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# coding=utf-8
#
# This file is part of Hypothesis, which may be found at
# https://github.com/HypothesisWorks/hypothesis-python
#
# Most of this work is copyright (C) 2013-2016 David R. MacIver
# (david@drmaciver.com), but it contains contributions by others. See
# CONTRIBUTING.rst for a full list of people who may hold copyright, and
# consult the git log if you need to determine who owns an individual
# contribution.
#
# 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 http://mozilla.org/MPL/2.0/.
#
# END HEADER
from __future__ import division, print_function, absolute_import
from random import Random
from flaky import flaky
import hypothesis.strategies as st
from hypothesis import find, given, example, settings
from hypothesis.internal.debug import timeout
from hypothesis.internal.compat import integer_types
def test_can_generate_with_large_branching():
def flatten(x):
if isinstance(x, list):
return sum(map(flatten, x), [])
else:
return [x]
xs = find(
st.recursive(
st.integers(), lambda x: st.lists(x, average_size=50),
max_leaves=100),
lambda x: isinstance(x, list) and len(flatten(x)) >= 50
)
assert flatten(xs) == [0] * 50
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 = find(
st.recursive(st.integers(), lambda x: st.lists(x, average_size=100)),
lambda x: depth(x) > 1
)
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
broad = find(
st.recursive(st.booleans(), lambda x: st.lists(x, max_size=10)),
lambda x: breadth(x) >= 20,
settings=settings(max_examples=10000)
)
assert breadth(broad) == 20
def test_drawing_many_near_boundary():
ls = find(
st.lists(st.recursive(
st.booleans(),
lambda x: st.lists(x, min_size=8, max_size=10).map(tuple),
max_leaves=9)),
lambda x: len(set(x)) >= 5,
settings=settings(max_examples=10000, database=None, max_shrinks=2000)
)
assert len(ls) == 5
@given(st.randoms())
@settings(max_examples=50, max_shrinks=0)
@example(Random(-1363972488426139))
@example(Random(-4))
def test_can_use_recursive_data_in_sets(rnd):
nested_sets = st.recursive(
st.booleans(),
lambda js: st.frozensets(js, average_size=2.0),
max_leaves=10
)
nested_sets.example(rnd)
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
assert rnd is not None
x = find(
nested_sets, lambda x: len(flatten(x)) == 2, random=rnd,
settings=settings(database=None, max_shrinks=1000, max_examples=1000))
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():
trees = st.sets(st.recursive(
st.booleans(),
lambda x: st.lists(x, min_size=5).map(tuple),
max_leaves=20))
xs = find(trees, lambda x: len(x) >= 10, settings=settings(
database=None, timeout=20, max_shrinks=1000, max_examples=1000
))
assert len(xs) == 10
@given(st.randoms())
@settings(max_examples=2, database=None)
@timeout(60)
def test_can_flatmap_to_recursive_data(rnd):
stuff = st.lists(st.integers(), min_size=1).flatmap(
lambda elts: st.recursive(
st.sampled_from(elts), lambda x: st.lists(x, average_size=25),
max_leaves=25
))
def flatten(x):
if isinstance(x, integer_types):
return [x]
else:
return sum(map(flatten, x), [])
tree = find(
stuff, lambda x: sum(flatten(x)) >= 100,
settings=settings(
database=None, max_shrinks=2000, max_examples=1000,
timeout=20,
),
random=rnd
)
flat = flatten(tree)
assert (sum(flat) == 1000) or (len(set(flat)) == 1)
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