Makes the flow engine reachable from the API, which is what M3 needs before
any of it can reach the browser.
- app/flow is a package now; the prototype's watch-dir scripts and the
matplotlib/networkx visualiser are gone with their dependencies.
- Messages carry a serializable dtype instead of a live Python type, and a
port name, so the graph can speak qualified names while node functions keep
local arguments. Redis state is JSON, not pickle.
- Message names are namespaced per flow ("heating.temp"); a bare name resolves
to its own flow, a dotted one crosses flows.
- Several nodes may provide the same message: producers are a list, so fan-in
is a real edge instead of a silently dropped one.
- Flows are stored as flow.json plus node sources in a git repository, one
commit per save, with identical saves skipped so autosave stays quiet.
- Node failures are isolated and reported per node; validate() returns cycles
and unconnected inputs instead of raising deep in a run.
- Credentials live in an encrypted store and are referenced as {"$secret": …}.
- Engine events reach websocket clients through a bus, so values, node status
and execution show up live.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016WzrvW7rjQbynnhF6pxh6i
112 lines
2.8 KiB
Python
112 lines
2.8 KiB
Python
"""Synchronous nodes wait until every input is fresh.
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The ordering guarantee at the stateful boundary rests on the state backend's
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atomic operations, so those are covered here too.
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"""
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from concurrent.futures import ThreadPoolExecutor
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from app.flow.messages import DType, MessageSpec
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from app.flow.nodes import Node
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from app.flow.pipeline import Pipeline
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from app.flow.state import MemoryState
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def spec(name: str) -> MessageSpec:
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return MessageSpec(name=name, dtype=DType.FLOAT)
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def node(node_id: str, f, requires=(), provides=(), params=None) -> Node:
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n = Node(
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f=f,
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requires=list(requires),
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provides=list(provides),
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params=params or {},
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name=node_id,
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)
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n.assign_flow("f", node_id)
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return n
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def test_synchronous_node_waits_for_all_inputs_to_be_fresh():
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runs: list[str] = []
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def sensor_a(params):
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return {"a": 1.0}
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def sensor_b(params):
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return {"b": 2.0}
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def sync(a, b, params):
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runs.append("sync")
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return None
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def eager(a, b, params):
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runs.append("eager")
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return None
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a = node("a", sensor_a, provides=[spec("a")])
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b = node("b", sensor_b, provides=[spec("b")])
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sync_node = node(
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"sync", sync, requires=[spec("a"), spec("b")], params={"synchronous": True}
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)
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eager_node = node("eager", eager, requires=[spec("a"), spec("b")])
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Pipeline(nodes=[a, b, sync_node, eager_node], max_workers=1)
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a.inject()
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assert runs == [] # b has never arrived
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b.inject()
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assert runs.count("eager") == 1
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assert runs.count("sync") == 1
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# Only a is new: the eager node runs again, the synchronous one waits.
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runs.clear()
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a.inject()
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assert runs == ["eager"]
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# Now b is new as well, so both have moved on.
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runs.clear()
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b.inject()
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assert sorted(runs) == ["eager", "sync"]
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def test_increment_and_multi_get():
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state = MemoryState()
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assert state.increment("counter") == 1
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assert state.increment("counter") == 2
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state.update({"a": 1, "b": 2})
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assert state.get_multi(["a", "b", "missing"]) == {
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"a": 1,
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"b": 2,
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"missing": None,
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}
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def test_compare_and_swap_only_applies_on_match():
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state = MemoryState()
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state.update({"a": 1, "b": 2})
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assert state.compare_and_swap_multi({"a": 1, "b": 2}, {"a": 10, "new": 100})
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assert state.get("a") == 10
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assert state.get("new") == 100
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assert not state.compare_and_swap_multi({"a": 1}, {"a": 99})
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assert state.get("a") == 10
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def test_only_one_thread_wins_a_compare_and_swap():
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state = MemoryState()
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state.set("version", 1)
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def claim() -> bool:
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return state.compare_and_swap_multi({"version": 1}, {"version": 2})
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with ThreadPoolExecutor(max_workers=8) as pool:
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results = list(pool.map(lambda _: claim(), range(8)))
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assert sum(results) == 1
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