def test_starmap_async(self):
pool = CtxThreadPool(processes=2, worker_contexts=[0, 1])
xy = [(i, i) for i in range(10)]
result = pool.starmap_async(ctx_func2, xy).get()
assert sorted([r[1] for r in result]) == [i * 2 for i in range(10)]
assert {r[0] for r in result}.issubset({0, 1})
pool.close()
pool.join()
def test_imap_unordered(self):
pool = CtxThreadPool(processes=2, worker_contexts=[0, 1])
x = [i for i in range(10)]
result = pool.imap_unordered(ctx_func, x)
assert sorted([r[1] for r in result]) == x
assert {r[0] for r in result}.issubset({0, 1})
pool.close()
pool.join()
def test_map_async(self):
pool = CtxThreadPool(processes=2, worker_contexts=[0, 1])
x = [i for i in range(10)]
result = pool.map_async(ctx_func, x).get()
assert sorted([r[1] for r in result]) == x
assert set([r[0] for r in result]).issubset({0, 1})
pool.close()
pool.join()
def test_multiple_ctx_map(self):
# test whether two context thread pools will interfere with each other
pool = CtxThreadPool(processes=2, worker_contexts=[0, 1])
pool2 = CtxThreadPool(processes=2, worker_contexts=[2, 3])
# create enough work items so that the execution period of two pools
# will overlap
x = [i for i in range(50000)]
result = pool.map(ctx_func, x)
result2 = pool2.map(ctx_func, x)
assert sorted([r[1] for r in result]) == x
assert {r[0] for r in result}.issubset({0, 1})
assert sorted([r[1] for r in result2]) == x
assert {r[0] for r in result2}.issubset({2, 3})
pool.close()
pool.join()
pool2.close()
pool2.join()
def test_apply_async(self):
pool = CtxThreadPool(processes=2)
assert pool.apply_async(ctx_func, (1,)).get()[1] == 1
pool.close()
pool.join()
def test_apply(self):
pool = CtxThreadPool(processes=2)
assert pool.apply(ctx_func, (1,))[1] == 1
# for pytest-cov to run on sub processes
pool.close()
pool.join()
def test_init(self):
with pytest.raises(ValueError, match="not equal to the number"):
_ = CtxThreadPool(processes=2, worker_contexts=[0, 1, 2, 3])
pool = CtxThreadPool(
processes=2, initializer=init_func, initargs=("some_args",)
)
pool.close()
pool.join()
pool = CtxThreadPool(processes=2, worker_contexts=[0, 1])
pool.close()
pool.join()
