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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 hashlib
import math
from random import Random
from hypothesis import Verbosity, assume, settings
from hypothesis.database import InMemoryExampleDatabase
from hypothesis.internal.compat import PYPY
from hypothesis.internal.floats import clamp, float_to_int, int_to_float, is_negative
from hypothesis.stateful import Bundle, RuleBasedStateMachine, rule
from hypothesis.strategies import (
binary,
booleans,
complex_numbers,
data,
decimals,
floats,
fractions,
integers,
just,
lists,
none,
sampled_from,
text,
tuples,
)
AVERAGE_LIST_LENGTH = 2
class HypothesisSpec(RuleBasedStateMachine):
def __init__(self):
super().__init__()
self.database = None
strategies = Bundle("strategy")
strategy_tuples = Bundle("tuples")
objects = Bundle("objects")
basic_data = Bundle("basic")
varied_floats = Bundle("varied_floats")
def teardown(self):
self.clear_database()
@rule()
def clear_database(self):
if self.database is not None:
self.database = None
@rule()
def set_database(self):
self.teardown()
self.database = InMemoryExampleDatabase()
@rule(
target=strategies,
spec=sampled_from(
(
integers(),
booleans(),
floats(),
complex_numbers(),
fractions(),
decimals(),
text(),
binary(),
none(),
tuples(),
)
),
)
def strategy(self, spec):
return spec
@rule(target=strategies, values=lists(integers() | text(), min_size=1))
def sampled_from_strategy(self, values):
return sampled_from(values)
@rule(target=strategies, spec=strategy_tuples)
def strategy_for_tupes(self, spec):
return tuples(*spec)
@rule(target=strategies, source=strategies, level=integers(1, 10), mixer=text())
def filtered_strategy(self, source, level, mixer):
def is_good(x):
seed = hashlib.sha384((mixer + repr(x)).encode()).digest()
return bool(Random(seed).randint(0, level))
return source.filter(is_good)
@rule(target=strategies, elements=strategies)
def list_strategy(self, elements):
return lists(elements)
@rule(target=strategies, left=strategies, right=strategies)
def or_strategy(self, left, right):
return left | right
@rule(target=varied_floats, source=floats())
def float(self, source):
return source
@rule(target=varied_floats, source=varied_floats, offset=integers(-100, 100))
def adjust_float(self, source, offset):
return int_to_float(clamp(0, float_to_int(source) + offset, 2**64 - 1))
@rule(target=strategies, left=varied_floats, right=varied_floats)
def float_range(self, left, right):
assume(math.isfinite(left) and math.isfinite(right))
left, right = sorted((left, right))
assert left <= right
# exclude deprecated case where left = 0.0 and right = -0.0
assume(left or right or not (is_negative(right) and not is_negative(left)))
return floats(left, right)
@rule(
target=strategies,
source=strategies,
result1=strategies,
result2=strategies,
mixer=text(),
p=floats(0, 1),
)
def flatmapped_strategy(self, source, result1, result2, mixer, p):
assume(result1 is not result2)
def do_map(value):
rep = repr(value)
random = Random(hashlib.sha384((mixer + rep).encode()).digest())
if random.random() <= p:
return result1
else:
return result2
return source.flatmap(do_map)
@rule(target=strategies, value=objects)
def just_strategy(self, value):
return just(value)
@rule(target=strategy_tuples, source=strategies)
def single_tuple(self, source):
return (source,)
@rule(target=strategy_tuples, left=strategy_tuples, right=strategy_tuples)
def cat_tuples(self, left, right):
return left + right
@rule(target=objects, strat=strategies, data=data())
def get_example(self, strat, data):
data.draw(strat)
@rule(target=strategies, left=integers(), right=integers())
def integer_range(self, left, right):
left, right = sorted((left, right))
return integers(left, right)
@rule(strat=strategies)
def repr_is_good(self, strat):
assert " at 0x" not in repr(strat)
MAIN = __name__ == "__main__"
TestHypothesis = HypothesisSpec.TestCase
TestHypothesis.settings = settings(
TestHypothesis.settings,
stateful_step_count=10 if PYPY else 50,
verbosity=max(TestHypothesis.settings.verbosity, Verbosity.verbose),
max_examples=10000 if MAIN else 200,
)
if MAIN:
TestHypothesis().runTest()
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