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 wrapped_test(*arguments, **kwargs):
selfy = None
# 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
test_runner(
lambda: test(*arguments, **example_kwargs)
)
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 v.value
else:
return just(v)
given_specifier = (
tuple(map(convert_to_specifier, arguments)),
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_for(
given_specifier, search_strategy)
else:
storage = None
def is_template_example(xs):
try:
test_runner(reify_and_execute(search_strategy, xs, test))
return False
except UnsatisfiedAssumption as e:
raise e
except Exception:
return True
is_template_example.__name__ = test.__name__
is_template_example.__qualname__ = getattr(
test, '__qualname__', test.__name__)
falsifying_template = None
try:
falsifying_template = best_satisfying_template(
search_strategy, random, is_template_example,
settings, storage
)
except NoSuchExample:
return
test_runner(reify_and_execute(
search_strategy, falsifying_template, test,
print_example=True
))
test_runner(reify_and_execute(
search_strategy, falsifying_template, test_is_flaky(test),
print_example=True
))
def wrapped_test(*arguments, **kwargs):
selfy = None
# 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
test_runner(lambda: test(*arguments, **example_kwargs))
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 v.value
else:
return just(v)
given_specifier = (tuple(map(convert_to_specifier, arguments)),
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_for(
given_specifier, search_strategy)
else:
storage = None
def is_template_example(xs):
try:
test_runner(reify_and_execute(search_strategy, xs, test))
return False
except UnsatisfiedAssumption as e:
raise e
except Exception:
return True
is_template_example.__name__ = test.__name__
is_template_example.__qualname__ = getattr(test, '__qualname__',
test.__name__)
falsifying_template = None
try:
falsifying_template = best_satisfying_template(
search_strategy, random, is_template_example, settings,
storage)
except NoSuchExample:
return
test_runner(
reify_and_execute(search_strategy,
falsifying_template,
test,
print_example=True))
test_runner(
reify_and_execute(search_strategy,
falsifying_template,
test_is_flaky(test),
print_example=True))
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 = executor(selfy)
for example in reversed(
getattr(wrapped_test, 'hypothesis_explicit_examples', ())):
if example.args:
example_kwargs = dict(
zip(original_argspec.args[-len(example.args):],
example.args))
else:
example_kwargs = example.kwargs
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(lambda: test(*arguments, **example_kwargs))
except BaseException:
report(message_on_failure)
for n in b.notes:
report(n)
raise
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):
message += (
'\nSee http://hypothesis.readthedocs.org/en/latest/health'
'checks.html for more information about this.')
if settings.strict:
raise FailedHealthCheck(message)
else:
warnings.warn(FailedHealthCheck(message))
search_strategy = given_specifier
search_strategy.validate()
if settings.database:
storage = settings.database.storage(fully_qualified_name(test))
else:
storage = None
start = time.time()
warned_random = [False]
perform_health_check = settings.perform_health_check
if Settings.default is not None:
perform_health_check &= Settings.default.perform_health_check
if perform_health_check:
initial_state = getglobalrandomstate()
health_check_random = Random(random.getrandbits(128))
count = 0
bad_draws = 0
filtered_draws = 0
errors = 0
while (count < 10 and time.time() < start + 1
and filtered_draws < 50 and bad_draws < 50):
try:
with Settings(settings, verbosity=Verbosity.quiet):
test_runner(
reify_and_execute(
search_strategy,
search_strategy.draw_template(
health_check_random,
search_strategy.draw_parameter(
health_check_random, )),
lambda *args, **kwargs: None,
))
count += 1
except BadTemplateDraw:
bad_draws += 1
except UnsatisfiedAssumption:
filtered_draws += 1
except Exception:
if errors == 0:
report(traceback.format_exc())
errors += 1
if test_runner is default_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 yo've passed to "
'it to construct your data.')
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. ')
if filtered_draws >= 50:
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.') % (filtered_draws, count))
if bad_draws >= 50:
fail_health_check(
'Hypothesis is struggling to generate examples. '
'This is often a sign of a recursive strategy which '
'fans out too broadly. If you\'re using recursive, '
'try to reduce the size of the recursive step or '
'increase the maximum permitted number of leaves.')
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. Try decreasing '
"size of the data yo're generating (with e.g."
'average_size or max_leaves parameters).') %
(count, runtime))
if getglobalrandomstate() != initial_state:
warned_random[0] = True
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.')
last_exception = [None]
repr_for_last_exception = [None]
def is_template_example(xs):
if perform_health_check and not warned_random[0]:
initial_state = getglobalrandomstate()
record_repr = [None]
try:
result = test_runner(
reify_and_execute(
search_strategy,
xs,
test,
record_repr=record_repr,
))
if result is not None and settings.perform_health_check:
raise FailedHealthCheck(
('Tests run under @given should return None, but '
'%s returned %r instead.') %
(test.__name__, result), settings)
return False
except (HypothesisDeprecationWarning, FailedHealthCheck,
UnsatisfiedAssumption):
raise
except Exception:
last_exception[0] = traceback.format_exc()
repr_for_last_exception[0] = record_repr[0]
verbose_report(last_exception[0])
return True
finally:
if (not warned_random[0] and perform_health_check
and getglobalrandomstate() != initial_state):
warned_random[0] = True
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.')
is_template_example.__name__ = test.__name__
is_template_example.__qualname__ = qualname(test)
with settings:
falsifying_template = None
try:
falsifying_template = best_satisfying_template(
search_strategy,
random,
is_template_example,
settings,
storage,
start_time=start,
)
except NoSuchExample:
return
assert last_exception[0] is not None
try:
test_runner(
reify_and_execute(search_strategy,
falsifying_template,
test,
print_example=True,
is_final=True))
except UnsatisfiedAssumption:
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], )
try:
test_runner(
reify_and_execute(search_strategy,
falsifying_template,
test_is_flaky(
test,
repr_for_last_exception[0]),
print_example=True,
is_final=True))
except UnsatisfiedAssumption:
raise Flaky(
'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.')
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 wrapped_test(*arguments, **kwargs):
if settings.derandomize:
random = Random(function_digest(test))
else:
random = provided_random or new_random()
import hypothesis.strategies as sd
from hypothesis.internal.strategymethod import strategy
selfy = None
arguments, kwargs = convert_positional_arguments(
wrapped_test, arguments, kwargs)
for arg in hypothesis_owned_arguments:
try:
value = kwargs[arg]
except KeyError:
continue
if not isinstance(value, HypothesisProvided):
note_deprecation(
'Passing in explicit values to override Hypothesis '
'provided values is deprecated and will no longer '
'work in Hypothesis 2.0. If you need to do this, '
'extract a common function and call that from a '
'Hypothesis based test.', settings
)
# 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 reversed(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:
with BuildContext() as b:
test_runner(
lambda: test(*arguments, **example_kwargs)
)
except BaseException:
report(message_on_failure)
for n in b.notes:
report(n)
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()))
)
def fail_health_check(message):
message += (
'\nSee http://hypothesis.readthedocs.org/en/latest/health'
'checks.html for more information about this.'
)
if settings.strict:
raise FailedHealthCheck(message)
else:
warnings.warn(FailedHealthCheck(message))
search_strategy = strategy(given_specifier, settings)
search_strategy.validate()
if settings.database:
storage = settings.database.storage(
fully_qualified_name(test))
else:
storage = None
start = time.time()
warned_random = [False]
perform_health_check = settings.perform_health_check
if Settings.default is not None:
perform_health_check &= Settings.default.perform_health_check
if perform_health_check:
initial_state = getglobalrandomstate()
health_check_random = Random(random.getrandbits(128))
count = 0
bad_draws = 0
filtered_draws = 0
errors = 0
while (
count < 10 and time.time() < start + 1 and
filtered_draws < 50 and bad_draws < 50
):
try:
with Settings(settings, verbosity=Verbosity.quiet):
test_runner(reify_and_execute(
search_strategy,
search_strategy.draw_template(
health_check_random,
search_strategy.draw_parameter(
health_check_random,
)),
lambda *args, **kwargs: None,
))
count += 1
except BadTemplateDraw:
bad_draws += 1
except UnsatisfiedAssumption:
filtered_draws += 1
except Exception:
if errors == 0:
report(traceback.format_exc())
errors += 1
if test_runner is default_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.'
)
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. '
)
if filtered_draws >= 50:
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.') % (
filtered_draws, count
))
if bad_draws >= 50:
fail_health_check(
'Hypothesis is struggling to generate examples. '
'This is often a sign of a recursive strategy which '
'fans out too broadly. If you\'re using recursive, '
'try to reduce the size of the recursive step or '
'increase the maximum permitted number of leaves.'
)
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. Try decreasing '
"size of the data you're generating (with e.g."
'average_size or max_leaves parameters).'
) % (count, runtime))
if getglobalrandomstate() != initial_state:
warned_random[0] = True
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.'
)
last_exception = [None]
repr_for_last_exception = [None]
def is_template_example(xs):
if perform_health_check and not warned_random[0]:
initial_state = getglobalrandomstate()
record_repr = [None]
try:
result = test_runner(reify_and_execute(
search_strategy, xs, test,
record_repr=record_repr,
))
if result is not None:
note_deprecation((
'Tests run under @given should return None, but '
'%s returned %r instead.'
'In Hypothesis 2.0 this will become an error.'
) % (test.__name__, result), settings)
return False
except HypothesisDeprecationWarning:
raise
except UnsatisfiedAssumption as e:
raise e
except Exception as e:
last_exception[0] = traceback.format_exc()
repr_for_last_exception[0] = record_repr[0]
verbose_report(last_exception[0])
return True
finally:
if (
not warned_random[0] and
perform_health_check and
getglobalrandomstate() != initial_state
):
warned_random[0] = True
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.'
)
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, start_time=start,
)
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 wrapped_test(*arguments, **kwargs):
selfy = None
# 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
test_runner(
lambda: test(*arguments, **example_kwargs)
)
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 v.value
else:
return just(v)
given_specifier = (
tuple(map(convert_to_specifier, arguments)),
{k: convert_to_specifier(v) for k, v in kwargs.items()}
)
if settings.database:
storage = settings.database.storage_for(given_specifier)
else:
storage = None
search_strategy = strategy(given_specifier, settings)
def is_template_example(xs):
try:
test_runner(reify_and_execute(search_strategy, xs, test))
return False
except UnsatisfiedAssumption as e:
raise e
except Exception:
return True
is_template_example.__name__ = test.__name__
is_template_example.__qualname__ = getattr(
test, '__qualname__', test.__name__)
falsifying_template = None
try:
falsifying_template = best_satisfying_template(
search_strategy, random, is_template_example,
settings, storage
)
except NoSuchExample:
return
try:
# We run this one final time so we get good errors
# Otherwise we would have swallowed all the reports of it
# actually having gone wrong.
test_runner(reify_and_execute(
search_strategy, falsifying_template, test_must_fail(test),
print_example=True
))
finally:
# Some strategies use a weakref cache keyed off templates.
# By cleaning up this template now we make it easier for python
# to clear the cache early in some circumstances.
del falsifying_template
def wrapped_test(*arguments, **kwargs):
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, '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 wrapped_test(*arguments, **kwargs):
selfy = None
# 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
test_runner(
lambda: test(*arguments, **example_kwargs)
)
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]
def is_template_example(xs):
try:
test_runner(reify_and_execute(
search_strategy, xs, test,
always_print=settings.max_shrinks <= 0
))
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()
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),
print_example=True
))
def wrapped_test(*arguments, **kwargs):
selfy = None
# 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
test_runner(
lambda: test(*arguments, **example_kwargs)
)
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]
def is_template_example(xs):
try:
test_runner(reify_and_execute(
search_strategy, xs, test,
always_print=settings.max_shrinks <= 0
))
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()
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),
print_example=True
))