def test_enr_partitioning(num_enr_records, max_payload_size):
enrs = ENRFactory.create_batch(num_enr_records)
batches = partition_enrs(enrs, max_payload_size)
assert sum(len(batch) for batch in batches) == len(enrs)
assert set(itertools.chain(*batches)) == set(enrs)
for batch in batches:
encoded_batch = rlp.encode(batch,
sedes=rlp.sedes.CountableList(ENRSedes))
assert len(encoded_batch) <= max_payload_size
for batch, next_batch in sliding_window(2, batches):
overfull_batch = tuple(batch) + (next_batch[0], )
encoded_batch = rlp.encode(overfull_batch,
sedes=rlp.sedes.CountableList(ENRSedes))
assert len(encoded_batch) > max_payload_size
@pytest.mark.trio
async def test_client_send_find_nodes(alice, bob, alice_client, bob_client):
with trio.fail_after(2):
async with alice.events.find_nodes_sent.subscribe_and_wait():
async with bob.events.find_nodes_received.subscribe_and_wait():
await alice_client.send_find_nodes(bob.endpoint,
bob.node_id,
distances=[255])
@pytest.mark.parametrize(
"enrs",
(
ENRFactory.create_batch(1),
ENRFactory.create_batch(2),
ENRFactory.create_batch(10),
ENRFactory.create_batch(50),
),
)
@pytest.mark.trio
async def test_client_send_found_nodes(alice, bob, alice_client, bob_client,
enrs):
with trio.fail_after(2):
async with alice.events.found_nodes_sent.subscribe_and_wait():
async with bob.events.found_nodes_received.subscribe(
) as subscription:
await alice_client.send_found_nodes(
bob.endpoint,
bob.node_id,