def test_weak_array_key_map():
def assert_empty_after_gc_collect(container, retries=3):
for i in range(retries):
if len(container) == 0:
return
gc.collect()
assert len(container) == 0
a = np.ones(42)
m = _WeakArrayKeyMap()
m.set(a, 'a')
assert m.get(a) == 'a'
b = a
assert m.get(b) == 'a'
m.set(b, 'b')
assert m.get(a) == 'b'
del a
gc.collect()
assert len(m._data) == 1
assert m.get(b) == 'b'
del b
assert_empty_after_gc_collect(m._data)
c = np.ones(42)
m.set(c, 'c')
assert len(m._data) == 1
assert m.get(c) == 'c'
with raises(KeyError):
m.get(np.ones(42))
del c
assert_empty_after_gc_collect(m._data)
# Check that creating and dropping numpy arrays with potentially the same
# object id will not cause the map to get confused.
def get_set_get_collect(m, i):
a = np.ones(42)
with raises(KeyError):
m.get(a)
m.set(a, i)
assert m.get(a) == i
return id(a)
unique_ids = set([get_set_get_collect(m, i) for i in range(1000)])
if platform.python_implementation() == 'CPython':
# On CPython (at least) the same id is often reused many times for the
# temporary arrays created under the local scope of the
# get_set_get_collect function without causing any spurious lookups /
# insertions in the map.
assert len(unique_ids) < 100
def test_weak_array_key_map_no_pickling():
m = _WeakArrayKeyMap()
with raises(pickle.PicklingError):
pickle.dumps(m)
def test_weak_array_key_map_no_pickling():
m = _WeakArrayKeyMap()
with raises(pickle.PicklingError):
pickle.dumps(m)