Tuple[element_type,...])
return st.sets(element_type) | st.lists(element_type) | anySizeTuple
elif issubclass(x, Generator):
toGen = lambda xs: (x for x in xs) # type: Callable[[Iterable[T]], Generator[T]]
return recur(List[element_type]).map(toGen)
# not sure how to create an Iterable (it doesn't have an `__next__` method)
elif issubclass(x, Iterator) or issubclass(x, Iteratable):
return recur(List[element_type]).map(iter)
else:
raise ValueError("Could not find strategy for type %s" % x)
def objects(elements=None, *,
required_fields=None,
optional_fields=None,
min_size=None,
average_size=None,
max_size=None):
"""Returns a strategy that generates dicts of specified `elements`.
The `elements` must be valid Hypothesis strategy. The keys are ensured to
be string only as JSON requires.
While choice of `elements` left here for user side, it's not recommended to
use anything that produces non-serializable to JSON values.
Also possible to ensure that some fields with values generated by a certain
strategy are always exists (`required_fields`) or just optional
(`optional_fields`).
"""
def check_type(varname, var, expected):
if not isinstance(var, expected):
raise TypeError('{} must be {}, got {}'.format(
varname, expected, type(var)))
acc = []
if required_fields:
check_type('required_fields', required_fields, dict)
for key in required_fields:
check_type('required field name', key, str)
acc.append(st.fixed_dictionaries(required_fields))
if optional_fields:
check_type('optional_fields', optional_fields, dict)
for key in optional_fields:
check_type('optional field name', key, str)
acc.append(st.sets(st.sampled_from(optional_fields)).flatmap(
lambda keys: st.fixed_dictionaries({key: optional_fields[key]
for key in keys})))
if elements:
acc.append(st.dictionaries(strings(), elements,
min_size=min_size,
average_size=average_size,
max_size=max_size))
if not acc:
raise RuntimeError('object must have any strategy for fields')
return st.tuples(*reversed(acc)).map(
lambda s: reduce(lambda a, d: dict(a, **d), s))
def simple_attrs_with_metadata(draw):
"""
Create a simple attribute with arbitrary metadata.
"""
c_attr = draw(simple_attrs)
keys = st.booleans() | st.binary() | st.integers() | st.text()
vals = st.booleans() | st.binary() | st.integers() | st.text()
metadata = draw(st.dictionaries(
keys=keys, values=vals, min_size=1, max_size=5))
return attr.ib(
default=c_attr._default,
validator=c_attr._validator,
repr=c_attr.repr,
cmp=c_attr.cmp,
hash=c_attr.hash,
init=c_attr.init,
metadata=metadata,
type=None,
converter=c_attr.converter,
)
def test_produces_dictionaries_of_at_least_minimum_size():
t = minimal(
ds.dictionaries(ds.booleans(), ds.integers(), min_size=2), lambda x: True
)
assert t == {False: 0, True: 0}
def json_strat(depth=5):
return st.recursive(st.floats() | st.booleans() | st.text() | st.none(),
lambda children: st.dictionaries(st.text(), children),
max_leaves=depth)
def random_dict_variable_homogeneous_value(**kwargs):
"""Return a strategy which generates a random dictionary of variable name and value"""
return primitive_types.flatmap(
lambda s: hs.dictionaries(valid_identifier(), s(), **kwargs))
@pytest.mark.parametrize("tree_type", [AVLTree, RBTree])
@given(dict_and_key()) # pylint: disable=no-value-for-parameter
def test_pop(tree_type, givens):
items, test_key = givens
tree = AVLTree()
for k, v in items.items():
tree[k] = v
assert tree.pop(test_key) == items.pop(test_key)
@pytest.mark.parametrize("tree_type", [AVLTree, RBTree])
@given(st.dictionaries(st.integers(), st.uuids()))
def test_iter(tree_type, items):
keys = sorted(items.keys())
tree = AVLTree()
for k, v in items.items():
assert tree.insert(k, v) is None
ret = list(tree.items())
assert len(ret) == len(keys)
for k1, kv in zip(keys, ret):
assert k1 == kv[0]
assert items[k1] == kv[1]
return builds(ABC, x, y, z)
standard_types = [
lists(none(), max_size=0),
tuples(),
sets(none(), max_size=0),
frozensets(none(), max_size=0),
fixed_dictionaries({}),
abc(booleans(), booleans(), booleans()),
abc(booleans(), booleans(), integers()),
fixed_dictionaries({
"a": integers(),
"b": booleans()
}),
dictionaries(booleans(), integers()),
dictionaries(text(), booleans()),
one_of(integers(), tuples(booleans())),
sampled_from(range(10)),
one_of(just("a"), just("b"), just("c")),
sampled_from(("a", "b", "c")),
integers(),
integers(min_value=3),
integers(min_value=(-(2**32)), max_value=(2**64)),
floats(),
floats(min_value=-2.0, max_value=3.0),
floats(),
floats(min_value=-2.0),
floats(),
floats(max_value=-0.0),
floats(),
class TestClusterMaster(BaseUnitTestCase):
_PAGINATION_OFFSET = 0
_PAGINATION_LIMIT = 5
_PAGINATION_MAX_LIMIT = 10
_NUM_BUILDS = _NUM_SUBJOBS = _NUM_ATOMS = 20
def setUp(self):
super().setUp()
self.patch('app.util.fs.create_dir')
self.patch('app.util.fs.async_delete')
self.patch('os.makedirs')
self.mock_slave_allocator = self.patch(
'app.master.cluster_master.SlaveAllocator').return_value
self.mock_scheduler_pool = self.patch(
'app.master.cluster_master.BuildSchedulerPool').return_value
# Two threads are ran everytime we start up the ClusterMaster. We redirect the calls to
# `ThreadPoolExecutor.submit` through a mock proxy so we can capture events.
self.thread_pool_executor = ThreadPoolExecutor(max_workers=2)
self._thread_pool_executor_cls = self.patch(
'app.master.cluster_master.ThreadPoolExecutor')
self._thread_pool_executor_cls.return_value.submit.side_effect = \
self.thread_pool_executor.submit
Configuration['pagination_offset'] = self._PAGINATION_OFFSET
Configuration['pagination_limit'] = self._PAGINATION_LIMIT
Configuration['pagination_max_limit'] = self._PAGINATION_MAX_LIMIT
Configuration['database_name'] = TEST_DB_NAME
Configuration['database_url'] = TEST_DB_URL
Connection.create(Configuration['database_url'])
BuildStore._cached_builds_by_id.clear()
def tearDown(self):
super().tearDown()
self.thread_pool_executor.shutdown()
def tearDownClass():
"""Delete testing database after we're done"""
remove(TEST_DB_NAME)
@genty_dataset(
slave_id_specified=({
'slave_id': 400
}, ),
slave_url_specified=({
'slave_url': 'michelangelo.turtles.gov'
}, ),
)
def test_get_slave_raises_exception_on_slave_not_found(
self, get_slave_kwargs):
master = ClusterMaster()
master.connect_slave('raphael.turtles.gov', 10)
master.connect_slave('leonardo.turtles.gov', 10)
master.connect_slave('donatello.turtles.gov', 10)
with self.assertRaises(ItemNotFoundError):
master.get_slave(**get_slave_kwargs)
@genty_dataset(
both_arguments_specified=({
'slave_id': 1,
'slave_url': 'raphael.turtles.gov'
}, ),
neither_argument_specified=({}, ),
)
def test_get_slave_raises_exception_on_invalid_arguments(
self, get_slave_kwargs):
master = ClusterMaster()
master.connect_slave('raphael.turtles.gov', 10)
with self.assertRaises(ValueError):
master.get_slave(**get_slave_kwargs)
def test_get_slave_returns_expected_value_given_valid_arguments(self):
master = ClusterMaster()
master.connect_slave('raphael.turtles.gov', 10)
master.connect_slave('leonardo.turtles.gov', 10)
master.connect_slave('donatello.turtles.gov', 10)
actual_slave_by_id = master.get_slave(slave_id=2)
actual_slave_by_url = master.get_slave(
slave_url='leonardo.turtles.gov')
self.assertEqual(
2, actual_slave_by_id.id,
'Retrieved slave should have the same id as requested.')
self.assertEqual(
'leonardo.turtles.gov', actual_slave_by_url.url,
'Retrieved slave should have the same url as requested.')
def test_connect_slave_adds_new_slave_if_slave_never_connected_before(
self):
master = ClusterMaster()
master.connect_slave('never-before-seen.turtles.gov', 10)
self.assertEqual(
1, len(master.all_slaves_by_id()),
'Exactly one slave should be registered with the master.')
self.assertIsNotNone(
master.get_slave(slave_id=None,
slave_url='never-before-seen.turtles.gov'),
'Registered slave does not have the expected url.')
def test_connect_slave_with_existing_dead_slave_creates_new_alive_instance(
self):
master = ClusterMaster()
master.connect_slave('existing-slave.turtles.gov', 10)
existing_slave = master.get_slave(
slave_id=None, slave_url='existing-slave.turtles.gov')
existing_slave.set_is_alive(False)
existing_slave_id = existing_slave.id
connect_response = master.connect_slave('existing-slave.turtles.gov',
10)
new_slave = master._all_slaves_by_url.get('existing-slave.turtles.gov')
self.assertNotEqual(
str(existing_slave_id), connect_response['slave_id'],
'The re-connected slave should have generated a new slave id.')
self.assertTrue(
new_slave.is_alive(use_cached=True),
'The new slave should have been marked as alive once instantiated.'
)
self.assertEquals(
2, self.mock_slave_allocator.add_idle_slave.call_count,
'Expected slave to be added to the idle slaves list.')
def test_connect_slave_with_existing_slave_running_build_cancels_build(
self):
master = ClusterMaster()
master.connect_slave('running-slave.turtles.gov', 10)
build_mock = MagicMock(spec_set=Build)
BuildStore._cached_builds_by_id[1] = build_mock
existing_slave = master.get_slave(
slave_id=None, slave_url='running-slave.turtles.gov')
existing_slave.current_build_id = 1
master.connect_slave('running-slave.turtles.gov', 10)
self.assertTrue(build_mock.cancel.called,
'The build was not cancelled.')
def test_update_build_with_valid_params_succeeds(self):
build_id = 1
update_params = {'key': 'value'}
master = ClusterMaster()
build = Mock()
BuildStore._cached_builds_by_id[build_id] = build
build.validate_update_params = Mock(return_value=(True, update_params))
build.update_state = Mock()
success, response = master.handle_request_to_update_build(
build_id, update_params)
build.update_state.assert_called_once_with(update_params)
self.assertTrue(success, "Update build should return success")
self.assertEqual(response, {}, "Response should be empty")
def test_update_build_with_bad_build_id_fails(self):
build_id = 1
invalid_build_id = 0
update_params = {'key': 'value'}
master = ClusterMaster()
build = Mock()
BuildStore._cached_builds_by_id[build_id] = build
build.validate_update_params = Mock(return_value=(True, update_params))
build.update_state = Mock()
with self.assertRaises(ItemNotFoundError):
master.handle_request_to_update_build(invalid_build_id,
update_params)
def test_updating_slave_to_disconnected_state_should_mark_slave_as_dead(
self):
master = ClusterMaster()
slave_url = 'raphael.turtles.gov'
master.connect_slave(slave_url, num_executors=10)
slave = master.get_slave(slave_url=slave_url)
self.assertTrue(slave.is_alive())
master.handle_slave_state_update(slave, SlaveState.DISCONNECTED)
self.assertFalse(slave.is_alive())
def test_updating_slave_to_disconnected_state_should_reset_slave_current_build_id(
self):
master = ClusterMaster()
slave_url = 'raphael.turtles.gov'
master.connect_slave(slave_url, num_executors=10)
slave = master.get_slave(slave_url=slave_url)
slave.current_build_id = 4
master.handle_slave_state_update(slave, SlaveState.DISCONNECTED)
self.assertIsNone(slave.current_build_id)
def test_updating_slave_to_setup_completed_state_should_tell_build_to_begin_subjob_execution(
self):
master = ClusterMaster()
fake_build = MagicMock(spec_set=Build)
master.get_build = MagicMock(return_value=fake_build)
slave_url = 'raphael.turtles.gov'
master.connect_slave(slave_url, 10)
slave = master.get_slave(slave_url=slave_url)
mock_scheduler = self.mock_scheduler_pool.get(fake_build)
scheduler_begin_event = Event()
mock_scheduler.begin_subjob_executions_on_slave.side_effect = lambda **_: scheduler_begin_event.set(
)
master.handle_slave_state_update(slave, SlaveState.SETUP_COMPLETED)
was_called = scheduler_begin_event.wait(timeout=5)
self.assertTrue(
was_called,
'scheduler.begin_subjob_executions_on_slave should be called in response '
'to slave setup completing.')
_, call_kwargs = mock_scheduler.begin_subjob_executions_on_slave.call_args
self.assertEqual(call_kwargs.get('slave'), slave)
def test_updating_slave_to_shutdown_should_call_slave_set_shutdown_mode(
self):
master = ClusterMaster()
slave_url = 'raphael.turtles.gov'
master.connect_slave(slave_url, 10)
slave = master.get_slave(slave_url=slave_url)
slave.set_shutdown_mode = Mock()
master.handle_slave_state_update(slave, SlaveState.SHUTDOWN)
slave.set_shutdown_mode.assert_called_once_with()
def test_updating_slave_to_nonexistent_state_should_raise_bad_request_error(
self):
master = ClusterMaster()
slave_url = 'raphael.turtles.gov'
master.connect_slave(slave_url, 10)
slave = master.get_slave(slave_url=slave_url)
with self.assertRaises(BadRequestError):
master.handle_slave_state_update(slave, 'NONEXISTENT_STATE')
def test_handle_result_reported_from_slave_when_build_is_canceled(self):
build_id = 1
slave_url = "url"
build = Build(BuildRequest({}))
self.patch('app.master.build.util')
build.generate_project_type()
build.cancel()
self.patch_object(build, '_handle_subjob_payload')
self.patch_object(build, '_mark_subjob_complete')
master = ClusterMaster()
BuildStore._cached_builds_by_id[build_id] = build
master._all_slaves_by_url[slave_url] = Mock()
mock_scheduler = self.mock_scheduler_pool.get(build)
master.handle_result_reported_from_slave(slave_url, build_id, 1)
self.assertEqual(build._handle_subjob_payload.call_count, 1,
"Canceled builds should "
"handle payload")
self.assertEqual(
build._mark_subjob_complete.call_count, 1,
"Canceled builds should mark "
"their subjobs complete")
self.assertTrue(
mock_scheduler.execute_next_subjob_or_free_executor.called)
def test_exception_raised_during_complete_subjob_does_not_prevent_slave_teardown(
self):
slave_url = 'raphael.turtles.gov'
mock_build = Mock(spec_set=Build,
build_id=lambda: 777,
is_finished=False)
mock_build.complete_subjob.side_effect = [RuntimeError('Write failed')]
master = ClusterMaster()
BuildStore._cached_builds_by_id[mock_build.build_id()] = mock_build
master._all_slaves_by_url[slave_url] = Mock()
mock_scheduler = self.mock_scheduler_pool.get(mock_build)
with self.assertRaisesRegex(RuntimeError, 'Write failed'):
master.handle_result_reported_from_slave(slave_url,
mock_build.build_id(),
subjob_id=888)
self.assertEqual(
mock_scheduler.execute_next_subjob_or_free_executor.call_count, 1)
@given(dictionaries(text(), text()))
def test_handle_request_for_new_build_does_not_raise_exception(
self, build_params):
master = ClusterMaster()
master.handle_request_for_new_build(build_params)
@given(integers(), dictionaries(text(), text()))
def test_handle_request_to_update_build_does_not_raise_exception(
self, build_id, update_params):
master = ClusterMaster()
BuildStore._cached_builds_by_id = {build_id: Build({})}
master.handle_request_to_update_build(build_id, update_params)
@genty_dataset(
# No params simulates a v1 request
no_params=(None, None, 1, 0 + _NUM_BUILDS),
# Params simulate a v2 request
offset_param=(3, _PAGINATION_LIMIT, 3 + 1, 3 + _PAGINATION_LIMIT),
limit_param=(_PAGINATION_OFFSET, 5, _PAGINATION_OFFSET + 1,
_PAGINATION_OFFSET + 5),
offset_and_limit_params=(3, 5, 3 + 1, 3 + 5),
low_limit=(_PAGINATION_OFFSET, 2, _PAGINATION_OFFSET + 1,
_PAGINATION_OFFSET + 2),
max_limit=(_PAGINATION_OFFSET, _PAGINATION_MAX_LIMIT,
_PAGINATION_OFFSET + 1,
_PAGINATION_OFFSET + _PAGINATION_MAX_LIMIT),
too_high_offset=(1000, _PAGINATION_LIMIT, None, None),
)
def test_builds_with_pagination_request(
self,
offset: Optional[int],
limit: Optional[int],
expected_first_build_id: int,
expected_last_build_id: int,
):
master = ClusterMaster()
# Create 20 mock builds with ids 1 to 20
for build_id in range(1, self._NUM_BUILDS + 1):
build_mock = Mock(spec=Build)
build_mock.build_id = build_id
BuildStore._cached_builds_by_id[build_id] = build_mock
# Normally `get_builds` counts the amount of builds in database, but since we're directly
# adding builds into the cache here, we want to count those instead.
self.patch('app.database.build_store.BuildStore.count_all_builds',
autospec=False).return_value = len(
BuildStore._cached_builds_by_id)
requested_builds = master.get_builds(offset, limit)
id_of_first_build = requested_builds[0].build_id if len(
requested_builds) else None
id_of_last_build = requested_builds[-1].build_id if len(
requested_builds) else None
num_builds = len(requested_builds)
self.assertEqual(id_of_first_build, expected_first_build_id,
'Received the wrong first build from request')
self.assertEqual(id_of_last_build, expected_last_build_id,
'Received the wrong last build from request')
if offset is not None and limit is not None:
self.assertLessEqual(num_builds, self._PAGINATION_MAX_LIMIT,
'Received too many builds from request')
@genty_dataset(
# No params simulates a v1 request
no_params=(None, None, 1, 0 + _NUM_SUBJOBS),
# Params simulate a v2 request
offset_param=(3, _PAGINATION_LIMIT, 3 + 1, 3 + _PAGINATION_LIMIT),
limit_param=(_PAGINATION_OFFSET, 5, _PAGINATION_OFFSET + 1,
_PAGINATION_OFFSET + 5),
offset_and_limit_params=(3, 5, 3 + 1, 3 + 5),
low_limit=(_PAGINATION_OFFSET, 2, _PAGINATION_OFFSET + 1,
_PAGINATION_OFFSET + 2),
max_limit=(_PAGINATION_OFFSET, _PAGINATION_MAX_LIMIT,
_PAGINATION_OFFSET + 1,
_PAGINATION_OFFSET + _PAGINATION_MAX_LIMIT),
too_high_offset=(1000, _PAGINATION_LIMIT, None, None),
)
def test_subjobs_with_pagination_request(
self,
offset: Optional[int],
limit: Optional[int],
expected_first_subjob_id: int,
expected_last_subjob_id: int,
):
build = Build(BuildRequest({}))
# Create 20 mock subjobs with ids 1 to 20
for subjob_id in range(1, self._NUM_SUBJOBS + 1):
subjob_mock = Mock(spec=Subjob)
subjob_mock.subjob_id = subjob_id
build._all_subjobs_by_id[subjob_id] = subjob_mock
requested_subjobs = build.get_subjobs(offset, limit)
id_of_first_subjob = requested_subjobs[0].subjob_id if len(
requested_subjobs) else None
id_of_last_subjob = requested_subjobs[-1].subjob_id if len(
requested_subjobs) else None
num_subjobs = len(requested_subjobs)
self.assertEqual(id_of_first_subjob, expected_first_subjob_id,
'Received the wrong first subjob from request')
self.assertEqual(id_of_last_subjob, expected_last_subjob_id,
'Received the wrong last subjob from request')
if offset is not None and limit is not None:
self.assertLessEqual(num_subjobs, self._PAGINATION_MAX_LIMIT,
'Received too many subjobs from request')
@genty_dataset(
# No params simulates a v1 request
no_params=(None, None, 1, 0 + _NUM_ATOMS),
# Params simulate a v2 request
offset_param=(3, _PAGINATION_LIMIT, 3 + 1, 3 + _PAGINATION_LIMIT),
limit_param=(_PAGINATION_OFFSET, 5, _PAGINATION_OFFSET + 1,
_PAGINATION_OFFSET + 5),
offset_and_limit_params=(3, 5, 3 + 1, 3 + 5),
low_limit=(_PAGINATION_OFFSET, 2, _PAGINATION_OFFSET + 1,
_PAGINATION_OFFSET + 2),
max_limit=(_PAGINATION_OFFSET, _PAGINATION_MAX_LIMIT,
_PAGINATION_OFFSET + 1,
_PAGINATION_OFFSET + _PAGINATION_MAX_LIMIT),
too_high_offset=(1000, _PAGINATION_LIMIT, None, None),
)
def test_atoms_with_pagination_request(
self,
offset: Optional[int],
limit: Optional[int],
expected_first_atom_id: int,
expected_last_atom_id: int,
):
# Create 20 mock atoms with ids 1 to 20
atoms = []
for atom_id in range(1, self._NUM_ATOMS + 1):
atom_mock = Mock(spec=Atom)
atom_mock.id = atom_id
atoms.append(atom_mock)
build_id = 1
subjob_id = 1
project_type = None
job_config = None
subjob_atoms = atoms
subjob = Subjob(build_id, subjob_id, project_type, job_config, atoms)
requested_atoms = subjob.get_atoms(offset, limit)
id_of_first_atom = requested_atoms[0].id if len(
requested_atoms) else None
id_of_last_atom = requested_atoms[-1].id if len(
requested_atoms) else None
num_atoms = len(requested_atoms)
self.assertEqual(id_of_first_atom, expected_first_atom_id,
'Received the wrong first atom from request')
self.assertEqual(id_of_last_atom, expected_last_atom_id,
'Received the wrong last atom from request')
if offset is not None and limit is not None:
self.assertLessEqual(num_atoms, self._PAGINATION_MAX_LIMIT,
'Received too many atoms from request')
}, hostnames, exact_image_names, image_tags)
image_obj_registry_repository_values = strats.builds(
lambda r, n, t: {
'image': {
'registry': r,
'repository': '%s:%s' % (n, t)
},
'_containers': [{
kubeyaml.FHR_CONTAINER: '%s/%s:%s' % (r, n, t)
}]
}, hostnames, exact_image_names, image_tags)
# One of the above
toplevel_image_values = image_only_values | image_tag_values | image_registry_values | image_registry_tag_values | image_obj_values | image_obj_registry_tag_values | image_obj_registry_repository_values
# Some of the above, in fields
named_image_values = strats.dictionaries(
keys=dns_labels, values=toplevel_image_values).map(lift_containers)
# Combo of top-level image, and images in subfields
all_image_values = strats.builds(combine_containers,
strats.just(None) | toplevel_image_values,
named_image_values)
values_noise = strats.deferred(lambda: strats.dictionaries(
keys=dns_labels,
values=values_noise | strats.integers() | strats.lists(
values_noise) | strats.booleans() | strats.text(printable),
max_size=3))
@settings(suppress_health_check=[HealthCheck.too_slow])
@given(all_image_values, values_noise)
def test_extract_custom_containers(image_values, noise):
def test_minimize_multi_key_dicts():
assert minimal(dictionaries(keys=booleans(), values=booleans()), bool) == {
False: False
}
def extend_fn(children):
lists_st = st.lists(children)
dicts_st = st.dictionaries(encodable_text, children)
return lists_st | dicts_st
quoted = (
st.none()
| st.booleans()
| st.integers()
| st.floats(allow_nan=False)
| st.complex_numbers(allow_nan=False)
| st.binary() # bytes
)
literals = st.recursive(
# strings, bytes, numbers, tuples, lists, dicts, sets, booleans, and None
quoted,
lambda children: st.lists(children)
| st.sets(quoted)
| st.builds(tuple, st.lists(children))
| st.dictionaries(quoted, children),
)
class TestCompileGeneral(TestCase):
@given(
literals
| st.dates()
| st.datetimes()
| st.decimals(allow_nan=False)
| st.fractions()
| st.timedeltas()
| st.times()
| st.uuids()
)
def test_compile_pickle(self, form):
def test_validates_min_size_for_sets():
ds.sets(ds.booleans(), min_size=2)
with pytest.raises(InvalidArgument):
ds.sets(ds.booleans(), min_size=3).example()
def test_produces_dictionaries_of_at_least_minimum_size():
t = find(
ds.dictionaries(ds.booleans(), ds.integers(), min_size=2),
lambda x: True)
assert t == {False: 0, True: 0}
@given(
ds.dictionaries(ds.integers(), ds.integers(), max_size=5),
settings=Settings(max_examples=50))
def test_dictionaries_respect_size(d):
assert len(d) <= 5
@given(
ds.dictionaries(ds.integers(), ds.integers(), max_size=0),
settings=Settings(max_examples=50))
def test_dictionaries_respect_zero_size(d):
assert len(d) <= 5
@given(
ds.lists(ds.none(), max_size=5)
)
for is_last_element, var in core.signal_last(l):
if is_last_element:
assert var == last
def test_signal_last_raises_value_error_with_no_length():
"""It raises value error when no length"""
with pytest.raises(ValueError):
items: List[Any] = []
for i in core.signal_last(items):
print(i)
@given(
strategies.dictionaries(keys=strategies.text(min_size=1),
values=strategies.integers(),
min_size=1))
def test_signal_last_dictionary(d):
"""It returns last element for dictionary"""
*_, last = d
for is_last_element, var in core.signal_last(d.items()):
if is_last_element:
key, value = var
assert key == last
@given(
strategies.dictionaries(keys=strategies.text(min_size=1),
values=strategies.integers(),
min_size=1))
def test_signal_last_truth(d):
def test_find_dictionary():
smallest = minimal(
dictionaries(keys=integers(), values=integers()),
lambda xs: any(kv[0] > kv[1] for kv in xs.items()),
)
assert len(smallest) == 1
class TestPropertyBasedSuite:
@pytest.mark.skip('example')
@settings(deadline=None, max_examples=100)
@given(
var_bin=strategies.binary(
5, 25).filter(lambda x: x != b'\x00\x00\x00\x00\x00'),
var_char=strategies.characters('S').filter(
lambda x: x not in ['@', '#', '$']),
var_text=strategies.text(
ascii_letters, min_size=10,
max_size=10).map(lambda x: x.lower()), # <<< map
var_rec=strategies.recursive(
strategies.integers()
| strategies.floats(),
lambda children: strategies.lists(children, min_size=3)
| strategies.dictionaries(
strategies.text(printable), children, min_size=3),
max_leaves=10),
var_dt_lists=strategies.integers(1, 5).flatmap(
lambda x: strategies.lists(strategies.datetimes(), x, x)))
@pytest.mark.asyncio
async def test_case_strategies(self, var_bin, var_char, var_text, var_rec,
var_dt_lists):
print()
print(var_bin)
print(var_char)
print(var_text)
print(var_rec)
print(var_dt_lists)
print('-' * 25)
# bad behaviour with verkey field - hypothesis resend txns with the same verkey that cause rejects
@settings(deadline=None, max_examples=250, verbosity=Verbosity.debug)
@given(reqid=strategies.integers(min_value=1, max_value=max_size),
dest=strategies.text(ascii_letters, min_size=16, max_size=16),
alias=strategies.text(min_size=1, max_size=10000))
@pytest.mark.asyncio
async def test_case_nym(self, pool_handler, wallet_handler,
get_default_trustee, reqid, dest, alias):
trustee_did, trustee_vk = get_default_trustee
req = {
'protocolVersion': 2,
'reqId': reqid,
'identifier': trustee_did,
'operation': {
'type': '1',
'dest': base58.b58encode(dest).decode(),
'role': '201',
'alias': alias
}
}
print(req)
res = json.loads(await ledger.sign_and_submit_request(
pool_handler, wallet_handler, trustee_did, json.dumps(req)))
print(res)
assert res['op'] == 'REPLY'
@settings(deadline=None, max_examples=250)
@given(reqid=strategies.integers(min_value=1, max_value=max_size),
xhash=strategies.text().map(
lambda x: hashlib.sha256(x.encode()).hexdigest()),
key=strategies.text(min_size=1, alphabet=printable),
value=strategies.text(min_size=1, alphabet=printable),
enc=strategies.text(min_size=1))
@pytest.mark.asyncio
async def test_case_attrib(self, pool_handler, wallet_handler,
get_default_trustee, reqid, xhash, key, value,
enc):
trustee_did, trustee_vk = get_default_trustee
target_did, target_vk = await did.create_and_store_my_did(
wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did,
target_did, target_vk)
assert res['op'] == 'REPLY'
req_base = {
'protocolVersion': 2,
'identifier': target_did,
'operation': {
'type': '100',
'dest': target_did
}
}
req1 = copy.deepcopy(req_base)
req1['reqId'] = reqid + 1
req1['operation']['hash'] = xhash
res1 = json.loads(await ledger.sign_and_submit_request(
pool_handler, wallet_handler, target_did, json.dumps(req1)))
print(req1)
print(res1)
assert res1['op'] == 'REPLY'
req2 = copy.deepcopy(req_base)
req2['reqId'] = reqid + 2
req2['operation']['raw'] = json.dumps({key: value})
res2 = json.loads(await ledger.sign_and_submit_request(
pool_handler, wallet_handler, target_did, json.dumps(req2)))
print(req2)
print(res2)
assert res2['op'] == 'REPLY'
req3 = copy.deepcopy(req_base)
req3['reqId'] = reqid + 3
req3['operation']['enc'] = enc
res3 = json.loads(await ledger.sign_and_submit_request(
pool_handler, wallet_handler, target_did, json.dumps(req3)))
print(req3)
print(res3)
assert res3['op'] == 'REPLY'
@settings(deadline=None, max_examples=250)
@given(reqid=strategies.integers(min_value=1, max_value=max_size),
version=strategies.floats(min_value=0.1, max_value=999.999),
name=strategies.text(min_size=1),
attrs=strategies.lists(strategies.text(min_size=1),
min_size=1,
max_size=125))
@pytest.mark.asyncio
async def test_case_schema(self, pool_handler, wallet_handler,
get_default_trustee, reqid, version, name,
attrs):
trustee_did, trustee_vk = get_default_trustee
creator_did, creator_vk = await did.create_and_store_my_did(
wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did,
creator_did, creator_vk, None, 'TRUSTEE')
assert res['op'] == 'REPLY'
req = {
'protocolVersion': 2,
'reqId': reqid,
'identifier': creator_did,
'operation': {
'type': '101',
'data': {
'version': str(version),
'name': name,
'attr_names': attrs
}
}
}
res = json.loads(await ledger.sign_and_submit_request(
pool_handler, wallet_handler, creator_did, json.dumps(req)))
print(req)
print(res)
assert res['op'] == 'REPLY'
@settings(deadline=None, max_examples=250, verbosity=Verbosity.verbose)
@given(reqid=strategies.integers(min_value=1, max_value=max_size),
tag=strategies.text(printable, min_size=1),
primary=strategies.recursive(
strategies.dictionaries(strategies.text(printable, min_size=1),
strategies.text(printable, min_size=1),
min_size=1,
max_size=3),
lambda x: strategies.dictionaries(strategies.text(printable,
min_size=1),
x,
min_size=1,
max_size=3)))
@pytest.mark.asyncio
async def test_case_cred_def(self, pool_handler, wallet_handler,
get_default_trustee, reqid, tag, primary):
trustee_did, trustee_vk = get_default_trustee
creator_did, creator_vk = await did.create_and_store_my_did(
wallet_handler, '{}')
res = await send_nym(pool_handler, wallet_handler, trustee_did,
creator_did, creator_vk, None, 'TRUSTEE')
assert res['op'] == 'REPLY'
schema_id, res = await send_schema(pool_handler,
wallet_handler, creator_did,
random_string(10), '1.0',
json.dumps(['attribute']))
assert res['op'] == 'REPLY'
await asyncio.sleep(1)
res = await get_schema(pool_handler, wallet_handler, creator_did,
schema_id)
schema_id, schema_json = await ledger.parse_get_schema_response(
json.dumps(res))
req = {
'protocolVersion': 2,
'reqId': reqid,
'identifier': creator_did,
'operation': {
'type': '102',
'ref': json.loads(schema_json)['seqNo'],
'signature_type': 'CL',
'tag': tag,
'data': {
'primary': primary
}
}
}
res = json.loads(await ledger.sign_and_submit_request(
pool_handler, wallet_handler, creator_did, json.dumps(req)))
print(res)
assert res['op'] == 'REPLY'
@settings(deadline=None, max_examples=10000, verbosity=Verbosity.verbose)
@given(values=strategy_for_op_and_data_cases())
@pytest.mark.asyncio
async def test_case_random_req_op(self, pool_handler, wallet_handler,
get_default_trustee, values):
trustee_did, trustee_vk = get_default_trustee
req = {
'protocolVersion': 2,
'reqId': values[0],
'identifier': trustee_did,
'operation': values[2]
}
# client-side validation
with pytest.raises(IndyError):
await ledger.sign_and_submit_request(pool_handler, wallet_handler,
trustee_did, json.dumps(req))
@settings(deadline=None, max_examples=10000, verbosity=Verbosity.verbose)
@given(values=strategy_for_op_and_data_cases())
@pytest.mark.asyncio
async def test_case_random_req_data(self, pool_handler, wallet_handler,
get_default_trustee, values):
trustee_did, trustee_vk = get_default_trustee
req = {
'protocolVersion': 2,
'reqId': values[0],
'identifier': trustee_did,
'operation': {
'type': str(values[1]),
'data': values[2]
}
}
res = json.loads(await ledger.sign_and_submit_request(
pool_handler, wallet_handler, trustee_did, json.dumps(req)))
# server-side static validation
try:
assert res['op'] == 'REQNACK'
except KeyError:
res = {k: json.loads(v) for k, v in res.items()}
assert all([v['op'] == 'REQNACK' for k, v in res.items()])
@settings(deadline=None, max_examples=10000, verbosity=Verbosity.verbose)
@given(amount=strategies.integers(min_value=0, max_value=max_size),
seqno=strategies.integers(min_value=0, max_value=max_size),
signatures=strategies.text(ascii_letters,
min_size=0,
max_size=max_size),
reqid=strategies.integers(min_value=1, max_value=max_size))
@pytest.mark.asyncio
async def test_case_invalid_payment(self, payment_init, pool_handler,
wallet_handler, get_default_trustee,
amount, seqno, signatures, reqid):
libsovtoken_payment_method = 'sov'
trustee_did, _ = get_default_trustee
try:
address1 = await payment.create_payment_address(
wallet_handler, libsovtoken_payment_method,
json.dumps({'seed': '0000000000000000000000000Wallet1'}))
address2 = await payment.create_payment_address(
wallet_handler, libsovtoken_payment_method,
json.dumps({'seed': '0000000000000000000000000Wallet2'}))
except IndyError:
address1 = 'pay:sov:aRczGoccsHV7mNJgpBVYwCveytvyL8JBa1X28GFSwD44m76eE'
address2 = 'pay:sov:H8v7bJwwKEnEUjd5dGec3oTbLMwgFLUVHL7kDKtVqBtLaQ2JG'
req = {
'operation': {
'type': '10001',
'outputs': [{
'address': address2.split(':')[-1],
'amount': amount
}],
'inputs': [{
'address': address1.split(':')[-1],
'seqNo': seqno
}],
'signatures': [signatures]
},
'reqId': reqid,
'protocolVersion': 2,
'identifier': trustee_did
}
print(req)
res = json.loads(await ledger.sign_and_submit_request(
pool_handler, wallet_handler, trustee_did, json.dumps(req)))
print(res)
assert res['op'] == 'REQNACK'
class StatusMagicFolder(AsyncTestCase):
"""
Tests for ``magic-folder status``.
"""
@defer.inlineCallbacks
def test_command_exists(self):
"""
There is a status command at all.
"""
outcome = yield cli(
FilePath(self.mktemp()),
[b"status", b"--help"],
)
addOutcomeDetails(self, outcome)
self.assertThat(
outcome.succeeded(),
Equals(True),
)
@defer.inlineCallbacks
def test_command_error(self):
"""
If the status command encounters an error it reports it on stderr and
exits with a non-zero code.
"""
outcome = yield cli(
# Pass in a fanciful node directory to provoke a predictable
# error.
FilePath(self.mktemp()),
[b"status"],
)
self.expectThat(
outcome.succeeded(),
Equals(False),
)
self.expectThat(
outcome.stderr,
Contains(b"does not exist"),
)
@defer.inlineCallbacks
def test_command_success(self):
"""
If the status command succeeds it reports some information on stdout.
"""
client_fixture = SelfConnectedClient(reactor)
yield client_fixture.use_on(self)
# Create a magic folder so that we can inspect its status.
magic_folder = client_fixture.tempdir.child(u"magic-folder")
outcome = yield cli(
client_fixture.node_directory,
[
b"create",
b"magic-folder-alias:",
b"member-alias",
magic_folder.asBytesMode().path,
],
)
self.assertThat(
outcome.succeeded(),
Equals(True),
)
assigner = SameProcessStreamEndpointAssigner()
assigner.setUp()
self.addCleanup(assigner.tearDown)
ignored, endpoint_description = assigner.assign(reactor)
# Start the magic folder service after creating the magic folder so it
# will be noticed.
magic_folder_service = magic_folder_cli.MagicFolderService.from_node_directory(
reactor,
client_fixture.node_directory.path,
endpoint_description,
)
magic_folder_service.startService()
self.addCleanup(magic_folder_service.stopService)
outcome = yield cli(
client_fixture.node_directory,
[b"status"],
)
addOutcomeDetails(self, outcome)
self.assertThat(
outcome.succeeded(),
Equals(True),
)
@given(
folder_names(),
datetimes(),
dictionaries(
path_segments(),
tuples(just(u"filenode"), filenodes()),
),
# Laziness
path_segments(),
lists(queued_items()),
lists(queued_items()),
)
def test_formatting(
self,
folder_name,
now,
local_files,
remote_name,
upload_items,
download_items,
):
self.assertThat(
magic_folder_cli._format_status(
now,
Status(
folder_name,
local_files=local_files,
remote_files={remote_name: local_files},
folder_status=list(
status_for_item(kind, item) for (kind, items) in [
("upload", upload_items),
("download", download_items),
] for item in items),
),
),
IsInstance(unicode),
)
NON_NAMED_BIDICT_TYPES = one_of(t.NON_NAMED_BIDICT_TYPES)
ORDERED_MAPPING_TYPES = one_of(t.ORDERED_MAPPING_TYPES)
HASHABLE_MAPPING_TYPES = one_of(t.HASHABLE_MAPPING_TYPES)
ON_DUP_ACTIONS = one_of((DROP_NEW, DROP_OLD, RAISE))
ON_DUP = st.tuples(ON_DUP_ACTIONS, ON_DUP_ACTIONS, ON_DUP_ACTIONS).map(OnDup._make)
BOOLEANS = st.booleans()
# Combine a few different strategies together that generate atomic values
# that can be used to initialize test bidicts with. Including only None, bools, and ints
# provides enough coverage; including more just slows down example generation.
ATOMS = st.none() | BOOLEANS | st.integers()
PAIRS = st.tuples(ATOMS, ATOMS)
NON_MAPPINGS = ATOMS | st.iterables(ATOMS)
ALPHABET = tuple(chr(i) for i in range(0x10ffff) if chr(i).isidentifier())
VALID_NAMES = st.text(ALPHABET, min_size=1, max_size=16)
DICTS_KW_PAIRS = st.dictionaries(VALID_NAMES, ATOMS, max_size=MAX)
L_PAIRS = st.lists(PAIRS, max_size=MAX)
I_PAIRS = st.iterables(PAIRS, max_size=MAX)
FST_SND = (itemgetter(0), itemgetter(1))
L_PAIRS_NODUP = st.lists(PAIRS, unique_by=FST_SND, max_size=MAX)
I_PAIRS_NODUP = st.iterables(PAIRS, unique_by=FST_SND, max_size=MAX)
# Reserve a disjoint set of atoms as a source of values guaranteed not to have been
# inserted into a test bidict already.
DIFF_ATOMS = st.characters()
DIFF_PAIRS = st.tuples(DIFF_ATOMS, DIFF_ATOMS)
L_DIFF_PAIRS_NODUP = st.lists(DIFF_PAIRS, unique_by=FST_SND, min_size=1, max_size=MAX)
DIFF_ITEMS = st.tuples(L_PAIRS_NODUP, L_DIFF_PAIRS_NODUP)
RANDOMS = st.randoms(use_true_random=False)
SAME_ITEMS_DIFF_ORDER = st.tuples(
st.lists(PAIRS, unique_by=FST_SND, min_size=2, max_size=MAX), RANDOMS
).map(
from hypothesis import given
from hypothesis import strategies as st
from giap.consumer import Method, Operation
from giap.core import GIAP
@given(
st.one_of(st.integers(min_value=1), st.text()),
st.text(),
st.dictionaries(st.text(), st.text()),
st.one_of(st.none(),
st.ip_addresses().map(str)),
st.text(),
)
def test_track(mock_consumer, id_, name, properties, ip_address, token):
giap = GIAP(token, "")
giap.track(id_, name, properties, ip_address)
args = mock_consumer.send.call_args_list[-1][0]
assert args[0] == "/events"
assert args[2] == token
data = args[1]["events"][0]
assert data["$distinct_id"] == str(id_)
assert data["$name"] == name
assert isinstance(data["$time"], int)
assert "$lib" in data
assert "$lib_version" in data
assert headers_to_scrapy([{'name': 'Content-Type', 'value': 'text/html'}]) == html_headers
_primitive = (
st.floats(allow_infinity=False, allow_nan=False) |
st.booleans() |
st.text() |
st.none() |
st.integers()
)
_data = st.recursive(_primitive,
lambda children: (
children |
st.lists(children) |
st.tuples(children) |
st.dictionaries(st.text(), children) |
st.tuples(st.just('h'), children)
),
max_leaves=5,
)
_data_notuples = st.recursive(_primitive,
lambda children: (
children |
st.lists(children) |
st.dictionaries(st.text(), children)
),
max_leaves=5,
)
@given(_data, _data)
def dict_and_key(draw, keys=st.integers(), values=st.uuids()):
d = draw(st.dictionaries(keys, values, min_size=1))
key = draw(st.sampled_from(list(d.keys())))
return (d, key)
def homogeneous_dictionary(**kwargs):
"""Return a strategy which generates a dictionary of uniform key:value type."""
return index_types.flatmap(lambda s: hs.dictionaries(s(), s(), **kwargs))
def dict_node(draw, key=const_node(), value=const_node(), **kwargs):
items = draw(hs.dictionaries(key, value, **kwargs)).items()
node = nodes.Dict()
node.postinit(items)
return node
def test_map_empty():
m: Map[str, int] = map.empty
assert map.is_empty(m)
assert len(m) == 0
assert not m
def test_map_non_empty():
m: Map[str, int] = map.empty.add("test", 42)
assert not map.is_empty(m)
assert len(m) == 1
assert m
@given(st.dictionaries(keys=st.text(), values=st.integers()))
def test_map_create(xs: Dict[str, int]):
items: Iterable[Tuple[str, int]] = xs.items()
m = map.create(items)
assert len(m) == len(xs)
@given(st.dictionaries(keys=st.text(), values=st.integers()))
def test_map_of_seq(xs: Dict[str, int]):
items: ItemsView[str, int] = xs.items()
m = map.of_seq(items)
assert len(m) == len(xs)
@given(st.dictionaries(keys=st.text(), values=st.integers()))
def test_map_to_list_fluent(xs: Dict[str, int]):
def random_dictionary(**kwargs):
"""Return a strategy which generates a random list."""
return hs.dictionaries(primitive_values, primitive_values, **kwargs)
def test_produces_dictionaries_of_at_least_minimum_size():
t = find(ds.dictionaries(ds.booleans(), ds.integers(), min_size=2),
lambda x: True)
assert t == {False: 0, True: 0}
class TestAutoMonitoring:
@staticmethod
def assert_feature_data_correctness(feature_data, in_df, out_df):
"""Verifies that profiler type and reference are correct for column."""
col_type = feature_data.labels["col_type"]
source_df = in_df if col_type == "input" else out_df
assert feature_data.feature_name in source_df
# reconstruct reference distribution
reference_content = json.loads(feature_data.content)
reference = _verta_data_type._VertaDataType._from_dict(
reference_content)
# reconstruct profiler
profiler_name = feature_data.profiler_name
profiler_args = json.loads(feature_data.profiler_parameters)
feature_profiler = getattr(profiler, profiler_name)(**profiler_args)
# verify re-profiling column yields reference distribution
_, profile = feature_profiler.profile_column(
source_df,
feature_data.feature_name,
)
assert profile == reference
def test_non_df(self, model_version):
pd = pytest.importorskip("pandas")
with pytest.raises(TypeError):
model_version.log_training_data_profile(
"abc",
pd.DataFrame([1, 2, 3]),
)
with pytest.raises(TypeError):
model_version.log_training_data_profile(
pd.DataFrame([1, 2, 3]),
2,
)
# coerce out_df if Series
model_version.log_training_data_profile(
pd.DataFrame([1, 2, 3], columns=["in"]),
pd.Series([1, 2, 3], name="out"),
)
@hypothesis.settings(deadline=None) # building DataFrames can be slow
@hypothesis.given(
df=strategies.simple_dataframes(), # pylint: disable=no-value-for-parameter
labels=st.dictionaries(st.text(), st.text()),
)
def test_create_summaries(self, df, labels):
"""Unit test for the exact expected output of discrete & continuous columns."""
pytest.importorskip("numpy")
# missing
for col in ["continuous", "discrete"]:
feature_data = RegisteredModelVersion._create_missing_value_summary(
df,
col,
labels,
)
_sample = profiler.MissingValuesProfiler([col]).profile(df)
_histogram = list(_sample.values())[0]
assert feature_data.feature_name == col
assert feature_data.profiler_name == "MissingValuesProfiler"
assert json.loads(feature_data.profiler_parameters) == {
"columns": [col]
}
assert feature_data.summary_type_name == "verta.discreteHistogram.v1"
assert feature_data.labels == labels
assert json.loads(feature_data.content) == _histogram._as_dict()
# continuous distribution
feature_data = RegisteredModelVersion._create_continuous_histogram_summary(
df,
"continuous",
labels,
)
_sample = profiler.ContinuousHistogramProfiler(["continuous"
]).profile(df)
_histogram = list(_sample.values())[0]
assert feature_data.feature_name == "continuous"
assert feature_data.profiler_name == "ContinuousHistogramProfiler"
assert json.loads(feature_data.profiler_parameters) == {
"columns": ["continuous"],
"bins": _histogram._bucket_limits,
}
assert feature_data.summary_type_name == "verta.floatHistogram.v1"
assert feature_data.labels == labels
assert json.loads(feature_data.content) == _histogram._as_dict()
# discrete distribution
feature_data = RegisteredModelVersion._create_discrete_histogram_summary(
df,
"discrete",
labels,
)
_sample = profiler.BinaryHistogramProfiler(["discrete"]).profile(df)
_histogram = list(_sample.values())[0]
assert feature_data.feature_name == "discrete"
assert feature_data.profiler_name == "BinaryHistogramProfiler"
assert json.loads(feature_data.profiler_parameters) == {
"columns": ["discrete"]
}
assert feature_data.summary_type_name == "verta.discreteHistogram.v1"
assert feature_data.labels == labels
assert json.loads(feature_data.content) == _histogram._as_dict()
@hypothesis.settings(deadline=None) # building DataFrames can be slow
@hypothesis.given(
df=strategies.dataframes( # pylint: disable=no-value-for-parameter
min_rows=1,
min_cols=2,
), )
def test_compute_training_data_profile(self, df):
"""Unit test for helper functions handling DFs of various sizes."""
in_df, out_df = df.iloc[:, :-1], df.iloc[:, [-1]]
feature_data_list = RegisteredModelVersion._compute_training_data_profile(
in_df,
out_df,
)
for feature_data in feature_data_list:
self.assert_feature_data_correctness(feature_data, in_df, out_df)
@hypothesis.settings(deadline=None) # building DataFrames can be slow
@hypothesis.given(
df=strategies.dataframes( # pylint: disable=no-value-for-parameter
min_rows=1,
min_cols=2,
), )
def test_collect_feature_data_and_vis_attributes(self, df):
"""Unit test that attributes pre-logging are the correct format."""
in_df, out_df = df.iloc[:, :-1], df.iloc[:, [-1]]
feature_data_list = RegisteredModelVersion._compute_training_data_profile(
in_df,
out_df,
)
feature_data_attrs = (
RegisteredModelVersion._collect_feature_data_and_vis_attributes(
feature_data_list, ))
for key, val in feature_data_attrs.items():
if key.startswith(_deployable_entity._FEATURE_DATA_ATTR_PREFIX):
feature_data = _utils.json_to_proto(val,
FeatureDataInModelVersion)
self.assert_feature_data_correctness(feature_data, in_df,
out_df)
if feature_data.profiler_name == "MissingValuesProfiler":
sample_key = feature_data.feature_name + "MissingValues"
else:
sample_key = feature_data.feature_name + "Distribution"
sample_key = (
_deployable_entity._TRAINING_DATA_ATTR_PREFIX +
RegisteredModelVersion._normalize_attribute_key(sample_key)
)
assert feature_data_attrs[sample_key] == json.loads(
feature_data.content)
def test_profile_training_data(self, model_version):
"""Integration test for logging attributes with correct structure."""
pd = pytest.importorskip("pandas")
np = pytest.importorskip("numpy")
cont_col = np.random.random(100)
discrete_col = np.random.choice(5, 100)
string_discrete_col = np.random.choice(["a", "b", "c", "d", "e"],
size=100)
string_freeform_col = [
uuid.uuid4().hex.upper()[0:10] for _ in range(100)
]
other_col = [datetime.datetime.now() for x in range(100)]
output_col = np.random.choice(2, 100)
col_names = [
"Continuous_Numeric",
"Discrete_Numeric",
"Discrete_String",
"Freeform_String",
"Other",
"Output_Col",
]
supported_col_names = [
"Continuous_Numeric", "Discrete_Numeric", "Output_Col"
]
# create dataframes
df = pd.DataFrame(
list(
zip(
cont_col,
discrete_col,
string_discrete_col,
string_freeform_col,
other_col,
output_col,
)),
columns=col_names,
)
# log to model version with new method
model_version.log_training_data_profile(
df.loc[:, df.columns != "Output_Col"],
pd.DataFrame(df["Output_Col"]),
)
# get back attributes to validate
attributes = model_version.get_attributes()
key = _deployable_entity._FEATURE_DATA_ATTR_PREFIX + "{}"
discrete_col_missing_summary = _utils.json_to_proto(
model_version.get_attribute(key.format("2")),
FeatureDataInModelVersion, # missing value
)
discrete_col_distribution_summary = _utils.json_to_proto(
model_version.get_attribute(key.format("3")),
FeatureDataInModelVersion, # missing value
)
# missing value, distribution summary for each supported column +
# equal number of attributes for visualization
assert len(attributes.keys()) == len(supported_col_names) * 2 * 2
assert (discrete_col_distribution_summary.summary_type_name ==
"verta.discreteHistogram.v1")
assert (discrete_col_distribution_summary.profiler_name ==
"BinaryHistogramProfiler")
assert (len(
json.loads(discrete_col_distribution_summary.content)
["discreteHistogram"]["buckets"]) <= 5)
assert (discrete_col_missing_summary.summary_type_name ==
"verta.discreteHistogram.v1")
assert discrete_col_missing_summary.profiler_name == "MissingValuesProfiler"
assert (len(
json.loads(discrete_col_missing_summary.content)
["discreteHistogram"]["buckets"]) == 2)
# reference distribution attributes can be fetched back as histograms
for col in supported_col_names:
key = _deployable_entity._TRAINING_DATA_ATTR_PREFIX + col + "Distribution"
histogram = model_version.get_attribute(key)
assert isinstance(histogram, _verta_data_type._VertaDataType)
def test_reconstruct_profilers(self, model_version):
"""Profiler and ref distribution can be reconstructed from attr."""
np = pytest.importorskip("numpy")
pd = pytest.importorskip("pandas")
in_col = "continuous"
out_col = "discrete"
num_rows = 24
df = pd.DataFrame(
{
in_col: np.random.random(size=num_rows) * 10,
out_col: range(num_rows),
}, )
model_version.log_training_data_profile(
in_df=df[[in_col]],
out_df=df[[out_col]],
)
for key, val in model_version.get_attributes().items():
if key.startswith(_deployable_entity._FEATURE_DATA_ATTR_PREFIX):
feature_data = val
reference_content = json.loads(feature_data["content"])
reference = _verta_data_type._VertaDataType._from_dict(
reference_content)
profiler_name = feature_data["profiler_name"]
profiler_args = json.loads(feature_data["profiler_parameters"])
feature_profiler = getattr(profiler,
profiler_name)(**profiler_args)
if isinstance(feature_profiler,
profiler.MissingValuesProfiler):
point = None
elif isinstance(feature_profiler,
profiler.BinaryHistogramProfiler):
point = np.random.randint(num_rows)
elif isinstance(feature_profiler,
profiler.ContinuousHistogramProfiler):
point = np.random.random() * 10
else:
raise TypeError(
"this test doesn't support profiler type {}".format(
type(feature_profiler)))
point_profile = feature_profiler.profile_point(
point, reference)
assert point_profile._type_string(
) == feature_data["summary_type_name"]
def test_minimize_multi_key_dicts():
assert find(
dictionaries(keys=booleans(), values=booleans()),
bool
) == {False: False}
def test_decimals():
assert minimal(ds.decimals(), lambda f: f.is_finite() and f >= 1) == 1
def test_non_float_decimal():
minimal(ds.decimals(), lambda d: d.is_finite() and decimal.Decimal(float(d)) != d)
def test_produces_dictionaries_of_at_least_minimum_size():
t = minimal(
ds.dictionaries(ds.booleans(), ds.integers(), min_size=2), lambda x: True
)
assert t == {False: 0, True: 0}
@given(ds.dictionaries(ds.integers(), ds.integers(), max_size=5))
@settings(max_examples=50)
def test_dictionaries_respect_size(d):
assert len(d) <= 5
@given(ds.dictionaries(ds.integers(), ds.integers(), max_size=0))
@settings(max_examples=50)
def test_dictionaries_respect_zero_size(d):
assert len(d) <= 5
@given(ds.lists(ds.none(), max_size=5))
def test_none_lists_respect_max_size(ls):
assert len(ls) <= 5
def extend_fn(children):
lists_st = st.lists(children)
dicts_st = st.dictionaries(encodable_text, children)
return lists_st | dicts_st
indicating that it is the currently selected volume.
"""
dvol = VoluminousOptions()
dvol.parseOptions(ARGS + ["-p", self.tmpdir.path, "init", "foo"])
dvol.parseOptions(ARGS + ["-p", self.tmpdir.path, "init", "bar"])
dvol.parseOptions(ARGS + ["-p", self.tmpdir.path, "rm", "-f", "bar"])
dvol.parseOptions(ARGS + ["-p", self.tmpdir.path, "list"])
header, rest = self._parse_list_output(dvol)
expected_volumes = [["foo", "master"]]
self.assertEqual(
sorted(expected_volumes),
sorted(rest),
)
@skip_if_go_version
@given(volumes=dictionaries(
volume_names(), branch_names(), min_size=1).map(items))
def test_branch_multi_volumes(self, volumes):
"""
Always show the last checked-out branch for all volumes in ``list``.
"""
tmpdir = FilePath(self.mktemp())
tmpdir.makedirs()
dvol = VoluminousOptions()
for volume, branch in volumes:
dvol.parseOptions(ARGS + ["-p", tmpdir.path, "init", volume])
dvol.parseOptions(ARGS + ["-p", tmpdir.path, "commit", "-m", "hello"])
dvol.parseOptions(ARGS + ["-p", tmpdir.path, "checkout", "-b", branch])
dvol.parseOptions(ARGS + ["-p", tmpdir.path, "list"])
lines = dvol.voluminous.getOutput()[-1].split("\n")
get_integer_bounds,
get_number_bounds,
get_type,
is_valid,
merged,
resolve_all_refs,
)
JSON_STRATEGY: st.SearchStrategy[JSONType] = st.recursive(
st.none()
| st.booleans()
| st.integers()
| st.floats(allow_nan=False, allow_infinity=False).map(lambda x: x or 0.0)
| st.text(),
lambda strategy: st.lists(strategy, max_size=3)
| st.dictionaries(st.text(), strategy, max_size=3),
)
def merged_as_strategies(schemas: List[Schema]) -> st.SearchStrategy[JSONType]:
assert schemas, "internal error: must pass at least one schema to merge"
if len(schemas) == 1:
return from_schema(schemas[0])
# Try to merge combinations of strategies.
strats = []
combined: Set[str] = set()
inputs = {encode_canonical_json(s): s for s in schemas}
for group in itertools.chain.from_iterable(
itertools.combinations(inputs, n)
for n in range(len(inputs), 0, -1)):
if combined.issuperset(group):
for data in data_type:
with pytest.raises(TypeError):
s.state = data
if isinstance(t, str):
with pytest.raises(ValueError):
s.state = t
for val in states._stage_state_values.keys():
s.state = val
# ------------------------------------------------------------------------------
#
@given(l=st.lists(st.text()),
d=st.dictionaries(st.text(), st.text()))
def test_stage_post_exec_assignment(l, d):
s = Stage()
def func():
return True
with pytest.raises(TypeError):
s.post_exec = l
with pytest.raises(TypeError):
s.post_exec = d
s.post_exec = func
class TestIntegration(unittest.TestCase):
@given(filepath())
def test_release(self, project_root):
argv = [
'release', '--platform-config', '../path/to/config',
'--release-data ami_id=ami-z9876', '42'
]
with patch('cdflow.docker') as docker, \
patch('cdflow.os') as os, \
patch('cdflow.abspath') as abspath, \
patch('cdflow.open') as open_:
abs_path_to_config = '/root/path/to/config'
abspath.return_value = abs_path_to_config
image = MagicMock(spec=Image)
docker.from_env.return_value.images.pull.return_value = image
image.attrs = {'RepoDigests': ['hash']}
docker.from_env.return_value.containers.run.return_value.attrs = {
'State': {
'ExitCode': 0,
}
}
os.getcwd.return_value = project_root
os.getenv.return_value = False
config_file = MagicMock(spec=TextIOWrapper)
config_file.read.return_value = yaml.dump({'team': 'a-team'})
open_.return_value.__enter__.return_value = config_file
exit_status = main(argv)
assert exit_status == 0
docker.from_env.assert_called_once()
docker.from_env.return_value.images.pull.assert_called_once_with(
'mergermarket/cdflow-commands:latest')
docker.from_env.return_value.containers.run.assert_called_once_with(
'mergermarket/cdflow-commands:latest',
command=argv,
environment={
'AWS_ACCESS_KEY_ID': ANY,
'AWS_SECRET_ACCESS_KEY': ANY,
'AWS_SESSION_TOKEN': ANY,
'FASTLY_API_KEY': ANY,
'GITHUB_TOKEN': ANY,
'CDFLOW_IMAGE_DIGEST': 'hash',
'LOGENTRIES_ACCOUNT_KEY': ANY,
'DATADOG_APP_KEY': ANY,
'DATADOG_API_KEY': ANY,
},
detach=True,
volumes={
project_root: {
'bind': project_root,
'mode': 'rw',
},
abs_path_to_config: {
'bind': abs_path_to_config,
'mode': 'ro',
},
'/var/run/docker.sock': {
'bind': '/var/run/docker.sock',
'mode': 'ro',
},
},
working_dir=project_root)
docker.from_env.return_value.containers.run.return_value.logs.\
assert_called_once_with(
stream=True,
follow=True,
stdout=True,
stderr=True,
)
@given(
fixed_dictionaries({
'project_root':
filepath(),
'environment':
dictionaries(
keys=text(alphabet=printable, min_size=1, max_size=3),
values=text(alphabet=printable, min_size=1, max_size=3),
max_size=3,
),
'image_id':
image_id(),
}))
def test_release_with_pinned_command_image(self, fixtures):
argv = ['release', '42', '--platform-config', 'path/to/config']
project_root = fixtures['project_root']
environment = fixtures['environment']
pinned_image_id = fixtures['image_id']
environment['CDFLOW_IMAGE_ID'] = pinned_image_id
with patch('cdflow.docker') as docker, \
patch('cdflow.os') as os, \
patch('cdflow.abspath') as abspath, \
patch('cdflow.open') as open_:
abs_path_to_config = '/root/path/to/config'
abspath.return_value = abs_path_to_config
image = MagicMock(spec=Image)
docker.from_env.return_value.images.pull.return_value = image
image.attrs = {'RepoDigests': ['hash']}
docker.from_env.return_value.containers.run.return_value.attrs = {
'State': {
'ExitCode': 0,
}
}
os.getcwd.return_value = project_root
os.getenv.return_value = False
os.environ = environment
config_file = MagicMock(spec=TextIOWrapper)
config_file.read.return_value = yaml.dump({'team': 'a-team'})
open_.return_value.__enter__.return_value = config_file
exit_status = main(argv)
assert exit_status == 0
docker.from_env.return_value.images.pull.assert_called_once_with(
pinned_image_id)
docker.from_env.return_value.containers.run.assert_called_once_with(
pinned_image_id,
command=argv,
environment={
'AWS_ACCESS_KEY_ID': ANY,
'AWS_SECRET_ACCESS_KEY': ANY,
'AWS_SESSION_TOKEN': ANY,
'FASTLY_API_KEY': ANY,
'GITHUB_TOKEN': ANY,
'CDFLOW_IMAGE_DIGEST': 'hash',
'LOGENTRIES_ACCOUNT_KEY': ANY,
'DATADOG_APP_KEY': ANY,
'DATADOG_API_KEY': ANY,
},
detach=True,
volumes={
project_root: {
'bind': project_root,
'mode': 'rw',
},
abs_path_to_config: {
'bind': abs_path_to_config,
'mode': 'ro',
},
'/var/run/docker.sock': {
'bind': '/var/run/docker.sock',
'mode': 'ro',
},
},
working_dir=project_root)
@given(
fixed_dictionaries({
'project_root':
filepath(),
's3_bucket_and_key':
s3_bucket_and_key(),
'release_bucket':
text(
alphabet=VALID_ALPHABET,
min_size=3,
max_size=5,
),
}))
def test_classic_deploy(self, fixtures):
argv = ['deploy', 'aslive', '42']
with patch('cdflow.Session') as Session, \
patch('cdflow.BytesIO') as BytesIO, \
patch('cdflow.docker') as docker, \
patch('cdflow.os') as os, \
patch('cdflow.open') as open_:
s3_resource = Mock()
image_digest = 'sha:12345asdfg'
s3_resource.Object.return_value.metadata = {
'cdflow_image_digest': image_digest
}
Session.return_value.resource.return_value = s3_resource
BytesIO.return_value.__enter__.return_value.read.return_value = '''
{{
"release-bucket": "{}",
"classic-metadata-handling": true
}}
'''.format(fixtures['release_bucket'])
config_file = MagicMock(spec=TextIOWrapper)
config_file.read.return_value = yaml.dump({
'account-scheme-url':
's3://{}/{}'.format(*fixtures['s3_bucket_and_key']),
'team':
'a-team',
})
open_.return_value.__enter__.return_value = config_file
docker_client = MagicMock(spec=DockerClient)
docker.from_env.return_value = docker_client
docker.from_env.return_value.containers.run.return_value.attrs = {
'State': {
'ExitCode': 0,
}
}
project_root = fixtures['project_root']
os.getcwd.return_value = project_root
exit_status = main(argv)
assert exit_status == 0
s3_resource.Object.assert_any_call(
fixtures['s3_bucket_and_key'][0],
fixtures['s3_bucket_and_key'][1],
)
docker_client.containers.run.assert_called_once_with(
image_digest,
command=argv,
environment=ANY,
detach=True,
volumes={
project_root: ANY,
'/var/run/docker.sock': ANY
},
working_dir=project_root,
)
docker.from_env.return_value.containers.run.return_value.logs.\
assert_called_once_with(
stream=True,
follow=True,
stdout=True,
stderr=True,
)
@given(
fixed_dictionaries({
'project_root':
filepath(),
's3_bucket_and_key':
s3_bucket_and_key(),
'release_bucket':
text(
alphabet=VALID_ALPHABET,
min_size=3,
max_size=5,
),
'team_name':
text(
alphabet=VALID_ALPHABET,
min_size=3,
max_size=5,
),
'component_name':
text(
alphabet=VALID_ALPHABET,
min_size=3,
max_size=5,
),
}))
def test_deploy(self, fixtures):
version = '42'
component_name = fixtures['component_name']
argv = ['deploy', 'aslive', version, '--component', component_name]
with patch('cdflow.Session') as Session, \
patch('cdflow.BytesIO') as BytesIO, \
patch('cdflow.docker') as docker, \
patch('cdflow.os') as os, \
patch('cdflow.open') as open_:
s3_resource = Mock()
image_digest = 'sha:12345asdfg'
s3_resource.Object.return_value.metadata = {
'cdflow_image_digest': image_digest
}
Session.return_value.resource.return_value = s3_resource
BytesIO.return_value.__enter__.return_value.read.return_value = '''
{{
"release-bucket": "{}"
}}
'''.format(fixtures['release_bucket'])
config_file = MagicMock(spec=TextIOWrapper)
config_file.read.return_value = yaml.dump({
'account-scheme-url':
's3://{}/{}'.format(*fixtures['s3_bucket_and_key']),
'team':
fixtures['team_name'],
})
open_.return_value.__enter__.return_value = config_file
docker_client = MagicMock(spec=DockerClient)
docker.from_env.return_value = docker_client
docker.from_env.return_value.containers.run.return_value.attrs = {
'State': {
'ExitCode': 0,
}
}
project_root = fixtures['project_root']
os.getcwd.return_value = project_root
exit_status = main(argv)
assert exit_status == 0
s3_resource.Object.assert_any_call(
fixtures['s3_bucket_and_key'][0],
fixtures['s3_bucket_and_key'][1],
)
s3_resource.Object.assert_any_call(
fixtures['release_bucket'],
'{}/{}/{}-{}.zip'.format(
fixtures['team_name'],
component_name,
component_name,
version,
),
)
docker_client.containers.run.assert_called_once_with(
image_digest,
command=argv,
environment=ANY,
detach=True,
volumes={
project_root: ANY,
'/var/run/docker.sock': ANY
},
working_dir=project_root,
)
docker.from_env.return_value.containers.run.return_value.logs.\
assert_called_once_with(
stream=True,
follow=True,
stdout=True,
stderr=True,
)
@given(lists(elements=text(alphabet=printable, max_size=3), max_size=3))
def test_invalid_arguments_passed_to_container_to_handle(self, argv):
with patch('cdflow.docker') as docker, \
patch('cdflow.os') as os, \
patch('cdflow.open') as open_:
account_id = '1234567890'
config_file = MagicMock(spec=TextIOWrapper)
config_file.read.return_value = json.dumps(
{'platform_config': {
'account_id': account_id
}})
open_.return_value.__enter__.return_value = config_file
error = ContainerError(container=CDFLOW_IMAGE_ID,
exit_status=1,
command=argv,
image=CDFLOW_IMAGE_ID,
stderr='help text')
docker.from_env.return_value.containers.run.side_effect = error
os.path.abspath.return_value = '/'
exit_status = main(argv)
assert exit_status == 1
docker.from_env.return_value.containers.run.assert_called_once_with(
CDFLOW_IMAGE_ID,
command=argv,
environment=ANY,
detach=True,
volumes=ANY,
working_dir=ANY)
text,
)
import superintendent.prioritisation
from superintendent.distributed import SemiSupervisor
primitive_strategy = text() | integers() | floats(allow_nan=False) | booleans()
guaranteed_dtypes = (
boolean_dtypes()
| integer_dtypes()
| floating_dtypes()
| unicode_string_dtypes()
)
container_strategy = dictionaries(text(), primitive_strategy) | lists(
primitive_strategy
)
nested_strategy = recursive(
container_strategy,
lambda children: lists(children) | dictionaries(text(), children),
)
container_strategy = dictionaries(text(), primitive_strategy) | lists(
primitive_strategy
)
nested_strategy = recursive(
container_strategy,
lambda children: lists(children) | dictionaries(text(), children),
def resolve_Counter(thing):
return st.dictionaries(
keys=st.from_type(thing.__args__[0]),
values=st.integers(),
).map(collections.Counter)
"""echo api testing
"""
import json
from string import printable
from hypothesis import strategies as st
from hypothesis import given
from django.test import Client
from .views import echo
json_data = st.recursive(
st.booleans() | st.floats() | st.text(printable),
lambda children: st.dictionaries(st.text(printable), children))
class TestEcho:
@given(json_data=json_data)
def test_echo_json_status_result(self, json_data, rf):
"""Testing echo api response status result is function correctly with json data
"""
data = {'null': json.dumps(json_data)}
request = rf.post('/echo/', data, content_type='application/json')
response = echo(request)
assert response.status_code == 200
response.render()
assert response.data == data
import horse.blen
import horse.types
words = st.integers(0, horse.types.MAX_WORD)
bytes = st.integers(0, horse.types.MAX_BYTE)
nibbles = st.integers(0, horse.types.MAX_NIBBLE)
MIN_SIGNED_INT = -(1 << horse.types.WORD_N_BITS - 1)
MAX_SIGNED_INT = (1 << horse.types.WORD_N_BITS - 1) - 1
in_range_signed_integers = st.integers(MIN_SIGNED_INT, MAX_SIGNED_INT)
binary_operations = st.sampled_from(
tuple(horse.blen.BINARY_OPERATIONS.values()))
unary_operations = st.sampled_from(tuple(horse.blen.UNARY_OPERATIONS.values()))
memories = st.dictionaries(words, words).map(lambda d: defaultdict(int, d))
machines = st.builds(
horse.blen.Machine,
memory=memories,
registers=st.fixed_dictionaries(
{register: words
for register in horse.blen.Register}),
)
class Tests(unittest.TestCase):
@hypothesis.given(words)
def test_signed_integer_encode_decode(self, word):
there = horse.blen.word_to_signed_integer(word)
back_again = horse.blen.signed_integer_to_word(there)
assert word == back_again, there
@given(
st.integers(min_value=1),
st.integers(min_value=1),
st.integers(min_value=1))
def test_fix_window_size(w, h, blocksize):
if (w % blocksize == 1) or (h % blocksize == 1):
assert _adjust_block_size(w, h, blocksize) == blocksize + 1
else:
assert _adjust_block_size(w, h, blocksize) == blocksize
# Testing _check_crs_function from utils
crs_strategy = st.lists(
elements=st.dictionaries(
st.sampled_from(['crs']),
st.sampled_from(
('EPSG:32654', 'EPSG:25832', 'EPSG:3857')
),
min_size=1),
min_size=2, max_size=2)
@given(crs_strategy)
def test_check_crs(crs_list):
if crs_list[0]['crs'] != crs_list[1]['crs']:
with pytest.raises(RuntimeError):
_check_crs(crs_list)
# Testing _create_apply_mask function from utils
@given(arrays(np.uint16, (3, 8, 8),
elements=st.integers(
def test_decimals():
assert find(ds.decimals(), lambda f: f.is_finite() and f >= 1) == 1
def test_non_float_decimal():
find(ds.decimals(),
lambda d: d.is_finite() and decimal.Decimal(float(d)) != d)
def test_produces_dictionaries_of_at_least_minimum_size():
t = find(ds.dictionaries(ds.booleans(), ds.integers(), min_size=2),
lambda x: True)
assert t == {False: 0, True: 0}
@given(ds.dictionaries(ds.integers(), ds.integers(), max_size=5))
@settings(max_examples=50)
def test_dictionaries_respect_size(d):
assert len(d) <= 5
@given(ds.dictionaries(ds.integers(), ds.integers(), max_size=0))
@settings(max_examples=50)
def test_dictionaries_respect_zero_size(d):
assert len(d) <= 5
@given(ds.lists(ds.none(), max_size=5))
def test_none_lists_respect_max_size(ls):
assert len(ls) <= 5
