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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/.
from random import Random
import pytest
from hypothesis import settings, strategies as st
from hypothesis.internal.compat import ceil
from hypothesis.internal.conjecture.engine import ConjectureData, ConjectureRunner
from hypothesis.strategies._internal import SearchStrategy
from tests.conjecture.common import interesting_origin
POISON = "POISON"
class Poisoned(SearchStrategy):
def __init__(self, poison_chance):
super().__init__()
self.__poison_chance = poison_chance
self.__ints = st.integers(0, 10)
def do_draw(self, data):
if data.draw_boolean(self.__poison_chance):
return POISON
else:
return data.draw(self.__ints)
class LinearLists(SearchStrategy):
def __init__(self, elements, size):
super().__init__()
self.__length = st.integers(0, size)
self.__elements = elements
def do_draw(self, data):
return [data.draw(self.__elements) for _ in range(data.draw(self.__length))]
class Matrices(SearchStrategy):
def __init__(self, elements, size):
super().__init__()
self.__length = st.integers(0, ceil(size**0.5))
self.__elements = elements
def do_draw(self, data):
n = data.draw(self.__length)
m = data.draw(self.__length)
return [data.draw(self.__elements) for _ in range(n * m)]
LOTS = 10**6
TRIAL_SETTINGS = settings(max_examples=LOTS, database=None)
@pytest.mark.parametrize(
"seed", [2282791295271755424, 1284235381287210546, 14202812238092722246, 26097]
)
@pytest.mark.parametrize("size", [5, 10, 20])
@pytest.mark.parametrize("p", [0.01, 0.1])
@pytest.mark.parametrize("strategy_class", [LinearLists, Matrices])
def test_minimal_poisoned_containers(seed, size, p, strategy_class):
elements = Poisoned(p)
strategy = strategy_class(elements, size)
def test_function(data):
v = data.draw(strategy)
data.output = repr(v)
if POISON in v:
data.mark_interesting(interesting_origin())
runner = ConjectureRunner(
test_function, random=Random(seed), settings=TRIAL_SETTINGS
)
runner.run()
(v,) = runner.interesting_examples.values()
result = ConjectureData.for_choices(v.choices).draw(strategy)
assert len(result) == 1
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