def test_local_cluster_adapt(self):
adapt_kwargs = {"minimum": 1, "maximum": 1}
called_with = None
class MyCluster(distributed.LocalCluster):
def adapt(self, **kwargs):
nonlocal called_with
called_with = kwargs
super().adapt(**kwargs)
executor = DaskExecutor(
cluster_class=MyCluster,
cluster_kwargs={
"processes": False,
"n_workers": 0
},
adapt_kwargs=adapt_kwargs,
)
assert executor.adapt_kwargs == adapt_kwargs
with executor.start():
res = executor.wait(executor.submit(lambda x: x + 1, 1))
assert res == 2
assert called_with == adapt_kwargs
def test_start_local_cluster(self):
executor = DaskExecutor(cluster_kwargs={"processes": False})
assert executor.cluster_class == distributed.LocalCluster
assert executor.cluster_kwargs == {
"processes": False,
"silence_logs": logging.CRITICAL,
}
with executor.start():
res = executor.wait(executor.submit(lambda x: x + 1, 1))
assert res == 2
def test_connect_to_running_cluster(self):
with distributed.Client(processes=False, set_as_default=False) as client:
executor = DaskExecutor(address=client.scheduler.address)
assert executor.address == client.scheduler.address
assert executor.cluster_class is None
assert executor.cluster_kwargs is None
assert executor.client_kwargs == {"set_as_default": False}
with executor.start():
res = executor.wait(executor.submit(lambda x: x + 1, 1))
assert res == 2