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# This file is part of Hypothesis, which may be found at
# https://github.com/HypothesisWorks/hypothesis/
#
# Copyright the Hypothesis Authors.
# Individual contributors are listed in AUTHORS.rst and the git log.
#
# This Source Code Form is subject to the terms of the Mozilla Public License,
# v. 2.0. If a copy of the MPL was not distributed with this file, You can
# obtain one at https://mozilla.org/MPL/2.0/.
import threading
from hypothesis import HealthCheck, given, settings, strategies as st
from tests.common.debug import find_any, minimal
from tests.common.utils import flaky
def test_can_generate_with_large_branching():
def flatten(x):
if isinstance(x, list):
return sum(map(flatten, x), [])
else:
return [x]
size = 20
xs = minimal(
st.recursive(
st.integers(),
lambda x: st.lists(x, min_size=size // 2),
max_leaves=size * 2,
),
lambda x: isinstance(x, list) and len(flatten(x)) >= size,
timeout_after=None,
)
assert flatten(xs) == [0] * size
def test_can_generate_some_depth_with_large_branching():
def depth(x):
if x and isinstance(x, list):
return 1 + max(map(depth, x))
else:
return 1
xs = minimal(
st.recursive(st.integers(), st.lists),
lambda x: depth(x) > 1,
timeout_after=None,
)
assert xs in ([0], [[]])
def test_can_find_quite_broad_lists():
def breadth(x):
if isinstance(x, list):
return sum(map(breadth, x))
else:
return 1
target = 10
broad = minimal(
st.recursive(st.booleans(), lambda x: st.lists(x, max_size=target // 2)),
lambda x: breadth(x) >= target,
settings=settings(max_examples=10000),
timeout_after=None,
)
assert breadth(broad) == target
def test_drawing_many_near_boundary():
target = 4
ls = minimal(
st.lists(
st.recursive(
st.booleans(),
lambda x: st.lists(
x, min_size=2 * (target - 1), max_size=2 * target
).map(tuple),
max_leaves=2 * target - 1,
)
),
lambda x: len(set(x)) >= target,
timeout_after=None,
)
assert len(ls) == target
def test_can_use_recursive_data_in_sets():
nested_sets = st.recursive(st.booleans(), st.frozensets, max_leaves=3)
find_any(nested_sets, settings=settings(deadline=None))
def flatten(x):
if isinstance(x, bool):
return frozenset((x,))
else:
result = frozenset()
for t in x:
result |= flatten(t)
if len(result) == 2:
break
return result
x = minimal(nested_sets, lambda x: len(flatten(x)) == 2, settings(deadline=None))
assert x in (
frozenset((False, True)),
frozenset((False, frozenset((True,)))),
frozenset((frozenset((False, True)),)),
)
@flaky(max_runs=2, min_passes=1)
def test_can_form_sets_of_recursive_data():
size = 3
trees = st.sets(
st.recursive(
st.booleans(),
lambda x: st.lists(x, min_size=size).map(tuple),
max_leaves=20,
)
)
xs = minimal(trees, lambda x: len(x) >= size, timeout_after=None)
assert len(xs) == size
def test_drawing_from_recursive_strategy_is_thread_safe():
shared_strategy = st.recursive(
st.integers(), lambda s: st.lists(s, max_size=2), max_leaves=20
)
errors = []
@settings(
database=None, deadline=None, suppress_health_check=[HealthCheck.too_slow]
)
@given(data=st.data())
def test(data):
try:
data.draw(shared_strategy)
except Exception as exc:
errors.append(exc)
threads = []
for _ in range(4):
threads.append(threading.Thread(target=test))
for thread in threads:
thread.start()
for thread in threads:
thread.join()
assert not errors
SELF_REF = st.recursive(
st.deferred(lambda: st.booleans() | SELF_REF),
lambda s: st.lists(s, min_size=1),
)
@given(SELF_REF)
def test_self_ref_regression(_):
# See https://github.com/HypothesisWorks/hypothesis/issues/2794
pass
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