def run(data):
if not hasattr(data, 'can_reproduce_example_from_repr'):
data.can_reproduce_example_from_repr = True
with local_settings(self.settings):
with BuildContext(data, is_final=is_final):
with deterministic_PRNG():
args, kwargs = data.draw(self.search_strategy)
if expected_failure is not None:
text_repr[0] = arg_string(test, args, kwargs)
if print_example:
example = '%s(%s)' % (
test.__name__, arg_string(test, args, kwargs))
try:
ast.parse(example)
except SyntaxError:
data.can_reproduce_example_from_repr = False
report('Falsifying example: %s' % (example,))
elif current_verbosity() >= Verbosity.verbose:
report(
lambda: 'Trying example: %s(%s)' % (
test.__name__, arg_string(test, args, kwargs)))
with deterministic_PRNG():
return test(*args, **kwargs)
def print_step(self, step):
"""Print a step to the current reporter.
This is called right before a step is executed.
"""
self.step_count = getattr(self, u'step_count', 0) + 1
report(u'Step #%d: %s' % (self.step_count, nicerepr(step)))
def wrapped_test(*arguments, **kwargs):
# Tell pytest to omit the body of this function from tracebacks
__tracebackhide__ = True
settings = wrapped_test._hypothesis_internal_use_settings
random = get_random_for_wrapped_test(test, wrapped_test)
if infer in generator_kwargs.values():
hints = get_type_hints(test)
for name in [name for name, value in generator_kwargs.items()
if value is infer]:
if name not in hints:
raise InvalidArgument(
'passed %s=infer for %s, but %s has no type annotation'
% (name, test.__name__, name))
generator_kwargs[name] = st.from_type(hints[name])
processed_args = process_arguments_to_given(
wrapped_test, arguments, kwargs, generator_arguments,
generator_kwargs, argspec, test, settings
)
arguments, kwargs, test_runner, search_strategy = processed_args
execute_explicit_examples(
test_runner, test, wrapped_test, settings, arguments, kwargs
)
if settings.max_examples <= 0:
return
if not (
Phase.reuse in settings.phases or
Phase.generate in settings.phases
):
return
try:
perform_health_checks(
random, settings, test_runner, search_strategy)
state = StateForActualGivenExecution(
test_runner, search_strategy, test, settings, random)
state.run()
except:
generated_seed = \
wrapped_test._hypothesis_internal_use_generated_seed
if generated_seed is not None:
if running_under_pytest:
report((
'You can add @seed(%(seed)d) to this test or run '
'pytest with --hypothesis-seed=%(seed)d to '
'reproduce this failure.') % {
'seed': generated_seed},)
else:
report((
'You can add @seed(%d) to this test to reproduce '
'this failure.') % (generated_seed,))
raise
def note(value):
# type: (AnyStr) -> None
"""Report this value in the final execution."""
context = _current_build_context.value
if context is None:
raise InvalidArgument("Cannot make notes outside of a test")
context.notes.append(value)
if context.is_final or settings.default.verbosity >= Verbosity.verbose:
report(value)
def close(self):
any_failed = False
for task in self.tasks:
try:
task()
except:
any_failed = True
report(traceback.format_exc())
return any_failed
def note(value):
"""Report this value in the final execution."""
context = _current_build_context.value
if context is None:
raise InvalidArgument(
'Cannot make notes outside of a test')
context.notes.append(value)
if context.is_final:
report(value)
def run():
with BuildContext():
args, kwargs = search_strategy.reify(template)
text_version = arg_string(test, args, kwargs)
if print_example:
report(lambda: "Falsifying example: %s(%s)" % (test.__name__, text_version))
elif current_verbosity() >= Verbosity.verbose or always_print:
report(lambda: "Trying example: %s(%s)" % (test.__name__, text_version))
if record_repr is not None:
record_repr[0] = text_version
return test(*args, **kwargs)
def print_step(self, step):
rule, data = step
data_repr = {}
for k, v in data.items():
data_repr[k] = self.__pretty(v)
self.step_count = getattr(self, u'step_count', 0) + 1
report(u'%sstate.%s(%s)' % (
u'%s = ' % (self.upcoming_name(),) if rule.targets else u'',
rule.function.__name__,
u', '.join(u'%s=%s' % kv for kv in data_repr.items())
))
def __exit__(self, exc_type, exc_value, tb):
any_failed = False
for task in self.tasks:
try:
task()
except:
any_failed = True
report(traceback.format_exc())
self.assign_variable.__exit__(exc_type, exc_value, tb)
if exc_type is None and any_failed:
raise CleanupFailed()
def run(data):
with BuildContext(is_final=is_final):
args, kwargs = data.draw(search_strategy)
if print_example:
report(
lambda: 'Falsifying example: %s(%s)' % (
test.__name__, arg_string(test, args, kwargs)))
elif current_verbosity() >= Verbosity.verbose:
report(
lambda: 'Trying example: %s(%s)' % (
test.__name__, arg_string(test, args, kwargs)))
return test(*args, **kwargs)
def run(data):
from hypothesis.control import note
with BuildContext(is_final=is_final):
seed = data.draw(random_module()).seed
if seed != 0:
note("random.seed(%d)" % (seed,))
args, kwargs = data.draw(search_strategy)
if print_example:
report(lambda: "Falsifying example: %s(%s)" % (test.__name__, arg_string(test, args, kwargs)))
elif current_verbosity() >= Verbosity.verbose:
report(lambda: "Trying example: %s(%s)" % (test.__name__, arg_string(test, args, kwargs)))
return test(*args, **kwargs)
def note(value):
"""Report this value in the final execution.
Will always call string conversion function of the value even if not
printing for consistency of execution
"""
context = _current_build_context.value
if context is None:
raise InvalidArgument(
'Cannot make notes outside of build context')
context.notes.append(value)
if context.is_final:
report(value)
def print_step(self, step):
rule, data = step
data_repr = {}
for k, v in data.items():
data_repr[k] = self.__pretty(v)
self.step_count = getattr(self, u"step_count", 0) + 1
report(
u"%sstate.%s(%s)"
% (
u"%s = " % (self.upcoming_name(),) if rule.targets else u"",
rule.function.__name__,
u", ".join(u"%s=%s" % kv for kv in data_repr.items()),
)
)
def print_step(self, step):
if isinstance(step, ShuffleBundle):
return
rule, data = step
data_repr = {}
for k, v in data.items():
data_repr[k] = self.__pretty(v)
self.step_count = getattr(self, u'step_count', 0) + 1
report(u'Step #%d: %s%s(%s)' % (
self.step_count,
u'%s = ' % (self.upcoming_name(),) if rule.targets else u'',
rule.function.__name__,
u', '.join(u'%s=%s' % kv for kv in data_repr.items())
))
def print_step(self, step):
rule, data = step
data_repr = {}
for k, v in data.items():
if isinstance(v, VarReference):
data_repr[k] = v.name
else:
data_repr[k] = repr(v)
self.step_count = getattr(self, u'step_count', 0) + 1
report(u'Step #%d: %s%s(%s)' % (
self.step_count,
u'%s = ' % (self.upcoming_name(),) if rule.targets else u'',
rule.function.__name__,
u', '.join(u'%s=%s' % kv for kv in data_repr.items())
))
def execute_explicit_examples(
test_runner, test, wrapped_test, settings, arguments, kwargs
):
original_argspec = getfullargspec(test)
for example in reversed(getattr(
wrapped_test, 'hypothesis_explicit_examples', ()
)):
example_kwargs = dict(original_argspec.kwonlydefaults or {})
if example.args:
if len(example.args) > len(original_argspec.args):
raise InvalidArgument(
'example has too many arguments for test. '
'Expected at most %d but got %d' % (
len(original_argspec.args), len(example.args)))
example_kwargs.update(dict(zip(
original_argspec.args[-len(example.args):],
example.args
)))
else:
example_kwargs.update(example.kwargs)
if Phase.explicit not in settings.phases:
continue
example_kwargs.update(kwargs)
# Note: Test may mutate arguments and we can't rerun explicit
# examples, so we have to calculate the failure message at this
# point rather than than later.
example_string = '%s(%s)' % (
test.__name__, arg_string(test, arguments, example_kwargs)
)
with local_settings(settings):
try:
with BuildContext(None) as b:
verbose_report('Trying example: ' + example_string)
test_runner(
None, lambda data: test(*arguments, **example_kwargs)
)
except BaseException:
report('Falsifying example: ' + example_string)
for n in b.notes:
report(n)
raise
def run(data):
with BuildContext(data, is_final=is_final):
orig = sys.gettrace()
try: # pragma: no cover
sys.settrace(None)
import random as rnd_module
rnd_module.seed(0)
finally: # pragma: no cover
sys.settrace(orig)
args, kwargs = data.draw(search_strategy)
if print_example:
report(
lambda: 'Falsifying example: %s(%s)' % (
test.__name__, arg_string(test, args, kwargs)))
elif current_verbosity() >= Verbosity.verbose:
report(
lambda: 'Trying example: %s(%s)' % (
test.__name__, arg_string(test, args, kwargs)))
return test(*args, **kwargs)
def run():
args, kwargs = search_strategy.reify(template)
if print_example:
report(
lambda: 'Falsifying example: %s(%s)' % (
test.__name__,
arg_string(
test, args, kwargs
)
)
)
else:
verbose_report(
lambda: 'Trying example: %s(%s)' % (
test.__name__,
arg_string(
test, args, kwargs
)
)
)
return test(*args, **kwargs)
def run():
args, kwargs = search_strategy.reify(template)
if print_example:
report(
lambda: 'Falsifying example: %s(%s)' % (
test.__name__,
arg_string(
test, args, kwargs
)
)
)
elif current_verbosity() >= Verbosity.verbose or always_print:
report(
lambda: 'Trying example: %s(%s)' % (
test.__name__,
arg_string(
test, args, kwargs
)
)
)
return test(*args, **kwargs)
def template_condition(data):
with BuildContext(data):
try:
data.is_find = True
result = data.draw(search)
data.note(result)
success = condition(result)
except UnsatisfiedAssumption:
data.mark_invalid()
if success:
successful_examples[0] += 1
if settings.verbosity == Verbosity.verbose:
if not successful_examples[0]:
report(lambda: u'Trying example %s' % (
nicerepr(result),
))
elif success:
if successful_examples[0] == 1:
report(lambda: u'Found satisfying example %s' % (
nicerepr(result),
))
else:
report(lambda: u'Shrunk example to %s' % (
nicerepr(result),
))
last_data[0] = data
if success and not data.frozen:
data.mark_interesting()
def template_condition(data):
with BuildContext(data):
try:
data.is_find = True
with deterministic_PRNG():
result = data.draw(search)
data.note(result)
success = condition(result)
except UnsatisfiedAssumption:
data.mark_invalid()
if success:
successful_examples[0] += 1
if settings.verbosity >= Verbosity.verbose:
if not successful_examples[0]:
report(
u'Tried non-satisfying example %s' % (nicerepr(result),))
elif success:
if successful_examples[0] == 1:
last_repr[0] = nicerepr(result)
report(u'Found satisfying example %s' % (last_repr[0],))
last_data[0] = data
elif (
sort_key(hbytes(data.buffer)) <
sort_key(last_data[0].buffer)
) and nicerepr(result) != last_repr[0]:
last_repr[0] = nicerepr(result)
report(u'Shrunk example to %s' % (last_repr[0],))
last_data[0] = data
if success and not data.frozen:
data.mark_interesting()
def run(data):
with BuildContext(data, is_final=is_final):
import random as rnd_module
rnd_module.seed(0)
args, kwargs = data.draw(search_strategy)
if print_example:
report(
lambda: 'Falsifying example: %s(%s)' % (
test.__name__, arg_string(test, args, kwargs)))
elif current_verbosity() >= Verbosity.verbose:
report(
lambda: 'Trying example: %s(%s)' % (
test.__name__, arg_string(test, args, kwargs)))
if collector is None:
return test(*args, **kwargs)
else: # pragma: no cover
try:
collector.start()
return test(*args, **kwargs)
finally:
collector.stop()
def print_start(self):
report(u'state = %s()' % (self.__class__.__name__, ))
def print_end(self):
report(u'state.teardown()')
def execute_once(self,
data,
print_example=False,
is_final=False,
expected_failure=None):
"""Run the test function once, using ``data`` as input.
If the test raises an exception, it will propagate through to the
caller of this method. Depending on its type, this could represent
an ordinary test failure, or a fatal error, or a control exception.
If this method returns normally, the test might have passed, or
it might have placed ``data`` in an unsuccessful state and then
swallowed the corresponding control exception.
"""
text_repr = [None]
if self.settings.deadline is None:
test = self.test
else:
@proxies(self.test)
def test(*args, **kwargs):
self.__test_runtime = None
initial_draws = len(data.draw_times)
start = benchmark_time()
result = self.test(*args, **kwargs)
finish = benchmark_time()
internal_draw_time = sum(data.draw_times[initial_draws:])
runtime = datetime.timedelta(seconds=finish - start -
internal_draw_time)
self.__test_runtime = runtime
current_deadline = self.settings.deadline
if not is_final:
current_deadline = (current_deadline // 4) * 5
if runtime >= current_deadline:
raise DeadlineExceeded(runtime, self.settings.deadline)
return result
def run(data):
# Set up dynamic context needed by a single test run.
with local_settings(self.settings):
with deterministic_PRNG():
with BuildContext(data, is_final=is_final):
# Generate all arguments to the test function.
args, kwargs = data.draw(self.search_strategy)
if expected_failure is not None:
text_repr[0] = arg_string(test, args, kwargs)
if print_example:
example = "%s(%s)" % (
test.__name__,
arg_string(test, args, kwargs),
)
report("Falsifying example: %s" % (example, ))
elif current_verbosity() >= Verbosity.verbose:
report(lambda: "Trying example: %s(%s)" % (
test.__name__, arg_string(test, args, kwargs)))
return test(*args, **kwargs)
# Run the test function once, via the executor hook.
# In most cases this will delegate straight to `run(data)`.
result = self.test_runner(data, run)
# If a failure was expected, it should have been raised already, so
# instead raise an appropriate diagnostic error.
if expected_failure is not None:
exception, traceback = expected_failure
if (isinstance(exception, DeadlineExceeded)
and self.__test_runtime is not None):
report(
("Unreliable test timings! On an initial run, this "
"test took %.2fms, which exceeded the deadline of "
"%.2fms, but on a subsequent run it took %.2f ms, "
"which did not. If you expect this sort of "
"variability in your test timings, consider turning "
"deadlines off for this test by setting deadline=None.") %
(
exception.runtime.total_seconds() * 1000,
self.settings.deadline.total_seconds() * 1000,
self.__test_runtime.total_seconds() * 1000,
))
else:
report("Failed to reproduce exception. Expected: \n" +
traceback)
self.__flaky(
("Hypothesis %s(%s) produces unreliable results: Falsified"
" on the first call but did not on a subsequent one") %
(test.__name__, text_repr[0]))
return result
def wrapped_test(*arguments, **kwargs):
# Tell pytest to omit the body of this function from tracebacks
__tracebackhide__ = True
if getattr(test, 'is_hypothesis_test', False):
note_deprecation(
'You have applied @given to a test more than once. In '
'future this will be an error. Applying @given twice '
'wraps the test twice, which can be extremely slow. A '
'similar effect can be gained by combining the arguments '
'of the two calls to given. For example, instead of '
'@given(booleans()) @given(integers()), you could write '
'@given(booleans(), integers())')
settings = wrapped_test._hypothesis_internal_use_settings
random = get_random_for_wrapped_test(test, wrapped_test)
if infer in generator_kwargs.values():
hints = get_type_hints(test)
for name in [
name for name, value in generator_kwargs.items()
if value is infer
]:
if name not in hints:
raise InvalidArgument(
'passed %s=infer for %s, but %s has no type annotation'
% (name, test.__name__, name))
generator_kwargs[name] = st.from_type(hints[name])
processed_args = process_arguments_to_given(
wrapped_test, arguments, kwargs, generator_arguments,
generator_kwargs, argspec, test, settings)
arguments, kwargs, test_runner, search_strategy = processed_args
runner = getattr(search_strategy, 'runner', None)
if isinstance(runner, TestCase) and test.__name__ in dir(TestCase):
msg = ('You have applied @given to the method %s, which is '
'used by the unittest runner but is not itself a test.'
' This is not useful in any way.' % test.__name__)
fail_health_check(settings, msg, HealthCheck.not_a_test_method)
if bad_django_TestCase(runner): # pragma: no cover
# Covered by the Django tests, but not the pytest coverage task
raise InvalidArgument(
'You have applied @given to a method on %s, but this '
'class does not inherit from the supported versions in '
'`hypothesis.extra.django`. Use the Hypothesis variants '
'to ensure that each example is run in a separate '
'database transaction.' % qualname(type(runner)))
state = StateForActualGivenExecution(
test_runner,
search_strategy,
test,
settings,
random,
had_seed=wrapped_test._hypothesis_internal_use_seed)
reproduce_failure = \
wrapped_test._hypothesis_internal_use_reproduce_failure
if reproduce_failure is not None:
expected_version, failure = reproduce_failure
if expected_version != __version__:
raise InvalidArgument(
('Attempting to reproduce a failure from a different '
'version of Hypothesis. This failure is from %s, but '
'you are currently running %r. Please change your '
'Hypothesis version to a matching one.') %
(expected_version, __version__))
try:
state.execute(
ConjectureData.for_buffer(decode_failure(failure)),
print_example=True,
is_final=True,
)
raise DidNotReproduce(
'Expected the test to raise an error, but it '
'completed successfully.')
except StopTest:
raise DidNotReproduce(
'The shape of the test data has changed in some way '
'from where this blob was defined. Are you sure '
"you're running the same test?")
except UnsatisfiedAssumption:
raise DidNotReproduce(
'The test data failed to satisfy an assumption in the '
'test. Have you added it since this blob was '
'generated?')
execute_explicit_examples(test_runner, test, wrapped_test,
settings, arguments, kwargs)
if settings.max_examples <= 0:
return
if not (Phase.reuse in settings.phases
or Phase.generate in settings.phases):
return
try:
if isinstance(runner, TestCase) and hasattr(runner, 'subTest'):
subTest = runner.subTest
try:
setattr(runner, 'subTest', fake_subTest)
state.run()
finally:
setattr(runner, 'subTest', subTest)
else:
state.run()
except BaseException:
generated_seed = \
wrapped_test._hypothesis_internal_use_generated_seed
if generated_seed is not None and not state.failed_normally:
if running_under_pytest:
report(
('You can add @seed(%(seed)d) to this test or run '
'pytest with --hypothesis-seed=%(seed)d to '
'reproduce this failure.') %
{'seed': generated_seed}, )
else:
report(
('You can add @seed(%d) to this test to reproduce '
'this failure.') % (generated_seed, ))
raise
def execute(
self, data,
print_example=False,
is_final=False,
expected_failure=None, collect=False,
):
text_repr = [None]
if self.settings.deadline is None:
test = self.test
else:
@proxies(self.test)
def test(*args, **kwargs):
self.__test_runtime = None
initial_draws = len(data.draw_times)
start = benchmark_time()
result = self.test(*args, **kwargs)
finish = benchmark_time()
internal_draw_time = sum(data.draw_times[initial_draws:])
runtime = (finish - start - internal_draw_time) * 1000
self.__test_runtime = runtime
if self.settings.deadline is not_set:
if (
not self.__warned_deadline and
runtime >= 200
):
self.__warned_deadline = True
note_deprecation((
'Test: %s took %.2fms to run. In future the '
'default deadline setting will be 200ms, which '
'will make this an error. You can set deadline to '
'an explicit value of e.g. %d to turn tests '
'slower than this into an error, or you can set '
'it to None to disable this check entirely.') % (
self.test.__name__, runtime,
ceil(runtime / 100) * 100,
))
else:
current_deadline = self.settings.deadline
if not is_final:
current_deadline *= 1.25
if runtime >= current_deadline:
raise DeadlineExceeded(runtime, self.settings.deadline)
return result
def run(data):
if not hasattr(data, 'can_reproduce_example_from_repr'):
data.can_reproduce_example_from_repr = True
with local_settings(self.settings):
with BuildContext(data, is_final=is_final):
with deterministic_PRNG():
args, kwargs = data.draw(self.search_strategy)
if expected_failure is not None:
text_repr[0] = arg_string(test, args, kwargs)
if print_example:
example = '%s(%s)' % (
test.__name__, arg_string(test, args, kwargs))
try:
ast.parse(example)
except SyntaxError:
data.can_reproduce_example_from_repr = False
report('Falsifying example: %s' % (example,))
elif current_verbosity() >= Verbosity.verbose:
report(
lambda: 'Trying example: %s(%s)' % (
test.__name__, arg_string(test, args, kwargs)))
with deterministic_PRNG():
return test(*args, **kwargs)
result = self.test_runner(data, run)
if expected_failure is not None:
exception, traceback = expected_failure
if (
isinstance(
exception,
DeadlineExceeded
) and self.__test_runtime is not None
):
report((
'Unreliable test timings! On an initial run, this '
'test took %.2fms, which exceeded the deadline of '
'%.2fms, but on a subsequent run it took %.2f ms, '
'which did not. If you expect this sort of '
'variability in your test timings, consider turning '
'deadlines off for this test by setting deadline=None.'
) % (
exception.runtime,
self.settings.deadline, self.__test_runtime
))
else:
report(
'Failed to reproduce exception. Expected: \n' +
traceback,
)
self.__flaky((
'Hypothesis %s(%s) produces unreliable results: Falsified'
' on the first call but did not on a subsequent one'
) % (test.__name__, text_repr[0],))
return result
def wrapped_test(*arguments, **kwargs):
settings = wrapped_test._hypothesis_internal_use_settings
if wrapped_test._hypothesis_internal_use_seed is not None:
random = Random(wrapped_test._hypothesis_internal_use_seed)
elif settings.derandomize:
random = Random(function_digest(test))
else:
random = new_random()
import hypothesis.strategies as sd
selfy = None
arguments, kwargs = convert_positional_arguments(
wrapped_test, arguments, kwargs)
# If the test function is a method of some kind, the bound object
# will be the first named argument if there are any, otherwise the
# first vararg (if any).
if argspec.args:
selfy = kwargs.get(argspec.args[0])
elif arguments:
selfy = arguments[0]
test_runner = new_style_executor(selfy)
for example in reversed(
getattr(wrapped_test, 'hypothesis_explicit_examples', ())):
if example.args:
if len(example.args) > len(original_argspec.args):
raise InvalidArgument(
'example has too many arguments for test. '
'Expected at most %d but got %d' %
(len(original_argspec.args), len(example.args)))
example_kwargs = dict(
zip(original_argspec.args[-len(example.args):],
example.args))
else:
example_kwargs = example.kwargs
if Phase.explicit not in settings.phases:
continue
example_kwargs.update(kwargs)
# Note: Test may mutate arguments and we can't rerun explicit
# examples, so we have to calculate the failure message at this
# point rather than than later.
message_on_failure = 'Falsifying example: %s(%s)' % (
test.__name__, arg_string(test, arguments, example_kwargs))
try:
with BuildContext() as b:
test_runner(
None,
lambda data: test(*arguments, **example_kwargs))
except BaseException:
report(message_on_failure)
for n in b.notes:
report(n)
raise
if settings.max_examples <= 0:
return
arguments = tuple(arguments)
given_specifier = sd.tuples(
sd.just(arguments),
sd.fixed_dictionaries(generator_kwargs).map(
lambda args: dict(args, **kwargs)))
def fail_health_check(message, label):
if label in settings.suppress_health_check:
return
message += (
'\nSee http://hypothesis.readthedocs.org/en/latest/health'
'checks.html for more information about this. ')
message += (
'If you want to disable just this health check, add %s '
'to the suppress_health_check settings for this test.') % (
label, )
raise FailedHealthCheck(message)
search_strategy = given_specifier
if selfy is not None:
search_strategy = WithRunner(search_strategy, selfy)
search_strategy.validate()
perform_health_check = settings.perform_health_check
perform_health_check &= Settings.default.perform_health_check
from hypothesis.internal.conjecture.data import TestData, Status, \
StopTest
if not (Phase.reuse in settings.phases
or Phase.generate in settings.phases):
return
if perform_health_check:
initial_state = getglobalrandomstate()
health_check_random = Random(random.getrandbits(128))
# We "pre warm" the health check with one draw to give it some
# time to calculate any cached data. This prevents the case
# where the first draw of the health check takes ages because
# of loading unicode data the first time.
data = TestData(max_length=settings.buffer_size,
draw_bytes=lambda data, n, distribution:
distribution(health_check_random, n))
with Settings(settings, verbosity=Verbosity.quiet):
try:
test_runner(
data,
reify_and_execute(
search_strategy,
lambda *args, **kwargs: None,
))
except BaseException:
pass
count = 0
overruns = 0
filtered_draws = 0
start = time.time()
while (count < 10 and time.time() < start + 1
and filtered_draws < 50 and overruns < 20):
try:
data = TestData(
max_length=settings.buffer_size,
draw_bytes=lambda data, n, distribution:
distribution(health_check_random, n))
with Settings(settings, verbosity=Verbosity.quiet):
test_runner(
data,
reify_and_execute(
search_strategy,
lambda *args, **kwargs: None,
))
count += 1
except UnsatisfiedAssumption:
filtered_draws += 1
except StopTest:
if data.status == Status.INVALID:
filtered_draws += 1
else:
assert data.status == Status.OVERRUN
overruns += 1
except InvalidArgument:
raise
except Exception:
report(traceback.format_exc())
if test_runner is default_new_style_executor:
fail_health_check(
'An exception occurred during data '
'generation in initial health check. '
'This indicates a bug in the strategy. '
'This could either be a Hypothesis bug or '
"an error in a function you've passed to "
'it to construct your data.',
HealthCheck.exception_in_generation,
)
else:
fail_health_check(
'An exception occurred during data '
'generation in initial health check. '
'This indicates a bug in the strategy. '
'This could either be a Hypothesis bug or '
'an error in a function you\'ve passed to '
'it to construct your data. Additionally, '
'you have a custom executor, which means '
'that this could be your executor failing '
'to handle a function which returns None. ',
HealthCheck.exception_in_generation,
)
if overruns >= 20 or (not count and overruns > 0):
fail_health_check((
'Examples routinely exceeded the max allowable size. '
'(%d examples overran while generating %d valid ones)'
'. Generating examples this large will usually lead to'
' bad results. You should try setting average_size or '
'max_size parameters on your collections and turning '
'max_leaves down on recursive() calls.') %
(overruns, count),
HealthCheck.data_too_large)
if filtered_draws >= 50 or (not count and filtered_draws > 0):
fail_health_check((
'It looks like your strategy is filtering out a lot '
'of data. Health check found %d filtered examples but '
'only %d good ones. This will make your tests much '
'slower, and also will probably distort the data '
'generation quite a lot. You should adapt your '
'strategy to filter less. This can also be caused by '
'a low max_leaves parameter in recursive() calls') %
(filtered_draws, count),
HealthCheck.filter_too_much)
runtime = time.time() - start
if runtime > 1.0 or count < 10:
fail_health_check(
('Data generation is extremely slow: Only produced '
'%d valid examples in %.2f seconds (%d invalid ones '
'and %d exceeded maximum size). Try decreasing '
"size of the data you're generating (with e.g."
'average_size or max_leaves parameters).') %
(count, runtime, filtered_draws, overruns),
HealthCheck.too_slow,
)
if getglobalrandomstate() != initial_state:
fail_health_check(
'Data generation depends on global random module. '
'This makes results impossible to replay, which '
'prevents Hypothesis from working correctly. '
'If you want to use methods from random, use '
'randoms() from hypothesis.strategies to get an '
'instance of Random you can use. Alternatively, you '
'can use the random_module() strategy to explicitly '
'seed the random module.',
HealthCheck.random_module,
)
last_exception = [None]
repr_for_last_exception = [None]
performed_random_check = [False]
def evaluate_test_data(data):
if perform_health_check and not performed_random_check[0]:
initial_state = getglobalrandomstate()
performed_random_check[0] = True
else:
initial_state = None
try:
result = test_runner(
data, reify_and_execute(
search_strategy,
test,
))
if result is not None and settings.perform_health_check:
fail_health_check(
('Tests run under @given should return None, but '
'%s returned %r instead.') %
(test.__name__, result), HealthCheck.return_value)
return False
except UnsatisfiedAssumption:
data.mark_invalid()
except (
HypothesisDeprecationWarning,
FailedHealthCheck,
StopTest,
):
raise
except Exception:
last_exception[0] = traceback.format_exc()
verbose_report(last_exception[0])
data.mark_interesting()
finally:
if (initial_state is not None
and getglobalrandomstate() != initial_state):
fail_health_check(
'Your test used the global random module. '
'This is unlikely to work correctly. You should '
'consider using the randoms() strategy from '
'hypothesis.strategies instead. Alternatively, '
'you can use the random_module() strategy to '
'explicitly seed the random module.',
HealthCheck.random_module,
)
from hypothesis.internal.conjecture.engine import TestRunner
falsifying_example = None
database_key = str_to_bytes(fully_qualified_name(test))
start_time = time.time()
runner = TestRunner(
evaluate_test_data,
settings=settings,
random=random,
database_key=database_key,
)
runner.run()
run_time = time.time() - start_time
timed_out = (settings.timeout > 0 and run_time >= settings.timeout)
if runner.last_data is None:
return
if runner.last_data.status == Status.INTERESTING:
falsifying_example = runner.last_data.buffer
if settings.database is not None:
settings.database.save(database_key, falsifying_example)
else:
if runner.valid_examples < min(
settings.min_satisfying_examples,
settings.max_examples,
):
if timed_out:
raise Timeout(
('Ran out of time before finding a satisfying '
'example for '
'%s. Only found %d examples in ' + '%.2fs.') %
(get_pretty_function_description(test),
runner.valid_examples, run_time))
else:
raise Unsatisfiable(
('Unable to satisfy assumptions of hypothesis '
'%s. Only %d examples considered '
'satisfied assumptions') % (
get_pretty_function_description(test),
runner.valid_examples,
))
return
assert last_exception[0] is not None
try:
with settings:
test_runner(
TestData.for_buffer(falsifying_example),
reify_and_execute(search_strategy,
test,
print_example=True,
is_final=True))
except (UnsatisfiedAssumption, StopTest):
report(traceback.format_exc())
raise Flaky(
'Unreliable assumption: An example which satisfied '
'assumptions on the first run now fails it.')
report(
'Failed to reproduce exception. Expected: \n' +
last_exception[0], )
filter_message = (
'Unreliable test data: Failed to reproduce a failure '
'and then when it came to recreating the example in '
'order to print the test data with a flaky result '
'the example was filtered out (by e.g. a '
'call to filter in your strategy) when we didn\'t '
'expect it to be.')
try:
test_runner(
TestData.for_buffer(falsifying_example),
reify_and_execute(search_strategy,
test_is_flaky(
test, repr_for_last_exception[0]),
print_example=True,
is_final=True))
except (UnsatisfiedAssumption, StopTest):
raise Flaky(filter_message)
def test_can_print_bytes():
with capture_out() as o:
with reporting.with_reporter(reporting.default):
report(b"hi")
assert o.getvalue() == u"hi\n"
def execute(
self,
data,
print_example=False,
is_final=False,
expected_failure=None,
collect=False,
):
text_repr = [None]
if self.settings.deadline is None:
test = self.test
else:
@proxies(self.test)
def test(*args, **kwargs):
self.__test_runtime = None
initial_draws = len(data.draw_times)
start = benchmark_time()
result = self.test(*args, **kwargs)
finish = benchmark_time()
internal_draw_time = sum(data.draw_times[initial_draws:])
runtime = (finish - start - internal_draw_time) * 1000
self.__test_runtime = runtime
if self.settings.deadline is not_set:
if (not self.__warned_deadline and runtime >= 200):
self.__warned_deadline = True
note_deprecation(
('Test took %.2fms to run. In future the default '
'deadline setting will be 200ms, which will '
'make this an error. You can set deadline to '
'an explicit value of e.g. %d to turn tests '
'slower than this into an error, or you can set '
'it to None to disable this check entirely.') % (
runtime,
ceil(runtime / 100) * 100,
))
else:
current_deadline = self.settings.deadline
if not is_final:
current_deadline *= 1.25
if runtime >= current_deadline:
raise DeadlineExceeded(runtime, self.settings.deadline)
return result
def run(data):
if not hasattr(data, 'can_reproduce_example_from_repr'):
data.can_reproduce_example_from_repr = True
with local_settings(self.settings):
with BuildContext(data, is_final=is_final):
with deterministic_PRNG():
args, kwargs = data.draw(self.search_strategy)
if expected_failure is not None:
text_repr[0] = arg_string(test, args, kwargs)
if print_example:
example = '%s(%s)' % (test.__name__,
arg_string(test, args, kwargs))
try:
ast.parse(example)
except SyntaxError:
data.can_reproduce_example_from_repr = False
report('Falsifying example: %s' % (example, ))
elif current_verbosity() >= Verbosity.verbose:
report(lambda: 'Trying example: %s(%s)' %
(test.__name__, arg_string(test, args, kwargs)))
if self.collector is None or not collect:
with deterministic_PRNG():
return test(*args, **kwargs)
else: # pragma: no cover
try:
self.collector.start()
with deterministic_PRNG():
return test(*args, **kwargs)
finally:
self.collector.stop()
result = self.test_runner(data, run)
if expected_failure is not None:
exception, traceback = expected_failure
if (isinstance(exception, DeadlineExceeded)
and self.__test_runtime is not None):
report(
('Unreliable test timings! On an initial run, this '
'test took %.2fms, which exceeded the deadline of '
'%.2fms, but on a subsequent run it took %.2f ms, '
'which did not. If you expect this sort of '
'variability in your test timings, consider turning '
'deadlines off for this test by setting deadline=None.') %
(exception.runtime, self.settings.deadline,
self.__test_runtime))
else:
report(
'Failed to reproduce exception. Expected: \n' +
traceback, )
self.__flaky(
('Hypothesis %s(%s) produces unreliable results: Falsified'
' on the first call but did not on a subsequent one') % (
test.__name__,
text_repr[0],
))
return result
def run_state_machine(factory, data):
cd = data.conjecture_data
machine = factory()
check_type(RuleBasedStateMachine, machine, "state_machine_factory()")
cd.hypothesis_runner = machine
print_steps = (current_build_context().is_final
or current_verbosity() >= Verbosity.debug)
try:
if print_steps:
report(f"state = {machine.__class__.__name__}()")
machine.check_invariants()
max_steps = settings.stateful_step_count
steps_run = 0
while True:
# We basically always want to run the maximum number of steps,
# but need to leave a small probability of terminating early
# in order to allow for reducing the number of steps once we
# find a failing test case, so we stop with probability of
# 2 ** -16 during normal operation but force a stop when we've
# generated enough steps.
cd.start_example(STATE_MACHINE_RUN_LABEL)
if steps_run == 0:
cd.draw_bits(16, forced=1)
elif steps_run >= max_steps:
cd.draw_bits(16, forced=0)
break
else:
# All we really care about is whether this value is zero
# or non-zero, so if it's > 1 we discard it and insert a
# replacement value after
cd.start_example(SHOULD_CONTINUE_LABEL)
should_continue_value = cd.draw_bits(16)
if should_continue_value > 1:
cd.stop_example(discard=True)
cd.draw_bits(16,
forced=int(bool(should_continue_value)))
else:
cd.stop_example()
if should_continue_value == 0:
break
steps_run += 1
# Choose a rule to run, preferring an initialize rule if there are
# any which have not been run yet.
if machine._initialize_rules_to_run:
init_rules = [
st.tuples(st.just(rule),
st.fixed_dictionaries(rule.arguments))
for rule in machine._initialize_rules_to_run
]
rule, data = cd.draw(st.one_of(init_rules))
machine._initialize_rules_to_run.remove(rule)
else:
rule, data = cd.draw(machine._rules_strategy)
# Pretty-print the values this rule was called with *before* calling
# _add_result_to_targets, to avoid printing arguments which are also
# a return value using the variable name they are assigned to.
# See https://github.com/HypothesisWorks/hypothesis/issues/2341
if print_steps:
data_to_print = {
k: machine._pretty_print(v)
for k, v in data.items()
}
# Assign 'result' here in case executing the rule fails below
result = multiple()
try:
data = dict(data)
for k, v in list(data.items()):
if isinstance(v, VarReference):
data[k] = machine.names_to_values[v.name]
result = rule.function(machine, **data)
if rule.targets:
if isinstance(result, MultipleResults):
for single_result in result.values:
machine._add_result_to_targets(
rule.targets, single_result)
else:
machine._add_result_to_targets(
rule.targets, result)
finally:
if print_steps:
# 'result' is only used if the step has target bundles.
# If it does, and the result is a 'MultipleResult',
# then 'print_step' prints a multi-variable assignment.
machine._print_step(rule, data_to_print, result)
machine.check_invariants()
cd.stop_example()
finally:
if print_steps:
report("state.teardown()")
machine.teardown()
def run(self):
# Tell pytest to omit the body of this function from tracebacks
__tracebackhide__ = True
if global_force_seed is None:
database_key = function_digest(self.test)
else:
database_key = None
runner = ConjectureRunner(
self.evaluate_test_data,
settings=self.settings,
random=self.random,
database_key=database_key,
)
try:
runner.run()
finally:
self.used_examples_from_database = runner.used_examples_from_database
note_engine_for_statistics(runner)
self.used_examples_from_database = runner.used_examples_from_database
if runner.call_count == 0:
return
if runner.interesting_examples:
self.falsifying_examples = sorted(
[d for d in runner.interesting_examples.values()],
key=lambda d: sort_key(d.buffer),
reverse=True,
)
else:
if runner.valid_examples == 0:
raise Unsatisfiable(
"Unable to satisfy assumptions of hypothesis %s." %
(get_pretty_function_description(self.test), ))
if not self.falsifying_examples:
return
elif not self.settings.report_multiple_bugs:
del self.falsifying_examples[:-1]
self.failed_normally = True
flaky = 0
for falsifying_example in self.falsifying_examples:
info = falsifying_example.extra_information
ran_example = ConjectureData.for_buffer(falsifying_example.buffer)
self.__was_flaky = False
assert info.__expected_exception is not None
try:
self.execute(
ran_example,
print_example=True,
is_final=True,
expected_failure=(
info.__expected_exception,
info.__expected_traceback,
),
)
except (UnsatisfiedAssumption, StopTest):
report(traceback.format_exc())
self.__flaky(
"Unreliable assumption: An example which satisfied "
"assumptions on the first run now fails it.")
except BaseException as e:
if len(self.falsifying_examples) <= 1:
raise
tb = get_trimmed_traceback()
report("".join(traceback.format_exception(type(e), e, tb)))
finally: # pragma: no cover
# This section is in fact entirely covered by the tests in
# test_reproduce_failure, but it seems to trigger a lovely set
# of coverage bugs: The branches show up as uncovered (despite
# definitely being covered - you can add an assert False else
# branch to verify this and see it fail - and additionally the
# second branch still complains about lack of coverage even if
# you add a pragma: no cover to it!
# See https://bitbucket.org/ned/coveragepy/issues/623/
if self.settings.print_blob is not PrintSettings.NEVER:
failure_blob = encode_failure(falsifying_example.buffer)
# Have to use the example we actually ran, not the original
# falsifying example! Otherwise we won't catch problems
# where the repr of the generated example doesn't parse.
can_use_repr = ran_example.can_reproduce_example_from_repr
if self.settings.print_blob is PrintSettings.ALWAYS or (
self.settings.print_blob is PrintSettings.INFER
and self.settings.verbosity >= Verbosity.normal
and not can_use_repr and len(failure_blob) < 200):
report((
"\nYou can reproduce this example by temporarily "
"adding @reproduce_failure(%r, %r) as a decorator "
"on your test case") % (__version__, failure_blob))
if self.__was_flaky:
flaky += 1
# If we only have one example then we should have raised an error or
# flaky prior to this point.
assert len(self.falsifying_examples) > 1
if flaky > 0:
raise Flaky(
("Hypothesis found %d distinct failures, but %d of them "
"exhibited some sort of flaky behaviour.") %
(len(self.falsifying_examples), flaky))
else:
raise MultipleFailures(("Hypothesis found %d distinct failures.") %
(len(self.falsifying_examples)))
def test_can_print_bytes():
with capture_out() as o:
with reporting.with_reporter(reporting.default):
report(b'hi')
assert o.getvalue() == u'hi\n'
def run(self):
# Tell pytest to omit the body of this function from tracebacks
__tracebackhide__ = True
if global_force_seed is None:
database_key = str_to_bytes(fully_qualified_name(self.test))
else:
database_key = None
self.start_time = time.time()
global in_given
runner = ConjectureRunner(
self.evaluate_test_data,
settings=self.settings,
random=self.random,
database_key=database_key,
)
if in_given or self.collector is None:
runner.run()
else: # pragma: no cover
in_given = True
original_trace = sys.gettrace()
try:
sys.settrace(None)
runner.run()
finally:
in_given = False
sys.settrace(original_trace)
self.used_examples_from_database = \
runner.used_examples_from_database
note_engine_for_statistics(runner)
run_time = time.time() - self.start_time
self.used_examples_from_database = runner.used_examples_from_database
if runner.used_examples_from_database:
if self.settings.derandomize:
note_deprecation(
'In future derandomize will imply database=None, but your '
'test is currently using examples from the database. To '
'get the future behaviour, update your settings to '
'include database=None.')
if self.__had_seed:
note_deprecation(
'In future use of @seed will imply database=None in your '
'settings, but your test is currently using examples from '
'the database. To get the future behaviour, update your '
'settings for this test to include database=None.')
timed_out = runner.exit_reason == ExitReason.timeout
if runner.call_count == 0:
return
if runner.interesting_examples:
self.falsifying_examples = sorted(
[d for d in runner.interesting_examples.values()],
key=lambda d: sort_key(d.buffer),
reverse=True)
else:
if timed_out:
note_deprecation((
'Your tests are hitting the settings timeout (%.2fs). '
'This functionality will go away in a future release '
'and you should not rely on it. Instead, try setting '
'max_examples to be some value lower than %d (the number '
'of examples your test successfully ran here). Or, if you '
'would prefer your tests to run to completion, regardless '
'of how long they take, you can set the timeout value to '
'hypothesis.unlimited.') % (self.settings.timeout,
runner.valid_examples),
self.settings)
if runner.valid_examples == 0:
if timed_out:
raise Timeout(
('Ran out of time before finding a satisfying '
'example for %s. Only found %d examples in %.2fs.') %
(get_pretty_function_description(
self.test), runner.valid_examples, run_time))
else:
raise Unsatisfiable(
'Unable to satisfy assumptions of hypothesis %s.' %
(get_pretty_function_description(self.test), ))
if not self.falsifying_examples:
return
self.failed_normally = True
flaky = 0
for falsifying_example in self.falsifying_examples:
ran_example = ConjectureData.for_buffer(falsifying_example.buffer)
self.__was_flaky = False
assert falsifying_example.__expected_exception is not None
try:
self.execute(ran_example,
print_example=True,
is_final=True,
expected_failure=(
falsifying_example.__expected_exception,
falsifying_example.__expected_traceback,
))
except (UnsatisfiedAssumption, StopTest):
report(traceback.format_exc())
self.__flaky(
'Unreliable assumption: An example which satisfied '
'assumptions on the first run now fails it.')
except BaseException:
if len(self.falsifying_examples) <= 1:
raise
report(traceback.format_exc())
finally: # pragma: no cover
# This section is in fact entirely covered by the tests in
# test_reproduce_failure, but it seems to trigger a lovely set
# of coverage bugs: The branches show up as uncovered (despite
# definitely being covered - you can add an assert False else
# branch to verify this and see it fail - and additionally the
# second branch still complains about lack of coverage even if
# you add a pragma: no cover to it!
# See https://bitbucket.org/ned/coveragepy/issues/623/
if self.settings.print_blob is not PrintSettings.NEVER:
failure_blob = encode_failure(falsifying_example.buffer)
# Have to use the example we actually ran, not the original
# falsifying example! Otherwise we won't catch problems
# where the repr of the generated example doesn't parse.
can_use_repr = ran_example.can_reproduce_example_from_repr
if (self.settings.print_blob is PrintSettings.ALWAYS or
(self.settings.print_blob is PrintSettings.INFER
and not can_use_repr and len(failure_blob) < 200)):
report((
'\n'
'You can reproduce this example by temporarily '
'adding @reproduce_failure(%r, %r) as a decorator '
'on your test case') % (
__version__,
failure_blob,
))
if self.__was_flaky:
flaky += 1
# If we only have one example then we should have raised an error or
# flaky prior to this point.
assert len(self.falsifying_examples) > 1
if flaky > 0:
raise Flaky(
('Hypothesis found %d distinct failures, but %d of them '
'exhibited some sort of flaky behaviour.') %
(len(self.falsifying_examples), flaky))
else:
raise MultipleFailures(('Hypothesis found %d distinct failures.') %
(len(self.falsifying_examples, )))
def wrapped_test(*arguments, **kwargs):
settings = wrapped_test._hypothesis_internal_use_settings
if wrapped_test._hypothesis_internal_use_seed is not None:
random = Random(wrapped_test._hypothesis_internal_use_seed)
elif settings.derandomize:
random = Random(function_digest(test))
else:
random = new_random()
import hypothesis.strategies as sd
selfy = None
arguments, kwargs = convert_positional_arguments(wrapped_test, arguments, kwargs)
# If the test function is a method of some kind, the bound object
# will be the first named argument if there are any, otherwise the
# first vararg (if any).
if argspec.args:
selfy = kwargs.get(argspec.args[0])
elif arguments:
selfy = arguments[0]
test_runner = new_style_executor(selfy)
for example in reversed(getattr(wrapped_test, "hypothesis_explicit_examples", ())):
if example.args:
if len(example.args) > len(original_argspec.args):
raise InvalidArgument(
"example has too many arguments for test. "
"Expected at most %d but got %d" % (len(original_argspec.args), len(example.args))
)
example_kwargs = dict(zip(original_argspec.args[-len(example.args) :], example.args))
else:
example_kwargs = example.kwargs
if Phase.explicit not in settings.phases:
continue
example_kwargs.update(kwargs)
# Note: Test may mutate arguments and we can't rerun explicit
# examples, so we have to calculate the failure message at this
# point rather than than later.
message_on_failure = "Falsifying example: %s(%s)" % (
test.__name__,
arg_string(test, arguments, example_kwargs),
)
try:
with BuildContext() as b:
test_runner(None, lambda data: test(*arguments, **example_kwargs))
except BaseException:
report(message_on_failure)
for n in b.notes:
report(n)
raise
if settings.max_examples <= 0:
return
arguments = tuple(arguments)
given_specifier = sd.tuples(
sd.just(arguments), sd.fixed_dictionaries(generator_kwargs).map(lambda args: dict(args, **kwargs))
)
def fail_health_check(message, label):
if label in settings.suppress_health_check:
return
message += (
"\nSee https://hypothesis.readthedocs.io/en/latest/health"
"checks.html for more information about this. "
)
message += (
"If you want to disable just this health check, add %s "
"to the suppress_health_check settings for this test."
) % (label,)
raise FailedHealthCheck(message)
search_strategy = given_specifier
if selfy is not None:
search_strategy = WithRunner(search_strategy, selfy)
search_strategy.validate()
perform_health_check = settings.perform_health_check
perform_health_check &= Settings.default.perform_health_check
from hypothesis.internal.conjecture.data import TestData, Status, StopTest
if not (Phase.reuse in settings.phases or Phase.generate in settings.phases):
return
if perform_health_check:
health_check_random = Random(random.getrandbits(128))
# We "pre warm" the health check with one draw to give it some
# time to calculate any cached data. This prevents the case
# where the first draw of the health check takes ages because
# of loading unicode data the first time.
data = TestData(
max_length=settings.buffer_size,
draw_bytes=lambda data, n, distribution: distribution(health_check_random, n),
)
with Settings(settings, verbosity=Verbosity.quiet):
try:
test_runner(data, reify_and_execute(search_strategy, lambda *args, **kwargs: None))
except BaseException:
pass
count = 0
overruns = 0
filtered_draws = 0
start = time.time()
while count < 10 and time.time() < start + 1 and filtered_draws < 50 and overruns < 20:
try:
data = TestData(
max_length=settings.buffer_size,
draw_bytes=lambda data, n, distribution: distribution(health_check_random, n),
)
with Settings(settings, verbosity=Verbosity.quiet):
test_runner(data, reify_and_execute(search_strategy, lambda *args, **kwargs: None))
count += 1
except UnsatisfiedAssumption:
filtered_draws += 1
except StopTest:
if data.status == Status.INVALID:
filtered_draws += 1
else:
assert data.status == Status.OVERRUN
overruns += 1
except InvalidArgument:
raise
except Exception:
if HealthCheck.exception_in_generation in settings.suppress_health_check:
raise
report(traceback.format_exc())
if test_runner is default_new_style_executor:
fail_health_check(
"An exception occurred during data "
"generation in initial health check. "
"This indicates a bug in the strategy. "
"This could either be a Hypothesis bug or "
"an error in a function you've passed to "
"it to construct your data.",
HealthCheck.exception_in_generation,
)
else:
fail_health_check(
"An exception occurred during data "
"generation in initial health check. "
"This indicates a bug in the strategy. "
"This could either be a Hypothesis bug or "
"an error in a function you've passed to "
"it to construct your data. Additionally, "
"you have a custom executor, which means "
"that this could be your executor failing "
"to handle a function which returns None. ",
HealthCheck.exception_in_generation,
)
if overruns >= 20 or (not count and overruns > 0):
fail_health_check(
(
"Examples routinely exceeded the max allowable size. "
"(%d examples overran while generating %d valid ones)"
". Generating examples this large will usually lead to"
" bad results. You should try setting average_size or "
"max_size parameters on your collections and turning "
"max_leaves down on recursive() calls."
)
% (overruns, count),
HealthCheck.data_too_large,
)
if filtered_draws >= 50 or (not count and filtered_draws > 0):
fail_health_check(
(
"It looks like your strategy is filtering out a lot "
"of data. Health check found %d filtered examples but "
"only %d good ones. This will make your tests much "
"slower, and also will probably distort the data "
"generation quite a lot. You should adapt your "
"strategy to filter less. This can also be caused by "
"a low max_leaves parameter in recursive() calls"
)
% (filtered_draws, count),
HealthCheck.filter_too_much,
)
runtime = time.time() - start
if runtime > 1.0 or count < 10:
fail_health_check(
(
"Data generation is extremely slow: Only produced "
"%d valid examples in %.2f seconds (%d invalid ones "
"and %d exceeded maximum size). Try decreasing "
"size of the data you're generating (with e.g."
"average_size or max_leaves parameters)."
)
% (count, runtime, filtered_draws, overruns),
HealthCheck.too_slow,
)
last_exception = [None]
repr_for_last_exception = [None]
def evaluate_test_data(data):
try:
result = test_runner(data, reify_and_execute(search_strategy, test))
if result is not None and settings.perform_health_check:
fail_health_check(
("Tests run under @given should return None, but " "%s returned %r instead.")
% (test.__name__, result),
HealthCheck.return_value,
)
return False
except UnsatisfiedAssumption:
data.mark_invalid()
except (HypothesisDeprecationWarning, FailedHealthCheck, StopTest):
raise
except Exception:
last_exception[0] = traceback.format_exc()
verbose_report(last_exception[0])
data.mark_interesting()
from hypothesis.internal.conjecture.engine import TestRunner
falsifying_example = None
database_key = str_to_bytes(fully_qualified_name(test))
start_time = time.time()
runner = TestRunner(evaluate_test_data, settings=settings, random=random, database_key=database_key)
runner.run()
run_time = time.time() - start_time
timed_out = settings.timeout > 0 and run_time >= settings.timeout
if runner.last_data is None:
return
if runner.last_data.status == Status.INTERESTING:
falsifying_example = runner.last_data.buffer
if settings.database is not None:
settings.database.save(database_key, falsifying_example)
else:
if runner.valid_examples < min(settings.min_satisfying_examples, settings.max_examples):
if timed_out:
raise Timeout(
(
"Ran out of time before finding a satisfying "
"example for "
"%s. Only found %d examples in " + "%.2fs."
)
% (get_pretty_function_description(test), runner.valid_examples, run_time)
)
else:
raise Unsatisfiable(
(
"Unable to satisfy assumptions of hypothesis "
"%s. Only %d examples considered "
"satisfied assumptions"
)
% (get_pretty_function_description(test), runner.valid_examples)
)
return
assert last_exception[0] is not None
try:
with settings:
test_runner(
TestData.for_buffer(falsifying_example),
reify_and_execute(search_strategy, test, print_example=True, is_final=True),
)
except (UnsatisfiedAssumption, StopTest):
report(traceback.format_exc())
raise Flaky(
"Unreliable assumption: An example which satisfied " "assumptions on the first run now fails it."
)
report("Failed to reproduce exception. Expected: \n" + last_exception[0])
filter_message = (
"Unreliable test data: Failed to reproduce a failure "
"and then when it came to recreating the example in "
"order to print the test data with a flaky result "
"the example was filtered out (by e.g. a "
"call to filter in your strategy) when we didn't "
"expect it to be."
)
try:
test_runner(
TestData.for_buffer(falsifying_example),
reify_and_execute(
search_strategy,
test_is_flaky(test, repr_for_last_exception[0]),
print_example=True,
is_final=True,
),
)
except (UnsatisfiedAssumption, StopTest):
raise Flaky(filter_message)
def wrapped_test(*arguments, **kwargs):
# Tell pytest to omit the body of this function from tracebacks
__tracebackhide__ = True
if getattr(test, 'is_hypothesis_test', False):
note_deprecation(
('You have applied @given to a test more than once. In '
'future this will be an error. Applying @given twice '
'wraps the test twice, which can be extremely slow. A '
'similar effect can be gained by combining the arguments '
'to the two calls to given. For example, instead of '
'@given(booleans()) @given(integers()), you could write '
'@given(booleans(), integers())'))
settings = wrapped_test._hypothesis_internal_use_settings
random = get_random_for_wrapped_test(test, wrapped_test)
if infer in generator_kwargs.values():
hints = get_type_hints(test)
for name in [
name for name, value in generator_kwargs.items()
if value is infer
]:
if name not in hints:
raise InvalidArgument(
'passed %s=infer for %s, but %s has no type annotation'
% (name, test.__name__, name))
generator_kwargs[name] = st.from_type(hints[name])
processed_args = process_arguments_to_given(
wrapped_test, arguments, kwargs, generator_arguments,
generator_kwargs, argspec, test, settings)
arguments, kwargs, test_runner, search_strategy = processed_args
execute_explicit_examples(test_runner, test, wrapped_test,
settings, arguments, kwargs)
if settings.max_examples <= 0:
return
if not (Phase.reuse in settings.phases
or Phase.generate in settings.phases):
return
try:
state = StateForActualGivenExecution(test_runner,
search_strategy, test,
settings, random)
state.run()
except BaseException:
generated_seed = \
wrapped_test._hypothesis_internal_use_generated_seed
if generated_seed is not None:
if running_under_pytest:
report(
('You can add @seed(%(seed)d) to this test or run '
'pytest with --hypothesis-seed=%(seed)d to '
'reproduce this failure.') %
{'seed': generated_seed}, )
else:
report(
('You can add @seed(%d) to this test to reproduce '
'this failure.') % (generated_seed, ))
raise
def print_end(self):
report(u"state.teardown()")
def run(self):
# Tell pytest to omit the body of this function from tracebacks
__tracebackhide__ = True
database_key = str_to_bytes(fully_qualified_name(self.test))
self.start_time = time.time()
global in_given
runner = ConjectureRunner(
self.evaluate_test_data,
settings=self.settings,
random=self.random,
database_key=database_key,
)
if in_given or self.collector is None:
runner.run()
else: # pragma: no cover
in_given = True
original_trace = sys.gettrace()
try:
sys.settrace(None)
runner.run()
finally:
in_given = False
sys.settrace(original_trace)
note_engine_for_statistics(runner)
run_time = time.time() - self.start_time
timed_out = runner.exit_reason == ExitReason.timeout
if runner.last_data is None:
return
if runner.interesting_examples:
self.falsifying_examples = sorted(
[d for d in runner.interesting_examples.values()],
key=lambda d: sort_key(d.buffer),
reverse=True)
else:
if timed_out:
note_deprecation((
'Your tests are hitting the settings timeout (%.2fs). '
'This functionality will go away in a future release '
'and you should not rely on it. Instead, try setting '
'max_examples to be some value lower than %d (the number '
'of examples your test successfully ran here). Or, if you '
'would prefer your tests to run to completion, regardless '
'of how long they take, you can set the timeout value to '
'hypothesis.unlimited.') % (self.settings.timeout,
runner.valid_examples),
self.settings)
if runner.valid_examples < min(
self.settings.min_satisfying_examples,
self.settings.max_examples,
) and not (runner.exit_reason == ExitReason.finished
and self.at_least_one_success):
if timed_out:
raise Timeout(
('Ran out of time before finding a satisfying '
'example for '
'%s. Only found %d examples in ' + '%.2fs.') %
(get_pretty_function_description(
self.test), runner.valid_examples, run_time))
else:
raise Unsatisfiable(
('Unable to satisfy assumptions of hypothesis '
'%s. Only %d examples considered '
'satisfied assumptions') % (
get_pretty_function_description(self.test),
runner.valid_examples,
))
if not self.falsifying_examples:
return
flaky = 0
for falsifying_example in self.falsifying_examples:
self.__was_flaky = False
assert falsifying_example.__expected_exception is not None
try:
self.execute(ConjectureData.for_buffer(
falsifying_example.buffer),
print_example=True,
is_final=True,
expected_failure=(
falsifying_example.__expected_exception,
falsifying_example.__expected_traceback,
))
except (UnsatisfiedAssumption, StopTest):
report(traceback.format_exc())
self.__flaky(
'Unreliable assumption: An example which satisfied '
'assumptions on the first run now fails it.')
except BaseException:
if len(self.falsifying_examples) <= 1:
raise
report(traceback.format_exc())
if self.__was_flaky:
flaky += 1
# If we only have one example then we should have raised an error or
# flaky prior to this point.
assert len(self.falsifying_examples) > 1
if flaky > 0:
raise Flaky(
('Hypothesis found %d distinct failures, but %d of them '
'exhibited some sort of flaky behaviour.') %
(len(self.falsifying_examples), flaky))
else:
raise MultipleFailures(('Hypothesis found %d distinct failures.') %
(len(self.falsifying_examples, )))
def run(self):
# Tell pytest to omit the body of this function from tracebacks
__tracebackhide__ = True
database_key = str_to_bytes(fully_qualified_name(self.test))
self.start_time = time.time()
global in_given
runner = ConjectureRunner(
self.evaluate_test_data,
settings=self.settings,
random=self.random,
database_key=database_key,
)
if in_given or self.collector is None:
runner.run()
else: # pragma: no cover
in_given = True
original_trace = sys.gettrace()
try:
sys.settrace(None)
runner.run()
finally:
in_given = False
sys.settrace(original_trace)
note_engine_for_statistics(runner)
run_time = time.time() - self.start_time
timed_out = runner.exit_reason == ExitReason.timeout
if runner.last_data is None:
return
if runner.interesting_examples:
self.falsifying_examples = sorted(
[d for d in runner.interesting_examples.values()],
key=lambda d: sort_key(d.buffer),
reverse=True)
else:
if timed_out:
note_deprecation((
'Your tests are hitting the settings timeout (%.2fs). '
'This functionality will go away in a future release '
'and you should not rely on it. Instead, try setting '
'max_examples to be some value lower than %d (the number '
'of examples your test successfully ran here). Or, if you '
'would prefer your tests to run to completion, regardless '
'of how long they take, you can set the timeout value to '
'hypothesis.unlimited.') % (self.settings.timeout,
runner.valid_examples),
self.settings)
if runner.valid_examples < min(
self.settings.min_satisfying_examples,
self.settings.max_examples,
) and not (runner.exit_reason == ExitReason.finished
and self.at_least_one_success):
if timed_out:
raise Timeout(
('Ran out of time before finding a satisfying '
'example for '
'%s. Only found %d examples in ' + '%.2fs.') %
(get_pretty_function_description(
self.test), runner.valid_examples, run_time))
else:
raise Unsatisfiable(
('Unable to satisfy assumptions of hypothesis '
'%s. Only %d examples considered '
'satisfied assumptions') % (
get_pretty_function_description(self.test),
runner.valid_examples,
))
if not self.falsifying_examples:
return
flaky = 0
self.__in_final_replay = True
for falsifying_example in self.falsifying_examples:
self.__was_flaky = False
try:
with self.settings:
self.test_runner(
ConjectureData.for_buffer(falsifying_example.buffer),
reify_and_execute(self.search_strategy,
self.test,
print_example=True,
is_final=True))
except (UnsatisfiedAssumption, StopTest):
report(traceback.format_exc())
self.__flaky(
'Unreliable assumption: An example which satisfied '
'assumptions on the first run now fails it.')
except BaseException:
if len(self.falsifying_examples) <= 1:
raise
report(traceback.format_exc())
else:
if (isinstance(falsifying_example.__expected_exception,
DeadlineExceeded)
and self.__test_runtime is not None):
report((
'Unreliable test timings! On an initial run, this '
'test took %.2fms, which exceeded the deadline of '
'%.2fms, but on a subsequent run it took %.2f ms, '
'which did not. If you expect this sort of '
'variability in your test timings, consider turning '
'deadlines off for this test by setting deadline=None.'
) % (falsifying_example.__expected_exception.runtime,
self.settings.deadline, self.__test_runtime))
else:
report(
'Failed to reproduce exception. Expected: \n' +
falsifying_example.__expected_traceback, )
filter_message = (
'Unreliable test data: Failed to reproduce a failure '
'and then when it came to recreating the example in '
'order to print the test data with a flaky result '
'the example was filtered out (by e.g. a '
'call to filter in your strategy) when we didn\'t '
'expect it to be.')
try:
self.test_runner(
ConjectureData.for_buffer(falsifying_example.buffer),
reify_and_execute(self.search_strategy,
test_is_flaky(
self.test,
self.repr_for_last_exception),
print_example=True,
is_final=True))
except (UnsatisfiedAssumption, StopTest):
self.__flaky(filter_message)
except Flaky as e:
if len(self.falsifying_examples) > 1:
self.__flaky(e.args[0])
else:
raise
if self.__was_flaky:
flaky += 1
# If we only have one example then we should have raised an error or
# flaky prior to this point.
assert len(self.falsifying_examples) > 1
if flaky > 0:
raise Flaky(
('Hypothesis found %d distinct failures, but %d of them '
'exhibited some sort of flaky behaviour.') %
(len(self.falsifying_examples), flaky))
else:
raise MultipleFailures(('Hypothesis found %d distinct failures.') %
(len(self.falsifying_examples, )))
def run(self):
# Tell pytest to omit the body of this function from tracebacks
__tracebackhide__ = True
if global_force_seed is None:
database_key = str_to_bytes(fully_qualified_name(self.test))
else:
database_key = None
self.start_time = benchmark_time()
runner = ConjectureRunner(
self.evaluate_test_data,
settings=self.settings, random=self.random,
database_key=database_key,
)
try:
runner.run()
finally:
self.used_examples_from_database = \
runner.used_examples_from_database
note_engine_for_statistics(runner)
run_time = benchmark_time() - self.start_time
self.used_examples_from_database = runner.used_examples_from_database
if runner.used_examples_from_database:
if self.settings.derandomize:
note_deprecation((
'In future derandomize will imply database=None, but your '
'test: %s is currently using examples from the database. '
'To get the future behaviour, update your settings to '
'include database=None.') % (self.test.__name__, )
)
if self.__had_seed:
note_deprecation((
'In future use of @seed will imply database=None in your '
'settings, but your test: %s is currently using examples '
'from the database. To get the future behaviour, update '
'your settings for this test to include database=None.')
% (self.test.__name__,)
)
timed_out = runner.exit_reason == ExitReason.timeout
if runner.call_count == 0:
return
if runner.interesting_examples:
self.falsifying_examples = sorted(
[d for d in runner.interesting_examples.values()],
key=lambda d: sort_key(d.buffer), reverse=True
)
else:
if runner.valid_examples == 0:
if timed_out:
raise Timeout((
'Ran out of time before finding a satisfying '
'example for %s. Only found %d examples in %.2fs.'
) % (
get_pretty_function_description(self.test),
runner.valid_examples, run_time
))
else:
raise Unsatisfiable(
'Unable to satisfy assumptions of hypothesis %s.' %
(get_pretty_function_description(self.test),)
)
if not self.falsifying_examples:
return
self.failed_normally = True
flaky = 0
for falsifying_example in self.falsifying_examples:
ran_example = ConjectureData.for_buffer(falsifying_example.buffer)
self.__was_flaky = False
assert falsifying_example.__expected_exception is not None
try:
self.execute(
ran_example,
print_example=True, is_final=True,
expected_failure=(
falsifying_example.__expected_exception,
falsifying_example.__expected_traceback,
)
)
except (UnsatisfiedAssumption, StopTest):
report(traceback.format_exc())
self.__flaky(
'Unreliable assumption: An example which satisfied '
'assumptions on the first run now fails it.'
)
except BaseException:
if len(self.falsifying_examples) <= 1:
raise
report(traceback.format_exc())
finally: # pragma: no cover
# This section is in fact entirely covered by the tests in
# test_reproduce_failure, but it seems to trigger a lovely set
# of coverage bugs: The branches show up as uncovered (despite
# definitely being covered - you can add an assert False else
# branch to verify this and see it fail - and additionally the
# second branch still complains about lack of coverage even if
# you add a pragma: no cover to it!
# See https://bitbucket.org/ned/coveragepy/issues/623/
if self.settings.print_blob is not PrintSettings.NEVER:
failure_blob = encode_failure(falsifying_example.buffer)
# Have to use the example we actually ran, not the original
# falsifying example! Otherwise we won't catch problems
# where the repr of the generated example doesn't parse.
can_use_repr = ran_example.can_reproduce_example_from_repr
if (
self.settings.print_blob is PrintSettings.ALWAYS or (
self.settings.print_blob is PrintSettings.INFER and
self.settings.verbosity >= Verbosity.normal and
not can_use_repr and
len(failure_blob) < 200
)
):
report((
'\n'
'You can reproduce this example by temporarily '
'adding @reproduce_failure(%r, %r) as a decorator '
'on your test case') % (
__version__, failure_blob,))
if self.__was_flaky:
flaky += 1
# If we only have one example then we should have raised an error or
# flaky prior to this point.
assert len(self.falsifying_examples) > 1
if flaky > 0:
raise Flaky((
'Hypothesis found %d distinct failures, but %d of them '
'exhibited some sort of flaky behaviour.') % (
len(self.falsifying_examples), flaky))
else:
raise MultipleFailures((
'Hypothesis found %d distinct failures.') % (
len(self.falsifying_examples,)))
def test_function(self, data):
if self.__pending_call_explanation is not None:
self.debug(self.__pending_call_explanation)
self.__pending_call_explanation = None
assert isinstance(data.observer, TreeRecordingObserver)
self.call_count += 1
interrupted = False
try:
self.__stoppable_test_function(data)
except KeyboardInterrupt:
interrupted = True
raise
except BaseException:
self.save_buffer(data.buffer)
raise
finally:
# No branch, because if we're interrupted we always raise
# the KeyboardInterrupt, never continue to the code below.
if not interrupted: # pragma: no branch
data.freeze()
call_stats = {
"status":
data.status.name.lower(),
"runtime":
data.finish_time - data.start_time,
"drawtime":
math.fsum(data.draw_times),
"events":
sorted({self.event_to_string(e)
for e in data.events}),
}
self.stats_per_test_case.append(call_stats)
self.__data_cache[data.buffer] = data.as_result()
self.debug_data(data)
if self.pareto_front is not None and self.pareto_front.add(
data.as_result()):
self.save_buffer(data.buffer, sub_key=b"pareto")
assert len(data.buffer) <= BUFFER_SIZE
if data.status >= Status.VALID:
for k, v in data.target_observations.items():
self.best_observed_targets[k] = max(
self.best_observed_targets[k], v)
if k not in self.best_examples_of_observed_targets:
self.best_examples_of_observed_targets[k] = data.as_result(
)
continue
existing_example = self.best_examples_of_observed_targets[k]
existing_score = existing_example.target_observations[k]
if v < existing_score:
continue
if v > existing_score or sort_key(data.buffer) < sort_key(
existing_example.buffer):
self.best_examples_of_observed_targets[k] = data.as_result(
)
if data.status == Status.VALID:
self.valid_examples += 1
if data.status == Status.INTERESTING:
key = data.interesting_origin
changed = False
try:
existing = self.interesting_examples[key]
except KeyError:
changed = True
self.last_bug_found_at = self.call_count
if self.first_bug_found_at is None:
self.first_bug_found_at = self.call_count
else:
if sort_key(data.buffer) < sort_key(existing.buffer):
self.shrinks += 1
self.downgrade_buffer(existing.buffer)
self.__data_cache.unpin(existing.buffer)
changed = True
if changed:
self.save_buffer(data.buffer)
self.interesting_examples[key] = data.as_result()
self.__data_cache.pin(data.buffer)
self.shrunk_examples.discard(key)
if self.shrinks >= MAX_SHRINKS:
self.exit_with(ExitReason.max_shrinks)
if (not self.ignore_limits
and self.finish_shrinking_deadline is not None
and self.finish_shrinking_deadline < time.perf_counter()):
# See https://github.com/HypothesisWorks/hypothesis/issues/2340
report(
"WARNING: Hypothesis has spent more than five minutes working to shrink "
"a failing example, and stopped because it is making very slow "
"progress. When you re-run your tests, shrinking will resume and "
"may take this long before aborting again.\n"
"PLEASE REPORT THIS if you can provide a reproducing example, so that "
"we can improve shrinking performance for everyone.")
self.exit_with(ExitReason.very_slow_shrinking)
if not self.interesting_examples:
# Note that this logic is reproduced to end the generation phase when
# we have interesting examples. Update that too if you change this!
# (The doubled implementation is because here we exit the engine entirely,
# while in the other case below we just want to move on to shrinking.)
if self.valid_examples >= self.settings.max_examples:
self.exit_with(ExitReason.max_examples)
if self.call_count >= max(
self.settings.max_examples * 10,
# We have a high-ish default max iterations, so that tests
# don't become flaky when max_examples is too low.
1000,
):
self.exit_with(ExitReason.max_iterations)
if self.__tree_is_exhausted():
self.exit_with(ExitReason.finished)
self.record_for_health_check(data)
def wrapped_test(*arguments, **kwargs):
# Tell pytest to omit the body of this function from tracebacks
__tracebackhide__ = True
test = wrapped_test.hypothesis.inner_test
if getattr(test, 'is_hypothesis_test', False):
note_deprecation((
'You have applied @given to test: %s more than once. In '
'future this will be an error. Applying @given twice '
'wraps the test twice, which can be extremely slow. A '
'similar effect can be gained by combining the arguments '
'of the two calls to given. For example, instead of '
'@given(booleans()) @given(integers()), you could write '
'@given(booleans(), integers())') % (test.__name__, )
)
settings = wrapped_test._hypothesis_internal_use_settings
random = get_random_for_wrapped_test(test, wrapped_test)
if infer in generator_kwargs.values():
hints = get_type_hints(test)
for name in [name for name, value in generator_kwargs.items()
if value is infer]:
if name not in hints:
raise InvalidArgument(
'passed %s=infer for %s, but %s has no type annotation'
% (name, test.__name__, name))
generator_kwargs[name] = st.from_type(hints[name])
processed_args = process_arguments_to_given(
wrapped_test, arguments, kwargs, generator_arguments,
generator_kwargs, argspec, test, settings
)
arguments, kwargs, test_runner, search_strategy = processed_args
runner = getattr(search_strategy, 'runner', None)
if isinstance(runner, TestCase) and test.__name__ in dir(TestCase):
msg = ('You have applied @given to the method %s, which is '
'used by the unittest runner but is not itself a test.'
' This is not useful in any way.' % test.__name__)
fail_health_check(settings, msg, HealthCheck.not_a_test_method)
if bad_django_TestCase(runner): # pragma: no cover
# Covered by the Django tests, but not the pytest coverage task
raise InvalidArgument(
'You have applied @given to a method on %s, but this '
'class does not inherit from the supported versions in '
'`hypothesis.extra.django`. Use the Hypothesis variants '
'to ensure that each example is run in a separate '
'database transaction.' % qualname(type(runner))
)
state = StateForActualGivenExecution(
test_runner, search_strategy, test, settings, random,
had_seed=wrapped_test._hypothesis_internal_use_seed
)
reproduce_failure = \
wrapped_test._hypothesis_internal_use_reproduce_failure
if reproduce_failure is not None:
expected_version, failure = reproduce_failure
if expected_version != __version__:
raise InvalidArgument((
'Attempting to reproduce a failure from a different '
'version of Hypothesis. This failure is from %s, but '
'you are currently running %r. Please change your '
'Hypothesis version to a matching one.'
) % (expected_version, __version__))
try:
state.execute(ConjectureData.for_buffer(
decode_failure(failure)),
print_example=True, is_final=True,
)
raise DidNotReproduce(
'Expected the test to raise an error, but it '
'completed successfully.'
)
except StopTest:
raise DidNotReproduce(
'The shape of the test data has changed in some way '
'from where this blob was defined. Are you sure '
"you're running the same test?"
)
except UnsatisfiedAssumption:
raise DidNotReproduce(
'The test data failed to satisfy an assumption in the '
'test. Have you added it since this blob was '
'generated?'
)
execute_explicit_examples(
test_runner, test, wrapped_test, settings, arguments, kwargs
)
if settings.max_examples <= 0:
return
if not (
Phase.reuse in settings.phases or
Phase.generate in settings.phases
):
return
try:
if isinstance(runner, TestCase) and hasattr(runner, 'subTest'):
subTest = runner.subTest
try:
setattr(runner, 'subTest', fake_subTest)
state.run()
finally:
setattr(runner, 'subTest', subTest)
else:
state.run()
except BaseException:
generated_seed = \
wrapped_test._hypothesis_internal_use_generated_seed
if generated_seed is not None and not state.failed_normally:
with local_settings(settings):
if running_under_pytest:
report(
'You can add @seed(%(seed)d) to this test or '
'run pytest with --hypothesis-seed=%(seed)d '
'to reproduce this failure.' % {
'seed': generated_seed})
else:
report(
'You can add @seed(%d) to this test to '
'reproduce this failure.' % (generated_seed,))
raise
def wrapped_test(*arguments, **kwargs):
# Tell pytest to omit the body of this function from tracebacks
__tracebackhide__ = True
test = wrapped_test.hypothesis.inner_test
if getattr(test, "is_hypothesis_test", False):
raise InvalidArgument((
"You have applied @given to the test %s more than once, which "
"wraps the test several times and is extremely slow. A "
"similar effect can be gained by combining the arguments "
"of the two calls to given. For example, instead of "
"@given(booleans()) @given(integers()), you could write "
"@given(booleans(), integers())") % (test.__name__, ))
settings = wrapped_test._hypothesis_internal_use_settings
random = get_random_for_wrapped_test(test, wrapped_test)
if infer in generator_kwargs.values():
hints = get_type_hints(test)
for name in [
name for name, value in generator_kwargs.items()
if value is infer
]:
if name not in hints:
raise InvalidArgument(
"passed %s=infer for %s, but %s has no type annotation"
% (name, test.__name__, name))
generator_kwargs[name] = st.from_type(hints[name])
processed_args = process_arguments_to_given(
wrapped_test,
arguments,
kwargs,
generator_arguments,
generator_kwargs,
argspec,
test,
settings,
)
arguments, kwargs, test_runner, search_strategy = processed_args
runner = getattr(search_strategy, "runner", None)
if isinstance(runner, TestCase) and test.__name__ in dir(TestCase):
msg = ("You have applied @given to the method %s, which is "
"used by the unittest runner but is not itself a test."
" This is not useful in any way." % test.__name__)
fail_health_check(settings, msg, HealthCheck.not_a_test_method)
if bad_django_TestCase(runner): # pragma: no cover
# Covered by the Django tests, but not the pytest coverage task
raise InvalidArgument(
"You have applied @given to a method on %s, but this "
"class does not inherit from the supported versions in "
"`hypothesis.extra.django`. Use the Hypothesis variants "
"to ensure that each example is run in a separate "
"database transaction." % qualname(type(runner)))
state = StateForActualGivenExecution(
test_runner,
search_strategy,
test,
settings,
random,
had_seed=wrapped_test._hypothesis_internal_use_seed,
)
reproduce_failure = wrapped_test._hypothesis_internal_use_reproduce_failure
if reproduce_failure is not None:
expected_version, failure = reproduce_failure
if expected_version != __version__:
raise InvalidArgument(
("Attempting to reproduce a failure from a different "
"version of Hypothesis. This failure is from %s, but "
"you are currently running %r. Please change your "
"Hypothesis version to a matching one.") %
(expected_version, __version__))
try:
state.execute(
ConjectureData.for_buffer(decode_failure(failure)),
print_example=True,
is_final=True,
)
raise DidNotReproduce(
"Expected the test to raise an error, but it "
"completed successfully.")
except StopTest:
raise DidNotReproduce(
"The shape of the test data has changed in some way "
"from where this blob was defined. Are you sure "
"you're running the same test?")
except UnsatisfiedAssumption:
raise DidNotReproduce(
"The test data failed to satisfy an assumption in the "
"test. Have you added it since this blob was "
"generated?")
execute_explicit_examples(test_runner, test, wrapped_test,
settings, arguments, kwargs)
if settings.max_examples <= 0:
return
if not (Phase.reuse in settings.phases
or Phase.generate in settings.phases):
return
try:
if isinstance(runner, TestCase) and hasattr(runner, "subTest"):
subTest = runner.subTest
try:
setattr(runner, "subTest", fake_subTest)
state.run()
finally:
setattr(runner, "subTest", subTest)
else:
state.run()
except BaseException as e:
generated_seed = wrapped_test._hypothesis_internal_use_generated_seed
with local_settings(settings):
if not (state.failed_normally or generated_seed is None):
if running_under_pytest:
report(
"You can add @seed(%(seed)d) to this test or "
"run pytest with --hypothesis-seed=%(seed)d "
"to reproduce this failure." %
{"seed": generated_seed})
else:
report("You can add @seed(%d) to this test to "
"reproduce this failure." %
(generated_seed, ))
# The dance here is to avoid showing users long tracebacks
# full of Hypothesis internals they don't care about.
# We have to do this inline, to avoid adding another
# internal stack frame just when we've removed the rest.
if PY2:
# Python 2 doesn't have Exception.with_traceback(...);
# instead it has a three-argument form of the `raise`
# statement. Unfortunately this is a SyntaxError on
# Python 3, and before Python 2.7.9 it was *also* a
# SyntaxError to use it in a nested function so we
# can't `exec` or `eval` our way out (BPO-21591).
# So unless we break some versions of Python 2, none
# of them get traceback elision.
raise
# On Python 3, we swap out the real traceback for our
# trimmed version. Using a variable ensures that the line
# which will actually appear in trackbacks is as clear as
# possible - "raise the_error_hypothesis_found".
the_error_hypothesis_found = e.with_traceback(
get_trimmed_traceback())
raise the_error_hypothesis_found
def __flaky(self, message):
if len(self.falsifying_examples) <= 1:
raise Flaky(message)
else:
self.__was_flaky = True
report('Flaky example! ' + message)
def __flaky(self, message):
if len(self.falsifying_examples) <= 1:
raise Flaky(message)
else:
self.__was_flaky = True
report('Flaky example! ' + message)
def custom_reporter(value):
"""
Custom reporter used to slightly modify hypothesis output
"""
textified = f"{value}".replace("state", "machine")
if "teardown" not in textified and "check" not in textified:
print(textified)
if __name__ == "__main__":
args = parser().parse_args()
with reporter.with_value(custom_reporter):
try:
run_state_machine_as_test(
lambda: state_machine_factory(
args.path,
args.seed,
config.states,
config.inputs,
config.outputs,
),
settings=settings(max_examples=1000),
)
except AssertionError as e:
report(e)
report(
"Implementation contains errors, correct them and try again!",
)
def wrapped_test(*arguments, **kwargs):
selfy = None
arguments, kwargs = convert_positional_arguments(wrapped_test, arguments, kwargs)
# Because we converted all kwargs to given into real args and
# error if we have neither args nor kwargs, this should always
# be valid
assert argspec.args
selfy = kwargs.get(argspec.args[0])
if isinstance(selfy, HypothesisProvided):
selfy = None
test_runner = executor(selfy)
for example in getattr(wrapped_test, "hypothesis_explicit_examples", ()):
if example.args:
example_kwargs = dict(zip(argspec.args[-len(example.args) :], example.args))
else:
example_kwargs = dict(example.kwargs)
for k, v in kwargs.items():
if not isinstance(v, HypothesisProvided):
example_kwargs[k] = v
# Note: Test may mutate arguments and we can't rerun explicit
# examples, so we have to calculate the failure message at this
# point rather than than later.
message_on_failure = "Falsifying example: %s(%s)" % (
test.__name__,
arg_string(test, arguments, example_kwargs),
)
try:
test_runner(lambda: test(*arguments, **example_kwargs))
except BaseException:
report(message_on_failure)
raise
if not any(isinstance(x, HypothesisProvided) for xs in (arguments, kwargs.values()) for x in xs):
# All arguments have been satisfied without needing to invoke
# hypothesis
test_runner(lambda: test(*arguments, **kwargs))
return
def convert_to_specifier(v):
if isinstance(v, HypothesisProvided):
return strategy(v.value, settings)
else:
return sd.just(v)
given_specifier = sd.tuples(
sd.tuples(*map(convert_to_specifier, arguments)),
sd.fixed_dictionaries(dict((k, convert_to_specifier(v)) for (k, v) in kwargs.items())),
)
search_strategy = strategy(given_specifier, settings)
if settings.database:
storage = settings.database.storage(fully_qualified_name(test))
else:
storage = None
last_exception = [None]
repr_for_last_exception = [None]
def is_template_example(xs):
record_repr = [None]
try:
test_runner(
reify_and_execute(
search_strategy, xs, test, always_print=settings.max_shrinks <= 0, record_repr=record_repr
)
)
return False
except UnsatisfiedAssumption as e:
raise e
except Exception as e:
if settings.max_shrinks <= 0:
raise e
last_exception[0] = traceback.format_exc()
repr_for_last_exception[0] = record_repr[0]
verbose_report(last_exception[0])
return True
is_template_example.__name__ = test.__name__
is_template_example.__qualname__ = qualname(test)
falsifying_template = None
try:
falsifying_template = best_satisfying_template(
search_strategy, random, is_template_example, settings, storage
)
except NoSuchExample:
return
assert last_exception[0] is not None
with settings:
test_runner(reify_and_execute(search_strategy, falsifying_template, test, print_example=True))
report("Failed to reproduce exception. Expected: \n" + last_exception[0])
test_runner(
reify_and_execute(
search_strategy,
falsifying_template,
test_is_flaky(test, repr_for_last_exception[0]),
print_example=True,
)
)
def report_buffered():
for f in fragments_reported:
report(f)
del fragments_reported[:]
def wrapped_test(*arguments, **kwargs):
import hypothesis.strategies as sd
from hypothesis.internal.strategymethod import strategy
selfy = None
arguments, kwargs = convert_positional_arguments(
wrapped_test, arguments, kwargs)
# Anything in unused_kwargs hasn't been injected through
# argspec.defaults, so we need to add them.
for k in unused_kwargs:
if k not in kwargs:
kwargs[k] = unused_kwargs[k]
# If the test function is a method of some kind, the bound object
# will be the first named argument if there are any, otherwise the
# first vararg (if any).
if argspec.args:
selfy = kwargs.get(argspec.args[0])
elif arguments:
selfy = arguments[0]
if isinstance(selfy, HypothesisProvided):
selfy = None
test_runner = executor(selfy)
for example in getattr(
wrapped_test, u'hypothesis_explicit_examples', ()
):
if example.args:
example_kwargs = dict(zip(
argspec.args[-len(example.args):], example.args
))
else:
example_kwargs = dict(example.kwargs)
for k, v in kwargs.items():
if not isinstance(v, HypothesisProvided):
example_kwargs[k] = v
# Note: Test may mutate arguments and we can't rerun explicit
# examples, so we have to calculate the failure message at this
# point rather than than later.
message_on_failure = u'Falsifying example: %s(%s)' % (
test.__name__, arg_string(test, arguments, example_kwargs)
)
try:
test_runner(
lambda: test(*arguments, **example_kwargs)
)
except BaseException:
report(message_on_failure)
raise
if not any(
isinstance(x, HypothesisProvided)
for xs in (arguments, kwargs.values())
for x in xs
):
# All arguments have been satisfied without needing to invoke
# hypothesis
test_runner(lambda: test(*arguments, **kwargs))
return
def convert_to_specifier(v):
if isinstance(v, HypothesisProvided):
return strategy(v.value, settings)
else:
return sd.just(v)
given_specifier = sd.tuples(
sd.tuples(*map(convert_to_specifier, arguments)),
sd.fixed_dictionaries(dict(
(k, convert_to_specifier(v)) for (k, v) in kwargs.items()))
)
search_strategy = strategy(given_specifier, settings)
if settings.database:
storage = settings.database.storage(
fully_qualified_name(test))
else:
storage = None
last_exception = [None]
repr_for_last_exception = [None]
def is_template_example(xs):
record_repr = [None]
try:
test_runner(reify_and_execute(
search_strategy, xs, test,
always_print=settings.max_shrinks <= 0,
record_repr=record_repr,
))
return False
except UnsatisfiedAssumption as e:
raise e
except Exception as e:
if settings.max_shrinks <= 0:
raise e
last_exception[0] = traceback.format_exc()
repr_for_last_exception[0] = record_repr[0]
verbose_report(last_exception[0])
return True
is_template_example.__name__ = test.__name__
is_template_example.__qualname__ = qualname(test)
falsifying_template = None
try:
falsifying_template = best_satisfying_template(
search_strategy, random, is_template_example,
settings, storage
)
except NoSuchExample:
return
assert last_exception[0] is not None
with settings:
test_runner(reify_and_execute(
search_strategy, falsifying_template, test,
print_example=True, is_final=True
))
report(
u'Failed to reproduce exception. Expected: \n' +
last_exception[0],
)
test_runner(reify_and_execute(
search_strategy, falsifying_template,
test_is_flaky(test, repr_for_last_exception[0]),
print_example=True, is_final=True
))
def execute(
self,
data,
print_example=False,
is_final=False,
expected_failure=None,
collect=False,
):
text_repr = [None]
if self.settings.deadline is None:
test = self.test
else:
@proxies(self.test)
def test(*args, **kwargs):
self.__test_runtime = None
initial_draws = len(data.draw_times)
start = benchmark_time()
result = self.test(*args, **kwargs)
finish = benchmark_time()
internal_draw_time = sum(data.draw_times[initial_draws:])
runtime = (finish - start - internal_draw_time) * 1000
self.__test_runtime = runtime
current_deadline = self.settings.deadline
if not is_final:
current_deadline *= 1.25
if runtime >= current_deadline:
raise DeadlineExceeded(runtime, self.settings.deadline)
return result
def run(data):
if not hasattr(data, "can_reproduce_example_from_repr"):
data.can_reproduce_example_from_repr = True
with local_settings(self.settings):
with BuildContext(data, is_final=is_final):
with deterministic_PRNG():
args, kwargs = data.draw(self.search_strategy)
if expected_failure is not None:
text_repr[0] = arg_string(test, args, kwargs)
if print_example:
example = "%s(%s)" % (
test.__name__,
arg_string(test, args, kwargs),
)
try:
ast.parse(example)
except SyntaxError:
data.can_reproduce_example_from_repr = False
report("Falsifying example: %s" % (example, ))
elif current_verbosity() >= Verbosity.verbose:
report(lambda: "Trying example: %s(%s)" % (
test.__name__, arg_string(test, args, kwargs)))
return test(*args, **kwargs)
result = self.test_runner(data, run)
if expected_failure is not None:
exception, traceback = expected_failure
if (isinstance(exception, DeadlineExceeded)
and self.__test_runtime is not None):
report(
("Unreliable test timings! On an initial run, this "
"test took %.2fms, which exceeded the deadline of "
"%.2fms, but on a subsequent run it took %.2f ms, "
"which did not. If you expect this sort of "
"variability in your test timings, consider turning "
"deadlines off for this test by setting deadline=None.") %
(exception.runtime, self.settings.deadline,
self.__test_runtime))
else:
report("Failed to reproduce exception. Expected: \n" +
traceback)
self.__flaky(
("Hypothesis %s(%s) produces unreliable results: Falsified"
" on the first call but did not on a subsequent one") %
(test.__name__, text_repr[0]))
return result