def new_buffer(self):
self.last_data = TestData(max_length=self.settings.buffer_size,
draw_bytes=lambda data, n, distribution:
distribution(self.random, n))
self.test_function(self.last_data)
self.last_data.freeze()
self.note_for_corpus(self.last_data)
def test_distribution_is_correctly_translated(inter, rnd):
assert inter == sorted(inter)
lower, c1, c2, upper = inter
d = TestData(draw_bytes=lambda data, n, distribution: distribution(rnd, n),
max_length=10**6)
assert d.draw(interval(lower, upper, c1, lambda r: c2)) == c2
assert d.draw(interval(lower, upper, c2, lambda r: c1)) == c1
def test_distribution_is_correctly_translated(inter, rnd):
assert inter == sorted(inter)
lower, c1, c2, upper = inter
d = TestData(
draw_bytes=lambda data, n, distribution: distribution(rnd, n),
max_length=10 ** 6
)
assert d.draw(interval(lower, upper, c1, lambda r: c2)) == c2
assert d.draw(interval(lower, upper, c2, lambda r: c1)) == c1
def incorporate_new_buffer(self, buffer):
if buffer in self.seen:
return False
assert self.last_data.status == Status.INTERESTING
if (
self.settings.timeout > 0 and
time.time() >= self.start_time + self.settings.timeout
):
raise RunIsComplete()
self.examples_considered += 1
buffer = buffer[:self.last_data.index]
if sort_key(buffer) >= sort_key(self.last_data.buffer):
return False
assert sort_key(buffer) <= sort_key(self.last_data.buffer)
data = TestData.for_buffer(buffer)
self.test_function(data)
data.freeze()
self.note_for_corpus(data)
if self.consider_new_test_data(data):
self.shrinks += 1
self.last_data = data
if self.shrinks >= self.settings.max_shrinks:
raise RunIsComplete()
self.last_data = data
self.changed += 1
return True
return False
def test_draw_past_end_sets_overflow():
x = TestData.for_buffer(bytes(5))
with pytest.raises(StopTest) as e:
x.draw_bytes(6)
assert e.value.testcounter == x.testcounter
assert x.frozen
assert x.status == Status.OVERRUN
def incorporate_new_buffer(self, buffer):
if buffer in self.seen:
return False
assert self.last_data.status == Status.INTERESTING
if (self.settings.timeout > 0
and time.time() >= self.start_time + self.settings.timeout):
raise RunIsComplete()
self.examples_considered += 1
buffer = buffer[:self.last_data.index]
if sort_key(buffer) >= sort_key(self.last_data.buffer):
return False
assert sort_key(buffer) <= sort_key(self.last_data.buffer)
data = TestData.for_buffer(buffer)
self.test_function(data)
data.freeze()
self.note_for_corpus(data)
if self.consider_new_test_data(data):
self.shrinks += 1
self.last_data = data
if self.shrinks >= self.settings.max_shrinks:
raise RunIsComplete()
self.last_data = data
self.changed += 1
return True
return False
def test_draw_past_end_sets_overflow():
x = TestData.for_buffer(bytes(5))
with pytest.raises(StopTest) as e:
x.draw_bytes(6)
assert e.value.testcounter == x.testcounter
assert x.frozen
assert x.status == Status.OVERRUN
def new_buffer(self):
self.last_data = TestData(
max_length=self.settings.buffer_size,
draw_bytes=lambda data, n, distribution:
distribution(self.random, n)
)
self.test_function(self.last_data)
self.last_data.freeze()
def test_variadic_draw():
def draw_list(data):
result = []
while True:
data.start_example()
d = data.draw_bytes(1)[0] & 7
if d:
result.append(data.draw_bytes(d))
data.stop_example()
if not d:
break
return result
@run_to_buffer
def b(data):
if any(all(d) for d in draw_list(data)):
data.mark_interesting()
l = draw_list(TestData.for_buffer(b))
assert len(l) == 1
assert len(l[0]) == 1
def test_variadic_draw():
def draw_list(data):
result = []
while True:
data.start_example()
d = data.draw_bytes(1)[0] & 7
if d:
result.append(data.draw_bytes(d))
data.stop_example()
if not d:
break
return result
@run_to_buffer
def b(data):
if any(all(d) for d in draw_list(data)):
data.mark_interesting()
l = draw_list(TestData.for_buffer(b))
assert len(l) == 1
assert len(l[0]) == 1
def test_can_double_freeze():
x = TestData.for_buffer(b'hi')
x.freeze()
assert x.frozen
x.freeze()
assert x.frozen
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:
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 test_can_double_freeze():
x = TestData.for_buffer(b'hi')
x.freeze()
assert x.frozen
x.freeze()
assert x.frozen
def test_buffer_draws_as_self(buf):
x = TestData.for_buffer(buf)
assert x.draw_bytes(len(buf), bogus_dist) == buf
def _run(self):
self.last_data = None
mutations = 0
start_time = time.time()
if (
self.settings.database is not None and
self.database_key is not None
):
corpus = sorted(
self.settings.database.fetch(self.database_key),
key=lambda d: (len(d), d)
)
for existing in corpus:
if self.valid_examples >= self.settings.max_examples:
self.exit_reason = ExitReason.max_examples
return
if self.call_count >= max(
self.settings.max_iterations, self.settings.max_examples
):
self.exit_reason = ExitReason.max_iterations
return
data = TestData.for_buffer(existing)
self.test_function(data)
data.freeze()
self.last_data = data
if data.status < Status.VALID:
self.settings.database.delete(
self.database_key, existing)
elif data.status == Status.VALID:
# Incremental garbage collection! we store a lot of
# examples in the DB as we shrink: Those that stay
# interesting get kept, those that become invalid get
# dropped, but those that are merely valid gradually go
# away over time.
if self.random.randint(0, 2) == 0:
self.settings.database.delete(
self.database_key, existing)
else:
assert data.status == Status.INTERESTING
self.last_data = data
break
if Phase.generate in self.settings.phases:
if (
self.last_data is None or
self.last_data.status < Status.INTERESTING
):
self.new_buffer()
mutator = self._new_mutator()
while self.last_data.status != Status.INTERESTING:
if self.valid_examples >= self.settings.max_examples:
self.exit_reason = ExitReason.max_examples
return
if self.call_count >= max(
self.settings.max_iterations, self.settings.max_examples
):
self.exit_reason = ExitReason.max_iterations
return
if (
self.settings.timeout > 0 and
time.time() >= start_time + self.settings.timeout
):
self.exit_reason = ExitReason.timeout
return
if mutations >= self.settings.max_mutations:
mutations = 0
self.new_buffer()
mutator = self._new_mutator()
else:
data = TestData(
draw_bytes=mutator,
max_length=self.settings.buffer_size
)
self.test_function(data)
data.freeze()
prev_data = self.last_data
if self.consider_new_test_data(data):
self.last_data = data
if data.status > prev_data.status:
mutations = 0
else:
mutator = self._new_mutator()
mutations += 1
data = self.last_data
if data is None:
self.exit_reason = ExitReason.finished
return
assert isinstance(data.output, text_type)
if self.settings.max_shrinks <= 0:
self.exit_reason = ExitReason.max_shrinks
return
if Phase.shrink not in self.settings.phases:
self.exit_reason = ExitReason.finished
return
if not self.last_data.buffer:
self.exit_reason = ExitReason.finished
return
data = TestData.for_buffer(self.last_data.buffer)
self.test_function(data)
if data.status != Status.INTERESTING:
self.exit_reason = ExitReason.flaky
return
change_counter = -1
while self.changed > change_counter:
change_counter = self.changed
self.debug('Random interval deletes')
failed_deletes = 0
while self.last_data.intervals and failed_deletes < 10:
if self.random.randint(0, 1):
u, v = self.random.choice(self.last_data.intervals)
else:
n = len(self.last_data.buffer) - 1
u, v = sorted((
self.random.choice(self.last_data.intervals)
))
if (
v < len(self.last_data.buffer)
) and self.incorporate_new_buffer(
self.last_data.buffer[:u] +
self.last_data.buffer[v:]
):
failed_deletes = 0
else:
failed_deletes += 1
self.debug('Structured interval deletes')
i = 0
while i < len(self.last_data.intervals):
u, v = self.last_data.intervals[i]
if not self.incorporate_new_buffer(
self.last_data.buffer[:u] +
self.last_data.buffer[v:]
):
i += 1
if change_counter != self.changed:
self.debug('Restarting')
continue
self.debug('Lexicographical minimization of whole buffer')
minimize(
self.last_data.buffer, self.incorporate_new_buffer,
cautious=True
)
if change_counter != self.changed:
self.debug('Restarting')
continue
self.debug('Replacing blocks with simpler blocks')
i = 0
while i < len(self.last_data.blocks):
u, v = self.last_data.blocks[i]
buf = self.last_data.buffer
block = buf[u:v]
n = v - u
all_blocks = sorted(set([bytes(n)] + [
buf[a:a + n]
for a in self.last_data.block_starts[n]
]))
better_blocks = all_blocks[:all_blocks.index(block)]
for b in better_blocks:
if self.incorporate_new_buffer(
buf[:u] + b + buf[v:]
):
break
i += 1
self.debug('Simultaneous shrinking of duplicated blocks')
block_counter = -1
while block_counter < self.changed:
block_counter = self.changed
blocks = [
k for k, count in
Counter(
self.last_data.buffer[u:v]
for u, v in self.last_data.blocks).items()
if count > 1
]
for block in blocks:
parts = [
self.last_data.buffer[r:s]
for r, s in self.last_data.blocks
]
def replace(b):
return b''.join(
bytes(b if c == block else c) for c in parts
)
minimize(
block,
lambda b: self.incorporate_new_buffer(replace(b)),
self.random
)
self.debug('Shrinking of individual blocks')
i = 0
while i < len(self.last_data.blocks):
u, v = self.last_data.blocks[i]
minimize(
self.last_data.buffer[u:v],
lambda b: self.incorporate_new_buffer(
self.last_data.buffer[:u] + b +
self.last_data.buffer[v:],
), self.random
)
i += 1
self.debug('Replacing intervals with simpler intervals')
interval_counter = -1
while interval_counter != self.changed:
interval_counter = self.changed
i = 0
alternatives = None
while i < len(self.last_data.intervals):
if alternatives is None:
alternatives = sorted(set(
self.last_data.buffer[u:v]
for u, v in self.last_data.intervals), key=len)
u, v = self.last_data.intervals[i]
for a in alternatives:
buf = self.last_data.buffer
if (
len(a) < v - u or
(len(a) == (v - u) and a < buf[u:v])
):
if self.incorporate_new_buffer(
buf[:u] + a + buf[v:]
):
alternatives = None
break
i += 1
if change_counter != self.changed:
self.debug('Restarting')
continue
self.debug('Shuffling suffixes while shrinking %r' % (
self.last_data.bind_points,
))
b = 0
while b < len(self.last_data.bind_points):
cutoff = sorted(self.last_data.bind_points)[b]
def test_value(prefix):
for t in hrange(5):
alphabet = {}
for i, j in self.last_data.blocks[b:]:
alphabet.setdefault(j - i, []).append((i, j))
if t > 0:
for v in alphabet.values():
self.random.shuffle(v)
buf = bytearray(prefix)
for i, j in self.last_data.blocks[b:]:
u, v = alphabet[j - i].pop()
buf.extend(self.last_data.buffer[u:v])
if self.incorporate_new_buffer(hbytes(buf)):
return True
return False
minimize(
self.last_data.buffer[:cutoff], test_value, cautious=True
)
b += 1
self.exit_reason = ExitReason.finished
def _run(self):
self.last_data = None
mutations = 0
start_time = time.time()
if (self.settings.database is not None
and self.database_key is not None):
corpus = sorted(self.settings.database.fetch(self.database_key),
key=lambda d: (len(d), d))
for existing in corpus:
if self.valid_examples >= self.settings.max_examples:
return
if self.iterations >= max(self.settings.max_iterations,
self.settings.max_examples):
return
data = TestData.for_buffer(existing)
self.test_function(data)
data.freeze()
self.last_data = data
if data.status < Status.VALID:
self.settings.database.delete(self.database_key, existing)
elif data.status == Status.VALID:
# Incremental garbage collection! we store a lot of
# examples in the DB as we shrink: Those that stay
# interesting get kept, those that become invalid get
# dropped, but those that are merely valid gradually go
# away over time.
if self.random.randint(0, 2) == 0:
self.settings.database.delete(self.database_key,
existing)
else:
assert data.status == Status.INTERESTING
self.last_data = data
break
if Phase.generate in self.settings.phases:
if (self.last_data is None
or self.last_data.status < Status.INTERESTING):
self.new_buffer()
mutator = self._new_mutator()
while self.last_data.status != Status.INTERESTING:
if self.valid_examples >= self.settings.max_examples:
return
if self.iterations >= max(self.settings.max_iterations,
self.settings.max_examples):
return
if (self.settings.timeout > 0
and time.time() >= start_time + self.settings.timeout):
return
if mutations >= self.settings.max_mutations:
mutations = 0
self.new_buffer()
mutator = self._new_mutator()
else:
data = TestData(draw_bytes=mutator,
max_length=self.settings.buffer_size)
self.test_function(data)
data.freeze()
self.note_for_corpus(data)
prev_data = self.last_data
if self.consider_new_test_data(data):
self.last_data = data
if data.status > prev_data.status:
mutations = 0
else:
mutator = self._new_mutator()
mutations += 1
data = self.last_data
if data is None:
return
assert isinstance(data.output, text_type)
if self.settings.max_shrinks <= 0:
return
if Phase.shrink not in self.settings.phases:
return
if not self.last_data.buffer:
return
data = TestData.for_buffer(self.last_data.buffer)
self.test_function(data)
if data.status != Status.INTERESTING:
return
change_counter = -1
while self.changed > change_counter:
change_counter = self.changed
failed_deletes = 0
while self.last_data.intervals and failed_deletes < 10:
if self.random.randint(0, 1):
u, v = self.random.choice(self.last_data.intervals)
else:
n = len(self.last_data.buffer) - 1
u, v = sorted(
(self.random.choice(self.last_data.intervals)))
if (
v < len(self.last_data.buffer)
) and self.incorporate_new_buffer(self.last_data.buffer[:u] +
self.last_data.buffer[v:]):
failed_deletes = 0
else:
failed_deletes += 1
i = 0
while i < len(self.last_data.intervals):
u, v = self.last_data.intervals[i]
if not self.incorporate_new_buffer(self.last_data.buffer[:u] +
self.last_data.buffer[v:]):
i += 1
i = 0
while i + 1 < len(self.last_data.buffer):
if not self.incorporate_new_buffer(self.last_data.buffer[:i] +
self.last_data.buffer[i +
1:]):
i += 1
i = 0
while i < len(self.last_data.blocks):
u, v = self.last_data.blocks[i]
buf = self.last_data.buffer
block = buf[u:v]
n = v - u
all_blocks = sorted(
set([bytes(n)] +
[buf[a:a + n]
for a in self.last_data.block_starts[n]]))
better_blocks = all_blocks[:all_blocks.index(block)]
for b in better_blocks:
if self.incorporate_new_buffer(buf[:u] + b + buf[v:]):
break
i += 1
block_counter = -1
while block_counter < self.changed:
block_counter = self.changed
blocks = [
k for k, count in Counter(
self.last_data.buffer[u:v]
for u, v in self.last_data.blocks).items() if count > 1
]
for block in blocks:
parts = [
self.last_data.buffer[r:s]
for r, s in self.last_data.blocks
]
def replace(b):
return b''.join(
bytes(b if c == block else c) for c in parts)
minimize(block,
lambda b: self.incorporate_new_buffer(replace(b)),
self.random)
i = 0
while i < len(self.last_data.blocks):
u, v = self.last_data.blocks[i]
minimize(
self.last_data.buffer[u:v],
lambda b: self.incorporate_new_buffer(
self.last_data.buffer[:u] + b + self.last_data.buffer[
v:], ), self.random)
i += 1
i = 0
alternatives = None
while i < len(self.last_data.intervals):
if alternatives is None:
alternatives = sorted(set(
self.last_data.buffer[u:v]
for u, v in self.last_data.intervals),
key=len)
u, v = self.last_data.intervals[i]
for a in alternatives:
buf = self.last_data.buffer
if (len(a) < v - u
or (len(a) == (v - u) and a < buf[u:v])):
if self.incorporate_new_buffer(buf[:u] + a + buf[v:]):
alternatives = None
break
i += 1
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
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):
message += (
'\nSee http://hypothesis.readthedocs.org/en/latest/health'
'checks.html for more information about this.'
)
raise FailedHealthCheck(message)
search_strategy = given_specifier
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 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 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 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 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
))
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
))
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))
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.'
)
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:
raise FailedHealthCheck((
'Tests run under @given should return None, but '
'%s returned %r instead.'
) % (test.__name__, result), settings)
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.')
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.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 bc():
return BuildContext(TD.for_buffer(b''))
def find(specifier, condition, settings=None, random=None, database_key=None):
settings = settings or Settings(
max_examples=2000,
min_satisfying_examples=0,
max_shrinks=2000,
)
if database_key is None and settings.database is not None:
database_key = function_digest(condition)
if not isinstance(specifier, SearchStrategy):
raise InvalidArgument('Expected SearchStrategy but got %r of type %s' %
(specifier, type(specifier).__name__))
search = specifier
random = random or new_random()
successful_examples = [0]
last_data = [None]
def template_condition(data):
with BuildContext():
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()
from hypothesis.internal.conjecture.engine import TestRunner
from hypothesis.internal.conjecture.data import TestData, Status
start = time.time()
runner = TestRunner(
template_condition,
settings=settings,
random=random,
database_key=database_key,
)
runner.run()
run_time = time.time() - start
if runner.last_data.status == Status.INTERESTING:
with BuildContext():
return TestData.for_buffer(runner.last_data.buffer).draw(search)
if runner.valid_examples <= settings.min_satisfying_examples:
if settings.timeout > 0 and run_time > settings.timeout:
raise Timeout(
('Ran out of time before finding enough valid examples for '
'%s. Only %d valid examples found in %.2f seconds.') %
(get_pretty_function_description(condition),
runner.valid_examples, run_time))
else:
raise Unsatisfiable(
('Unable to satisfy assumptions of '
'%s. Only %d examples considered satisfied assumptions') % (
get_pretty_function_description(condition),
runner.valid_examples,
))
raise NoSuchExample(get_pretty_function_description(condition))
def test_can_mark_interesting():
x = TestData.for_buffer(bytes())
with pytest.raises(StopTest):
x.mark_interesting()
assert x.frozen
assert x.status == Status.INTERESTING
def test_closes_interval_on_error_in_strategy():
x = TestData.for_buffer(b'hi')
with pytest.raises(ValueError):
x.draw(BoomStrategy())
x.freeze()
assert len(x.intervals) == 1
class TestRunner(object):
def __init__(
self,
test_function,
settings=None,
random=None,
database_key=None,
):
self._test_function = test_function
self.settings = settings or Settings()
self.last_data = None
self.changed = 0
self.shrinks = 0
self.examples_considered = 0
self.iterations = 0
self.valid_examples = 0
self.start_time = time.time()
self.random = random or Random(getrandbits(128))
self.database_key = database_key
self.seen = set()
def new_buffer(self):
self.last_data = TestData(max_length=self.settings.buffer_size,
draw_bytes=lambda data, n, distribution:
distribution(self.random, n))
self.test_function(self.last_data)
self.last_data.freeze()
self.note_for_corpus(self.last_data)
def test_function(self, data):
self.iterations += 1
try:
self._test_function(data)
data.freeze()
except StopTest as e:
if e.testcounter != data.testcounter:
self.save_buffer(data.buffer)
raise e
except:
self.save_buffer(data.buffer)
raise
if (data.status == Status.INTERESTING and
(self.last_data is None or data.buffer != self.last_data.buffer)):
self.debug_data(data)
if data.status >= Status.VALID:
self.valid_examples += 1
def consider_new_test_data(self, data):
# Transition rules:
# 1. Transition cannot decrease the status
# 2. Any transition which increases the status is valid
# 3. If the previous status was interesting, only shrinking
# transitions are allowed.
self.seen.add(hbytes(data.buffer))
if data.buffer == self.last_data.buffer:
return False
if self.last_data.status < data.status:
return True
if self.last_data.status > data.status:
return False
if data.status == Status.INVALID:
return data.index >= self.last_data.index
if data.status == Status.OVERRUN:
return data.overdraw <= self.last_data.overdraw
if data.status == Status.INTERESTING:
assert len(data.buffer) <= len(self.last_data.buffer)
if len(data.buffer) == len(self.last_data.buffer):
assert data.buffer < self.last_data.buffer
return True
return True
def save_buffer(self, buffer):
if (self.settings.database is not None
and self.database_key is not None
and Phase.reuse in self.settings.phases):
self.settings.database.save(self.database_key, hbytes(buffer))
def note_for_corpus(self, data):
if data.status == Status.INTERESTING:
self.save_buffer(data.buffer)
def debug(self, message):
with self.settings:
debug_report(message)
def debug_data(self, data):
self.debug(u'%d bytes %s -> %s, %s' % (
data.index,
unicode_safe_repr(list(data.buffer[:data.index])),
unicode_safe_repr(data.status),
data.output,
))
def incorporate_new_buffer(self, buffer):
if buffer in self.seen:
return False
assert self.last_data.status == Status.INTERESTING
if (self.settings.timeout > 0
and time.time() >= self.start_time + self.settings.timeout):
raise RunIsComplete()
self.examples_considered += 1
buffer = buffer[:self.last_data.index]
if sort_key(buffer) >= sort_key(self.last_data.buffer):
return False
assert sort_key(buffer) <= sort_key(self.last_data.buffer)
data = TestData.for_buffer(buffer)
self.test_function(data)
data.freeze()
self.note_for_corpus(data)
if self.consider_new_test_data(data):
self.shrinks += 1
self.last_data = data
if self.shrinks >= self.settings.max_shrinks:
raise RunIsComplete()
self.last_data = data
self.changed += 1
return True
return False
def run(self):
with self.settings:
try:
self._run()
except RunIsComplete:
pass
self.debug(
u'Run complete after %d examples (%d valid) and %d shrinks' % (
self.iterations,
self.valid_examples,
self.shrinks,
))
def _new_mutator(self):
def draw_new(data, n, distribution):
return distribution(self.random, n)
def draw_existing(data, n, distribution):
return self.last_data.buffer[data.index:data.index + n]
def draw_smaller(data, n, distribution):
existing = self.last_data.buffer[data.index:data.index + n]
r = distribution(self.random, n)
if r <= existing:
return r
return _draw_predecessor(self.random, existing)
def draw_larger(data, n, distribution):
existing = self.last_data.buffer[data.index:data.index + n]
r = distribution(self.random, n)
if r >= existing:
return r
return _draw_successor(self.random, existing)
def reuse_existing(data, n, distribution):
choices = data.block_starts.get(n, []) or \
self.last_data.block_starts.get(n, [])
if choices:
i = self.random.choice(choices)
return self.last_data.buffer[i:i + n]
else:
return distribution(self.random, n)
def flip_bit(data, n, distribution):
buf = bytearray(self.last_data.buffer[data.index:data.index + n])
i = self.random.randint(0, n - 1)
k = self.random.randint(0, 7)
buf[i] ^= (1 << k)
return hbytes(buf)
def draw_zero(data, n, distribution):
return b'\0' * n
def draw_constant(data, n, distribution):
return bytes_from_list([self.random.randint(0, 255)] * n)
options = [
draw_new,
reuse_existing,
reuse_existing,
draw_existing,
draw_smaller,
draw_larger,
flip_bit,
draw_zero,
draw_constant,
]
bits = [self.random.choice(options) for _ in hrange(3)]
def draw_mutated(data, n, distribution):
if (data.index + n > len(self.last_data.buffer)):
return distribution(self.random, n)
return self.random.choice(bits)(data, n, distribution)
return draw_mutated
def _run(self):
self.last_data = None
mutations = 0
start_time = time.time()
if (self.settings.database is not None
and self.database_key is not None):
corpus = sorted(self.settings.database.fetch(self.database_key),
key=lambda d: (len(d), d))
for existing in corpus:
if self.valid_examples >= self.settings.max_examples:
return
if self.iterations >= max(self.settings.max_iterations,
self.settings.max_examples):
return
data = TestData.for_buffer(existing)
self.test_function(data)
data.freeze()
self.last_data = data
if data.status < Status.VALID:
self.settings.database.delete(self.database_key, existing)
elif data.status == Status.VALID:
# Incremental garbage collection! we store a lot of
# examples in the DB as we shrink: Those that stay
# interesting get kept, those that become invalid get
# dropped, but those that are merely valid gradually go
# away over time.
if self.random.randint(0, 2) == 0:
self.settings.database.delete(self.database_key,
existing)
else:
assert data.status == Status.INTERESTING
self.last_data = data
break
if Phase.generate in self.settings.phases:
if (self.last_data is None
or self.last_data.status < Status.INTERESTING):
self.new_buffer()
mutator = self._new_mutator()
while self.last_data.status != Status.INTERESTING:
if self.valid_examples >= self.settings.max_examples:
return
if self.iterations >= max(self.settings.max_iterations,
self.settings.max_examples):
return
if (self.settings.timeout > 0
and time.time() >= start_time + self.settings.timeout):
return
if mutations >= self.settings.max_mutations:
mutations = 0
self.new_buffer()
mutator = self._new_mutator()
else:
data = TestData(draw_bytes=mutator,
max_length=self.settings.buffer_size)
self.test_function(data)
data.freeze()
self.note_for_corpus(data)
prev_data = self.last_data
if self.consider_new_test_data(data):
self.last_data = data
if data.status > prev_data.status:
mutations = 0
else:
mutator = self._new_mutator()
mutations += 1
data = self.last_data
if data is None:
return
assert isinstance(data.output, text_type)
if self.settings.max_shrinks <= 0:
return
if Phase.shrink not in self.settings.phases:
return
if not self.last_data.buffer:
return
data = TestData.for_buffer(self.last_data.buffer)
self.test_function(data)
if data.status != Status.INTERESTING:
return
change_counter = -1
while self.changed > change_counter:
change_counter = self.changed
failed_deletes = 0
while self.last_data.intervals and failed_deletes < 10:
if self.random.randint(0, 1):
u, v = self.random.choice(self.last_data.intervals)
else:
n = len(self.last_data.buffer) - 1
u, v = sorted(
(self.random.choice(self.last_data.intervals)))
if (
v < len(self.last_data.buffer)
) and self.incorporate_new_buffer(self.last_data.buffer[:u] +
self.last_data.buffer[v:]):
failed_deletes = 0
else:
failed_deletes += 1
i = 0
while i < len(self.last_data.intervals):
u, v = self.last_data.intervals[i]
if not self.incorporate_new_buffer(self.last_data.buffer[:u] +
self.last_data.buffer[v:]):
i += 1
i = 0
while i + 1 < len(self.last_data.buffer):
if not self.incorporate_new_buffer(self.last_data.buffer[:i] +
self.last_data.buffer[i +
1:]):
i += 1
i = 0
while i < len(self.last_data.blocks):
u, v = self.last_data.blocks[i]
buf = self.last_data.buffer
block = buf[u:v]
n = v - u
all_blocks = sorted(
set([bytes(n)] +
[buf[a:a + n]
for a in self.last_data.block_starts[n]]))
better_blocks = all_blocks[:all_blocks.index(block)]
for b in better_blocks:
if self.incorporate_new_buffer(buf[:u] + b + buf[v:]):
break
i += 1
block_counter = -1
while block_counter < self.changed:
block_counter = self.changed
blocks = [
k for k, count in Counter(
self.last_data.buffer[u:v]
for u, v in self.last_data.blocks).items() if count > 1
]
for block in blocks:
parts = [
self.last_data.buffer[r:s]
for r, s in self.last_data.blocks
]
def replace(b):
return b''.join(
bytes(b if c == block else c) for c in parts)
minimize(block,
lambda b: self.incorporate_new_buffer(replace(b)),
self.random)
i = 0
while i < len(self.last_data.blocks):
u, v = self.last_data.blocks[i]
minimize(
self.last_data.buffer[u:v],
lambda b: self.incorporate_new_buffer(
self.last_data.buffer[:u] + b + self.last_data.buffer[
v:], ), self.random)
i += 1
i = 0
alternatives = None
while i < len(self.last_data.intervals):
if alternatives is None:
alternatives = sorted(set(
self.last_data.buffer[u:v]
for u, v in self.last_data.intervals),
key=len)
u, v = self.last_data.intervals[i]
for a in alternatives:
buf = self.last_data.buffer
if (len(a) < v - u
or (len(a) == (v - u) and a < buf[u:v])):
if self.incorporate_new_buffer(buf[:u] + a + buf[v:]):
alternatives = None
break
i += 1
def test_does_not_double_freeze_in_interval_close():
x = TestData.for_buffer(b'hi')
with pytest.raises(StopTest):
x.draw(BigStrategy())
assert x.frozen
assert len(x.intervals) == 0
def test_fixed_size_bytes_just_draw_bytes():
from hypothesis.internal.conjecture.data import TestData
x = TestData.for_buffer(b'foo')
assert x.draw(binary(min_size=3, max_size=3)) == b'foo'
def test_cannot_draw_after_freeze():
x = TestData.for_buffer(b'hi')
x.draw_bytes(1)
x.freeze()
with pytest.raises(Frozen):
x.draw_bytes(1)
def test_can_mark_interesting():
x = TestData.for_buffer(bytes())
with pytest.raises(StopTest):
x.mark_interesting()
assert x.frozen
assert x.status == Status.INTERESTING
def test_can_draw_zero_bytes():
x = TestData.for_buffer(b'')
for _ in range(10):
assert x.draw_bytes(0) == b''
def test_closes_interval_on_error_in_strategy():
x = TestData.for_buffer(b'hi')
with pytest.raises(ValueError):
x.draw(BoomStrategy())
x.freeze()
assert len(x.intervals) == 1
def test_notes_repr():
x = TestData.for_buffer(b'')
x.note(b'hi')
assert repr(b'hi') in x.output
def test_buffer_draws_as_self(buf):
x = TestData.for_buffer(buf)
assert x.draw_bytes(len(buf), bogus_dist) == buf
def test_can_mark_invalid():
x = TestData.for_buffer(bytes())
with pytest.raises(StopTest):
x.mark_invalid()
assert x.frozen
assert x.status == Status.INVALID
def _run(self):
self.last_data = None
mutations = 0
start_time = time.time()
if (
self.settings.database is not None and
self.database_key is not None
):
corpus = sorted(
self.settings.database.fetch(self.database_key),
key=lambda d: (len(d), d)
)
for existing in corpus:
if self.valid_examples >= self.settings.max_examples:
return
if self.iterations >= max(
self.settings.max_iterations, self.settings.max_examples
):
return
data = TestData.for_buffer(existing)
self.test_function(data)
data.freeze()
self.last_data = data
if data.status < Status.VALID:
self.settings.database.delete(
self.database_key, existing)
elif data.status == Status.VALID:
# Incremental garbage collection! we store a lot of
# examples in the DB as we shrink: Those that stay
# interesting get kept, those that become invalid get
# dropped, but those that are merely valid gradually go
# away over time.
if self.random.randint(0, 2) == 0:
self.settings.database.delete(
self.database_key, existing)
else:
assert data.status == Status.INTERESTING
self.last_data = data
break
if Phase.generate in self.settings.phases:
if (
self.last_data is None or
self.last_data.status < Status.INTERESTING
):
self.new_buffer()
mutator = self._new_mutator()
while self.last_data.status != Status.INTERESTING:
if self.valid_examples >= self.settings.max_examples:
return
if self.iterations >= max(
self.settings.max_iterations, self.settings.max_examples
):
return
if (
self.settings.timeout > 0 and
time.time() >= start_time + self.settings.timeout
):
return
if mutations >= self.settings.max_mutations:
mutations = 0
self.new_buffer()
mutator = self._new_mutator()
else:
data = TestData(
draw_bytes=mutator,
max_length=self.settings.buffer_size
)
self.test_function(data)
data.freeze()
self.note_for_corpus(data)
prev_data = self.last_data
if self.consider_new_test_data(data):
self.last_data = data
if data.status > prev_data.status:
mutations = 0
else:
mutator = self._new_mutator()
mutations += 1
data = self.last_data
if data is None:
return
assert isinstance(data.output, text_type)
if self.settings.max_shrinks <= 0:
return
if Phase.shrink not in self.settings.phases:
return
if not self.last_data.buffer:
return
data = TestData.for_buffer(self.last_data.buffer)
self.test_function(data)
if data.status != Status.INTERESTING:
return
change_counter = -1
while self.changed > change_counter:
change_counter = self.changed
failed_deletes = 0
while self.last_data.intervals and failed_deletes < 10:
if self.random.randint(0, 1):
u, v = self.random.choice(self.last_data.intervals)
else:
n = len(self.last_data.buffer) - 1
u, v = sorted((
self.random.choice(self.last_data.intervals)
))
if (
v < len(self.last_data.buffer)
) and self.incorporate_new_buffer(
self.last_data.buffer[:u] +
self.last_data.buffer[v:]
):
failed_deletes = 0
else:
failed_deletes += 1
i = 0
while i < len(self.last_data.intervals):
u, v = self.last_data.intervals[i]
if not self.incorporate_new_buffer(
self.last_data.buffer[:u] +
self.last_data.buffer[v:]
):
i += 1
i = 0
while i + 1 < len(self.last_data.buffer):
if not self.incorporate_new_buffer(
self.last_data.buffer[:i] +
self.last_data.buffer[i + 1:]
):
i += 1
i = 0
while i < len(self.last_data.blocks):
u, v = self.last_data.blocks[i]
buf = self.last_data.buffer
block = buf[u:v]
n = v - u
all_blocks = sorted(set([bytes(n)] + [
buf[a:a + n]
for a in self.last_data.block_starts[n]
]))
better_blocks = all_blocks[:all_blocks.index(block)]
for b in better_blocks:
if self.incorporate_new_buffer(
buf[:u] + b + buf[v:]
):
break
i += 1
block_counter = -1
while block_counter < self.changed:
block_counter = self.changed
blocks = [
k for k, count in
Counter(
self.last_data.buffer[u:v]
for u, v in self.last_data.blocks).items()
if count > 1
]
for block in blocks:
parts = [
self.last_data.buffer[r:s]
for r, s in self.last_data.blocks
]
def replace(b):
return b''.join(
bytes(b if c == block else c) for c in parts
)
minimize(
block,
lambda b: self.incorporate_new_buffer(replace(b)),
self.random
)
i = 0
while i < len(self.last_data.blocks):
u, v = self.last_data.blocks[i]
minimize(
self.last_data.buffer[u:v],
lambda b: self.incorporate_new_buffer(
self.last_data.buffer[:u] + b +
self.last_data.buffer[v:],
), self.random
)
i += 1
i = 0
alternatives = None
while i < len(self.last_data.intervals):
if alternatives is None:
alternatives = sorted(set(
self.last_data.buffer[u:v]
for u, v in self.last_data.intervals), key=len)
u, v = self.last_data.intervals[i]
for a in alternatives:
buf = self.last_data.buffer
if (
len(a) < v - u or
(len(a) == (v - u) and a < buf[u:v])
):
if self.incorporate_new_buffer(buf[:u] + a + buf[v:]):
alternatives = None
break
i += 1
def test_does_not_double_freeze_in_interval_close():
x = TestData.for_buffer(b'hi')
with pytest.raises(StopTest):
x.draw(BigStrategy())
assert x.frozen
assert len(x.intervals) == 0
class TestRunner(object):
def __init__(
self, test_function, settings=None, random=None,
database_key=None,
):
self._test_function = test_function
self.settings = settings or Settings()
self.last_data = None
self.changed = 0
self.shrinks = 0
self.examples_considered = 0
self.iterations = 0
self.valid_examples = 0
self.start_time = time.time()
self.random = random or Random(getrandbits(128))
self.database_key = database_key
self.seen = set()
def new_buffer(self):
self.last_data = TestData(
max_length=self.settings.buffer_size,
draw_bytes=lambda data, n, distribution:
distribution(self.random, n)
)
self.test_function(self.last_data)
self.last_data.freeze()
self.note_for_corpus(self.last_data)
def test_function(self, data):
self.iterations += 1
try:
self._test_function(data)
data.freeze()
except StopTest as e:
if e.testcounter != data.testcounter:
self.save_buffer(data.buffer)
raise e
except:
self.save_buffer(data.buffer)
raise
if (
data.status == Status.INTERESTING and (
self.last_data is None or
data.buffer != self.last_data.buffer
)
):
self.debug_data(data)
if data.status >= Status.VALID:
self.valid_examples += 1
def consider_new_test_data(self, data):
# Transition rules:
# 1. Transition cannot decrease the status
# 2. Any transition which increases the status is valid
# 3. If the previous status was interesting, only shrinking
# transitions are allowed.
key = hbytes(data.buffer)
if key in self.seen:
return False
self.seen.add(key)
if data.buffer == self.last_data.buffer:
return False
if self.last_data.status < data.status:
return True
if self.last_data.status > data.status:
return False
if data.status == Status.INVALID:
return data.index >= self.last_data.index
if data.status == Status.OVERRUN:
return data.overdraw <= self.last_data.overdraw
if data.status == Status.INTERESTING:
assert len(data.buffer) <= len(self.last_data.buffer)
if len(data.buffer) == len(self.last_data.buffer):
assert data.buffer < self.last_data.buffer
return True
return True
def save_buffer(self, buffer):
if (
self.settings.database is not None and
self.database_key is not None and
Phase.reuse in self.settings.phases
):
self.settings.database.save(
self.database_key, hbytes(buffer)
)
def note_for_corpus(self, data):
if data.status == Status.INTERESTING:
self.save_buffer(data.buffer)
def debug(self, message):
with self.settings:
debug_report(message)
def debug_data(self, data):
self.debug(u'%d bytes %s -> %s, %s' % (
data.index,
unicode_safe_repr(list(data.buffer[:data.index])),
unicode_safe_repr(data.status),
data.output,
))
def incorporate_new_buffer(self, buffer):
if buffer in self.seen:
return False
assert self.last_data.status == Status.INTERESTING
if (
self.settings.timeout > 0 and
time.time() >= self.start_time + self.settings.timeout
):
raise RunIsComplete()
self.examples_considered += 1
buffer = buffer[:self.last_data.index]
if sort_key(buffer) >= sort_key(self.last_data.buffer):
return False
assert sort_key(buffer) <= sort_key(self.last_data.buffer)
data = TestData.for_buffer(buffer)
self.test_function(data)
data.freeze()
self.note_for_corpus(data)
if self.consider_new_test_data(data):
self.shrinks += 1
self.last_data = data
if self.shrinks >= self.settings.max_shrinks:
raise RunIsComplete()
self.last_data = data
self.changed += 1
return True
return False
def run(self):
with self.settings:
try:
self._run()
except RunIsComplete:
pass
self.debug(
u'Run complete after %d examples (%d valid) and %d shrinks' % (
self.iterations, self.valid_examples, self.shrinks,
))
def _new_mutator(self):
def draw_new(data, n, distribution):
return distribution(self.random, n)
def draw_existing(data, n, distribution):
return self.last_data.buffer[data.index:data.index + n]
def draw_smaller(data, n, distribution):
existing = self.last_data.buffer[data.index:data.index + n]
r = distribution(self.random, n)
if r <= existing:
return r
return _draw_predecessor(self.random, existing)
def draw_larger(data, n, distribution):
existing = self.last_data.buffer[data.index:data.index + n]
r = distribution(self.random, n)
if r >= existing:
return r
return _draw_successor(self.random, existing)
def reuse_existing(data, n, distribution):
choices = data.block_starts.get(n, []) or \
self.last_data.block_starts.get(n, [])
if choices:
i = self.random.choice(choices)
return self.last_data.buffer[i:i + n]
else:
return distribution(self.random, n)
def flip_bit(data, n, distribution):
buf = bytearray(
self.last_data.buffer[data.index:data.index + n])
i = self.random.randint(0, n - 1)
k = self.random.randint(0, 7)
buf[i] ^= (1 << k)
return hbytes(buf)
def draw_zero(data, n, distribution):
return b'\0' * n
def draw_constant(data, n, distribution):
return bytes_from_list([
self.random.randint(0, 255)
] * n)
options = [
draw_new,
reuse_existing, reuse_existing,
draw_existing, draw_smaller, draw_larger,
flip_bit, draw_zero, draw_constant,
]
bits = [
self.random.choice(options) for _ in hrange(3)
]
def draw_mutated(data, n, distribution):
if (
data.index + n > len(self.last_data.buffer)
):
return distribution(self.random, n)
return self.random.choice(bits)(data, n, distribution)
return draw_mutated
def _run(self):
self.last_data = None
mutations = 0
start_time = time.time()
if (
self.settings.database is not None and
self.database_key is not None
):
corpus = sorted(
self.settings.database.fetch(self.database_key),
key=lambda d: (len(d), d)
)
for existing in corpus:
if self.valid_examples >= self.settings.max_examples:
return
if self.iterations >= max(
self.settings.max_iterations, self.settings.max_examples
):
return
data = TestData.for_buffer(existing)
self.test_function(data)
data.freeze()
self.last_data = data
if data.status < Status.VALID:
self.settings.database.delete(
self.database_key, existing)
elif data.status == Status.VALID:
# Incremental garbage collection! we store a lot of
# examples in the DB as we shrink: Those that stay
# interesting get kept, those that become invalid get
# dropped, but those that are merely valid gradually go
# away over time.
if self.random.randint(0, 2) == 0:
self.settings.database.delete(
self.database_key, existing)
else:
assert data.status == Status.INTERESTING
self.last_data = data
break
if Phase.generate in self.settings.phases:
if (
self.last_data is None or
self.last_data.status < Status.INTERESTING
):
self.new_buffer()
mutator = self._new_mutator()
while self.last_data.status != Status.INTERESTING:
if self.valid_examples >= self.settings.max_examples:
return
if self.iterations >= max(
self.settings.max_iterations, self.settings.max_examples
):
return
if (
self.settings.timeout > 0 and
time.time() >= start_time + self.settings.timeout
):
return
if mutations >= self.settings.max_mutations:
mutations = 0
self.new_buffer()
mutator = self._new_mutator()
else:
data = TestData(
draw_bytes=mutator,
max_length=self.settings.buffer_size
)
self.test_function(data)
data.freeze()
self.note_for_corpus(data)
prev_data = self.last_data
if self.consider_new_test_data(data):
self.last_data = data
if data.status > prev_data.status:
mutations = 0
else:
mutator = self._new_mutator()
mutations += 1
data = self.last_data
if data is None:
return
assert isinstance(data.output, text_type)
if self.settings.max_shrinks <= 0:
return
if Phase.shrink not in self.settings.phases:
return
if not self.last_data.buffer:
return
data = TestData.for_buffer(self.last_data.buffer)
self.test_function(data)
if data.status != Status.INTERESTING:
return
change_counter = -1
while self.changed > change_counter:
change_counter = self.changed
failed_deletes = 0
while self.last_data.intervals and failed_deletes < 10:
if self.random.randint(0, 1):
u, v = self.random.choice(self.last_data.intervals)
else:
n = len(self.last_data.buffer) - 1
u, v = sorted((
self.random.choice(self.last_data.intervals)
))
if (
v < len(self.last_data.buffer)
) and self.incorporate_new_buffer(
self.last_data.buffer[:u] +
self.last_data.buffer[v:]
):
failed_deletes = 0
else:
failed_deletes += 1
i = 0
while i < len(self.last_data.intervals):
u, v = self.last_data.intervals[i]
if not self.incorporate_new_buffer(
self.last_data.buffer[:u] +
self.last_data.buffer[v:]
):
i += 1
i = 0
while i + 1 < len(self.last_data.buffer):
if not self.incorporate_new_buffer(
self.last_data.buffer[:i] +
self.last_data.buffer[i + 1:]
):
i += 1
i = 0
while i < len(self.last_data.blocks):
u, v = self.last_data.blocks[i]
buf = self.last_data.buffer
block = buf[u:v]
n = v - u
all_blocks = sorted(set([bytes(n)] + [
buf[a:a + n]
for a in self.last_data.block_starts[n]
]))
better_blocks = all_blocks[:all_blocks.index(block)]
for b in better_blocks:
if self.incorporate_new_buffer(
buf[:u] + b + buf[v:]
):
break
i += 1
block_counter = -1
while block_counter < self.changed:
block_counter = self.changed
blocks = [
k for k, count in
Counter(
self.last_data.buffer[u:v]
for u, v in self.last_data.blocks).items()
if count > 1
]
for block in blocks:
parts = [
self.last_data.buffer[r:s]
for r, s in self.last_data.blocks
]
def replace(b):
return b''.join(
bytes(b if c == block else c) for c in parts
)
minimize(
block,
lambda b: self.incorporate_new_buffer(replace(b)),
self.random
)
i = 0
while i < len(self.last_data.blocks):
u, v = self.last_data.blocks[i]
minimize(
self.last_data.buffer[u:v],
lambda b: self.incorporate_new_buffer(
self.last_data.buffer[:u] + b +
self.last_data.buffer[v:],
), self.random
)
i += 1
i = 0
alternatives = None
while i < len(self.last_data.intervals):
if alternatives is None:
alternatives = sorted(set(
self.last_data.buffer[u:v]
for u, v in self.last_data.intervals), key=len)
u, v = self.last_data.intervals[i]
for a in alternatives:
buf = self.last_data.buffer
if (
len(a) < v - u or
(len(a) == (v - u) and a < buf[u:v])
):
if self.incorporate_new_buffer(buf[:u] + a + buf[v:]):
alternatives = None
break
i += 1
def test_cannot_draw_after_freeze():
x = TestData.for_buffer(b'hi')
x.draw_bytes(1)
x.freeze()
with pytest.raises(Frozen):
x.draw_bytes(1)
def bc():
return BuildContext(TD.for_buffer(b''))
def test_can_draw_zero_bytes():
x = TestData.for_buffer(b'')
for _ in range(10):
assert x.draw_bytes(0) == b''
def test_does_not_draw_data_for_empty_range():
assert integer_range(TestData.for_buffer(b''), 1, 1) == 1
def test_notes_repr():
x = TestData.for_buffer(b'')
x.note(b'hi')
assert repr(b'hi') in x.output
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 test_can_mark_invalid():
x = TestData.for_buffer(bytes())
with pytest.raises(StopTest):
x.mark_invalid()
assert x.frozen
assert x.status == Status.INVALID
def find(specifier, condition, settings=None, random=None, database_key=None):
settings = settings or Settings(max_examples=2000, min_satisfying_examples=0, max_shrinks=2000)
if database_key is None and settings.database is not None:
database_key = function_digest(condition)
if not isinstance(specifier, SearchStrategy):
raise InvalidArgument("Expected SearchStrategy but got %r of type %s" % (specifier, type(specifier).__name__))
search = specifier
random = random or new_random()
successful_examples = [0]
last_data = [None]
def template_condition(data):
with BuildContext():
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()
from hypothesis.internal.conjecture.engine import TestRunner
from hypothesis.internal.conjecture.data import TestData, Status
start = time.time()
runner = TestRunner(template_condition, settings=settings, random=random, database_key=database_key)
runner.run()
run_time = time.time() - start
if runner.last_data.status == Status.INTERESTING:
with BuildContext():
return TestData.for_buffer(runner.last_data.buffer).draw(search)
if runner.valid_examples <= settings.min_satisfying_examples:
if settings.timeout > 0 and run_time > settings.timeout:
raise Timeout(
(
"Ran out of time before finding enough valid examples for "
"%s. Only %d valid examples found in %.2f seconds."
)
% (get_pretty_function_description(condition), runner.valid_examples, run_time)
)
else:
raise Unsatisfiable(
("Unable to satisfy assumptions of " "%s. Only %d examples considered satisfied assumptions")
% (get_pretty_function_description(condition), runner.valid_examples)
)
raise NoSuchExample(get_pretty_function_description(condition))
def test_does_not_draw_data_for_empty_range():
assert integer_range(TestData.for_buffer(b""), 1, 1) == 1
def test_fixed_size_bytes_just_draw_bytes():
from hypothesis.internal.conjecture.data import TestData
x = TestData.for_buffer(b'foo')
assert x.draw(binary(min_size=3, max_size=3)) == b'foo'
