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feat: add support for sparse connect (#680)
* init * add newsfragment * fix
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newsfragments/679.feature.rst
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newsfragments/679.feature.rst
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Added sparse connect utility function to pubsub test utilities for creating test networks with configurable connectivity.
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@ -17,6 +17,7 @@ from tests.utils.factories import (
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from tests.utils.pubsub.utils import (
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from tests.utils.pubsub.utils import (
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dense_connect,
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dense_connect,
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one_to_all_connect,
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one_to_all_connect,
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sparse_connect,
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)
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)
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@ -506,3 +507,84 @@ async def test_gossip_heartbeat(initial_peer_count, monkeypatch):
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# Check that the peer to gossip to is not in our fanout peers
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# Check that the peer to gossip to is not in our fanout peers
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assert peer not in fanout_peers
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assert peer not in fanout_peers
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assert topic_fanout in peers_to_gossip[peer]
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assert topic_fanout in peers_to_gossip[peer]
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@pytest.mark.trio
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async def test_dense_connect_fallback():
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"""Test that sparse_connect falls back to dense connect for small networks."""
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async with PubsubFactory.create_batch_with_gossipsub(3) as pubsubs_gsub:
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hosts = [pubsub.host for pubsub in pubsubs_gsub]
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degree = 2
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# Create network (should use dense connect)
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await sparse_connect(hosts, degree)
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# Wait for connections to be established
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await trio.sleep(2)
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# Verify dense topology (all nodes connected to each other)
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for i, pubsub in enumerate(pubsubs_gsub):
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connected_peers = len(pubsub.peers)
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expected_connections = len(hosts) - 1
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assert connected_peers == expected_connections, (
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f"Host {i} has {connected_peers} connections, "
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f"expected {expected_connections} in dense mode"
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)
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@pytest.mark.trio
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async def test_sparse_connect():
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"""Test sparse connect functionality and message propagation."""
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async with PubsubFactory.create_batch_with_gossipsub(10) as pubsubs_gsub:
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hosts = [pubsub.host for pubsub in pubsubs_gsub]
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degree = 2
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topic = "test_topic"
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# Create network (should use sparse connect)
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await sparse_connect(hosts, degree)
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# Wait for connections to be established
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await trio.sleep(2)
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# Verify sparse topology
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for i, pubsub in enumerate(pubsubs_gsub):
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connected_peers = len(pubsub.peers)
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assert degree <= connected_peers < len(hosts) - 1, (
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f"Host {i} has {connected_peers} connections, "
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f"expected between {degree} and {len(hosts) - 1} in sparse mode"
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)
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# Test message propagation
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queues = [await pubsub.subscribe(topic) for pubsub in pubsubs_gsub]
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await trio.sleep(2)
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# Publish and verify message propagation
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msg_content = b"test_msg"
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await pubsubs_gsub[0].publish(topic, msg_content)
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await trio.sleep(2)
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# Verify message propagation - ideally all nodes should receive it
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received_count = 0
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for queue in queues:
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try:
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msg = await queue.get()
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if msg.data == msg_content:
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received_count += 1
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except Exception:
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continue
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total_nodes = len(pubsubs_gsub)
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# Ideally all nodes should receive the message for optimal scalability
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if received_count == total_nodes:
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# Perfect propagation achieved
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pass
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else:
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# require more than half for acceptable scalability
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min_required = (total_nodes + 1) // 2
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assert received_count >= min_required, (
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f"Message propagation insufficient: "
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f"{received_count}/{total_nodes} nodes "
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f"received the message. Ideally all nodes should receive it, but at "
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f"minimum {min_required} required for sparse network scalability."
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)
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@ -40,3 +40,42 @@ async def one_to_all_connect(hosts: Sequence[IHost], central_host_index: int) ->
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for i, host in enumerate(hosts):
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for i, host in enumerate(hosts):
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if i != central_host_index:
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if i != central_host_index:
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await connect(hosts[central_host_index], host)
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await connect(hosts[central_host_index], host)
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async def sparse_connect(hosts: Sequence[IHost], degree: int = 3) -> None:
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"""
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Create a sparse network topology where each node connects to a limited number of
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other nodes. This is more efficient than dense connect for large networks.
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The function will automatically switch between dense and sparse connect based on
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the network size:
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- For small networks (nodes <= degree + 1), use dense connect
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- For larger networks, use sparse connect with the specified degree
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Args:
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hosts: Sequence of hosts to connect
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degree: Number of connections each node should maintain (default: 3)
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"""
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if len(hosts) <= degree + 1:
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# For small networks, use dense connect
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await dense_connect(hosts)
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return
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# For larger networks, use sparse connect
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# For each host, connect to 'degree' number of other hosts
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for i, host in enumerate(hosts):
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# Calculate which hosts to connect to
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# We'll connect to hosts that are 'degree' positions away in the sequence
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# This creates a more distributed topology
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for j in range(1, degree + 1):
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target_idx = (i + j) % len(hosts)
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# Create bidirectional connection
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await connect(host, hosts[target_idx])
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await connect(hosts[target_idx], host)
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# Ensure network connectivity by connecting each node to its immediate neighbors
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for i in range(len(hosts)):
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next_idx = (i + 1) % len(hosts)
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await connect(hosts[i], hosts[next_idx])
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await connect(hosts[next_idx], hosts[i])
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